DHS ANALYTICAL 

STUDIES 62

Integration of Infectiou

Disease Services w

Antenatal Care Services

Health Facilities in K

Malawi, andTanz

August 201

This publication was produced for review by the United States Agency for International Development. It was prepared by 

Lindsay Mallick, Rebecca Winter, Wenjuan Wang, and Jennifer Yourkavitch.

DHS Analytical Studies No. 62 

Integration of Infectious Disease Services with 

Antenatal Care Services at Health Facilities in Kenya, 

Malawi, and Tanzania 

Lindsay Mallick 

Rebecca Winter 

Wenjuan Wang 

Jennifer Yourkavitch 

ICF International 

Rockville, Maryland, USA 

August 2016 

Corresponding author: Lindsay Mallick, International Health and Development, ICF International, 530 

Gaither Road, Suite 500, Rockville, MD 20850, USA; phone: +1 301-572-0211; fax: +1 301–572-0950; 

email: Lindsay.Mallick@icfi.com 
Acknowledgment: The authors would like to thank Clara Burgert-Bruker and Trinadh Dontamsetti for 

using GPS data to calculate population density around SPA facilities; Clara Burgert-Bruker for providing 

malaria endemicity data around SPA facilities in Kenya using Kenya 2010 MIS data; Lia Florey for 

providing consultation on appropriate use of malaria-related data and providing guidance and insight on 

malaria-related national policies; Mai Do and Hamdy Moussa for their thoughtful reviews and comments, 

which improved the quality of this paper; Tom Pullum and Shireen Assaf for advice and feedback on data 

analysis; and Bryant Robey for editorial advice. 

Editor: Diane Stoy 

Document Production: Natalie La Roche 

This study was conducted with support provided by the United States Agency for International 

Development (USAID) through The DHS Program (#AIDOAA-C-13-00095). The views expressed are 

those of the authors and do not necessarily reflect the views of USAID or the United States Government. 

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. For additional information about The DHS Program contact: 

DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA. Phone: +1 

301-407-6500; fax: +1 301-407-6501; email: reports@dhsprogram.com; Internet: www.dhsprogram.com. 

Recommended citation: 

Mallick, Lindsay, Rebecca Winter, Wenjuan Wang, and Jennifer Yourkavitch. 2016. Integration of 

Infectious Disease Services with Antenatal Care Services at Health Facilities in Kenya, Malawi, and 

Tanzania. DHS Analytical Studies No. 62. Rockville, Maryland, USA: ICF International. 
iii 

Contents 

Tables ............................................................................................................................................................................ v 

Figures .........................................................................................................................................................................vi 

Abstract .......................................................................................................................................................................xi 

Executive Summary ................................................................................................................................................. xiii 

Introduction ................................................................................................................................................. xiii 

Methods ....................................................................................................................................................... xiii 

Results ......................................................................................................................................................... xiii 

Discussion and Conclusion .......................................................................................................................... xiv 

1. Introduction .......................................................................................................................................................... 1 

1.1. Background: ANC Utilization and HIV, TB, and Malaria Prevalence during Pregnancy ................ 1 

1.2. Integrated Care and How Services are Integrated ............................................................................. 4 

1.3. Rationale for This Study ................................................................................................................... 6 

2. Data and Methods ................................................................................................................................................ 7 

2.1. Data ................................................................................................................................................... 7 

2.2. Methods ............................................................................................................................................ 7 

3. Results ................................................................................................................................................................. 13 

3.1. Facilities and Providers That Provide ANC and Infectious Disease Services ................................. 13 

3.2. Integration within Facilities ............................................................................................................ 23 

3.3. Integrated Services Observed in ANC ............................................................................................ 39 

4. Discussion ............................................................................................................................................................ 51 

4.1. Overview of Findings ...................................................................................................................... 51 

4.2. ANC and PMTCT ........................................................................................................................... 51 

4.3. ANC and TB/HIV ........................................................................................................................... 53 

4.4. ANC and Malaria ............................................................................................................................ 53 

4.5. Strengths and Limitations ............................................................................................................... 54 

4.6. Conclusions ..................................................................................................................................... 55 

References .................................................................................................................................................................. 57 

Appendix .................................................................................................................................................................... 63 

v 

Tables 

Table 1. Selected indicators of maternal health, malaria, HIV, and TB in Kenya, Malawi, 

and Tanzania ....................................................................................................................... 2 

Table 2. Integration indicators and definitions, calculated as a percent among facilities 

providing ANC with integration items available on the day of the survey ......................... 9 

Table 3a. Among facilities that provide ANC, percentage that provide integrated services with 

PMTCT, by background characteristics, Kenya SPA 2010 .............................................. 24 

Table 3b. Among facilities that provide ANC, percentage that provide integrated services with 

PMTCT, by background characteristics, Malawi SPA 2013-14 ....................................... 25 

Table 3c. Among facilities that provide ANC, percentage that provide integrated services with 

PMTCT, by background characteristics, Tanzania SPA 2014-15 .................................... 26 

Table 4a. Among facilities that provide ANC, percentage that provide integrated services with 

TB/HIV, by background characteristics, Kenya SPA 2010 .............................................. 28 

Table 4b. Among facilities that provide ANC, percentage that provide integrated services with 

TB/HIV, by background characteristics, Malawi SPA 2013-14 ....................................... 29 

Table 4c. Among facilities that provide ANC, percentage that provide integrated services with 

TB/HIV, by background characteristics, Tanzania SPA 2014-15 .................................... 30 

Table 5a. Among facilities that provide ANC, percentage that provide integrated services with 

malaria, by background characteristics, Kenya SPA 2010 ............................................... 32 

Table 5b. Among facilities that provide ANC, percentage that provide integrated services with 

malaria, by background characteristics, Malawi SPA 2013-14 ........................................ 33 

Table 5c. Among facilities that provide ANC, percentage that provide integrated services with 

malaria, by background characteristics, Tanzania SPA 2014-15 ...................................... 34 

Table 6a. Background characteristics of women observed receiving integrated services during 

ANC visit, Kenya SPA 2010 ............................................................................................ 41 

Table 6b. Background characteristics of women observed receiving integrated services during 

ANC visits, Malawi SPA 2013-14 .................................................................................... 42 

Table 6c. Background characteristics of women observed receiving integrated services during 

ANC visits, Tanzania SPA 2014-15 ................................................................................. 43 

Table 7. Percent of women who discussed or received ITN during first ANC visit, by 

components of malaria integration in Kenya, Malawi, and Tanzania ............................... 46 

Table 8. Percent of women in the second and third trimester who received SP, by components 

of malaria integration in Kenya, Malawi, and Tanzania ................................................... 47 

Table 9. Percent of women asked about their HIV status, received counseling and given an 

HIV test during first ANC visit, by components of PMTCT integration in Kenya, 

Malawi, and Tanzania ....................................................................................................... 47

Table 10. Adjusted odds ratios of receipt of SP in the second or third trimester during ANC 

visits, Kenya and Tanzania ............................................................................................... 49 

Table 11. Adjusted odds ratios of whether a client was asked about their HIV status, received 

counseling, and was given an HIV test during first ANC visit, Tanzania ........................ 50 

Appendix Table 1a. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Kenya .............................................................. 63 

Appendix Table 1b. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Malawi ............................................................ 63 

Appendix Table 1c. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Tanzania .......................................................... 64 
vi 

Appendix Table 2. Distribution of all ANC providers interviewed in SPA surveys, Kenya, Malawi, 

Tanzania ............................................................................................................................ 65 

Appendix Table 3a. Provision of care and training in infectious disease services among providers who 

provide ANC care, Kenya ................................................................................................. 66 

Appendix Table 3b. Provision of care and training in infectious disease services among providers who 

provide ANC care, Malawi ............................................................................................... 67 

Appendix Table 3c. Provision of care and training in infectious disease services among providers who 

provide ANC care, Tanzania ............................................................................................ 68 

Appendix Table 4a. Overall integration of ANC with infectious disease services, by facility background 

characteristics, Kenya ....................................................................................................... 69 

Appendix Table 4b. Overall integration of ANC with infectious disease services, by facility background 

characteristics, Malawi ..................................................................................................... 69 

Appendix Table 4c. Overall integration of ANC with infectious disease services, by facility background 

characteristics, Tanzania ................................................................................................... 70 

Appendix Table 5. Background characteristics of women observed in ANC visits, percent distribution, 

Kenya, Malawi, and Tanzania .......................................................................................... 71 

Appendix Table 6. Mean integration score by services provided during ANC, Kenya, Malawi, and 

Tanzania ............................................................................................................................ 72 

Figures 

Figure 1. Distribution of facilities with ANC by characteristics, Kenya SPA 2010 ........................ 14 

Figure 2. Distribution of characteristics of facilities with ANC, Malawi SPA 2013-14 .................. 15 

Figure 3. Distribution of characteristics of facilities with ANC, Tanzania SPA 2014-15 ............... 16 

Figure 4. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Kenya SPA 2010 ............................................. 17 

Figure 5. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Malawi SPA 2013-14 ...................................... 18 

Figure 6. Percent of facilities with ANC services that also have infectious disease services 

available, by background characteristics, Tanzania SPA 2014-15 ................................... 19 

Figure 7. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Kenya SPA 2010 .............................................. 20 

Figure 8. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Malawi SPA 2013-14 ....................................... 21 

Figure 9. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Tanzania SPA 2014-15 ..................................... 22 

Figure 10. National average integration scores, Kenya SPA 2010 .................................................... 35 

Figure 11. National average integration scores, Malawi SPA 2013-14 ............................................. 35 

Figure 12. National average integration scores, Tanzania SPA 2014-15 ........................................... 36 

Figure 13. Average integration scores of ANC with infectious disease services, by facility 

background characteristics, Kenya SPA 2010 .................................................................. 37 

Figure 14. Average integration scores of ANC with infectious disease services, by facility 

background characteristics, Malawi SPA 2013-14 ........................................................... 38 

Figure 15. Overall integration of ANC with infectious disease services, by facility background 

characteristics, Tanzania SPA 2014-15 ............................................................................ 39 

Figure 16. Average facility integration score by receipt of integrated care among women in 

ANC, Kenya SPA 2010 .................................................................................................... 44 
vii 

Figure 17. Average facility integration score by receipt of integrated care among women in 

ANC, Malawi SPA 2013-14 ............................................................................................. 44 

Figure 18. Average facility integration score by receipt of integrated care among women in 

ANC, Tanzania SPA 2014-15 ........................................................................................... 45 

ix 

Preface 

The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data 

on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, 

HIV/AIDS, malaria, and provision of health services. 

One of the objectives of The DHS Program is to analyze DHS data and provide findings that will be useful 

to policymakers and program managers in low- and middle-income countries. DHS Analytical Studies serve 

this objective by providing in-depth research on a wide range of topics, typically including several countries 

and applying multivariate statistical tools and models. These reports are also intended to illustrate research 

methods and applications of DHS data that may build the capacity of other researchers. 

The topics in the DHS Analytical Studies series are selected by The DHS Program in consultation with the 

U.S. Agency for International Development. 

It is hoped that the DHS Analytical Studies will be useful to researchers, policymakers, and survey 

specialists, particularly those engaged in work in low- and middle-income countries. 

Sunita Kishor 

Director, The DHS Program 

xi 

Abstract 

The disproportionate demand for services related to infectious diseases such as HIV/AIDS, tuberculosis, 

and malaria among pregnant women in sub-Saharan Africa, given limited health facility attendance, drives 

a need to integrate these services with antenatal care (ANC). This paper uses data from Service Provision 

Assessments in Kenya (2010), Malawi (2013-14), and Tanzania (2014-15) to examine aspects of integrating 

services for HIV, specifically prevention of mother-to-child transmission (PMTCT), tuberculosis, and 

malaria into ANC services. For the study, we defined five components of ANC integration with each 

infectious disease service and created an integration score for each infectious disease by averaging the 

components. We examined the extent to which the health facility’s integration capacity was associated with 

selected facility characteristics and women’s receipt of integrated services during ANC visits. Overall, 

facilities with ANC had higher integration scores for PMTCT and malaria than for tuberculosis, although 

availability of the integration components varied by background characteristics across and within countries. 

Logistic regression results show that the ANC-malaria integration score was associated with consuming 

sulfadoxine-pyrimethamine (SP) in Kenya and Tanzania, and the ANC-PMTCT integration score was 

associated with receiving HIV counseling and testing during observed ANC visits in Tanzania. The only 

integration component associated with SP consumption, aside from having SP available, was the presence 

of at least one ANC provider at the facility who also provides malaria services and has recent training in 

these services. The only ANC-PMTCT component with a significant association with observation of HIV 

counseling and testing, except for the availability of HIV rapid diagnostic testing, was having HIV 

counseling and ANC services at the same site. More research is needed to determine the synergies among 

the different aspects of integrated services. 

KEY WORDS: integrated services, infectious disease services, antenatal care, Service Provision 

Assessment, health facilities

xiii 

Executive Summary 

Introduction 

Focused antenatal care (ANC) can provide key services that also prevent the spread of infectious diseases 

(ID), such as HIV/AIDS, tuberculosis (TB), and malaria. Integrating services can help to overcome the 

persistent difficulties in obtaining care, improving health outcomes, and saving clients’ time and money. 

There is a dearth of research and little consensus on the key components of integrated services and the level 

of facility integration that can influence service delivery and outcomes. It is generally agreed that two 

services are “integrated” when they are co-located in the same health facility, and the provider of one service 

can provide or assist with helping the client obtain appropriate services for another. Research has identified 

a continuum of integration among facilities that ranges from a completely vertical structure with no capacity 

for integration to a fully integrated structure. Although combining services may improve service utilization, 

more research is needed to determine how different levels and aspects of integrated care affect service 

delivery and use, as well as health outcomes. 

Methods 

Based on information from Service Provision Assessment (SPA) surveys conducted in Kenya (2010), 

Malawi (2013-14), and Tanzania (2014-15), this study assessed various components of integration and 

overall facility capacity to integrate ID services, specifically prevention of mother-to-child transmission 

(PMTCT) of HIV/AIDS, TB/HIV, and malaria, with ANC services. Five indicators for each of the three ID 

areas were defined based on the World Health Organization (WHO) Service Availability and Readiness 

Assessment. We used these five components to assess service availability and service readiness (defined as 

whether the facility has the means to deliver services) for providing integrated ANC and ID services. We 

calculated an overall score for integration for each ID area with ANC by averaging the five components 

and multiplying by 100 to standardize the scores. 

This study analyzed the three populations assessed by SPA surveys: facilities, providers, and clients. First, 

we describe the background characteristics of facilities that offer ANC services in the three countries, 

examine the availability of ID services at these facilities, and present the percentage of ANC providers who 

also offer and have recent training in each ID area. Second, we examine patterns in coverage of individual 

integration components and overall integration scores (for each ID service with ANC) across facility 

characteristics. Finally, we examine the association between facility integration and women’s receipt of 

integrated services during ANC visits. To do this, we examine three indicators for women’s receipt of 

integrated care: the provision of counseling or distribution of insecticide-treated mosquito nets (ITNs), 

direct observation of sulfadoxine-pyrimethamine (SP) consumption, and HIV counseling and 

testing (HCT). 

Results 

There are both similarities and differences among the three countries in the overall availability of ID 

services at facilities with ANC, health worker provision of and training in ID, capacity to provide integrated 

services, and observed integration of services during ANC visits. Malaria services are almost universally 

available and PMTCT services are widely available in all three countries. However, TB services are not 

common, particularly in areas with low population density, and are least common in Tanzania. Services for 

PMTCT and TB are more available in higher-level facilities in all three countries; in Kenya and Malawi, 

the services are more available in public than private facilities. ANC providers in each country more often 

provide and are recently trained in PMTCT, and are less trained in treating malaria; few are trained in 

treating TB. At the national level in each country, integrated services for ANC with TB/HIV are least 

common; the average PMTCT integration score is higher in Malawi and Tanzania than in Kenya, although 
xiv 

integration with malaria is highest in Kenya. The coverage of integrated malaria services varies 

substantially within the countries. Among women observed in ANC, receipt of integrated services varied 

by the specific service and country. 

In Malawi, where PMTCT integration is higher than in the two other countries, observation of HCT during 

ANC visits is lowest and was observed in only 7% of visits. The study found that in Malawi HIV testing 

occurs in another room prior to the ANC visit. Thus, while facilities are ready to provide integrated services 

in the same facility, receipt of integrated care was not recorded in the survey. 

After controlling for the characteristics of women, providers, and facilities, total facility integration and 

some integration components are significantly associated with receiving integrated care for consuming SP 

in Kenya and Tanzania, as well as for HCT in Tanzania. For HCT in Tanzania, the only significant predictor 

of receipt of HCT was the integration score. When a model included only the integration components, only 

one remained significantly associated with receipt of HCT: ANC and PMTCT services at the same site. 

Receipt of SP during ANC was significantly associated with overall integration of ANC with malaria in 

Kenya and Tanzania in the multivariable models. When analyzed by integration component, having at least 

one ANC provider who provides and was recently trained in malaria services at the facility was significantly 

associated with increased SP consumption. 

Conclusion 

The relatively high prevalence of the infectious diseases studied in this report (HIV, TB, and malaria), 

coupled with the recommendation for focused ANC in areas where women have limited access to care, 

such as Kenya, Malawi, and Tanzania, highlights the need to scrutinize how services for these conditions 

are integrated and how best to capitalize on the time spent at a facility. Our study finds variation in the 

availability of components of integration and in the average integration scores across the three countries 

and the three diseases studied. Regression analysis shows that having trained staff on-site and providing 

key services under one roof may be the key components in integrated services, although more research is 

necessary to confirm this finding. When considering availability and provision of integrated services, 

particularly for ANC and malaria, it is important to consider regional variations in prevalence and 

corresponding policies that may affect the provision of services. The study highlights the need for more 

precise definitions and survey tools that measure integration. 
1 

1. Introduction 

Pervasive inequities in access to health care characterize many developing countries. Many people face 

barriers to obtaining care for reproductive, maternal, newborn, and child health (RMNCH) and also to 

receiving services for HIV/AIDS, tuberculosis (TB), and malaria. Joining or integrating service delivery 

may be a way to help overcome barriers to care and to maximize health outcomes (PMNCH 2013; UNAIDS 

2011). Integrating interventions for HIV, TB, malaria, and RMNCH throughout the continuum of care can 

address critical gaps in service delivery, increase coverage, and save lives and money (Darmstadt et al. 

2005; Lassi, Haider, and Bhutta 2010; Pattinson et al. 2011; PMNCH 2013; WHO 2010). 

Pregnant women are among the most vulnerable to these diseases. Pregnant women are at higher risk of 

contracting malaria due to lowered immune function, can pass HIV/AIDS to their fetus or infant through 

vertical transmission, are susceptible to acquiring HIV from blood transfusions resulting from 

complications during birth, and can be more susceptible to TB infection in the postpartum period (Bates et 

al. 2004). Antenatal care (ANC) is a strategic platform for delivering critical tests, counseling, and 

treatment, and for establishing a relationship between mothers and the health system, a relationship that 

influences future care seeking (Abrams et al. 2007; An et al. 2015; Myer et al. 2005; Stinson, Jennings, and 

Myer 2013). Thus, ANC is a key point in the continuum of care throughout a mother and child’s lifetime—

from services during pregnancy, delivery, and the postpartum period to newborn and child health services, 

adolescent health, and family planning. The ability to care for all needs, including the prevention and 

treatment of infectious diseases, should be incorporated in these contacts because it can affect the quality 

and satisfaction with service delivery and encourage the continuation of services (Kerber et al. 2007). Yet, 

integrating ANC with services for infectious disease, specifically HIV, TB, and malaria, is understudied. 

This report uses SPA data from Kenya (2010), Malawi (2013-14), and Tanzania (2014-15) to report facility 

capacity to provide integrated services for HIV, TB, and malaria with ANC. We assessed the extent of 

integration by various aspects of integration as well as the overall level of facility integration to identify 

potential associations with observed integration of service delivery during ANC visits. 

1.1. Background: ANC Utilization and HIV, TB, and Malaria Prevalence during Pregnancy 

1.1.1. ANC: Recommendations and utilization 

About 25% of maternal deaths occur during pregnancy, with variance by region according to the prevalence 

of unsafe abortion, violence, and disease (WHO 2005). Between a third and half of maternal deaths from 

antepartum hemorrhage and hypertension result from inadequate care during pregnancy (Khan et al. 2006). 

Over 2 million women and children die from AIDS, TB, and malaria each year (PMNCH 2013); malaria 

and HIV/AIDS are associated with increased pregnancy complications and death (PMNCH 2006). Maternal 

infections during pregnancy can cause antepartum stillbirths (PMNCH 2006).

High-quality ANC provides the care that mothers need during pregnancy. Such care improves the health 

and survival of infants directly by reducing stillbirths and neonatal deaths and indirectly by providing an 

entry point for health contacts (PMNCH 2006). In addition, ANC improves the health and survival of 

mothers by diagnosing and treating infections and other complications that cause morbidity and mortality. 

Focused ANC services provide specific evidence-based interventions for women through a number of 

essential elements: the diagnosis and management of pregnancy-related complications (pre-eclampsia), 

screening for infectious diseases (syphilis and HIV) and other conditions (anemia); preventive measures 

such as intermittent preventive treatment with sulfadoxine-pyrimethamine (IPTp-SP) and insecticidetreated mosquito nets (ITNs); and advice and support for women and families (healthy behaviors) that are 

offered at certain critical times during a pregnancy (PMNCH 2006). Screening for and treating infections, 
2 

including TB and malaria, is part of the focused ANC protocol (PMNCH 2006), although effective coverage 

is hindered by uneven ANC attendance.

WHO recommends that mothers make at least four antenatal visits (PMNCH 2006). Although a high 

percentage of mothers attend at least one antenatal visit, ANC attendance gradually decreases as pregnancy 

progresses (Kinney et al. 2010). Table 1 shows the prevalence of ANC attendance in each country studied. 

According to the most recent Kenya DHS, 96% of women in Kenya attended at least one ANC visit, but 

only 58% attended the recommended four visits (KDHS 2014). Similar percentages of women attended at 

least four ANC visits in Malawi (46%) and Tanzania (43%). Although ANC could be an ideal platform for 

integrated care, participation with at least four visits is low, both in these countries and in sub-Saharan 

Africa overall. This limits the ability to provide continuous, integrated care of infectious diseases within 

ANC visits (Kinney et al. 2010). The need becomes apparent as we explore the burden of ID within this 

context and by geographic area.

Table 1. Selected indicators of maternal health, malaria, HIV, and TB in Kenya, Malawi, and Tanzania

Kenya DHS 

2014 

Malawi DHS 

2010 

Tanzania AIS/MIS 

2011-12 

At least one ANC visit in the last pregnancy 95.7 97.6 97.7 

Four or more ANC visits in last pregnancy 57.6 45.5 42.8 

First ANC visit before four months pregnant 19.7 12.4 19.7 

Facility delivery (all live births in the five 

years preceding survey) 

61.2 73.2 50.2 

Skilled birth attendant (all live births in the 

five years preceding survey) 

61.8 71.3 47.6 

Malaria prevalence in children under age five 5.0 33.2 4.1 

Pregnant women who slept under an ITN the 

night before the survey 

57.8 35.2 56.9 

SP consumption during ANC 50.8 85.8 60.5 

SP 2+ doses, at least 1 dose during ANC 34.7 53.8 26.3 

Pregnant women counseled for HIV during 

ANC visit 

67.5 85.7 64.0 

Pregnant women counseled and tested for 

HIV during ANC visit and who received 

results 

66.9 79.0 55.2 

HIV prevalence in women 8.0 (CI: 6.7 – 9.3) 12.9 (CI: 11.6 – 14.2) 6.2 (CI: 5.5 – 6.8) 

TB prevalence 0.3 0.3 0.5 

% TB patients who are HIV-positive 36.0 54.0 35.0 

Note: Data on malaria parasitemia are from the most recent MIS or AIS/MIS: Kenya in 2015, Malawi in 2014, and 

Tanzania 2011-12 (same as other data in table); most recent HIV prevalence data for Kenya are from the 2008-09 

KDHS; data on indicator for four or more ANC visits during last pregnancy resulting in a live birth in the five years 

preceding the survey for Tanzania are from the 2010 TDHS; DHS data are collected from The DHS Program 

STATcompiler: http://beta.statcompiler.com/; Tuberculosis data from the WHO Global Tuberculosis Report 2015 

(WHO 2015b). 

1.1.2. Infectious diseases affect maternal and child health 

1.1.2.1. HIV/AIDS and PMTCT 

Prevalence of HIV is high among women in the countries studied, at 6% in Tanzania, 8% in Kenya, and 

13% in Malawi (Table 1). In countries with high rates of HIV, HIV-associated infections exceed direct 
3 

causes of maternal death from hemorrhage, hypertension, and sepsis. This suggests that clinical HIV care 

should be integrated into maternity services (Madzimbamuto, Ray, and Mogobe 2013). Initiating 

antiretroviral therapy (ART) during pregnancy is important for preventing PMTCT and reducing maternal 

and infant morbidity and mortality related to HIV (Coutsoudis et al. 2010; Kuhn et al. 2010; Stinson, 

Jennings, and Myer 2013). In most of sub-Saharan Africa, the design of health systems is a barrier to ART 

during pregnancy because services are not co-located (Stinson, Jennings, and Myer 2013). The recognition 

that providing ART services to pregnant women requires additional counseling and interventions 

appropriate for pregnancy has prompted calls for integrating service provision (Abrams et al. 2007; Myer 

et al. 2005; Rosenfield and Figdor 2001; Stinson, Jennings, and Myer 2013). Since 2011, more than 20 

countries, including Malawi, Kenya, and Tanzania, have adopted Option B+ policies, under which women 

receive HIV testing at the first ANC visit; if found HIV-positive, the women then begin ART for life 

(Chimbwandira et al. 2013; IATT 2016). Option B+ is a strategy for enrolling pregnant women in PMTCT 

programs, which include interventions to prevent mother-to-child-transmission during pregnancy, labor and 

delivery, and breastfeeding. Although Tanzania adopted the Option B+ policy, a study by An et al. (2015) 

found supply-side deficiencies in inputs and processes to deliver HIV counseling and testing (HCT) during 

ANC, which affected the quality of care. 

1.1.2.2. Tuberculosis 

Tuberculosis is a disease of poverty exacerbated by malnutrition and food insecurity. The disease affects 

the most vulnerable (WHO 2015a) and is one of the top five killers of women age 20-59. An estimated 3.2 

million women were sick with TB in 2014 (WHO 2015b). There is often co-morbidity between TB and 

HIV. There were 140,000 TB deaths among HIV-positive women in 2014, which is nearly 30% of all TBrelated deaths among women and about a third of all AIDS-related deaths among women, almost all in 

Africa (WHO 2015b). In Malawi, more than half of TB patients are HIV-positive, and about a third in 

Kenya and Tanzania (Table 1). Like HIV/AIDS, TB is associated with stigma and discrimination (WHO 

2015b). Among mothers, TB affects both maternal and fetal health. There is a six-fold increase in perinatal 

death and two-fold risk of preterm birth and low birth weight, with a 300% risk of maternal and infant 

mortality for pregnant women with TB who are HIV-positive (WHO 2015b). In Africa, TB is 10 times 

more prevalent among pregnant women with HIV than pregnant women without HIV (WHO 2015b). 

Documented barriers to TB-PMTCT service integration include a lack of skilled providers, supervision of 

providers, the physical layout of service provision sites, and service delivery mechanisms (Uwimana and 

Jackson 2013). 

1.1.2.3. Malaria 

More than 30 million pregnant women live in malaria-endemic areas in sub-Saharan Africa (PATH 2014). 

Adult prevalence is less studied compared with child prevalence, although in Kenya one county reported 

an adult prevalence of 28%, with women 50% more likely to be infected than men (Jenkins et al. 2015). 

Malaria in pregnancy increases the risk of maternal anemia, miscarriage, stillbirth, prematurity, low birthweight, and death for mothers and newborns (Dellicour et al. 2015). Interventions include prevention with 

IPTp-SP and ITNs, as well as prompt diagnosis and treatment (WHO 2014). The timing and number of 

ANC visits is critical for prevention, early diagnosis, and treatment of malaria (WHO 2014). Given the 

small percentage of women who make more than one visit, however, ANC was found to be more effective 

for ITN distribution than for IPTp-SP because ITNs are delivered at one time while IPTp-SP requires 

follow-up (Hill et al. 2013). Among the countries studied, the percentage of women sleeping under an ITN 

each night varied from 35% in Malawi to 58% in Kenya (Table 1). Only one-quarter (26%) of women in 

Tanzania and about a third (35%) of women in Kenya received two doses of IPTp-SP (at least one dose 

during ANC) during their last pregnancy within the last five years, while just over half (54%) did so in 

Malawi (Table 1). These percentages are much lower than the percentage of women receiving at least one 

dose during ANC, which ranges from 51% in Kenya to 86% in Malawi (Table 1). Efforts to increase IPTp-
4 

SP distribution have shifted to the community level in some places; one study found that community health 

workers stocked with IPTp-SP had a positive impact on attendance of the recommended four ANC visits 

(PATH 2014). In addition, co-infection with malaria and HIV accelerates the spread of both diseases (AbuRaddad, Patnaik, and Kublin 2006). 

1.2. Integrated Care and How Services are Integrated 

Integrating services can increase health care coverage by delivering the services in a more cost-effective 

way (Bollinger and Adesina 2013). Two services are “integrated” when they are offered at the same health 

facility during the same hours, and the provider of one service encourages clients to consider using the other 

service during the visit (Foreit, Hardee, and Agarwal 2002). While practitioners generally agree with this 

premise, it has been difficult to precisely define “integration” in practice (Ahgren and Axelsson 2005; Uyei 

et al. 2014). A systematic review found few examples of either complete integration or complete nonintegration (Atun et al. 2010). The research acknowledged a continuum of integration and found that the 

dichotomy between vertical and horizontal programming is not rigid and that the extent of integration varies 

considerably among programs (Atun et al. 2009). That continuum describes the two extremes as full 

segregation (or vertical programming) or full integration of programs, joined together by the middle ground 

of linkage and coordination among networks (Atun et al. 2009): 

Full segregation > linkage and coordination among networks > full integration 

Integration is one of the seven core principles of the U.S. Global Health Initiative (US Government 2012). 

The WHO Consolidated Guidelines for ART recommended strategies for integration that included 

integrating PMTCT programs in maternal, newborn, and child health (MNCH) facilities (WHO 2013a). 

Analyses of integration efforts have examined how intervention elements can be integrated within the six 

health system building blocks that cut across all services: stewardship and governance; financing; planning; 

service delivery (structural, human resources, shared infrastructure, operational integration, 

referral/counter-referral systems, guidelines, procurement, and supply chain management); monitoring and 

evaluation (M&E); and demand generation (Atun et al. 2010). There are also supply-side needs such as 

infrastructure, space, commodities, and staff (Shigayeva et al. 2010). Integrated lab services also need 

adequate infrastructure, assays, reagents, maintenance, personnel, and policies (Birx, de Souza, and 

Nkengasong 2009). Some have observed that the influx of HIV/AIDS funding to establish labs threatens 

the existing fragile labs and makes service integration even more critical (Mbah et al. 2014). 

1.2.1. Benefits of integrated care 

There is some evidence that integrated care improves quality of services, outcomes, and saves money in 

some settings. Specifically, one study conducted by Kruk et al. (2015) found that integration of 

PMTCT/ART services with ANC/PNC services increases the quality of the RMNCH services, while 

another study found better outcomes (adherence to ARTs) and cost savings where HIV and MNCH services 

were integrated (Bollinger and Adesina 2013). Decreased patient time at a facility, increased efficiency, 

and closer patient-provider relationships all led to greater patient satisfaction (Winestone et al. 2012). In 

addition, providers believed that the improved confidentiality and decreased stigma made women more 

likely to initiate and adhere to ART (Winestone et al. 2012). A study in Malawi found that integration of 

PMTCT services into ANC increased participation in ANC, facility delivery, and postnatal care. There was 

also an increase in family planning consultations, treatment for sexually transmitted infection (STI), and 

testing for HIV-exposed infants, as well as a decrease in the proportion of infants who tested HIV-positive 

(Van den Akker et al. 2012). In South Africa, integration of ART into ANC increased initiation of treatment 

during pregnancy, when compared with vertical service provision, whether near or far from the ANC 

(Stinson, Jennings, and Myer 2013). A review of four studies found that ART integration in ANC clinics 

led to higher rates of ART initiation and coverage, and similar retention rates were found in referral-based 
5 

models of service provision (Suthar et al. 2013). There is also some evidence in Kenya of greater 

satisfaction among HIV-positive women who attended integrated services compared with those who 

attended non-integrated services (Vo et al. 2012). Research in Western Kenya found that women said that 

testing for disease, including HIV, was an important element of ANC (Mason et al. 2015). Testing for HIV 

also improved when it was integrated into routine TB services, while joint services improved adherence to 

TB and ART treatment among co-infected patients (Uyei et al. 2011). Although the benefits of integration 

of ANC and PMTCT have been well studied, a recent systematic review found no randomized controlled 

trial that attempted to measure the impact of integration of ANC on malaria or TB (de Jongh et al. 2016). 

More than half of development aid for reproductive health in 2009 and 2010 was allocated for HIV 

prevention, treatment, and care for women of reproductive age (NIDI 2010; Patel et al. 2009; PMNCH 

2013). Integrating services could leverage that investment to increase quality across the health system. With 

integration, laboratories use the same equipment for multiple health services such as HIV/AIDS, TB, and 

malaria, and laboratory upgrades realize multiplicative benefits (Birx, de Souza, and Nkengasong 2009). 

Further, vertical programs can have negative effects. These include the diversion of funding from the 

general health system and other services to support HIV services, the concern that opt-out HIV testing in 

ANC could reduce the use of pregnancy care because women would not want to bear the burden of HIV 

stigma, and increased demands on an understaffed workforce (Van den Akker et al. 2012). Such negative 

effects support the argument for service integration. 

1.2.2. Limitations of and challenges to integrated care 

Integrated care faces a number of limitations and challenges. Research by Winestone (2012) and by An and 

colleagues (2015) found that the integration of HIV and ANC services increased the workload of health 

care providers. Winestone (2012) also reported that integration can result in longer appointment times, 

which might lead to inadvertent disclosure of woman’s HIV status. An and colleagues (2015) found lower 

motivation among staff; providers gave only brief messages, despite the fact that they were knowledgeable. 

In these environments providers’ workloads can be overstretched, which leads to longer waiting times for 

women (An et al. 2015; Brugha et al. 2010; Simba et al. 2010; Walsh et al. 2010), while there may be 

overcrowding, which discourages women from remaining or returning for care (An et al. 2015). Concerns 

remain about the effect of integration on the quality of health services (Chi, Bolton-Moore, and Holmes 

2013), and health providers disagree about the potential benefit realized from increasing their skills and 

variety of work (Mutemwa et al. 2013). 

1.2.3. Measuring health service integration 

A systematic analysis of integration considers the types of services integrated and the outcomes of interest. 

The ultimate goal is improvement in measures of patient care and its cost (Devers et al. 1994; StrandbergLarsen and Krasnik 2009). There are multiple methods of analysis and several definitions of integration 

(Ahgren and Axelsson 2005; Atun et al. 2010; Strandberg-Larsen and Krasnik 2009). More than 20 

measurement methods are available and some are highly developed. Application is based on an explicit 

conceptual framework with the process objective of refining and validating existing methods rather than 

developing a new method (Strandberg-Larsen and Krasnik 2009). 

One study of the integration of HIV and TB care in South Africa used a comprehensive survey that rated 

35 items related to different aspects of integration of HIV and TB care on a Likert scale (Uyei et al. 2014). 

Principal components analysis established eight factors of integration, including service availability at the 

facility, routine screening, the same clinician providing care for both diseases, and patient receipt of care 

for both diseases in a single visit. The researchers tested the differences of mean scores between facilities 

where both TB and HIV services were available and facilities with only one or the other; co-location of 
6 

services alone did not ensure integrated care, since some clinics with single services scored better on some 

factors than clinics with both services. 

1.3. Rationale for this Study 

A number of issues highlight the need for this research: The increased vulnerabilities associated with 

HIV/AIDS, TB, and malaria among pregnant women; the high burden of these diseases in Kenya, Malawi, 

and Tanzania; the potential benefits of integrating services; and the lack of consensus about the definition 

of and best methods for assessing the most important components that integrate services for infectious 

diseases with provision of ANC. Although there is broad agreement about the potential for integrated 

services that could positively affect health outcomes while containing costs, there is scant research about 

the most critical aspects of integrated services and the standardization of critical aspects across the 

integration of different services. As mentioned, Uyei and colleagues (2014) found that co-location of 

services was insufficient to provide integrated care, and that a joint service delivery model was optimal; 

however, this study focused only on the integration of TB and HIV/AIDS care. A systematic review (Dudley 

and Garner 2011) found some evidence that adding services or linking to them may improve service 

utilization, although there was no evidence that fuller integration improves service coverage or health status. 

The review concluded that more studies of different strategies are needed. Further, a study in Swaziland 

found that HIV-integrated services were not as integrated in practice as they claimed to be (Church et al. 

2015). 

Additional research can serve as a reference point for the potential of integrated services, the degree to 

which integration translates to actual service delivery, and how the various components may influence 

service delivery independently or as a combined package. Based on the available indicators measured by 

the Service Provision Assessment (SPA) surveys, this study identifies potential components of integration 

for HIV, TB, and malaria with ANC services, and provides a baseline assessment of the level of integration 

in health facilities in Kenya, Malawi, and Tanzania. In addition, the study examines whether women are 

receiving integrated services and if the availability of various aspects of integration or overall level of 

integration are related to women’s receipt of services. These findings will inform future research and 

investments in strengthening health system that support integrated service delivery. 
7 

2. Data and Methods 

2.1. Data 

This study used data from Kenya, Malawi, and Tanzania, where there is a high burden of HIV/AIDS, TB, 

and malaria and a recent health facility survey. The DHS Program conducted health facility surveys—

Service Provision Assessments—in Kenya (2010), Malawi (2013-14), and Tanzania (2014-15) in 

collaboration with the host countries. The SPA surveys include several questionnaires that collect 

information about facilities with an inventory questionnaire, which includes questions about availability of 

health services, infrastructure, commodities, procedures, and resources; the health worker interview, which 

captures characteristics, qualifications, and satisfaction of providers; and the observation checklist, which 

identifies the content and quality of selected consultations. The observation of consultations is typically 

specific to visits for ANC, child health, and family planning, although some SPA surveys include 

observations of other types of visits such as birth and delivery services. Clients who were observed during 

a visit are eligible for an exit interview to assess the client’s perceptions of the visit. 

The SPA surveys are usually conducted with a sample of formal-sector health facilities in a given country; 

this was the case for the SPA surveys conducted in Kenya and Tanzania that were used in this study. A 

random subset of facilities are selected from a list of all facilities in the country, with the potential of overselection or over-sampling of facilities in regions with small populations or among facility types that are 

less common throughout the country, such as hospitals. In Malawi, the SPA is a complete census of facilities 

in that the survey included every formal-sector health facility in the country. 

After selecting the facilities, a total of 8-15 providers were randomly selected from a list of providers within 

each facility. Priority is given to those who conduct consultations, with a goal that three will be providers 

of services in the areas of ANC, family planning, and child health. Each health worker who completes the 

interview is observed during his or her consultations with up to five clients, if possible. Thus, the interviewer 

observes a maximum of 15 consultations for each service. Clients for these observations are selected from 

a sample of clients attending visits that day, with priority given to new clients or clients attending the first 

ANC visit for their current pregnancy. All clients observed are offered the opportunity to participate in the 

exit interview. 

This study uses data from the inventory questionnaire, health worker interview, the observation checklist, 

and the exit interview from facilities and health workers who provide ANC services and observation of 

women in ANC visits. In Kenya, this included 509 health facilities, 1,520 health workers, and 1,409 women 

observed in ANC visits; in Malawi, 632 facilities, 1,137 providers, and 2,068 women; and in Tanzania, a 

total of 1,005 facilities, 4,195 providers, and 4,007 women. 

2.2. Methods 

2.2.1. Construction of variables 

2.2.1.1. Integration 

A comprehensive review of each SPA survey identified questions that pertain to integrated services at the 

facility level and with observation of ANC visits. Five indicators for integration with each of the three 

infectious diseases (IDs) in this report are described in Table 2. It is important to note that the Kenya SPA 

was conducted prior to a major revision of SPA instruments. Although most questions between the surveys 

are the same or comparable, there are some discrepancies between surveys. Those are noted in Table 2. In 

addition to selecting indicators based on the availability of information in SPA surveys, we based indicator 

construction on current WHO recommendations for each ID, as defined in several WHO documents: A 
8 

Guide for Monitoring and Reporting on the Health Sector Response to HIV/AIDS (WHO 2011); A Strategic 

Framework for Malaria Prevention and Control during Pregnancy in the African Region (WHO 2004); 

WHO Policy Brief for the Implementation of Intermittent Preventive Treatment in Malaria in Pregnancy 

using Sulfadoxine-pyrimethamine (IPTP-SP) (WHO 2014); and the Service Availability and Readiness 

Assessment (SARA) Reference Manual (WHO 2013b). 

The variables for integration of ANC with PMTCT and TB/HIV are adapted from the indicators in the 

WHO SARA Reference Manual (2013b) and the WHO Guide for Monitoring and Reporting (WHO 2011). 

These documents designate recommended measures for PMTCT that include providing HIV testing and 

counseling during pregnancy and offering ARTs on site. Specifying that PMTCT should be available at the 

same site as ANC is specifically mentioned in the SARA Manual, and is also noted as a core element of 

integrated care (Foreit, Hardee, and Agarwal 2002; WHO 2013b). The PMTCT recommendations for 

appropriate maternal ART medications have changed in the last decade; thus, the national guidelines for 

each country nearest to the time of the survey guided the creation of ART variables for PMTCT (Kenya 

2005; Malawi 2011a; Tanzania 2012). The high co-infection with TB among people living with HIV 

prompted WHO to recommend that HIV patients should be screened for TB and newly enrolled HIV 

patients provided with TB prophylaxis (WHO 2013a). The WHO SARA Reference Manual also includes 

an indicator for screening for HIV among TB patients (WHO 2013b). 

The indicators related to malaria are taken from WHO guidelines (WHO 2014). The current 

recommendation for IPTp-SP is that women consume IPTp-SP during each ANC visit in the second and 

third trimester no more than once per month under direct observation. WHO also recommends that all 

pregnant women use ITNs throughout their entire pregnancy. In addition to the WHO recommendation of 

“prompt and effective treatment of malaria in pregnant women” (WHO 2014:1), the variable for provision 

and availability of rapid diagnostic testing (RDT) for malaria was included in response to the growing 

concern about SP resistance and the waning effectiveness of IPTp-SP. One proposed solution currently 

under study is the effectiveness of providing RDT and providing treatment only as needed (Williams et al. 

2016). 

Variables were then constructed to mimic the WHO domains that are used to calculate health service 

readiness for independent services (WHO 2013b). The domains include whether or not the facility provides 

the service (availability) and if the facility has the appropriate equipment or supplies necessary to carry out 

these activities (readiness). For each service area in the manual, indicators fall into four domains for 

readiness: staff and training, equipment, diagnostic, and medicines and commodities. The integration 

indicators used in this report follow a similar format to measure integration service readiness. An additional 

domain accounted for availability of both services. Although the WHO SARA Reference Manual 

differentiates between availability and readiness, this report examines elements of both availability and 

readiness-like indicators as components of integration and then combines these components to create an 

integration score that describes a facility’s capacity to provide integrated services. 

For each ID area, we calculated an overall integration score with integration of ANC. This was done by 

summing all five components within each area. To standardize the scores on a scale of 0 to 100 for ease of 

comparability, we divided the calculated score by five to create an average and then multiplied by 100. This 

provided an average integration score for each facility, which represents both availability and readiness to 

provide integrated services at the facility level. 
9 

Table 2. Integration indicators and definitions, calculated as a percent among facilities providing ANC 

with integration items available on the day of the survey 

 Indicator Definition Notes 

PMTCT Integration 

Availability ANC and HCT 

services 

HCT and ANC available at least 3 days per 

week 

 

Staff and Training Trained staff1 At least one ANC provider who also provides 

and has recent training in PMTCT services 

In Kenya, recent training refers to training 36 

months prior to the survey; in Malawi and 

Tanzania, it is 24 months. 

Equipment Same site PMTCT same site as ANC Service If the facility offers HCT to pregnant women at the 

same site as ANC site 

Diagnostics HIV testing Offer HCT during ANC and have RDT or 

functioning microscopy with reagents available; 

must be able to conduct the test at the PMTCT 

site or laboratory within the facility 

Diagnostic capacity includes RDT kit or ELISA 

test with ELISA washer, ELISA reader, incubator, 

specific assay kit. 

Medicine and 

Commodities 

PMTCT ART Provide ART as part of PMTCT and have 

recommended ART available 

The recommended ART for PMTCT varies by 

country and year. This variable was created 

following national guidelines for each country at 

the time of the survey. 

TB/HIV Integration

Availability ANC and TB 

services 

Offer TB services and ANC at least 3 days per 

week 

The question for number of days TB services are 

provided is not included in the Kenya SPA; the 

substitute indicator for Kenya is if the facility 

offers both services. 

Staff and Training Trained staff1 At least one ANC provider who also provides 

and has recent training in TB/HIV services 

In Kenya, recent training is in the 36 months prior 

to the survey, in Malawi and Tanzania, it is 24 

months. Recent training can include any aspect of 

TB for Kenya. For Malawi and Tanzania, training 

specifically refers to management of TB/HIV coinfection. 

Equipment NA No additional equipment recommended 

Diagnostics TB screening 

system and TB 

diagnostics for 

HIV+ patients 

Have an observed system for screening for TB 

for HIV+ patients and have TB diagnostic 

capacity 

Diagnostic capacity includes: Light or fluorescent 

microscope, slides, and ZN stain OR fluorescent 

microscope, slides, and auramine-rhodamine 

stain. 

HIV screening 

system and HIV 

diagnostics for 

TB+ patients 

Have an observed system for diagnosing HIV 

among TB+ patients and have HIV diagnostic 

capacity 

In Kenya, the questionnaire asks if testing is done 

routinely versus selectively, while in Malawi and 

Tanzania, the question asks if there is a system 

for testing. 

Medicine and 

Commodities 

TB prophylaxis 

for HIV+ patients 

Provide TB treatment for HIV+ patients and 

have preventive TB medicines with at least one 

in stock and valid 

TB prophylactic medication given to HIV+ patients 

is isoniazid and vitamin B6. 

Malaria Integration 

Availability ANC and 

Malaria services 

Offer malaria services and ANC at least 3 days 

per week 

The question for number of days malaria services 

are provided is not included in the Kenya SPA; 

the substitute indicator for Kenya is if the facility 

offers both services. 

Staff and Training Trained staff1 At least one ANC provider who also provides 

and has recent training in malaria services 

In Kenya, recent training is in the 36 months prior 

to the survey; in Malawi and Tanzania, it is 24 

months. Recent training can include any aspect of 

malaria. 

Equipment NA No additional equipment recommended 

Diagnostics Malaria RDT Routinely conduct RDT and have RDT 

available 

Routinely provision of RDT can be observed or 

reported. 

Medicine and 

Commodities 

ITNs Routinely distribute or counsel on ITNs and 

have ITN available 

In Malawi or Tanzania the question pertains to 

counseling on ITN use; in Kenya, the most 

comparable question pertains to distribution only. 

IPTp Have SP available Observed in service area or where routinely 

stored; in stock with at least one valid 

1 To calculate staff training indicators, we collapsed and merged the provider training data into the facility file, and created a variable for 

having at least one ANC provider at the facility trained in each ID area. 
10 

2.2.1.2. Facility characteristics 

The analysis incorporated several variables that describe the characteristics of facilities. Facility type was 

compared across all three surveys and comparable categories were created to include higher-level facilities 

such as a hospital, health center or maternity clinic, and lower-level facilities such as a dispensary, clinic, 

or other categories, which included health posts in Malawi. In Kenya stand-alone HIV counseling and 

testing facilities were excluded from the analysis because they are not equipped to provide ANC or other 

services. Managing authority was grouped across all three surveys as either public or private and other. 

Private and other included faith based organizations (FBOs) and both for-profit and not-for-profit nongovernmental organizations (NGOs), as well as parastatal facilities in Tanzania. The analysis also compared 

facilities by regions, although in Tanzania the 30 regions were re-grouped into six geographical zones with 

the two zones in Zanzibar combined (Tanzania DHS 2010). In Kenya, an additional variable referenced 

malaria endemicity when examining integration of ANC with malaria. Since prevalence varies throughout 

the country, calculations of malaria endemicity regions were based on the findings of prevalence testing 

from the 2010 Kenya MIS (Division of Malaria Control [Ministry of Public Health and Sanitation] and 

Macro 2011). 

The Kenya SPA survey did not report locality (urban or rural) status of the facilities; thus, a measure of 

population density was used as a proxy of locality. The population within the immediate service area (5km) 

of SPA facilities was estimated using population density rasters from WorldPop1

. The country-specific 

population density rasters represent the predicted population per grid square with national totals adjusted 

to match UN population estimates. A custom python script and ArcGIS 10.4 Buffered Zonal Statistics tool 

calculated the total population estimate within a 5km radius surrounding the SPA facilities’ GPS location. 

Among all facilities, the range of the weighted sum of the population density within 5km of a facility ranged 

between 0 and 1,545,653 in Kenya (Mean (M) = 87,174, Standard Deviation (SD) = 209,446.6), between 

117 and 295,658 (M = 47,196.6, SD = 7,0047.2) in Malawi, and between 44 and 841,291 (M = 63543.2, 

SD = 145,339.7) in Tanzania. The distribution of the population measure revealed highly positive skewness 

towards lower density areas in all three surveys, with skewness of 4.7 and kurtosis of 26.8 in Kenya, 

skewness of 2.1 and kurtosis of 6.3 in Malawi, and skewness of 3.1 and kurtosis of 12.9 in Tanzania. Two 

standardized cut points were used to categorize the variable into three groups across all three countries: a 

population density of less than <10,000 is defined as the lowest density, a population density of 10,000 to 

34,999 as low density, and above 35,000 as medium/high density. This lowest, low, and medium-high 

population density variable was compared with the urban and rural variable in Malawi and Tanzania and 

the association was found to be highly significant (p < .001). 

2.2.1.3. Provider characteristics 

This study also describes characteristics of service providers (or health workers) who offer ANC services. 

These characteristics include occupational category, years of education, salary type, and gender. 

Occupational category was standardized to create a dichotomous variable for more technical qualifications 

or highly qualified positions such as doctors, clinical technicians, or other advanced specialists, and less 

technical qualifications or less qualified positions such as nurses, midwives, or other health workers. 

Although years of education are recorded as a continuous number, this study categorized the number to 

create a variable that may represent less, moderate, or advanced education; up to 14 years of education 

would include primary and secondary education, 14-17 years would include advanced education, and over 

17 years would be the most advanced education, which is consistent with previous studies (Assaf 2015). 

Years of education, either the continuous variable or the categorized variable used in this report, is not 

 

1

 Data were retrieved on March 15, 2016, from: http://www.worldpop.org.uk/data/get_data/
11 

strongly correlated with provider category in any survey in this report. Salary type is defined as receiving 

no pay, regular pay, and no regular pay but other pay such as per diem. 

2.2.1.4. Client characteristics 

This report examines characteristics of clients who receive ANC services. These characteristics, as defined 

by the client in the exit interview, include education (none, primary, and secondary or higher); age (under 

20, 20-35, and 36 or older); number of weeks pregnant; first, second, or third trimester of pregnancy; the 

client’s first pregnancy or not; and the visit number (first, second, third, or fourth and higher). 

2.2.1.5. Outcomes 

At the client level, this study analyzes three outcomes of integrated care received during ANC visits as 

observed during the SPA. The first is ITN counseling or distribution. The precise definition of these terms 

varied by country due to the differences in the questionnaire. In Malawi and Tanzania, the question noted 

if a provider counseled the client on sleeping under an ITN to prevent malaria during pregnancy. In Kenya, 

the variable refers to whether or not the health worker gave the client an ITN (or a voucher to obtain an 

ITN) or counseled the client on ITN use during the ANC visit for their current pregnancy. Only women 

who are attending their first ANC visit are included for this outcome in all three countries, for a total of 556 

women in Kenya, 873 in Malawi, and 1,847 in Tanzania. The second variable is direct observation of 

provision and consumption of IPTp-SP. SP is not recommended for women in their first trimester; thus, 

this variable only includes women in the second or third trimester: 1,239 women in Kenya, 1,956 in Malawi, 

and 3,428 in Tanzania. The final outcome is if a client received HIV counseling and testing (HCT) during 

ANC. This variable measured whether the client was asked about her HIV status, had an HIV test, and 

received counseling, only among women who attended their first ANC visit. There is no observed potential 

outcome for TB/HIV. 

2.2.1.6. Analysis 

This study analyzed the three categories assessed by SPA surveys: facilities, providers, and clients. The 

first part of the analysis describes the background characteristics of facilities that offer ANC services, 

examines the availability of ID services at these facilities, and presents the percentage of ANC providers 

who provide and have recent training in each ID area. 

Second, the indicators of integration (described above) are examined at the facility level. Chi square tests 

of independence tested for significant differences in the coverage of each integration component across 

facility characteristics. One-way analysis of variance tests (ANOVA) tested for significant differences in 

the mean overall integration scores for integration of ANC service with each ID services across facility 

characteristics. 

Finally, the analysis tested differences among women attending ANC visits for receipt of three types of 

integrated care services (counseling or distribution of ITNs, direct observation of SP consumption, and 

HCT). We employed several types of statistical tests to understand these differences and potential 

associations. The chi square test of independence assessed associations between each of the three outcomes 

and background characteristics of women, providers, and facilities, including facility-level integration 

components. T-tests examined differences in mean overall integration scores between women who received 

integrated care and those who did not. When significant bivariate associations were found between overall 

integration and client outcomes, multivariable logistic regression models were conducted to understand the 

most highly associated co-factors of the receipt of integrated care. All independent variables relating to 

women, provider, and facility characteristics were included in the models. 
12 

When interpreting the results, it is important to consider national policy guidelines for each country, 

particularly for malaria. Guidelines for prevention and treatment of malaria in pregnancy in Tanzania are 

shifting to recommend provision of SP on the mainland only (PMI 2014); thus, the analysis of SP in 

Tanzania excludes women who attend ANC at facilities in Zanzibar. The integration indicators are 

calculated for Tanzania as whole, however. At the time of the survey, the voucher program that enabled 

distribution of ITNs during ANC had expired and a new program for direct distribution in ANC had not yet 

begun (PMI 2014). 

For all analyses, data are weighted to account for disproportionate sampling in Kenya and Tanzania and for 

non-response. Since selection and response vary among facilities, providers, and clients, a different weight 

is applied for each unit of analysis. The analysis also accounts for the complex survey design according to 

each survey’s design. For Malawi, confidence intervals estimation and significance testing were not 

performed for facility-level analyses because the Malawi SPA is a census of health facilities in the country 

and thus there were no sampling errors. However, confidence intervals and statistical tests of differences 

were still calculated when using Malawi’s provider- and client -level data, since these are sub-samples of 

their respective populations. All analyses are conducted using Stata 14.0. 
13 

3. Results 

3.1. Facilities and Providers That Provide ANC and Infectious Disease Services 

3.1.1. What is the distribution of facilities with ANC services available? 

In Kenya, more than half of facilities with ANC services available are dispensaries (56%), followed by 

clinics (16%), health centers (16%), hospitals (9%), and maternity wards (3%) (see Figure 1). 

Geographically, the Rift Valley region has the greatest share of facilities with ANC services (26%), while 

the North Eastern region has the smallest share (3%). More than 40% of ANC facilities are found in 

medium/high density areas of Kenya, while just one-fifth (22%) are found in lowest-density areas. Most 

facilities with ANC services are public (60%). 
14 

Figure 1. Distribution of facilities with ANC by characteristics, Kenya SPA 2010 

Hospital

9%

Health 

Center

16%

Maternity

3%

Dispensary

56%

Clinic

16%

Facility Type

Government/ 

local 

60%

NGO/ 

private not 

for profit

4%

Private for 

profit

21%

Mission/ 

faithbased

15%

Managing Authority

Nairobi

6%

Central

14%

Coast

11%

Eastern

17%

North 

Eastern

3%

Nyanza

15%

Rift Valley

26%

Western

8%

Region

Lowest 

density

22%

Low 

density

37%

Medium/high 

density

41%

Population Density
15 

In Malawi, nearly three-quarters of facilities with ANC services are health centers (71%), followed by 

hospitals (16%), clinics (10%), and dispensaries (3%) (see Figure 2). The ANC facilities are primarily 

public (63%) and located in the South (44%) and Central (37%) regions, with a smaller share in the North 

(19%). Just 13% of the facilities are located in areas with medium or high population density. 

Figure 2. Distribution of characteristics of facilities with ANC, Malawi SPA 2013-14 

Hospital

16%

Health 

Center

71%

Dispensary

3% Clinic

10%

Health 

Post

0%

Facility Type

Public

63%

FBO

24%

Private for 

profit

7%

NGO

2%

Company

4%

Managing Authority

North 

19%

Central

37%

South

44%

Region

Lowest 

density

31%

Low 

density

56%

Medium/high 

density

13%

Population Density
16 

In Tanzania, the vast majority of facilities that provide ANC services are dispensaries (83%), with a smaller 

share of health centers (12%), hospitals (4%), and clinics (1%) (see Figure 3). Geographically, ANC 

facilities are distributed roughly evenly across the mainland regions, with 3% found in Zanzibar. Twothirds of facilities with ANC services are found in areas with the lowest population density. As in Kenya 

and Malawi, most ANC facilities in Tanzania are public (82%). 

Figure 3. Distribution of characteristics of facilities with ANC, Tanzania SPA 2014-15 

Hospital

4%

Health 

Center

12%

Dispensary

83%

Clinic

1%

Facility Type

Public

82%

FBO

12%

Private for 

profit

6%

Parastatal

0%

Managing Authority

Central

13%

Northern

16%

Coastal

21%

Southern 

Highlands

23%

Lake 

24%

Zanzibar

3%

Zone

Lowest 

density

66%

Low 

density

20%

Medium/high 

density

14%

Population Density
17 

3.1.2. What percent of ANC facilities provide PMTCT, TB, or malaria services? 

As Figure 4 shows, in Kenya malaria services are nearly universal in facilities that offer ANC services, 

regardless of facility type, managing authority, region, or population density (see Figure 4, Appendix Table 

1a). The availability of PMTCT and TB services in ANC facilities is lower and more variable across facility 

characteristics. Both PMTCT and TB services are more prevalent in hospitals, health centers, and maternity 

clinics than in dispensaries, clinics, and other ANC facilities, and are more common in public ANC facilities 

than in private/other facilities. The availability of PMTCT and TB services also varies across geographic 

regions, with PMTCT service availability lowest in the North Eastern region (35%), and TB service 

availability lowest in the North Eastern (31%) and Rift Valley (31%) regions. 

Figure 4. Percent of facilities with ANC services that also have infectious disease services available, 

by background characteristics, Kenya SPA 2010 

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB Malaria

Region

Nairobi Central Coast

Eastern North Eastern Nyanza

Rift Valley Western

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Population Density

Lowest density Low density Medium/high density
18 

The patterns in availability of malaria, PMTCT, and TB services among ANC facilities in Tanzania and 

Malawi are similar to those described for Kenya (see Figures 5 and 6, Appendix Tables 1b-c). In all three 

countries, malaria services are nearly universal, PMTCT services are common, and PMTCT and TB 

services are more often available in hospitals, health centers, and maternity clinics than in dispensaries, 

clinics, and other facilities. Availability of TB services is notably lowest in Tanzania, although in all three 

countries availability of TB is lowest in the areas of lowest population density. Unlike in Kenya and Malawi, 

in Tanzania there is no difference in PMTCT or TB service availability in public versus private facilities. 

Figure 5. Percent of facilities with ANC services that also have infectious disease services available, 

by background characteristics, Malawi SPA 2013-14 

Note: Confidence intervals are not included since Malawi is a census of all facilities in the country. See methodology for more information. 

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Managing Authority

Public Private/Other

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

PMTCT TB Malaria

Region

Northern Central Southern

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Population Density

Lowest density Low density Medium/high density
19 

Figure 6. Percent of facilities with ANC services that also have infectious disease services available, 

by background characteristics, Tanzania SPA 2014-15 

3.1.3. What percentage of ANC providers also provide services in each ID area? 

Health workers analyzed in this study are those who provide ANC services. In all three countries, the 

majority of ANC providers are female nurses, midwives, or other less technical health professionals who 

work in public or government-managed facilities. Appendix Table 2 shows the distribution of ANC 

providers by their background characteristics and the facilities in which they work within each country. 

Figure 7 shows the differences in background characteristics of ANC providers who provide and have 

training in PMTCT, TB, and malaria in Kenya. Most of these differences are not significant. This 

information is also presented in Appendix Table 3a, with more information on lifetime training in these 

areas. Overall, more ANC providers also provide and have training in malaria services than in PMTCT or 

TB services. The percentage of ANC providers who provide and have training in PMTCT services is higher 

in public facilities than in private facilities. A higher percentage of doctors, clinicians, or specialists than 

nurses, midwives, or other qualifications provide and have training in TB and malaria services. For malaria 

services alone, a higher percentage of ANC providers also provide and have training in malaria services in 

dispensaries, clinics, or other facilities, compared with higher-level facilities, and in public facilities, 

compared with private or other facilities. Facilities in medium/high population density areas have the lowest 

percentage of ANC providers who provide and have training in malaria, compared with the low and lowest 

density areas (Appendix Table 3a). 

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

20

40

60

80

100

PMTCT TB Malaria

Zone

Central Northern Coastal

Southern Highlands Lake Zanzibar

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Managing Authority

Public Private/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB Malaria

Population Density

Lowest density Low density Medium/high density
20 

Figure 7. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Kenya SPA 2010 

0

20

40

60

80

100

PMTCT TB Malaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

20

40

60

80

100

PMTCT TB Malaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB Malaria

Region

Nairobi Central Coast Eastern

North Eastern Nyanza Rift Valley Western

0

20

40

60

80

100

PMTCT TB Malaria

Occupation

Doctor/clinical technician/specialist Nurse/midwife/other

0

20

40

60

80

100

PMTCT TB Malaria

Years of Education

<14 14-16 17+

0

20

40

60

80

100

PMTCT TB Malaria

Gender

Male Female
21 

Figures 8 and 9 along with Appendix Table 3b and 3c show service provision and recent training in ID 

among ANC providers, by background characteristics, in Malawi and Tanzania. Unlike in Kenya, a higher 

percentage of ANC providers in Malawi and Tanzania provide and have recent training in PMTCT than 

provide and have recent training in malaria services. Both the Malawi and Tanzania survey questionnaires 

ask about provision of services and recent training in TB and HIV co-infection. In Malawi, this category 

has the lowest coverage, at less than 10%. In Malawi, the percentage of ANC providers who provide and 

are trained in PMTCT is higher in hospitals, health centers, and maternity clinics than in lower-level 

facilities; and is higher among those with more technical occupations and those with more years of 

education. This is also true for ANC providers who provide and are trained in any TB services (except for 

years of education, where the differences are less pronounced). For malaria, the percentage of ANC 

providers who provide and are trained in malaria services is highest among more qualified providers and 

providers in the Central region. 

Figure 8. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Malawi SPA 2013-14 

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Region

North Central South

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Occupation

Doctor/clinical technician/specialist Nurse/midwife/other

0

20

40

60

80

100

PMTCT TB TB/HIV Coinfection

Malaria

Years of Education

<14 14-16 17+

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Gender

Male Female
22 

In Tanzania, there appear to be fewer ANC providers who provide services and are recently trained in all 

three ID service areas compared with Malawi and Kenya, although like the other two countries, fewer 

provide TB services, particularly TB/HIV co-infection services (less than 2%). Figure 9 and Appendix 

Table 3c show these results. The percentage of ANC providers who provide and are recently trained in 

PMTCT services is higher in lower-level facilities than in higher-level facilities, and is higher among staff 

in less-qualified positions, compared with doctors, clinical technicians, or specialists. Similar to Malawi, 

the percentage of ANC providers who are recently trained and provide any TB services is higher in higherlevel facilities, and among those with higher-level occupations and more years of education. The percentage 

of ANC providers who are recently trained and provide malaria services is higher among men than women, 

and among those with higher-level occupations and more years of education. 

Figure 9. Percent of ANC providers who provide and are recently trained in infectious disease 

services, by background characteristics, Tanzania SPA 2014-15 

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Zone

Central Northern Coastal Southern Highlands Lake Zanzibar

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Occupation

Doctor/clinical technician/specialist Nurse/midwife/other

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Years of Education

<14 14-16 17+

0

20

40

60

80

100

PMTCT TB TB/HIV CoinfectionMalaria

Gender

Male Female
23 

In all three countries, there were no differences for any ID area among different salary types and population 

density. 

3.2. Integration within Facilities 

3.2.1. What is the availability of different components of integration and how does that differ by facility 

characteristics? 

In this study, five components are used to assess a facility’s capacity to provide integrated services with 

infectious diseases. Table 2 describes each component of integration. Integration of ANC with each ID 

service is examined for differences among facilities, both by individual component and an overall average 

of components. 

3.2.2. PMTCT 

Tables 3a-3c show the integration of ANC with PMTCT services in Kenya, Malawi, and Tanzania for each 

component of integration, stratified by facility characteristics. In Kenya, there is a large gap between the 

availability of services and the actual capacity to provide these services. While more than half (59%) of all 

facilities with ANC services have both ANC and HCT services available at least three days per week, less 

than half have at least one provider who provides ANC and PMTCT services with recent training in PMTCT 

(48%), and offer HCT during ANC and have diagnostic capacity (45%). Only 7% offer ART during 

ANC/PMTCT and have the recommended ART available. Promisingly, three-quarters of all ANC facilities 

(75%) offer PMTCT at the same site as ANC services. Chi-square tests of independence show differences 

by facility type for all components of integration; higher-level facilities offer integrated services at a 

significantly higher percentage than lower-level facilities. While a higher percentage of public facilities 

have ART available and offer PMTCT at the same site, more privately managed facilities offer HCT and 

have testing capacity. There is significant variability by region and population density, although this 

variability is not consistent across the indicators. 
24

Table 3a. Among facilities that provide ANC, percentage that provide integrated services with PMTCT, by background characteristics, 

Kenya SPA 2010 

ANC and HCT services 

available at least 3 days 

per week 

At least one ANC provider 

who also provides and 

has recent training in 

PMTCT services 

ANC and PMTCT 

offered at the same site 

Offer HCT during ANC 

and have HIV testing 

capacity on-site 

Provide ART as part of 

PMTCT and have 

recommended ART 

available 

All ANC 

facilities

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility <.001 <.001 <.001 <.001 0.001 

Hospital/Health Center/ 

Maternity Clinic 

74.9 67.5 - 81.1 74.6 67.8 - 80.3 87.3 81.5 - 91.5 73.8 66.4 - 80.0 20.9 16.4 - 26.3 126 

Dispensary/Clinic/Other 54.2 46.4 - 61.8 39.0 31.1 - 47.4 70.6 62.4 - 77.7 35.3 27.7 - 43.7 2.5 1.2 - 5.4 383 

Managing Authority 0.400 0.217 0.030 0.003 <.001 

Public 61.5 54.1 - 68.4 51.0 42.4 - 59.6 80.3 71.8 - 86.6 36.9 29.8 - 44.6 9.4 6.8 - 13.0 306 Private/Other 56.1 45.4 - 66.2 43.0 34.1 - 52.3 66.6 56.0 - 75.7 56.7 46.1 - 66.7 3.5 2.1 - 5.9 204 

Region <.001 0.088 0.012 0.227 <.001 

Nairobi 39.5 26.2 - 54.7 61.0 44.4 - 75.3 64.4 47.3 - 78.5 37.2 23.8 - 53.0 14.2 7.3 - 26.0 33 Central 75.7 54.5 - 89.0 28.8 18.6 - 41.8 74.2 53.5 - 87.8 57.4 37.3 - 75.3 1.5 0.4 - 4.7 71 Coast 72.3 52.7 - 85.9 50.7 32.8 - 68.5 60.0 41.4 - 76.2 57.7 41.4 - 72.4 10.2 5.2 - 19.2 57 Eastern 78.7 60.1 - 90.1 43.2 27.6 - 60.3 69.7 51.9 - 83.0 41.2 27.0 - 57.0 11.4 7.9 - 16.1 84 North Eastern 38.3 18.8 - 62.6 36.5 18.3 - 59.6 34.0 16.4 - 57.5 17.4 7.2 - 36.6 3.4 1.5 - 7.5 17 Nyanza 65.6 50.6 - 78.0 62.3 47.4 - 75.2 86.8 72.6 - 94.3 45.9 33.5 - 58.8 13.7 6.6 - 26.2 78 Rift Valley 32.5 19.8 - 48.4 46.7 31.0 - 63.2 79.8 61.8 - 90.7 40.4 25.8 - 56.8 1.4 0.7 - 3.1 130 Western 71.0 56.6 - 82.1 55.7 41.9 - 68.7 92.5 80.5 - 97.4 42.2 31.4 - 53.7 4.8 2.2 - 10.1 41 

Population Density 0.096 0.252 0.156 0.001 0.016 

Lowest density 60.1 45.5 - 73.2 42.5 28.8 - 57.4 64.3 49.0 - 77.2 23.3 14.5 - 35.3 11.2 6.4 - 18.8 111 Low density 50.2 39.1 - 61.3 55.2 43.3 - 66.5 80.4 68.8 - 88.4 45.6 34.5 - 57.2 3.3 1.8 - 5.9 190 Medium/high density 67.2 57.5 - 75.7 43.9 35.6 - 52.5 75.3 66.0 - 82.7 55.6 45.8 - 65.0 8.4 5.4 - 12.6 208 

Total 59.3 53.2 - 65.2 47.8 41.5 - 54.2 74.8 68.4 - 80.2 44.8 38.6 - 51.2 7.1 5.4 - 9.3 509 Note: Excludes stand-alone voluntary counseling and testing (VCT) clinics; testing includes external testing if results are returned and are provided to clients within the facility. 
25 

Although chi-square testing was not necessary using census data in Malawi, differences in percentages of 

facilities with availability of integrated services by facility characteristics are still evident, as Table 3b 

shows. Overall, facilities in Malawi appear well equipped to provide integrated services according to each 

integration component. Although only 50% of the facilities in Malawi have HCT and ANC available at 

least three days per week, 87% of all facilities offer HCT during ANC and have testing capacity, and 86% 

offer ART as part of PMTCT and have the recommended ARTs available. Across each integration 

component, the percentage of hospitals, health centers, and maternity clinics that are equipped to provide 

these integration components is twice as high as the percentage of dispensaries, clinics, and other types of 

facilities. It should be noted that higher-level facilities account for 85% of all facilities in the country. A 

higher percentage of public than private facilities offers each of these services. 

In Table 3c the differences in PMTCT integration components by facility characteristics in Tanzania show 

similarities to Kenya. Overall availability of these services is higher in Tanzania than Kenya and is similar 

to Malawi. In Tanzanian facilities with ANC services, three-quarters (77%) have both ANC and PMTCT 

services available three days per week, while over 80% have testing and diagnostic capacity and offer 

PMTCT at the same site as ANC. Only 22% offer ART during ANC and have ART available, however. 

With the exception of PMTCT being located at the same site as ANC, facility type is associated with all 

PMTCT integration components; higher-level facilities are more likely than lower-level facilities to 

demonstrate availability of these components. Similar to Kenya, Tanzania’s regions vary in the percentage 

of availability of integration components, and there are significant differences between regions in all 

components except having services at the same site. There is little difference by managing authority and 

population density. 

Table 3b. Among facilities that provide ANC, percentage that provide integrated services with 

PMTCT, by background characteristics, Malawi SPA 2013-14 

ANC and 

HCT services 

available at 

least 3 days 

per week 

At least one ANC 

provider who also 

provides and has 

recent training in 

PMTCT services 

ANC and 

PMTCT 

offered at 

the same 

site 

Offer HCT 

during ANC 

and have HIV 

testing 

capacity onsite 

Provide ART 

as part of 

PMTCT and 

have 

recommended 

ART available 

All ANC 

facilities

 % % % % % N 

Type of Facility 

Hospital/Health Center/ 

Maternity Clinic 

53.5 68.5 79.6 92.0 91.8 548 

Dispensary/Clinic/Other 27.2 36.1 47.1 52.2 49.8 84 

Managing Authority 

Public 51.9 69.3 79.8 90.3 92.5 399 

Private/Other 46.9 55.6 67.5 80.6 75.5 233 

Region 

Northern 26.7 66.4 71.6 86.6 86.6 118 

Central 61.5 63.9 73.8 87.6 83.0 235 

Southern 50.2 63.6 78.0 86.0 88.8 280 

Population Density 

Lowest density 27.7 58.3 76.1 86.8 86.8 194 

Low density 57.9 66.8 76.9 89.8 89.0 352 

Medium/high density 69.7 67.3 66.2 73.2 74.4 83 

Total 50.0 64.2 75.3 86.7 86.2 632 

Note: Missing population density data for two facilities. Confidence intervals are not included since Malawi is a census of all

facilities in the country. See methodology for more information. 
26

Table 3c. Among facilities that provide ANC, percentage that provide integrated services with PMTCT, by background characteristics, 

Tanzania SPA 2014-15 

ANC and HCT services 

available at least 3 days 

per week 

At least one ANC 

provider who also 

provides and has recent 

training in PMTCT 

services 

ANC and PMTCT 

offered at the same site 

Offer HCT during ANC 

and have HIV testing 

capacity on-site 

Provide ART as part of 

PMTCT and have 

recommended ART 

available 

All ANC 

facilities 

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility 0.008 <.001 0.313 <.001 <.001 

Hospital/Health Center/ 

Maternity Clinic 

83.4 79.9 - 86.4 77.4 73.5 - 81.0 86.3 83.2 - 89.0 95.0 92.9 - 96.5 55.6 51.1 - 60.0 160 

Dispensary/Clinic/Other 76.2 71.5 - 80.2 61.4 56.2 - 66.3 83.9 79.7 - 87.4 84.9 80.9 - 88.2 15.5 12.1 - 19.7 845 

Managing Authority 0.190 0.276 0.008 0.068 0.502 

Public 78.5 74.3 - 82.3 65.1 60.2 - 69.7 86.4 82.7 - 89.4 88.0 84.5 - 90.8 21.3 18.0 - 25.1 823 Private/Other 71.7 60.6 - 80.6 58.7 48.1 - 68.7 74.6 64.0 - 83.0 80.0 69.2 - 87.7 24.3 17.1 - 33.4 182 

Zones 0.033 0.015 0.113 0.028 0.008 

Central 74.8 63.5 - 83.6 51.8 40.2 - 63.3 79.5 69.0 - 87.1 79.1 68.8 - 86.7 15.9 10.1 - 24.0 131 Northern 81.7 70.0 - 89.5 76.8 65.0 - 85.5 89.5 80.8 - 94.5 86.5 76.2 - 92.7 21.9 14.7 - 31.2 164 Coastal 84.2 74.5 - 90.6 61.3 50.7 - 70.9 86.8 78.0 - 92.4 91.6 82.8 - 96.1 31.2 23.3 - 40.4 210 Southern Highlands 80.4 71.6 - 86.9 61.0 51.6 - 69.7 87.8 79.3 - 93.1 91.1 83.3 - 95.4 22.1 15.6 - 30.2 228 Lake 66.8 58.5 - 74.2 68.9 59.8 - 76.8 79.5 70.7 - 86.2 84.5 76.3 - 90.2 19.6 14.3 - 26.3 241 Zanzibar 76.8 63.8 - 86.2 46.5 34.2 - 59.2 70.9 57.6 - 81.4 66.7 54.4 - 77.1 0.5 0.1 - 3.7 31 

Population Density 0.336 0.362 0.540 0.545 0.028 

Lowest density 76.3 71.4 - 80.7 64.5 58.9 - 69.7 82.8 78.1 - 86.7 85.0 80.5 - 88.6 18.5 15.0 - 22.6 645 

Low density 76.2 66.5 - 83.8 66.6 56.7 - 75.2 87.4 79.0 - 92.7 89.1 80.9 - 94.1 30.0 22.5 - 38.7 195 

Medium/high density 85.0 72.6 - 92.4 56.2 43.9 - 67.8 85.0 75.2 - 91.3 88.0 78.0 - 93.8 25.4 16.5 - 36.9 139 

Total 77.3 73.4 - 80.8 63.9 59.5 - 68.1 84.3 80.7 - 87.3 86.5 83.2 - 89.3 21.9 18.8 - 25.3 1,005 

Note: Missing population density data for 26 facilities. 
27 

In summary, at least half of facilities in all three countries are equipped to provide most integrated ANCPMTCT services, except for the provision of ART in Tanzania and Kenya. In all three countries, larger 

proportions of higher-level facilities are prepared to provide integrated services compared with lower-level 

facilities; for the most part, more of these facilities are public. There is variability by region, which appears 

more pronounced in Kenya and Tanzania than in Malawi. The differences by population density are 

generally non-significant and vary greatly by country and indicator within each country. 

3.2.3. TB/HIV 

Tables 4a-4c show the percentage of facilities that provide components of integrated services of ANC with 

TB/HIV, stratified by facility characteristics, for Kenya, Malawi and Tanzania respectively. The percentage 

of facilities in each country that provide components of integrated services of ANC with TB/HIV is much 

lower than the percentage that provide those same components of integrated services of ANC with PMTCT; 

at the time of the survey not more than about a third of all facilities in each country had any one of the 

TB/HIV integration indicators available. In each country, a higher percentage of higher-level facilities have 

integrated services capabilities compared with lower-level facilities. 

The Kenya, the SPA did not include a question about the number of days per week (or month) that TB 

services are available or a question about training of staff in TB/HIV co-infection. Unlike Tables 4b and 4c 

for Malawi and Tanzania, Table 4a for Kenya shows any availability of services for TB and ANC and staff 

training on any aspect of TB, the components that are included in the calculation of Kenya’s integration 

score. Therefore, the integration components and scores are not totally comparable across all three 

countries. Beyond the availability of services, the integration indicator most commonly available at 

facilities is having at least one ANC provider who also provides TB services and is recently trained in some 

aspect of TB care (36%). However, only 4% of ANC facilities offer TB treatment for HIV-positive patients 

and have preventive TB medications available. Similar to the integration of ANC and PMTCT, there are 

significant differences by facility type; this follows the same pattern of higher-level facilities having higher 

percentages of availability than lower-level facilities. There are fewer significant differences by other 

characteristics, as Table 4a shows. 
28

Table 4a. Among facilities that provide ANC, percentage that provide integrated services with TB/HIV, by background characteristics, Kenya SPA 2010 

ANC and TB services 

At least one provider 

who also provides and 

has recent training in 

TB services 

TB screening system 

for HIV+ patients and 

have TB diagnostics 

 on-site 

HIV screening system 

for TB+ patients and HIV 

diagnostics on-site 

Offer TB prophylaxis 

for HIV+ patients and 

have medication 

available 

All ANC 

facilities 

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility <.001 <.001 <.001 <.001 <.001 

Hospital/Health Center/ 

Maternity Clinic 

 89.7 84.3 - 93.4 63.9 56.2 - 70.9 62.2 54.5 - 69.2 68.3 60.9 - 75.0 10.7 7.0 - 16.0 126 

Dispensary/Clinic/Other 37.8 31.0 - 45.1 27.1 21.1 - 34.2 11.7 7.5 - 17.8 16.3 10.9 - 23.6 1.1 0.5 - 2.6 383 

Managing Authority 0.021 0.320 0.155 0.864 0.615 

Public 57.0 49.4 - 64.2 38.6 31.5 - 46.2 26.9 21.3 - 33.4 28.8 23.2 - 35.2 3.2 2.0 - 5.1 306 

Private/Other 41.2 32.0 - 51.1 32.7 25.0 - 41.4 20.1 14.5 - 27.3 29.8 21.4 - 39.8 3.9 2.1 - 7.3 204 

Region 0.002 0.075 0.294 0.362 <.001 

Nairobi 52.6 37.0 - 67.7 45.6 30.4 - 61.7 28.2 16.6 - 43.7 28.6 19.8 - 39.3 15.3 7.4 - 29.2 33 Central 59.5 41.1 - 75.6 33.0 21.6 - 46.8 18.2 11.0 - 28.6 27.6 14.6 - 45.7 1.6 0.8 - 3.1 71 Coast 62.0 43.1 - 77.9 41.3 25.1 - 59.6 30.3 16.5 - 48.9 33.8 19.5 - 51.7 0.0 57 Eastern 51.3 35.7 - 66.6 39.5 25.0 - 56.1 19.5 12.2 - 29.6 19.3 12.0 - 29.5 5.5 3.0 - 10.0 84 North Eastern 30.3 15.1 - 51.4 29.8 14.6 - 51.2 25.6 11.3 - 48.0 17.2 7.0 - 36.2 0.0 17 Nyanza 60.1 45.6 - 72.9 42.6 29.8 - 56.4 34.9 23.9 - 47.8 39.5 27.5 - 52.9 3.8 1.4 - 9.9 78 Rift Valley 30.9 22.5 - 40.9 23.1 14.5 - 34.8 21.3 13.2 - 32.6 30.0 19.0 - 43.9 1.7 0.4 - 7.4 130 Western 69.9 56.3 - 80.7 52.8 39.5 - 65.7 21.0 14.0 - 30.4 29.3 20.5 - 40.1 4.6 1.4 - 13.7 41 

Population Density 0.146 0.161 0.073 0.013 0.167 

Lowest density 41.4 28.8 - 55.2 27.2 17.0 - 40.4 14.9 8.9 - 23.8 14.5 8.6 - 23.5 1.1 0.3 - 4.4 111 

Low density 48.1 38.0 - 58.3 34.9 26.4 - 44.4 24.5 18.0 - 32.4 32.6 23.8 - 42.8 3.8 1.9 - 7.5 190 

Medium/high density 58.1 48.1 - 67.4 42.3 33.6 - 51.6 28.9 21.7 - 37.5 33.9 26.0 - 42.9 4.6 2.8 - 7.3 208 

Total 50.7 45.2 - 56.1 36.3 31.2 - 41.7 24.2 20.2 - 28.7 29.2 24.4 - 34.5 3.5 2.4 - 5.1 509 

Note: The indicator for ANC and TB services refers specifically to availability of services of each at least three days per week. These questions are not included in the Kenya SPA.Excludes stand-alone VCT clinics; testing includes external testing if results are returned and are provided to clients within the facility. 
29 

Table 4b shows that in Malawi over one-third (35%) of ANC facilities have both ANC and TB services 

available at least three days per week, although just 5% have a system for screening for TB among HIVpositive patients and the capacity for TB testing. In addition, only 8% of ANC facilities offer and have 

prophylactic TB medication available for these patients. Differences in facility preparedness in each of 

these components of integration are seen by type of facility (more higher-level than lower-level facilities 

provide services), managing authority (higher percentages of public compared with private facilities), 

region (the Central region has the highest percentage of services available), and population density (the 

lowest density areas have the least availability). 

Tanzania has much less capacity to provide services in the integration of ANC and TB/HIV compared with 

Malawi and Kenya (where indicators are comparable, as Table 4c shows). Less than 10% of facilities in 

Tanzania have at least one ANC provider trained in TB/HIV co-infection (7%) or have a system for 

screening for TB and TB diagnostic capacity (7%). Only 1% of facilities provide TB prophylaxis and have 

medications available for HIV-positive patients. As in Kenya and Malawi, higher-level facilities have 

greater capacity to provide the components of integrated care compared with lower-level facilities. There 

are also significant but inconsistent differences for some indicators among zones; for most indicators, lowdensity areas tend to have a higher proportion of capacity for integrated services than those with the lowest 

population density. 

Table 4b. Among facilities that provide ANC, percentage that provide integrated services with 

TB/HIV, by background characteristics, Malawi SPA 2013-14 

ANC and TB 

services 3 

days per 

week 

At least one 

provider who 

also provides 

and has 

recent 

training in 

TB/HIV 

services 

TB screening 

system for 

HIV+ patients 

and have TB 

diagnostics 

on-site 

HIV 

screening 

system for 

TB+ patients 

and HIV 

diagnostics 

on-site 

Offer TB 

prophylaxis 

for HIV+ 

patients and 

have 

medication 

available 

All ANC 

facilities 

 % % % % % N 

Type of Facility 

Hospital/Health Center/ 

Maternity Clinic 

39.8 32.8 5.1 29.1 8.7 548 

Dispensary/Clinic/Other 4.9 10.0 3.7 7.6 0.0 84 

Managing Authority 

Public 40.8 34.2 4.6 30.2 9.0 399 

Private/Other 25.6 22.2 5.5 19.3 5.0 233 

Region 

Northern 19.1 26.0 2.5 19.2 2.5 118 

Central 41.8 35.6 5.8 23.5 10.7 235 

Southern 36.4 26.5 5.3 31.4 6.9 280 

Population Density 

Lowest density 16.6 26.2 1.5 16.1 3.0 194 

Low density 44.0 32.0 4.4 30.1 9.1 352 

Medium/high density 42.1 29.3 15.4 33.9 11.6 83 

Total 35.2 29.8 4.9 26.2 7.5 632 

Note: Missing population density data for two facilities. Confidence intervals are not included since Malawi is a census of all facilities 

in the country. See methodology for more information.
30

Table 4c. Among facilities that provide ANC, percentage that provide integrated services with TB/HIV, by background characteristics, Tanzania SPA 2014-15 

ANC and TB services 3 

days per week 

At least one provider who 

also provides and has 

recent training in TB/HIV 

services 

TB screening system 

for HIV+ patients and 

have TB diagnostics 

on-site 

HIV screening system 

for TB+ patients and 

HIV diagnostics on-site 

Offer TB prophylaxis 

for HIV+ patients 

and have medication 

available 

All ANC 

facilities 

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility <.001 <.001 <.001 <.001 0.001 

Hospital/Health Center/ 

Maternity Clinic 

63.5 58.8 - 67.9 27.9 24.1 - 32.0 31.2 27.4 - 35.2 71.4 66.7 - 75.7 3.3 2.1 - 5.0 160 

Dispensary/Clinic/Other 15.8 12.2 - 20.1 3.5 2.1 - 6.0 1.8 0.8 - 4.1 11.9 8.8 - 15.9 0.2 0.0 - 1.7 845 

Managing Authority 0.239 0.974 0.059 0.174 0.992 

Public 24.2 20.6 - 28.3 7.4 5.6 - 9.6 5.9 4.5 - 7.6 20.3 17.1 - 23.9 0.7 0.3 - 1.5 823 

Private/Other 19.3 13.5 - 26.9 7.4 5.1 - 10.7 9.3 6.3 - 13.5 26.3 18.9 - 35.3 0.7 0.3 - 1.8 182 

Zones 0.055 0.456 0.003 0.016 0.007 

Central 15.1 9.7 - 22.8 8.1 4.3 - 14.7 4.1 2.9 - 5.9 11.0 8.0 - 14.9 0.3 0.1 - 1.0 131 Northern 25.8 17.9 - 35.6 8.5 5.1 - 13.7 8.4 4.4 - 15.5 22.6 16.2 - 30.5 2.4 0.8 - 6.8 164 Coastal 26.8 19.0 - 36.4 9.0 5.3 - 14.8 4.2 3.1 - 5.5 24.3 17.3 - 33.0 0.9 0.5 - 1.7 210 Southern Highlands 19.0 13.2 - 26.6 5.0 3.2 - 7.7 4.9 3.8 - 6.3 17.4 12.3 - 24.2 0.3 0.1 - 0.9 228 Lake 24.7 18.4 - 32.3 6.5 3.7 - 11.2 10.7 7.2 - 15.6 27.4 20.6 - 35.3 0.2 0.0 - 0.8 241 Zanzibar 42.4 33.2 - 52.1 12.0 6.9 - 20.0 2.2 0.8 - 5.7 21.9 14.9 - 31.0 0.0 31 

Population Density 0.001 0.006 0.001 <.001 0.153 

Lowest density 19.3 15.5 - 23.6 6.0 4.3 - 8.4 4.6 3.4 - 6.1 14.8 11.9 - 18.3 0.5 0.1 - 1.8 645 

Low density 36.3 28.0 - 45.4 12.8 8.5 - 18.9 11.4 7.5 - 17.0 31.3 23.8 - 39.8 0.8 0.4 - 1.8 195 

Medium/high density 27.6 18.3 - 39.2 6.8 4.1 - 10.9 8.6 5.1 - 14.1 34.6 24.3 - 46.6 1.7 0.9 - 3.1 139 

Total 23.3 20.1 - 26.9 7.4 5.9 - 9.3 6.5 5.2 - 8.0 21.4 18.5 - 24.6 0.7 0.4 - 1.3 1,005 

Note: Missing population density data for 26 facilities.
31 

3.2.4. Malaria 

Among facilities that provide ANC, Tables 5a-5c show the percentage that provide ANC integrated with 

malaria services. There is substantial variation in components of integrated services across the three 

countries overall, as well as by facility characteristics within each country. 

Table 5a shows results for Kenya. As with TB services, the Kenya SPA does not ask how many days in a 

given time period services are provided. Therefore, Table 5a substitutes any availability of services for 

services available three days per week. The other four indicators of integration of ANC and malaria services 

are the same in each country. While a high percentage of facilities in Kenya have at least one ANC provider 

who provides and is recently trained in some aspect in malaria (71%) and have SP available (86%), only 

6% routinely conduct RDT during ANC visits and have RDT available. As seen with the integration with 

other ID services, there are significant differences by type of facility, managing authority, region, and 

population density, although these differences are not seen among all indicators for each characteristic. In 

Kenya, there is a wide range of malaria prevalence across the country, which could account for the 

inconsistent findings for malaria services by facility characteristics. As mentioned in the Methods section, 

malaria endemicity is used to describe facilities in relation to integrated services with malaria. With the 

exception of facilities with trained staff, there are significant differences among the remaining three 

integration components by this characteristic. However, unlike having and providing RDT and ITNs 

available, having SP available is more common among areas of Kenya with lower malaria risk. 
32

Table 5a. Among facilities that provide ANC, percentage that provide integrated services with malaria, by background characteristics, KenyaSPA 2010 

Offer malaria services and 

ANC at least 3 days per 

week 

At least one ANC 

provider who also 

provides and has recent 

training in malaria 

services 

Routinely conduct RDT 

and have RDT available 

Routinely distribute ITNs 

and have ITNs available Have SP available 

All ANC 

facilities

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility 0.352 <.001 0.002 0.123 0.119 

Hospital/Health 

Center/Maternity Clinic 

100.0 83.3 77.2 - 88.0 11.1 7.9 - 15.5 57.9 51.2 - 64.3 90.7 85.4 - 94.3 126 

Dispensary/Clinic/ 

Other 

99.4 98.0 - 99.8 66.6 58.3 - 74.0 3.6 1.9 - 6.9 49.9 42.2 - 57.6 85.0 78.0 - 90.0 383 

Managing Authority 0.187 0.326 0.153 <.001 <.001 306 

Public 99.2 97.5 - 99.8 73.2 64.8 - 80.2 4.2 2.3 - 7.3 62.1 53.3 - 70.2 94.2 88.1 - 97.2 204 Private/Other 100.0 67.1 56.9 - 75.9 7.4 4.4 - 12.4 36.5 28.6 - 45.2 74.8 64.4 - 82.9 

Region <.001 0.511 <.001 <.001 0.091 

Nairobi 94.0 78.1 - 98.6 57.6 42.7 - 71.3 3.5 0.6 - 17.2 12.2 5.4 - 25.1 59.4 44.1 - 73.1 33 Central 100.0 64.1 43.5 - 80.5 4.1 2.3 - 7.1 31.1 19.9 - 45.2 90.0 66.7 - 97.6 71 Coast 100.0 75.5 58.7 - 87.0 17.1 6.9 - 36.5 44.5 28.9 - 61.2 85.5 64.9 - 95.0 57 Eastern 100.0 74.0 55.8 - 86.5 1.5 0.4 - 5.7 79.2 61.5 - 90.0 93.2 78.9 - 98.1 84 North Eastern 100.0 53.6 30.4 - 75.4 12.7 3.9 - 34.5 0.7 0.1 - 4.6 90.7 64.8 - 98.1 17 Nyanza 100.0 66.7 51.7 - 78.9 8.8 4.8 - 15.6 72.2 58.6 - 82.6 89.0 76.6 - 95.3 78 Rift Valley 99.7 98.2 - 100.0 78.0 60.5 - 89.1 1.1 0.5 - 2.6 43.9 27.8 - 61.5 84.3 67.9 - 93.2 130 Western 100.0 71.3 57.6 - 82.0 5.9 2.3 - 14.4 80.7 69.5 - 88.5 89.1 77.8 - 95.0 41 

Malaria Risk 0.316 0.230 0.001 0.001 0.036 

High risk 100.0 75.9 66.4 - 83.5 11.1 6.1 - 19.4 65.8 56.7 - 73.9 83.8 71.9 - 91.3 143 Epidemic/lowest 

risk/no information 

99.4 97.9 - 99.8 68.7 60.5 - 75.9 3.3 2.2 - 4.9 46.4 39.0 - 54.0 87.4 81.4 - 91.7 366 

Population Density 0.366 0.907 0.023 0.052 0.485 

Lowest density 100.0 68.8 54.0 - 80.5 3.5 1.3 - 9.0 48.0 33.9 - 62.4 93.6 83.9 - 97.6 111 Low density 100.0 70.2 57.9 - 80.1 3.1 1.5 - 6.0 62.5 50.9 - 72.9 90.0 79.6 - 95.3 190 Medium/high density 98.9 96.3 - 99.7 72.3 63.4 - 79.7 8.7 5.3 - 14.2 44.2 35.9 - 52.9 79.3 70.0 - 86.3 208 

Total 99.5 98.5 - 99.9 70.7 64.3 - 76.4 5.5 3.8 - 7.9 51.9 45.8 - 57.8 86.4 81.1 - 90.4 509 

Note: Excludes stand-alone VCT clinics; testing includes external testing if results are returned and are provided to clients within the facility. 
33 

Table 5b shows the percentage of facilities in Malawi with ANC services that provide components of 

integrated services of ANC with malaria. Nearly all facilities in Malawi are equipped to provide SP (99%) 

while only one-fifth (20%) offer and have RDT available for ANC clients. Some differences are seen by 

facility characteristics. More high-level than lower-level facilities appear ready to provide these integrated 

services, although the differences are more subtle and less patterned between public and private facilities, 

region, and population density. The Central region has a higher percentage of facilities that offer both 

services three days per week or more and has a higher percentage of facilities with at least one trained staff 

member. Medium/high density areas have almost half as many facilities that provide ITNs and have them 

available compared with low-density and lowest-density facilities, while facilities with ANC in 

medium/high density areas have RDT available more often than facilities in lower-density areas. 

Table 5c shows facility capacity to provide the components of integrated services for ANC and malaria in 

Tanzania. Although 81% of facilities offer ANC and malaria services at least three days per week, the 

availability of other components is much more limited. Sixty-one percent have SP available and 43% have 

at least one trained staff to provide services, while only 13% have RDT available and 12% have ITNs. 

There are significant or borderline significant differences in the coverage of components of integration by 

facility type, similar to other services and countries. In Tanzania, there is significant variation across region 

as well. Although Zanzibar has the lowest prevalence of malaria in the country, ITNs are ubiquitous (88%) 

compared with other regions and with the country as a whole. However, there is almost no availability of 

SP in Zanzibar. The national policy on malaria in pregnancy does not recommend providing SP during 

ANC visits in Zanzibar because of the low prevalence. 

Table 5b. Among facilities that provide ANC, percentage that provide integrated services 

with malaria, by background characteristics, Malawi SPA 2013-14 

Offer malaria 

services and 

ANC at least 3 

days per week 

At least one ANC 

provider who also 

provides and has 

recent training in 

malaria services 

Routinely 

conduct 

RDT and 

have RDT 

available 

Routinely 

distribute or 

counsel on 

ITNs and 

have ITNs 

available 

Have 

SP 

availa

ble 

All ANC 

facilities 

 % % % % % N 

Type of Facility 

Hospital/Health Center/ 

Maternity Clinic 

55.1 55.4 21.3 82.7 99.1 548 

Dispensary/Clinic/Other 34.6 28.3 15.0 49.5 96.2 84 

Managing Authority 

Public 53.1 56.9 20.6 82.2 99.2 399 

Private/Other 51.2 42.9 20.2 71.7 97.8 233 

Region 

Northern 29.2 48.6 20.9 78.2 100.0 118 

Central 64.4 62.7 21.7 77.7 99.6 235 

Southern 52.1 43.9 19.2 78.9 97.5 280 

Population Density 

Lowest density 29.2 42.0 18.3 80.7 99.5 194 

Low density 64.4 55.5 19.8 84.6 98.8 352 

Medium/high density 52.1 57.6 28.7 46.9 96.4 83 

Total 52.4 51.8 20.4 78.3 98.7 632 

Note: Missing population density data for two facilities. Confidence intervals are not included since Malawi is a 

census of all facilities in the country. See methodology for more information. 
34 

34

Table 5c. Among facilities that provide ANC, percentage that provide integrated services with malaria, by background characteristics, Tanzania SPA 2014-15 

Offer malaria services 

and ANC at least 3 days 

per week 

At least one ANC 

provider who also 

provides and has 

recent training in 

malaria services 

Routinely conduct RDT 

and have RDT available 

Routinely distribute or 

counsel on ITNs and have 

ITNs available Have SP available 

All ANC 

facilities

% 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value % 95% CI p-value N 

Type of Facility 0.001 <.001 <.001 <.001 0.102 

Hospital/Health Center/ 

Maternity Clinic 

87.8 84.6 - 90.4 63.9 59.3 - 68.2 29.5 25.7 - 33.5 26.7 23.1 - 30.7 65.7 61.6 - 69.6 160 

Dispensary/Clinic/Other 79.4 75.1 - 83.1 39.3 34.9 - 44.0 10.3 7.5 - 14.0 8.6 6.3 - 11.7 60.5 55.5 - 65.3 845 

Managing Authority 0.072 0.872 <.001 0.276 0.004 

Public 81.1 77.0 - 84.6 43.4 39.1 - 47.7 10.8 8.3 - 13.9 10.9 8.6 - 13.7 58.4 53.7 - 62.9 823 

Private/Other 79.2 69.0 - 86.7 42.5 33.4 - 52.1 24.8 16.9 - 34.9 14.3 9.2 - 21.6 74.6 64.5 - 82.6 182 

Zones 0.001 <.001 0.005 <.001 <.001 

Central 76.1 64.6 - 84.7 28.1 19.2 - 39.1 6.0 2.5 - 13.5 5.9 2.7 - 12.2 34.3 24.1 - 46.2 131 Northern 82.1 70.4 - 89.9 34.7 24.8 - 46.1 24.0 15.7 - 34.9 16.0 9.4 - 25.9 56.3 44.8 - 67.3 164 Coastal 87.3 78.5 - 92.9 57.2 48.3 - 65.6 14.8 8.9 - 23.7 7.1 3.7 - 13.1 70.7 60.0 - 79.5 210 Southern Highlands 87.8 80.7 - 92.6 31.6 24.4 - 39.9 12.2 8.3 - 17.7 7.8 4.4 - 13.4 74.7 65.4 - 82.2 228 Lake 68.5 60.3 - 75.7 53.1 45.0 - 61.0 9.3 5.6 - 15.1 9.1 5.2 - 15.3 66.0 57.3 - 73.7 241 Zanzibar 91.5 79.5 - 96.8 65.9 53.4 - 76.5 16.7 9.7 - 27.1 87.6 75.1 - 94.3 3.8 1.3 - 10.6 31 

Population Density 0.153 0.190 <.001 0.001 0.727 

Lowest density 79.5 74.7 - 83.5 42.3 37.3 - 47.4 9.2 6.8 - 12.4 8.0 5.7 - 11.2 60.3 54.9 - 65.4 645 

Low density 80.0 70.7 - 86.9 50.0 40.5 - 59.5 20.1 13.5 - 28.8 16.9 11.8 - 23.7 64.5 55.3 - 72.7 195 

Medium/high density 90.0 79.3 - 95.5 36.6 26.5 - 48.0 25.4 16.0 - 37.8 17.9 11.9 - 26.1 63.2 50.2 - 74.5 139 

Total 80.7 77.1 - 83.9 43.2 39.4 - 47.1 13.3 10.8 - 16.4 11.5 9.4 - 14.1 61.3 57.1 - 65.4 1,005 

Note: Missing population density data for 26 facilities. 
35 

3.2.5. What is the national average level of facility capacity to provide integrated services? 

For each of the service areas, we calculated a national integration score by averaging the respective five 

integration components and standardizing to a scale of 0 to 100. Figures 10, 11, and 12 present national 

scores for integration of ANC with the three types of infectious disease services (PMTCT, TB, and malaria) 

for Kenya, Malawi, and Tanzania respectively. On average and bearing in mind the slight difference in 

components, ANC facilities in Kenya are better prepared to provide integrated antenatal and malaria 

services (score of 63) compared with the other two types of integrated services. Facilities in Malawi and 

Tanzania scored the highest in providing integrated antenatal and PMTCT services with scores of 73 and 

67, respectively. The lowest national score was for the integration of ANC and TB/HIV services in all three 

countries, with scores of 29, 19 and 11 in Kenya, Malawi, and Tanzania respectively. 

Figure 10. National average integration scores, Kenya SPA 2010 

Figure 11. National average integration scores, Malawi SPA 2013-14 

0

10

20

30

40

50

60

70

80

90

100

Integration of ANC

and PMTCT

Integration of ANC

and TB/HIV

Integration of ANC

and malaria

0

10

20

30

40

50

60

70

80

90

100

Integration of ANC

and PMTCT

Integration of ANC

and TB/HIV

Integration of ANC

and malaria
36 

Figure 12. National average integration scores, Tanzania SPA 2014-15 

3.2.6. How does the integration score vary by facility characteristics? 

Figures 13-15 show differences in the national integration score by facility characteristics for the three 

countries studied. Integration scores within facility characteristics are compared with the national average, 

using one-way ANOVA to test for differences. The p-values are presented in Appendix Table 4. Similar to 

the variation seen in individual components, the largest notable differences by facility characteristic in 

integration scores are between high-level and low-level facilities—that is, hospitals, health centers, and 

maternity clinics versus dispensaries, clinics, and other facilities. There is a general trend for public 

facilities to be better equipped to provide these services, except in Tanzania for TB/HIV and malaria, but 

the differences are not significant. There is some variation by region or zone in Kenya and Tanzania, while 

differences by population density are less apparent in all three countries. 

0

10

20

30

40

50

60

70

80

90

100

Integration of ANC

and PMTCT

Integration of ANC

and TB/HIV

Integration of ANC

and malaria
37 

Figure 13. Average integration scores of ANC with infectious disease services, by facility 

background characteristics, Kenya SPA 2010 

0

20

40

60

80

100

PMTCT TB/HIV Malaria

Facility Type

Hospital/Health Center/Maternity Clinic

Dispensary/Clinic/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB/HIV Malaria

Region

Nairobi Central Coast Eastern

North Eastern Nyanza Rift Valley Western

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Population Density

Lowest density Low density Medium/high density
38 

Figure 14. Average integration scores of ANC with infectious disease services, by facility 

background characteristics, Malawi SPA 2013-14 

0

20

40

60

80

100

PMTCT TB/HIV Malaria

Facility Type

Hospital/Health Center/Maternity Clinic

Dispensary/Clinic/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Managing Authority

Public Private/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Region

Northern Central Southern

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Population Density

Lowest density Low density Medium/high density
39 

Figure 15. Overall integration of ANC with infectious disease services, by facility background 

characteristics, Tanzania SPA 2014-15 

3.3. Integrated Services Observed in ANC 

3.3.1. How often are women receiving integrated care and are there differences by background 

characteristics? 

As part of the SPA surveys, 1,409 ANC consultations were observed in Kenya; 2,068 in Tanzania, and, 

4,007 in Malawi. More than half of the pregnant women in each country were age 20-35; between 68% and 

75% were pregnant with their first child, and most were present for their first or second ANC visit. The 

majority of observed ANC visits took place at public facilities, and for 74% to 85% of these ANC visits the 

provider was female (see Appendix Table 5 for more detailed background information on observed ANC 

visits). 

Tables 6a-6c show the percentage of women who received integrated care during their observed ANC visits, 

according to background characteristics in Kenya, Malawi, and Tanzania respectively. 

Kenyan women were significantly more likely to receive an ITN during their first ANC visit if they attended 

a public facility rather than a private one; if the facility was in a high-malaria risk area rather than an area 

with low or no risk; if the provider was a nurse, midwife, or other provider rather than a doctor, clinical 

technician, or specialist; and if the provider had at least 14 years of education. 

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Facility Type

Hospital/Health Center/Maternity Clinic Dispensary/Clinic/Other

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Managing Authority

Public Private/Other

0

20

40

60

80

100

PMTCT TB/HIV Malaria

Zone

Central Northern Coastal

Southern Highlands Lake Zanzibar

0

10

20

30

40

50

60

70

80

90

100

PMTCT TB/HIV Malaria

Population Density

Lowest density Low density Medium/high density
40 

In Kenya, receiving SP in the second and third trimester was significantly related to the client’s trimester 

in pregnancy, the number of ANC visits she had completed, the facility’s managing authority and region, 

and the provider’s occupational category and gender. Women were significantly more likely to receive SP 

if they visited a public facility, and if the provider was female and a nurse, midwife, or other provider. 

The integration of HIV (PMTCT) services into observed ANC visits (as measured by whether women were 

asked about their HIV status, received counseling, and were given an HIV test during first ANC visit) was 

significantly related to the facility’s managing authority, the population density around the facility, and the 

provider’s occupational category, years of education, and gender. Women who visited public facilities, 

those who visited facilities in areas with medium or high population density, and those who saw providers 

who were female, nurses, midwifes, or other occupations, and those whose providers had fewer years of 

education were more likely to have PMTCT services integrated into their ANC visit. 

Unlike Kenya, few client and facility characteristics in Malawi were associated with receiving integrated 

care among the ANC clients observed. Receiving SP was associated with the client’s stage in pregnancy 

and number of ANC visits completed. Clients in the second trimester of pregnancy were more likely to 

receive SP than those in the third trimester. More than half of the first-visit and second-visit ANC clients 

received SP compared with 19% among those for whom the observed visit was their fourth visit or higher. 

A greater percentage (64%) of first-visit ANC clients at higher-level facilities (hospitals, health centers, or 

maternity clinics) discussed or received ITNs than those at lower-level facilities, such as dispensaries and 

clinics (24%). We did not find any evidence of significant associations between client and facility 

characteristics and the integration of HIV counseling and testing services into ANC. The integrated care 

during ANC visits did not appear to differ by any of the provider characteristics. 

In Tanzania, despite the low level of integration of malaria services into ANC (measured by discussing or 

receiving an ITN during first ANC visit and receiving SP in the second or third trimester), some client, 

facility, and provider characteristics were associated with women receiving integrated care. Over 40% of 

first-visit ANC clients at facilities in Zanzibar discussed or received ITNs during the observed visit 

compared with 6% to 14% in other regions. Clients seen by a female provider were more likely to be 

counseled about ITNs or receive ITNs. Receiving SP was significantly associated with the client’s trimester 

in pregnancy, the number of ANC visits completed, and the provider’s category. The integrated PMTCT 

services during ANC visits was only associated with region. Clients at facilities in Zanzibar were the least 

likely to receive HCT during their first ANC visit. 
41 

Table 6a. Background characteristics of women observed receiving integrated services during 

ANC visit, Kenya SPA 2010 

Percent of women who 

discussed or received ITN 

during first ANC visit 

Percent of women in the 

second and third trimester 

who received SP 

Percent of women asked 

about their HIV status, 

received counseling and 

given an HIV test during 

first ANC visit 

 % CI p-value % CI p-value % CI p-value 

Education 0.183 0.686 0.052 

None 47.2 32.7 - 62.2 38.7 18.8 - 63.2 19.5 6.6 - 45.2

Primary 65.8 57.0 - 73.6 45.2 38.6 - 52.1 48.5 40.2 - 56.9

Secondary or higher 62.8 52.2 - 72.3 42.0 35.5 - 48.9 50.1 38.8 - 61.4

Age 0.667 0.231 0.758

<20 62.2 46.8 - 75.5 45.2 36.0 - 54.9 51.2 37.4 - 64.9

20-35 63.5 55.9 - 70.5 41.5 35.8 - 47.5 46.3 38.2 - 54.7

36+ 69.3 55.6 - 80.2 49.2 39.3 - 59.2 49.7 36.1 - 63.4

Weeks pregnant 0.890 0.001 0.440

 4-13 60.0 33.8 - 81.5 33.9 14.5 - 60.6

 14-27 65.7 56.1 - 74.1 54.1 45.6 - 62.4 47.2 37.5 - 57.2

 28-40 64.1 55.3 - 72.2 38.9 32.8 - 45.3 51.2 41.5 - 60.8

First Pregnancy 0.271 0.312 0.702

No 65.6 57.4 - 72.9 42.2 35.6 - 49.1 46.2 37.8 - 54.9

Yes 59.1 48.5 - 68.8 46.7 39.4 - 54.3 48.6 37.8 - 59.6

Visit na <.001 na

First visit 63.4 56.5 - 69.8 55.3 47.2 - 63.1 47.0 39.5 - 54.6

Second visit 48.9 39.5 - 58.4

Third visit 25.8 18.2 - 35.1

Fourth or higher 23.8 16.6 - 32.9

Type of Facility 0.171 0.875 0.613

Hospital/Health Center/ 

Maternity Clinic 

59.7 51.5 - 67.3 44.0 38.3 - 49.9 48.6 41.1 - 56.3

Dispensary/Clinic/Other 70.3 56.7 - 81.1 43.0 31.5 - 55.2 44.1 29.4 - 59.9

Managing Authority 0.039 <.001 0.001

Public 67.3 59.0 - 74.6 49.0 42.3 - 55.7 52.9 44.1 - 61.5

Private/Other 51.2 38.4 - 63.9 24.4 16.6 - 34.2 27.5 17.4 - 40.6

Region <.001 0.002 0.241

Nairobi 13.8 6.1 - 28.4 33.0 21.6 - 46.9 41.1 18.0 - 68.8

Central 59.7 37.6 - 78.4 64.2 50.2 - 76.2 28.4 13.4 - 50.5

Coast 87.1 73.3 - 94.3 58.2 39.0 - 75.1 39.3 19.7 - 63.2

Eastern 86.2 70.2 - 94.3 26.9 17.9 - 38.4 64.4 45.7 - 79.5

North Eastern 5.5 1.4 - 19.2 20.4 7.4 - 45.0 9.4 3.0 - 25.8

Nyanza 69.7 55.2 - 81.2 34.7 23.2 - 48.4 53.2 37.2 - 68.6

Rift Valley 52.9 35.5 - 69.7 51.1 35.3 - 66.6 41.0 24.4 - 59.9

Western 78.8 64.1 - 88.5 55.4 45.2 - 65.2 52.0 37.4 - 66.3

Malaria Risk 0.020 0.337

High risk 76.1 66.4 - 83.7 47.5 38.3 - 56.8

Epidemic/lowest risk/no information 55.7 46.6 - 64.4 41.9 35.1 - 49.0

Population Density 0.164 0.260 0.035

Lowest density 49.9 33.9 - 66.0 32.3 17.8 - 51.2 32.7 15.8 - 55.7

Low density 69.2 57.6 - 78.9 48.5 38.4 - 58.9 39.0 29.2 - 49.7

Medium/high density 63.2 54.0 - 71.6 43.4 36.7 - 50.4 56.4 46.3 - 66.0

Provider Occupational Category <.001 <.001 <.001

Doctor/clinical technician/specialist 14.1 4.1 - 38.6 2.8 0.6 - 11.7 4.9 0.6 - 29.9

Nurse/midwife/other 65.2 58.0 - 71.7 45.0 39.3 - 50.8 48.4 40.7 - 56.1

Provider Years of Education 0.011 0.444 0.016

<14 27.2 12.1 - 50.4 39.7 24.9 - 56.7 38.9 14.1 - 71.2

14-16 67.1 58.7 - 74.4 45.5 38.7 - 52.4 51.9 43.0 - 60.6

17+ 58.2 44.2 - 71.1 39.1 30.8 - 48.1 27.8 17.7 - 40.9

Provider Salary Type 0.617 0.553 0.529

None 64.5 57.2 - 71.1 44.4 38.6 - 50.4 48.7 41.3 - 56.2

Monthly or daily salary 50.0 50.0 - 50.0 0.0 0.0 

No regular salary but other pay 60.4 35.6 - 80.7 46.1 22.3 - 71.8 37.8 12.7 - 71.7

Provider Gender 0.560 0.010 0.025

Male 59.7 44.0 - 73.6 27.7 16.9 - 41.9 31.5 18.7 - 48.0

Female 64.7 57.1 - 71.7 48.5 42.3 - 54.8 51.8 44.0 - 59.6

Total 63.5 56.6 - 69.9 43.6 38.1 - 49.4 47.0 39.5 - 54.6

N 556 1,239 556 
42 

Table 6b. Background characteristics of women observed receiving integrated services during 

ANC visits, Malawi SPA 2013-14 

Percent of women who 

discussed or received 

ITN during first ANC visit

Percent of women in the 

second and third trimester 

who received SP 

Percent of women asked 

about their HIV status, 

received counseling and 

given an HIV test during 

first ANC visit 

 % CI % CI p-value % CI p-value 

Education 0.918 0.716 0.731 

None 64.4 52.5 - 74.8 47.2 39.4 - 55.1 8.5 3.9 - 17.6 

Primary 61.9 54.0 - 69.2 44.5 40.6 - 48.5 6.9 4.1 - 11.3 

Secondary or higher 62.8 50.9 - 73.4 43.6 37.5 - 49.9 7.8 4.4 - 13.4 

Age 0.354 0.829 0.304 

<20 67.5 58.3 - 75.5 43.2 36.8 - 49.8 4.4 1.9 - 10.0 

20-35 62.1 54.2 - 69.4 45.1 40.8 - 49.6 8.4 5.2 - 13.4 

36+ 59.8 49.0 - 69.7 44.8 39.6 - 50.0 7.5 3.5 - 15.4 

Weeks pregnant 0.427 <.001 0.908 

 4-13 64.1 51.2 - 75.2 3.1 1.1 - 8.7 

 14-27 64.3 56.2 - 71.6 52.2 47.1 - 57.2 8.8 5.1 - 14.7 

 28-40 57.2 45.5 - 68.1 37.8 33.1 - 42.8 4.2 1.5 - 10.8 

First Pregnancy 0.041 0.080 0.545 

No 60.1 51.9 - 67.8 46.1 42.0 - 50.2 7.7 4.4 - 13.2 

Yes 70.1 61.3 - 77.6 40.3 34.4 - 46.4 6.3 3.4 - 11.2 

Visit <.001 

First visit 62.5 55.2 - 69.3 56.3 50.2 - 62.3 7.4 4.5 - 11.9 

Second visit 51.5 45.2 - 57.8 

Third visit 33.1 26.9 - 40.1 

Fourth or higher 18.8 13.4 - 25.9 

Type of Facility 0.003 0.316 0.822 

Hospital/Health Center/ 

Maternity Clinic 

63.5 56.0 - 70.3 45.0 41.2 - 48.8 7.3 4.4 - 12.0 

Dispensary/Clinic/Other 24.0 8.5 - 51.7 33.4 16.1 - 56.6 8.9 1.6 - 36.3 

Managing Authority 0.048 0.075 0.570 

Public 58.9 50.3 - 66.9 46.9 42.7 - 51.0 6.8 3.6 - 12.6 

Private/Other 73.3 61.3 - 82.6 38.7 31.2 - 46.7 9.0 4.3 - 18.0 

Region 0.195 0.322 0.140 

North 73.6 53.4 - 87.2 45.7 35.4 - 56.3 16.0 6.9 - 32.9 

Central 55.9 43.6 - 67.6 47.6 42.0 - 53.3 8.1 3.4 - 18.4 

South 66.0 56.9 - 74.1 41.7 36.3 - 47.3 4.8 2.5 - 9.0 

Population Density 0.066 0.862 0.245 

Lowest density 71.8 59.3 - 81.6 42.6 34.6 - 50.9 10.8 4.9 - 22.0 

Low density 64.8 56.8 - 72.0 45.3 40.7 - 50.0 5.0 2.8 - 8.7 

Medium/high density 44.7 25.0 - 66.3 44.6 34.9 - 54.7 12.0 3.6 - 33.5 

Provider Occupational Category 0.160 0.375 0.341 

Doctor/clinical technician/specialist 43.8 22.5 - 67.6 36.5 20.9 - 55.5 0.0 

Nurse/midwife/other 63.3 55.8 - 70.2 45.0 41.2 - 48.9 7.7 4.7 - 12.4 

Provider Years of Education 0.563 0.964 0.068 

<14 75.9 58.3 - 87.7 42.9 29.0 - 57.9 11.1 4.2 - 26.3 

14-16 62.2 54.8 - 69.1 44.4 39.8 - 49.1 5.5 3.1 - 9.3 

17+ 59.7 38.8 - 77.6 45.0 38.2 - 52.0 14.4 6.1 - 30.5 

Provider Salary Type 0.956 0.986 0.707 

None 60.2 40.9 - 76.7 43.7 32.5 - 55.7 11.5 4.3 - 27.0 

Monthly or daily salary 62.1 47.6 - 74.7 44.8 38.4 - 51.5 7.0 2.3 - 19.6 

No regular salary but other pay 63.3 54.8 - 71.0 44.7 40.0 - 49.6 6.8 4.0 - 11.2 

Provider Gender 0.757 0.301 0.601 

Male 60.7 46.8 - 73.1 41.5 34.4 - 49.0 5.9 2.3 - 14.5 

Female 63.1 54.7 - 70.7 45.7 41.6 - 49.9 7.8 4.4 - 13.4 

Total 62.5 55.2 - 69.3 44.7 40.9 - 48.5 7.4 4.5 - 11.9 

N 873 1,956 873 
43 

Table 6c. Background characteristics of women observed receiving integrated services during 

ANC visits, Tanzania SPA 2014-15 

Percent of women who 

discussed or received ITN 

during first ANC visit 

Percent of women in the 

second and third trimester 

who received SP 

Percent of women asked 

about their HIV status, 

received counseling and 

given an HIV test during 

first ANC visit 

 % CI p-value % CI p-value % CI p-value

Education 0.444 0.423 0.411

None 10.1 5.5 - 17.8 19.2 14.4 - 25.2 39.6 30.4 - 49.5

Primary 10.7 7.7 - 14.7 21.3 17.9 - 25.2 44.1 38.2 - 50.1

Secondary or higher 14.5 9.2 - 22.2 17.4 11.8 - 24.7 47.6 39.3 - 56.1

Age 0.370 0.382 0.482

<20 11.5 6.7 - 18.9 22.8 17.8 - 28.7 39.4 31.4 - 48.1

20-35 12.2 8.7 - 17.0 19.8 16.3 - 23.9 43.9 37.8 - 50.3

36+ 8.8 5.6 - 13.7 19.5 15.7 - 23.9 45.5 38.1 - 53.1

Weeks pregnant 0.181 0.009 0.578

 4-13 13.1 6.1 - 25.8 48.8 37.0 - 60.8

 14-27 12.2 8.7 - 16.8 23.1 19.2 - 27.5 43.3 37.8 - 49.0

 28-40 6.8 3.6 - 12.4 17.7 14.2 - 21.8 42.4 34.8 - 50.4

First Pregnancy 0.575 0.368 0.390

No 10.7 7.6 - 15.0 19.8 16.5 - 23.4 42.8 37.2 - 48.6

Yes 12.3 7.8 - 18.8 21.7 17.1 - 27.2 46.1 38.9 - 53.5

Visit na 0.003 na

First visit 11.1 8.1 - 15.0 24.0 19.7 - 29.0 43.5 38.4 - 48.9

Second visit 17.8 14.2 - 22.0 

Third visit 18.3 13.6 - 24.3 

Fourth or higher 14.3 10.2 - 19.8 

Type of Facility 0.451 0.053 0.082

Hospital/Health Center/ 

Maternity Clinic 

9.8 7.7 - 12.3 24.3 20.8 - 28.2 48.8 44.3 - 53.3

Dispensary/Clinic/Other 11.8 7.7 - 17.7 18.0 13.7 - 23.4 41.0 33.8 - 48.6

Managing Authority 0.174 0.408 0.683

Public 12.0 8.6 - 16.6 19.6 16.0 - 23.9 44.0 37.9 - 50.2

Private/Other 7.0 3.3 - 14.3 22.9 16.8 - 30.3 41.7 33.1 - 50.8

Region <.001 0.543 <.001

Central 9.0 4.2 - 18.5 20.2 13.3 - 29.4 56.1 44.1 - 67.4

Northern 7.7 3.3 - 16.6 18.8 12.3 - 27.5 59.8 47.4 - 71.0

Coastal 6.4 2.7 - 14.6 25.7 19.6 - 33.0 43.2 28.9 - 58.6

Southern Highlands 13.5 7.5 - 22.9 22.1 15.6 - 30.5 58.9 45.1 - 71.4

Lake 7.1 3.7 - 13.4 18.0 12.6 - 25.1 35.8 27.3 - 45.3

Zanzibar 41.5 21.4 - 64.9 na 13.6 7.2 - 24.0

Population Density 0.028 0.953 0.580

Lowest density 7.3 4.9 - 10.9 20.5 16.2 - 25.5 45.8 38.4 - 53.5

Low density 13.0 7.3 - 21.9 21.5 15.6 - 28.9 39.8 30.2 - 50.3

Medium/high density 20.7 10.4 - 37.0 19.3 11.6 - 30.5 41.4 30.8 - 52.9

Provider Occupational Category 0.220 0.018 0.245

Doctor/clinical technician/specialist 5.6 1.7 - 17.2 7.0 2.4 - 18.6 31.8 16.0 - 53.3

Nurse/midwife/other 11.5 8.4 - 15.5 21.2 17.8 - 25.0 44.3 39.0 - 49.7

Provider Years of Education 0.122 0.459 0.254

<14 8.9 5.5 - 13.9 20.5 16.3 - 25.4 40.4 33.8 - 47.3

14-16 14.2 9.6 - 20.5 19.0 14.5 - 24.6 47.0 39.0 - 55.2

17+ 18.0 7.9 - 35.8 26.8 18.0 - 38.0 50.2 35.9 - 64.5

Provider Salary Type 0.075 0.290 0.048

None 7.4 3.5 - 14.9 17.3 11.9 - 24.3 35.5 25.0 - 47.6

Monthly or daily salary 7.5 4.1 - 13.3 17.9 12.9 - 24.1 54.3 44.5 - 63.7

No regular salary but other pay 14.4 9.7 - 20.7 22.8 17.8 - 28.7 41.9 34.7 - 49.4

Provider Gender 0.036 0.116 0.662

Male 5.2 2.3 - 11.2 14.1 8.0 - 23.5 40.6 27.2 - 55.5

Female 12.3 8.8 - 16.9 21.6 18.1 - 25.5 44.1 38.6 - 49.8

Total 11.1 8.1 - 15.0 20.3 17.1 - 23.9 43.5 38.4 - 48.9

N 1,847 3,428 1,847 

Note: Since SP is not provided in ANC in Zanzibar, women in that area were excluded. 

 
44 

3.3.2. Is receiving integrated services in each area associated with higher integration capacity and/or 

integration components? 

Figures 16-18, for Kenya, Malawi, and Tanzania respectively, show the difference in the facility-level 

integration score of ANC with malaria and PMTCT among women attending ANC and their receipt of 

integrated care services related to malaria and PMTCT. Women who did not receive integrated care such 

as ITNs, SP, or HCT during ANC are compared with women who did, by their facility’s integration score. 

A t-test is applied to test the significance of these differences; Appendix Table 6 presents the corresponding 

p-values. Testing shows significant differences between women’s receipt of care and facility integration for 

overall facility integration of ANC with malaria and women’s receipt or counseling of ITNs in Kenya (p 

<.001), direct observation of SP consumption in Kenya (p <.001) and Tanzania (p <.001); and among 

women’s receipt of HCT and ANC-PMTCT integration in Tanzania (p <.001). 

Figure 16. Average facility integration score by receipt of integrated care among women in ANC, 

Kenya SPA 2010 

Figure 17. Average facility integration score by receipt of integrated care among women in ANC, 

Malawi SPA 2013-14 

0

10

20

30

40

50

60

70

80

90

100

Did not

receive ITN

or

counseling

Received

ITN or

counseling

Did not

receive SP

Received SP Did not

receive HCT

Received

HCT

Malaria score PMTCT score

Kenya

0

10

20

30

40

50

60

70

80

90

100

Did not

receive ITN

or

counseling

Received

ITN or

counseling

Did not

receive SP

Received SP Did not

receive HCT

Received

HCT

Malaria score PMTCT score

Malawi
45 

Figure 18. Average facility integration score by receipt of integrated care among women in ANC, 

Tanzania SPA 2014-15 

Since facility capacity to provide components of integration varied within each ID service area in a country, 

the potential differences in receipt of care was examined by availability of each component of integration. 

This was done to assess whether any single or combination of components influenced the associations with 

an overall score more strongly than another. With a chi-square test of independence, bivariate associations 

examined receipt of integrated care services and the various components of integration in the relative areas. 

Tables 7-9 present these results. 

Table 7 shows the percentage of women who discussed or received ITN during first ANC visit, by 

components of malaria integration in the three countries. As expected, the percentage of women who 

received or discussed ITNs during ANC is more than twice as high among women who received care in 

facilities that routinely distribute and have ITNs available. This is true even in Tanzania, where at the time 

of the survey there was no government-sponsored program to distribute free ITNs or vouchers. The only 

other significant association between women’s receipt of an ITN and any malaria-related integration 

component is by facilities with RDT available in Tanzania, although the association is not in the expected 

direction; a higher percentage of women received or discussed ITN use at facilities where RDT is not 

routinely given or available than women at facilities with RDT. 

0

10

20

30

40

50

60

70

80

90

100

Did not

receive ITN

or

counseling

Received

ITN or

counseling

Did not

receive SP

Received SP Did not

receive HCT

Received

HCT

Malaria score PMTCT score

Tanzania
46 

Table 7. Percent of women who discussed or received ITN during first ANC visit, by components of 

malaria integration in Kenya, Malawi, and Tanzania 

Kenya Malawi Tanzania 

 % 95% CI p-value % 95% CI p-value % 95% CI p-value

ANC and malaria services 0.180 0.703 0.877 

No 54.6 43.0 - 65.7 64.5 52.0 - 75.3 11.7 5.2 - 24.3 

Yes 63.6 56.6 - 70.0 61.7 52.7 - 69.9 11.0 7.8 - 15.2 

Trained staff 0.396 0.384 0.517 

No 57.0 40.5 - 72.1 58.5 48.5 - 67.8 9.8 5.9 - 15.9 

Yes 64.7 57.0 - 71.8 64.5 54.6 - 73.4 12.2 8.0 - 18.2 

Malaria RDT 0.652 0.163 0.043 

No 63.9 56.4 - 70.8 64.8 56.1 - 72.7 11.9 8.5 - 16.5 

Yes 59.8 42.7 - 74.8 54.2 41.5 - 66.3 6.7 4.1 - 10.6 

ITNs <.001 <.001 0.001 

No 34.4 25.4 - 44.7 26.7 13.2 - 46.4 8.1 5.6 - 11.6 

Yes 80.8 72.0 - 87.3 70.3 63.8 - 76.0 23.5 14.1 - 36.6

IPTp 0.401 0.080 

No 56.6 38.9 - 72.8 * 14.5 9.0 - 22.5 

Yes 64.5 57.1 - 71.2 62.6 55.3 - 69.4 8.6 5.9 - 12.2 Total 63.5 56.6 - 69.9 62.5 55.2 - 69.3 11.1 8.1 - 15.0 

N 556 873 1,847 

Note: Since SP is not provided in ANC in Zanzibar, women in that area were excluded from the Tanzania analysis. 

Table 8 shows the percentage of women who received SP during an ANC visit in their second and third 

trimester, by components of malaria integration. There are significant differences in SP consumption by 

certain integration components among women in Kenya and Tanzania, but not in Malawi. In both Kenya 

and Tanzania, women who attended ANC at facilities with at least one ANC provider who also provided 

and had recent training in malaria services were significantly more likely to consume SP than women at 

facilities without malaria-trained ANC providers, by over 10 percentage points in each country. In Kenya, 

women who attended ANC at facilities with ITNs available also consumed SP more often than women who 

at facilities without ITNs. As expected, women who attended ANC at facilities with SP consumed SP more 

than women at facilities without SP (p <.001 in Kenya and Tanzania). In Tanzania, no women at facilities 

without SP received SP during ANC. In Kenya, 15% of women still consumed SP at facilities without SP, 

and it is unclear where the women in these facilities obtained SP. 
47 

Table 8. Percent of women in the second and third trimester who received SP, by components of 

malaria integration in Kenya, Malawi, and Tanzania 

Kenya Malawi Tanzania 

 % 95% CI p-value % 95% CI p-value % 95% CI p-value 

ANC and malaria services 0.100 0.330 0.175 

No 54.6 43.0 - 65.7 41.5 34.2 - 49.2 13.8 8.3 - 22.0 

Yes 43.6 38.0 - 49.4 45.8 41.6 - 50.2 19.5 16.3 - 23.2

Trained staff 0.024 0.230 0.001 

No 31.9 22.9 - 42.5 41.6 35.9 - 47.5 12.5 9.1 - 16.9 

Yes 46.1 39.7 - 52.6 46.2 41.5 - 51.1 23.4 19.0 - 28.4

Malaria RDT 0.558 0.396 0.039 

No 44.0 38.1 - 50.2 45.5 41.1 - 49.9 17.1 13.9 - 20.9

Yes 39.4 26.4 - 54.1 41.8 34.7 - 49.2 25.4 18.7 - 33.4

ITNs 0.011 0.736 0.091 

No 34.8 27.5 - 42.8 46.2 36.7 - 55.9 19.5 16.0 - 23.7

Yes 48.7 41.5 - 56.0 44.3 40.3 - 48.4 13.9 9.9 - 19.2 

IPTp <.001 <.001 

No 15.2 6.7 - 31.0 * 0.370 0.0 0.0 - 0.2 

Yes 46.9 41.2 - 52.6 44.7 41.0 - 48.5 33.5 28.7 - 38.6

Total 43.6 38.1 - 49.4 44.7 40.9 - 48.5 20.3 17.1 - 23.9

N 1,239 1956 3,428 

Note: Since SP not provided in ANC in Zanzibar, women in that area were excluded from the Tanzania analysis. 

Table 9 shows the percentage of women who were asked about their HIV status, received counseling, and 

given an HIV test during their first ANC visit, by components of PMTCT integration in the three countries. 

Women’s receipt of HCT varied significantly across integration components only in Tanzania. In Tanzania, 

women who attended ANC at a facility with at least one ANC provider who also provides and has recent 

training in PMTCT, at clinics with PMTCT available at the same site as ANC, and at facilities with testing 

services available on-site received HCT significantly more than women at facilities without these services. 

Table 9. Percent of women asked about their HIV status, received counseling and given an HIV test 

during first ANC visit, by components of PMTCT integration in Kenya, Malawi, and Tanzania 

Kenya Malawi Tanzania 

 % 95% CI p-value % 95% CI p-value % 95% CI p-value

ANC and HCT services 0.300 0.740 0.329 

No 38.5 22.2 - 57.8 8.2 4.2 - 15.3 38.4 26.9 - 51.2 

Yes 49.4 41.5 - 57.3 7.0 3.5 - 13.4 45.3 39.6 - 51.1 

Trained staff 0.890 0.910 0.002 

No 47.8 34.2 - 61.8 7.0 2.5 - 17.8 30.6 22.7 - 40.0 

Yes 46.7 37.9 - 55.6 7.4 4.2 - 12.8 48.9 42.4 - 55.3 

Same site 0.469 0.851 <.001 

No 39.7 22.0 - 60.7 6.7 2.3 - 18.1 23.3 15.1 - 34.1 

Yes 47.9 39.9 - 56.1 7.5 4.3 - 12.9 47.9 42.0 - 53.9 

HIV testing 0.721 0.276 <.001 

No 49.3 33.6 - 65.1 0.0 10.5 4.2 - 23.8 

Yes 45.9 37.9 - 54.1 7.9 4.8 - 12.7 49.2 43.5 - 54.8 

PMTCT ART 0.721 0.582 0.161 

No 46.5 38.2 - 55.1 11.2 2.3 - 40.4 41.0 34.4 - 48.0 

Yes 49.6 35.5 - 63.8 7.1 4.2 - 11.8 48.6 40.7 - 56.5 

Total 47.0 39.5 - 54.6 7.4 4.5 - 11.9 43.5 38.4 - 48.9 

N 556 873 1,847 

The final phase of analysis used logistic regression models to test for associations between women’s receipt 

of integrated care and integration capacity at the facility while controlling for characteristics of women, 

providers, and facilities. The multivariable analysis included only outcomes in countries for which bivariate 

associations with overall integration are found: SP consumption in Kenya and Tanzania, and HCT in 

Tanzania. A logistic regression model was not used to examine predictors of receipt or counsel of ITNs 
48 

among women in Kenya because malaria prevalence varies throughout the country, the national malaria 

program’s provision of ITNs is not universally executed throughout Kenya, and there was a small sample 

of women observed attending the first ANC visit for that pregnancy in malaria-endemic and other areas. 

For the three remaining areas where integration is significantly associated with receipt of integrated care, 

the analysis required two models for each. One examined overall integration as the main predictor and the 

second with each integration component. One integration component was removed from the second model 

because of the circular relationship between the covariate and the outcome. For consumption of SP in ANC, 

the component of SP availability was excluded; for HCT, the component of availability of HIV diagnostic 

capacity was also excluded. 

Table 10 shows the results of the logistic regression models that tested for associations of consumption of 

SP among women in their second or third trimester in Kenya and Tanzania with characteristics of women, 

facilities and providers. In Kenya, the odds of a women consuming SP increase by 4% for every one unit 

increase in the overall facility integration score (p <.001). Because this integration score is standardized 

and represents an average of the availability of five components of integration multiplied by 100, we cannot 

conclude that one unit is equal to one integration component. If the integration score is de-standardized (rescaled to an average of components on a scale of 0 to 5) and included in the model instead, the odds ratio 

increases to 2.01 (results not shown). Therefore, the odds of consuming SP increase by 200%, or 

approximately doubles for every additional integration component available at a facility. However, this 

analysis does not explore whether or not each integration item is weighted equally. Given the redundancy 

between the outcome and one component of the integration score (women receiving SP and availability of 

SP at the facility), these results should be interpreted with caution. Similarly, in Tanzania, the odds of 

receiving SP were 5% higher for every unit increase in the integration score, with approximately 2.5 times 

the odds of receiving SP for every additional integration component available at the facility where the 

women attended their ANC visit. Women in Zanzibar were excluded from this analysis because there were 

differing policies on the island. 

To further explore the relationship between integrated services available at facilities and the receipt of 

integrated care, the facility’s integration score was replaced with the individual components in the model 

and the component for having SP available within the facility was excluded. In Kenya, there are associations 

with other integration components, as well as some characteristics of women, facilities, and providers. 

Women had almost twice the odds of receiving SP if they attended a facility with at least one ANC provider 

who also provides and has training in malaria services (odds ratio (OR) = 1.91, p<.05), and had 2.3 times 

the odds of consuming SP at a facility that also routinely distributed or provided counseling on ITNs and 

had them available (OR = 2.26, p<.01). Women age 36 or older were more likely than women under age 

36 (OR = 1.7, p<.01), women at private (or other) facilities versus public facilities (OR = 2.87, p<.001), 

and women with a female versus male provider (OR = 2.83, p<.01) were also more likely to have been 

observed consuming SP during their ANC visit. Women were less likely to receive SP if their provider was 

a doctor, clinical technician, or specialist compared with a nurse, midwife, or other occupation (OR = 0.13, 

p <.05) or if they were attending their third or fourth visit (OR = .25, p<.001 and OR = .24, p<.001, 

respectively). 

In Tanzania as in Kenya, if the facility had at least one ANC provider who also provided and had recent 

training in malaria, women had two and a half times the odds of receiving SP (OR = 2.51, p<.001). Unlike 

Kenya, however, no provider or facility characteristics in Tanzania were significantly associated with 

receiving integrated care. Only education (women with primary education compared with none, OR = 1.56, 

p<.05) and visit number (women attending their second visit compared with first, OR = .64, p<.01 and 

women attending their fourth visit, OR = .47, p<0.1) were associated with receiving integrated care. All 

models controlled for region, high or low malaria endemicity (Kenya only), population density, client’s 

first or subsequent pregnancy, client’s second versus third trimester, provider education, and provider 

salary. All differences were non-significant (results not shown). 
49 

Table 10. Adjusted odds ratios of receipt of SP in the second or third trimester during ANC visits, 

Kenya and Tanzania 

Kenya Tanzania 

 AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI 

Overall malaria integration 1.04*** 1.02 - 1.05 1.05*** 1.04 - 1.06

ANC and malaria services 1.74 0.40 - 7.52 1.33 0.67 - 2.61

Trained staff 1.91* 1.09 - 3.35 2.51*** 1.55 - 4.06

Malaria RDT 0.93 0.44 - 1.97 1.39 0.84 - 2.28

ITNs 2.26** 1.24 - 4.10 1.11 0.67 - 1.81

IPTp na na 

Education 

None 0.94 0.39 - 2.27 0.89 0.37 - 2.13 1.64 0.97 - 2.75 1.45 0.87 - 2.41

Primary 0.98 0.65 - 1.48 0.93 0.61 - 1.42 1.64* 1.05 - 2.55 1.56* 1.02 - 2.37

Secondary or higher 1.0 - 1.0 - 1.0 - 1.0 - 

Age <20 1.0 - 1.0 - 1.0 - 1.0 - 

20-35 1.02 0.64 - 1.64 1.02 0.63 - 1.64 0.82 0.58 - 1.18 0.89 0.63 - 1.26

36+ 1.91* 1.05 - 3.48 1.87* 1.01 - 3.45 0.73 0.49 - 1.09 0.78 0.53 - 1.16

Visit 

First visit 1.0 - 1.0 - 1.0 - 1.0 - 

Second visit 0.70 0.45 - 1.11 0.73 0.46 - 1.17 0.65** 0.47 - 0.89 0.64** 0.47 - 0.88

Third visit 0.25*** 0.14 - 0.42 0.25*** 0.15 - 0.43 0.71 0.49 - 1.01 0.71* 0.51 - 1.00

Fourth or higher 0.24*** 0.13 - 0.44 0.24*** 0.13 - 0.45 0.43** 0.26 - 0.72 0.47** 0.29 - 0.75 

Type of Facility Hospital/Health Center/ 

Maternity Clinic 

1.0 - 1.0 - 1.0 - 1.0 - 

Dispensary/Clinic/Other 1.35 0.75 - 2.45 1.20 0.64 - 2.25 1.74* 1.03 - 2.95 1.10 0.67 - 1.79

Managing Authority 

Public 1.0 - 1.0 - 1.0 - 1.0 - 

Private/Other 2.88*** 1.56 - 5.32 2.87*** 1.55 - 5.32 0.91 0.54 - 1.52 0.82 0.49 - 1.37 

Provider Occupational 

Category Doctor/clinical technician/ 

specialist 

0.15* 0.03 - 0.83 0.13* 0.02 - 0.76

0.37 

0.11 - 1.24 0.37 0.11 - 1.27

Nurse/midwife/other 1.0 - 1.0 - 1.0 - 1.0 - 

Provider Gender 

Male 1.0 - 1.0 - 1.0 - 1.0 - 

Female 2.91*** 1.56 - 5.45 2.83** 1.51 - 5.30 1.34 0.67 - 2.71 1.40 0.70 - 2.83

 N 1,205 1,205 3,371 3,371 

Note: The integration variables in the model are for the availability of these services; the reference category for each is the absence of 

availability. Models also adjusted for: region, malaria risk (Kenya only), population density, if it was a client’s first pregnancy, if she was 

in her second versus third trimester, provider education, and provider salary. Except for region in Kenya, all other covariates were not 

significant in the final adjusted model; SP is not routinely provided in ANC in Zanzibar so women in that area were excluded for the 

analysis of receipt of SP; Women who did not have complete background information for all variables were excluded from the regression 

analysis; P-values are represented by asterisks: *<0.05, **<0.01, ***<0.001. 
50 

Table 11 shows the results of the multivariable logistic regressions on women’s receipt of HCT during the 

first ANC visit in Tanzania. Women who received HCT were 2% more likely to receive HCT for every unit 

increase in PMTCT integration score. This translates to an increase of about one and a half times the odds 

of receiving HCT for every additional integration component available at the facility. When the individual 

PMTCT integration components (except for indicator for routinely providing tests and having diagnostic 

equipment available) are substituted for the overall score, only having PMTCT available at the same site as 

ANC is significantly associated with receiving HCT during ANC. Women who attended a facility that had 

PMTCT at the same site as ANC had almost two and half times the odds of receiving HCT than women 

who attended ANC at facilities without this structure available (OR = 2.41, p<.01). This model controlled 

for all other covariates, although no significant associations were found except for region. Women in 

Zanzibar were less likely to receive HCT compared with women in the Central zone (OR = .17, p<.001) 

(results not shown). 

Table 11. Adjusted odds ratios of whether a client was asked about their 

HIV status, received counseling, and was given an HIV test during first ANC 

visit, Tanzania 

 AOR 95% CI AOR 95% CI 

Overall PMTCT integration 1.02** 1.01 - 1.03 

ANC and HCT services 1.09 0.59 - 2.02 

Trained staff 1.54 0.91 - 2.61 

Same site 2.42** 1.28 - 4.58 

HIV testing na 

PMTCT ART 0.85 0.51 - 1.43 

N 1,687 1,687 

Note: The integration variables in the model are for the availability of these services, and the reference 

category for each is the absence of availability. Models also adjusted for: type of facility, managing 

authority, region, population density, if it was a client’s first pregnancy, number of weeks pregnant, 

client age and education, provider occupation, provider education, provider salary, and provider sex. 

All covariates were not significant except region. Women who did not have complete background 

information for all variables were excluded from the regression analysis; P-values are represented by 

asterisks: *<0.05, **<0.01, ***<0.001. 
51 

4. Discussion 

4.1. Overview of Findings 

The three countries examined in this study—Kenya, Malawi, and Tanzania—demonstrate both similarities 

and differences in overall availability of ID services at facilities with ANC services, health worker provision 

and training in multiple service areas, capacity to provide integrated services at facilities, and provision of 

integrated services during observed ANC visits. In all three countries, malaria services within ANC 

facilities are widely available and, to a lesser extent, PMTCT services. Availability of TB services is notably 

lowest in Tanzania, and in all three countries the availability of TB services is lowest in areas with the 

lowest population density. A larger percentage of hospitals, health centers, and maternity clinics have both 

ANC and PMTCT or TB services available compared with dispensaries, clinics, or other facilities. In Kenya 

and Malawi, these services are more available in public versus private facilities. Less than half of the ANC 

providers in each country offer and have recent training in PMTCT, and even fewer provide and are recently 

trained in malaria. Few provide ANC and TB services and have recent training in TB or TB/HIV coinfection. 

At the national level in each country, integrated services for ANC with TB/HIV are least common. The 

average PMTCT integration score is higher in Malawi and Tanzania than in Kenya, although integration 

with malaria is highest in Kenya. Across the countries, there is substantial variation in the availability of 

components of integrated malaria services; this may be due to differences in national and sub-national 

policies related to malaria in pregnancy. Thus, national-level results should be interpreted with caution. 

Among women observed in ANC, receipt of integrated services varied by the specific service and country, 

with fewer similarities seen across the countries. The integration score and select integration components 

are significantly associated with receiving integrated care for consuming SP in Kenya and Tanzania, as well 

as HCT in Tanzania. Further discussion of the integration with each infectious disease appears below. 

4.2. ANC and PMTCT 

In all three countries, about half of facilities that offer ANC services are equipped to provide each 

component of integrated ANC-PMTCT services, except for ARTs in Kenya and Tanzania. The average 

ANC-PMTCT integration score is higher in Malawi and Tanzania than in Kenya. In Malawi and Tanzania, 

the national integration score equates to facilities having about three and a half integration components 

available, compared with about two and a half in Kenya. In all three countries, higher-level facilities are 

prepared to provide integrated services at higher proportions than lower-level facilities, and for the most 

part public facilities are more prepared than private facilities, both for the individual components and across 

the national averages. The differences by region and population density are less pronounced. 

Just under half of the women observed during their first ANC visit were asked if they knew their status, 

given an HIV test, and counseled on HIV in Kenya and Tanzania; in Malawi, however, only 7% of women 

received this full package of services under direct observation of the interviewer. At the bivariate level of 

analysis, there were no significant differences by women’s background characteristics. A limited number 

of differences by facility characteristics appeared, although these differences were not consistent across the 

countries. Several provider characteristics were significantly associated with women’s receipt of HCT 

during ANC in Kenya only; most notable was the higher percentage of women who received HCT if 

attended by a nurse, midwife, or other occupation versus a doctor, clinical technician, or specialist. 

In Tanzania, the facility integration score for ANC with PMTCT was significantly associated with receipt 

of HCT (among women in their first ANC visit), at the bivariate level. This association remained significant 

after controlling for background characteristics of women, providers, and facilities. One important caveat 

in this model is that the integration score included the component that assessed whether the facility had 
52 

HIV diagnostic capacity. This component likely influenced the significance of the association between 

receipt of HCT and overall integration. After the second model excluded HIV diagnostic capacity, only one 

component remained significantly associated with receipt of HCT: having ANC and PMTCT services at 

the same site—which is the essence of integrated services (Foreit, Hardee, and Agarwal 2002). This finding 

contrasts with previous research that found that co-location was not sufficient for patient care, although the 

earlier study focused on integration of TB/HIV services (Uyei et al. 2014). 

In Malawi, there is a large disparity between availability of integrated PMTCT services and receipt of care. 

While the integration score was higher in Malawi than in the other two countries, receipt of HCT during 

ANC was the lowest by far. This finding is quite troublesome, for several reasons. First, according to the 

most recent DHS surveys in the three countries, Malawi has the highest HIV prevalence. Second, this 

finding differs from the information reported in the DHS, where 86% of women say they were counseled 

for HIV during ANC, and 79% say they were counseled, tested, and received the results during ANC 

(Malawi 2011b). The Malawi AIDS Progress Report of 2015 reports findings similar to the DHS (Malawi 

2015). 

As defined in this study, this indicator is based on whether a client was asked if she knew her status, if she 

received counseling and if a test was performed during the visit. When examining each of these elements 

of HCT separately, further analysis revealed that in Kenya and Tanzania the percentage of women being 

asked their status during ANC is comparable to the percentage of women receiving the same services in 

Kenya and Tanzania, but fewer women receive counseling in Malawi (41%) than in Kenya (58%) or 

Tanzania (74%). Even more striking is the difference in the percent of women who have a test performed 

during the visit. Only 9% of women in their first ANC visit received the test in Malawi, compared with 

79% in Kenya and 62% in Tanzania (results not shown). Incidentally, in Malawi 44% are referred for testing 

compared with 24% in Kenya and 10% in Tanzania. After combining internal and external testing, still only 

52% of women in Malawi receive tests, compared with 87% in Kenya and 71% of women in Tanzania. 

Why aren’t women observed at ANC facilities in Malawi receiving HIV counseling and testing services as 

often as in nearby countries with similar HIV prevalence, particularly when facilities and health workers in 

Malawi are so relatively well equipped to provide these services? Malawi’s national response to the 

HIV/AIDS epidemic has been a model for successful treatment with ART and reduction of HIV mortality 

(Dasgupta et al. 2016). WHO recommends that women should be offered testing whether or not their status 

is known (WHO 2011) and the Malawi National Guidelines for Management of HIV specify that providerinitiated counseling and testing (PITC) should be offered if the patient has tested negative or if that test was 

not done in the last three months (Malawi 2011a). Although the SPA questionnaire does not assess whether 

or not the test was offered and refused or if it was offered at all, qualitative research with women attending 

ANC in Malawi found that women feel they cannot refuse, or were not given an option to refuse the test 

(Angotti, Dionne, and Gaydosh 2011; Obermeyer et al. 2014). It does not appear that stock-outs of RDTs 

were a problem at the time of the survey, since only 33% of the health facilities that offer HIV RDT in 2014 

reported any stock-out in the previous 12 months (Malawi 2015). Our findings of availability of HIV RDT 

at the time of the survey also do not indicate that the availability of RDT available was an issue. 

One other explanation for the low level of observed HIV testing in Malawi is that testing occurs in another 

room dedicated to HCT and not in the room where the ANC visit is conducted. In Malawi, two items in the 

inventory questionnaire confirm that the vast majority of facilities with ANC services (87%) have a system 

that assures ANC procedures will occur prior to the observation of an ANC visit; these include HCT. This 

practice was reported or observed in 80% of all ANC facilities. A provider may not be observed performing 

the test, but since a woman does not require a referral to an outside source, she is not documented as being 

referred for testing either. Therefore, while the facilities are in fact equipped to perform multiple services 

under one roof, women who receive HCT are not actively observed receiving these integrated services and 

are therefore not accurately accounted for. In Tanzania, only 48% of facilities with ANC routinely provide 
53 

HCT prior to the ANC visit. (This question is not asked in the Kenya SPA). While this percentage is less 

than in Malawi, the difference in the system of service provision may explain the differences between 

observed HCT in ANC visits in Malawi and Tanzania. 

4.3. ANC and TB/HIV 

The capacity to provide integrated ANC-TB or ANC-TB/HIV services is much lower than the capacity to 

provide integrated ANC-PMTCT or ANC-malaria services. ANC providers are not as often trained in TB 

as other services. Across all three countries, more males and higher-qualified providers also provide and 

have training in TB services. Having the capacity to provide any one integrated service for ANC and TB or 

TB/HIV services is only seen in one-third or less of all facilities in all three countries, with the national 

average for each country less than 30%. This means that, on average, only approximately one and a half 

components of ANC and TB/HIV integration are available in Kenya, one in Malawi, and less than one in 

Tanzania. It is important to note that in Kenya, the score is perhaps more lenient. Service availability in 

Malawi and Tanzania requires availability three days per week for ANC and TB, whereas in Kenya, the 

survey does not capture the number of days per week. In each country, a greater percentage of higher-level 

facilities have integrated services capabilities compared with lower-level facilities; integrated services are 

offered at public facilities more than private facilities, and are least available at facilities in the areas with 

lowest population density. This is true among the components of integration as well as the national average. 

Although TB/HIV co-infection occurs in one-third to one-half of all people living with HIV in the three 

countries in this report, less than 10% of facilities in all three countries offer TB prophylactic medication 

to HIV patients or have the medication available, and less than 1% in Tanzania. These findings are 

consistent with other research that shows the capacity to diagnose and treat TB or TB/HIV co-infection as 

insufficient to halt the spread of TB, particularly with the emergence of drug-resistant forms of TB (Zumla 

et al. 2012). More financing for diagnostics and drugs will be needed to meet the goals of the End TB 

Strategy and the Sustainable Development Goals, which aim to eliminate or nearly eliminate TB (WHO 

2015a). 

4.4. ANC and Malaria 

The availability of integrated ANC-malaria services is much more varied by indicator and country, as well 

as facility characteristics within the countries. Surprisingly, few facilities in the three countries offer 

malaria-RDT during ANC and have RDT available. Similar to integration with TB, the service availability 

indicator in Malawi and Tanzania pertains to facilities with services available at least three days per week. 

With this exception in mind, Kenya scored slightly higher than Malawi and 20 percentage points higher 

than Tanzania for average availability of integrated services of ANC and malaria. These scores are roughly 

equivalent to having about three of the five integration components available at Kenyan and Malawian 

facilities, and roughly two components available in Tanzanian facilities. In Kenya, integration of ANC and 

malaria is more common than PMTCT; in Malawi and Tanzania, however, the opposite is true. 

The two outcomes that assessed whether or not malaria prevention and treatment is currently being 

integrated into ANC visits were counseling or distribution of ITNs and consumption of SP during the ANC 

visit. The proportion of women who received these services was roughly the same in Kenya and Malawi. 

Just under two-thirds of women in both countries received counseling or received an ITN during their first 

visit and just under half received and consumed SP. In Tanzania, these proportions are much lower. Only 

11% of women were counseled on or received an ITN and one-fifth of women (on the mainland) received 

SP. The low levels of malaria prevention interventions in ANC are consistent with results from other studies 

(Hill et al. 2013; van Eijk et al. 2011). 

Receipt of integrated ANC-malaria services, specifically direct observation of SP, was significantly 

associated with overall integration in Kenya and Tanzania. This was true even after controlling for the 
54 

characteristics of women, providers, and facilities. Like the receipt of HCT and having HIV diagnostic 

capacity, receipt of SP and the availability of SP within a facility are tautological. Thus, a second model 

within each country excluded this component and evaluated each remaining component for associations 

with the outcome. These models showed that a facility with at least one staff person who provides both 

ANC and malaria services and has received recent training in malaria is significantly associated with 

women’s receipt of SP. 

Many barriers to consumption of SP have been identified, such as women’s lack of knowledge about the 

benefits or health risks, delayed initiation of ANC, the cost of medication, poor knowledge or confusion on 

the part of the health worker, and frequent stock-outs (Hill et al. 2013; PMI 2009). Recommendations for 

the provision of SP have changed over time in both the timing of the provision and the number of doses to 

provide, and this may have contributed to confusion about the administration of IPTp-SP (WHO 2014). 

This may be seen in our finding that women in the third or fourth visit were less likely to receive SP than 

women in their first visit. In Kenya, there was a significant association between women attending facilities 

that provide counseling or distribute ITNs and receipt of SP. It is possible that these facilities are better 

stocked, are located in areas with higher prevalence of malaria, and are more prepared to manage malaria 

prevention and treatment. However, the model in Kenya controlled for malaria endemicity, and this variable 

was not significantly associated with the outcomes. 

When considering the availability and provision of integrated services with ANC and malaria, it is 

important to consider the endemicity of the region and region-specific malaria policies, particularly at the 

time of the survey. In Kenya and Tanzania, the prevalence of malaria varies greatly by region. At the time 

of the most recent AIS/MIS survey in Tanzania, the prevalence among children age 6-59 months was less 

than 1% in some regions and as high as 32% in another (TACAIDS 2013). In Kenya, the malaria prevalence 

in children tested during the 2010 MIS ranged from less than 1% to 38%. Therefore, it is not surprising that 

our findings show the distribution of ITNs and coverage of IPTp-SP to be distributed unevenly across 

geographical areas in these countries. This could also be due in part to regional policies (Zanzibar may 

revise their policy to discontinue IPTp-SP because of the low prevalence of malaria (PMI 2014)), or focused 

promotions of selected interventions, such as the distribution of ITNs to pregnant women in malariaendemic areas (Kenya 2009). 

4.5. Strengths and Limitations 

This study benefits the body of literature in integrated services because it examines the capacity of health 

facilities to provide integrated services of ANC with multiple types of ID in areas of high need. The high 

prevalence of these infectious diseases and co-morbidities in these three countries in East Africa warrants 

attention to health service delivery in order to identify the most efficient and effective ways to provide 

critical interventions where they are needed. This study links integration at the facility level to outputs at 

the client level related to receiving integrated service delivery. In addition, the analysis examines overall 

integration as a composite of multiple components that represent service availability and readiness related 

to integrated services, as well as by individual components. The study concludes that certain facets of 

integration may not be as important as others. 

The main limitation of this study is that the SPA questionnaires focus on vertical services and cannot fully 

measure integrated services. Thus, only through combining responses from several questions can we infer 

that integrated services are possible. One example of the SPA’s limited ability to capture integrated services 

is in Malawi, and to a lesser extent in Tanzania, where women can go to one facility to obtain multiple 

services, although the services are not delivered in the same room. This may fall in the middle of the 

integrated services continuum, somewhere between no integration and full integration. In addition, the 

survey design and the design of the variables used in this study are not sensitive enough to assess gradations 

of integrated services. There may be more direct ways of measuring integration with questionnaires 
55 

designed to examine the nuances of whether women who are attending ANC are also assessed and treated 

for certain infectious diseases during the same visit. The SPA surveys also do not measure all aspects of 

integration, such as an integrated financing, management, or surveillance systems. 

Another limitation of this study is that The DHS Program revised the standardized SPA survey between the 

time of the Kenya 2010 SPA and the most recent Malawi and Tanzania SPA surveys. Thus, the questions 

in the most recent Kenya SPA survey do not always match the questions in the Malawi and Tanzania 

surveys. These differences in questions prohibit making general comparisons across the three countries. 

Finally, policies and programs on malaria in pregnancy and prevalence differ by malaria endemicity of 

regions in Tanzania and Kenya. This makes it difficult to draw conclusions at the national level. It is difficult 

to know how malaria-specific or HIV-specific campaigns have affected women’s need for receiving the 

integrated services measured in the report. For example, an ITN distribution campaign that occurred prior 

to the ANC visit would have precluded the need for taking home an ITN during the observed visit. 

4.6. Conclusions 

With the high burden of infectious disease and with less than half of women attending the recommended 

number of at least four ANC visits in the three countries studied in this report, there is a great need to make 

the most of the time women spend at formal health facilities. Integrated services, which offer women care 

for multiple health-related needs in one visit, can improve efficiency and help ensure that women receive 

the care they need. Our study shows that, in some cases, having ANC providers on site who also provide 

and have training in ID service areas and providing key services at the same location are significant 

predictors for receiving care during pregnancy that addresses the need to prevent transmission of malaria 

and passing HIV from mother to child. However, our findings are not consistent across countries or by the 

ID services studied in this report. This study identified the need for more precise tools and definitions for 

measuring integration, and the need to ensure that measurement accounts for the country context and for 

programs and policies that may influence integration activities. Further research within each country, 

perhaps in each region, would provide more information on the most essential elements of integrated 

services. More investigation could also identify potential synergies of combined integrated services, and 

how such synergy could affect the desired outcomes. Regardless, for integration to be successful, health 

systems must be strengthened in ways that assure an adequate number of trained and motivated health 

workers who have the resources they need to do their job in a way that optimizes health outcomes and 

contains the costs of service delivery. 

57 

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63 

Appendix 

Appendix Table 1a. Percent of facilities with ANC services that also have infectious 

disease services available, by background characteristics, Kenya 

PMTCT TB Malaria 

All 

facilities 

with ANC 

 % 95% CI % 95% CI % 95% CI N 

Type of Facility 

Hospital/Health Center/ 

Maternity Clinic 

93.1 88.3 - 96.0 89.7 84.3 - 93.4 100.0 126 

Dispensary/Clinic/Other 73.5 65.5 - 80.3 37.8 31.0 - 45.1 99.4 98.0 - 99.8 383 

Managing Authority 

Public 83.0 74.6 - 89.1 57.0 49.4 - 64.2 99.2 97.5 - 99.8 306 

Private/Other 71.5 61.2 - 79.9 41.2 32.0 - 51.1 100.0 204 

Region 

Nairobi 65.0 47.8 - 79.0 52.6 37.0 - 67.7 94.0 78.1 - 98.6 33 

Central 80.6 59.2 - 92.3 59.5 41.1 - 75.6 100.0 71 

Coast 64.4 45.2 - 79.9 62.0 43.1 - 77.9 100.0 57 

Eastern 78.2 61.5 - 88.9 51.3 35.7 - 66.6 100.0 84 

North Eastern 34.7 16.9 - 58.0 30.3 15.1 - 51.4 100.0 17 

Nyanza 88.2 73.8 - 95.2 60.1 45.6 - 72.9 100.0 78 

Rift Valley 82.1 63.5 - 92.3 30.9 22.5 - 40.9 99.7 98.2 - 100.0 130 

Western 92.5 80.5 - 97.4 69.9 56.3 - 80.7 100.0 41 

Population Density 

Lowest density 68.3 53.2 - 80.3 41.4 28.8 - 55.2 100.0 111 

Low density 83.8 72.4 - 91.1 48.1 38.0 - 58.3 100.0 190 

Medium/high density 78.9 69.7 - 85.8 58.1 48.1 - 67.4 98.9 96.3 - 99.7 208 

Total 78.4 72.2 - 83.5 50.7 45.2 - 56.1 99.5 98.5 - 99.9 509 

Note: Excludes stand-alone VCT clinics; testing includes external testing if results are returned and are provided to 

clients within the facility. 

Appendix Table 1b. Percent of facilities with ANC services that 

also have infectious disease services available, by background 

characteristics, Malawi 

PMTCT TB Malaria 

All 

facilities 

with ANC 

 % % % N 

Type of Facility

Hospital/Health Center/Maternity Clinic 97.1 56.0 99.3 548 

Dispensary/Clinic/Other 56.0 18.8 96.4 84 

Managing Authority

Public 95.7 57.1 99.5 399 

Private/Other 84.8 40.7 97.9 233 

Region

Northern 91.7 42.6 100.0 194 

Central 89.7 49.3 97.9 352 

Southern 93.4 56.1 99.3 83 

Population Density

Lowest density 91.8 40.4 99.0 118 

Low density 94.2 56.0 99.2 235 

Medium/high density 80.4 54.0 97.5 280 

Total 91.7 51.1 98.9 632 
64 

Appendix Table 1c. Percent of facilities with ANC services that also have infectious disease 

services available, by background characteristics, Tanzania 

PMTCT TB Malaria 

All 

facilities 

with ANC 

 % 95% CI % 95% CI % 95% CI N 

Type of Facility 

Hospital/Health Center/Maternity Clinic 98.8 97.4 - 99.5 81.3 76.6 - 85.3 99.9 99.3 - 100.0 160 

Dispensary/Clinic/Other 93.4 90.3 - 95.5 19.9 16.1 - 24.5 99.9 99.7 - 100.0 845 

Managing Authority 

Public 95.0 92.3 - 96.8 29.1 25.3 - 33.3 100.0 823 

Private/Other 90.9 82.1 - 95.6 32.4 24.1 - 42.1 99.6 98.8 - 99.9 182 

Zones 

Central 86.8 76.8 - 92.8 19.6 13.3 - 27.9 100.0 131 

Northern 94.7 85.0 - 98.2 29.5 21.7 - 38.7 99.9 99.3 - 100.0 164 

Coastal 99.5 98.5 - 99.8 31.1 22.9 - 40.7 99.8 98.9 - 100.0 210 

Southern Highlands 93.6 85.8 - 97.3 21.1 15.2 - 28.6 100.0 228 

Lake 94.4 87.6 - 97.6 39.6 31.7 - 48.1 100.0 241 

Zanzibar 92.0 78.2 - 97.4 50.2 39.1 - 61.3 99.5 96.2 - 99.9 31 

Population Density 

Lowest density 93.7 90.2 - 96.0 23.4 19.5 - 27.8 100.0 645 

Low density 94.5 85.9 - 97.9 43.4 34.5 - 52.7 100.0 195 

Medium/high density 95.7 89.6 - 98.3 37.9 27.3 - 49.8 99.5 98.4 - 99.9 139 

Total 94.3 91.7 - 96.1 29.7 26.3 - 33.4 99.9 99.8 - 100.0 1,005 

 
65 

Appendix Table 2. Distribution of all ANC providers interviewed in SPA surveys, Kenya, Malawi, 

Tanzania 

Kenya Malawi Tanzania 

% 95% CI N % 95% CI N % 95% CI N 

Type of Facility 

Hospital 33.7 30.8 - 36.8 512 Hospital 34.4 31.5 - 37.5 392 Hospital 16.3 15.0 - 17.7 684 

Health Center 20.6 17.7 - 23.9 314 Health Center 56.9 53.8 - 59.9 647 Health Center 20.3 19.0 - 21.6 851 

Maternity 4.2 3.3 - 5.2 64 Dispensary 1.9 1.1 - 3.1 21 Dispensary 62.8 60.7 - 64.8 2,634 

Dispensary 29.1 26.0 - 32.5 443 Clinic 6.8 5.5 - 8.3 77 Clinic 0.6 0.4 - 1.0 26 

Clinic 12.3 9.1 - 16.5 188 Health Post 0.1 0.0 - 0.4 1 

Managing Authority 

Government/ 

local 

municipality 

57.8 52.8 - 62.6 878 Public 64.7 60.6 - 68.6 736 Public 76.1 72.5 - 79.3 3,192 

NGO/ private 

not for profit 

2.9 1.6 - 5.4 45 FBO 25.4 21.7 - 29.5 289 FBO 17.1 14.3 - 20.3 716 

Private for 

profit 

19.0 15.8 - 22.7 289 Private for 

profit 

5.7 4.4 - 7.5 65 Private for profit 6.1 4.3 - 8.4 254 

Mission/ 

faith-based 

20.3 16.1 - 25.3 308 NGO 1.2 0.7 - 2.2 14 Parastatal 0.8 0.4 - 1.5 33 

 Company 2.9 1.9 - 4.5 33 

Region 

Nairobi 10.2 8.2 - 12.7 155 North 16.0 13.9 - 18.3 182 Central 12.6 11.1 - 14.3 528 

Central 11.2 9.4 - 13.3 170 Central 41.6 38.6 - 44.7 474 Northern 17.7 15.8 - 19.7 741 

Coast 11.3 8.5 - 15.0 172 South 42.4 39.5 - 45.3 482 Coastal 23.2 20.8 - 25.7 972 

Eastern 17.5 15.2 - 20.2 267 Southern 

Highlands 

20.6 19.1 - 22.3 866 

North Eastern 1.9 1.3 - 2.7 29 Lake 23.4 21.5 - 25.4 980 

Nyanza 15.3 12.8 - 18.1 232 Zanzibar 2.6 2.1 - 3.1 108 

Rift Valley 23.5 20.5 - 26.8 357 

Western 9.0 7.6 - 10.6 137 

Population Density 

Lowest density 14.6 11.3 - 18.6 222 Lowest density 20.6 17.6 - 23.9 233 Lowest density 56.6 52.6 - 60.5 2,325 

Low density 33.1 28.1 - 38.6 503 Low density 60.4 55.5 - 65.1 685 Low density 24.2 21.0 - 27.7 994 

Medium/high 

density 

52.3 46.9 - 57.6 795 Medium/high 

density 

19.0 15.1 - 23.7 216 Medium/high 

density 

19.2 16.0 - 22.9 789 

Occupational Category 

Doctor/clinical 

technician/ 

specialist 

14.9 13.1 - 17.0 227 Doctor/clinical 

technician/ 

specialist 

25.3 23.3 - 27.4 287 Doctor/clinical 

technician/ 

specialist 

20.3 18.8 - 21.9 853 

Nurse/midwife/

other 

85.1 83.0 - 86.9 1,293 Nurse/midwife/

other 

74.7 72.6 - 76.7 850 Nurse/midwife/ 

other 

79.7 78.1 - 81.2 3,342 

 

Years of education 

<14 4.6 3.3 - 6.3 70 <14 16.1 13.3 - 19.4 183 <14 55.4 53.0 - 57.6 2,322 

14-16 74.7 71.3 - 77.8 1,136 14-16 63.0 60.0 - 65.9 717 14-16 35.4 33.3 - 37.7 1,487 

17+ 20.7 17.8 - 23.8 314 17+ 20.9 18.5 - 23.5 237 17+ 9.2 8.1 - 10.4 386 

Salary type 

None 86.6 83.5 - 89.1 1,312 None 14.7 12.4 - 17.5 168 None 22.3 20.1 - 24.8 938 

Monthly or 

daily salary 

2.0 1.3 - 3.2 31 Monthly or 

daily salary 

36.6 33.4 - 40.0 416 Monthly or daily 

salary 

30.7 27.8 - 33.7 1,286 

No regular 

salary but 

other pay 

11.4 9.0 - 14.4 173 No regular 

salary but 

other pay 

48.6 45.4 - 51.9 553 No regular salary 

but other pay 

47.0 44.0 - 50.0 1,971 

Gender 

Male 31.4 28.0 - 35.0 477 Male 45.5 42.6 - 48.4 517 Male 22.9 21.0 - 24.8 959 

Female 68.6 65.0 - 72.0 1,043 Female 54.5 51.6 - 57.4 620 Female 77.1 75.2 - 79.0 3,236 

Total 50.2 47.2 - 53.3 1,520 Total 42.8 40.4 - 45.2 1,137 Total 61.1 58.7 - 63.5 4,195 

Note: Providers with missing information were excluded from distribution of each characteristic; distribution of providers in Kenya excludes 

those who work at stand-alone VCT clinics. 
66

Appendix Table 3a. Provision of care and training in infectious disease services among providers who provide ANC care, Kenya

ANC PMTCT TB Malaria 

Ever trained 

in ANC 

Recent training in 

ANC 

Provide PMTCT 

services 

Provide 

PMTCT 

services & 

ever 

trained in 

PMTCT 

Provide PMTCT 

services & 

recently trained 

in PMTCT 

Provide TB 

services 

Provide TB 

services & 

ever 

trained in 

TB 

Provide TB 

services & 

recently trained 

in TB 

Provide TB 

services & 

recently trained 

TB/HIV coinfection Provide Malaria services 

Provide Malaria 

services & ever 

trained in 

Malaria 

Provide Malaria 

services & 

recently trained 

in Malaria 

All ANC 

providers 

% 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI N 

Type of Facility 

Hospital/Health 

Center/Maternity Clinic 

69.7 65.9 - 73.3 90.9 87.6 - 93.4 43.3 39.5 - 47.2 51.8 47.7 - 56.0 28.7 25.1 - 32.7 72.9 69.5 - 76.1 42.8 38.5 - 47.3 826

Dispensary/Clinic/Other 64.2 57.2 - 70.6 79.3 72.6 - 84.6 34.9 28.9 - 41.5 46.4 39.1 - 53.8 27.1 21.4 - 33.7 90.9 83.9 - 95.1 58.1 51.3 - 64.6 694

Managing Authority 

Public 67.4 62.5 - 71.9 90.6 85.7 - 94.0 42.4 37.7 - 47.1 52.6 47.5 - 57.7 29.7 25.5 - 34.3 82.7 78.1 - 86.5 54.4 49.2 - 59.5 878

Private/Other 66.9 60.8 - 72.5 78.7 72.7 - 83.6 35.6 30.1 - 41.4 44.8 38.3 - 51.6 25.7 20.4 - 31.8 79.0 74.6 - 82.8 43.6 38.0 - 49.3 642

Region 

Nairobi 81.8 72.0 - 88.7 85.9 76.2 - 92.1 49.1 39.1 - 59.2 53.8 39.4 - 67.6 44.0 30.5 - 58.4 69.2 60.5 - 76.8 34.8 25.4 - 45.6 155Central 57.0 45.8 - 67.5 78.5 67.7 - 86.5 24.7 17.8 - 33.2 45.9 34.6 - 57.8 24.1 17.7 - 32.0 77.9 73.3 - 81.9 47.0 36.6 - 57.7 170Coast 65.5 55.4 - 74.3 79.0 66.8 - 87.6 41.7 31.8 - 52.2 51.7 42.0 - 61.3 30.6 20.7 - 42.7 74.6 55.4 - 87.4 53.4 40.5 - 65.8 173Eastern 68.6 59.7 - 76.4 89.2 79.9 - 94.5 34.3 25.9 - 43.8 47.6 38.3 - 57.1 29.7 21.2 - 39.9 79.4 72.1 - 85.3 49.0 40.8 - 57.2 267North Eastern 66.5 54.7 - 76.6 81.8 64.3 - 91.8 38.6 26.2 - 52.6 49.7 27.4 - 72.1 35.1 16.1 - 60.3 89.1 73.9 - 95.9 66.4 49.9 - 79.6 29Nyanza 71.9 61.9 - 80.1 91.0 77.6 - 96.7 53.1 43.2 - 62.8 56.1 44.3 - 67.2 30.8 22.6 - 40.5 85.1 78.9 - 89.8 48.9 38.5 - 59.4 232Rift Valley 65.7 56.2 - 74.1 86.0 77.7 - 91.6 37.1 29.2 - 45.8 43.0 34.6 - 51.8 17.1 12.1 - 23.7 85.9 79.9 - 90.3 54.0 44.3 - 63.5 357Western 58.4 47.6 - 68.5 85.5 68.4 - 94.1 37.5 29.6 - 46.1 53.7 43.6 - 63.4 30.0 23.4 - 37.6 89.5 84.6 - 93.0 54.3 44.4 - 63.8 137

Population Density 

Lowest density 65.9 55.9 - 74.7 91.6 83.5 - 95.9 38.5 29.3 - 48.7 50.9 40.4 - 61.2 22.2 15.6 - 30.5 89.6 81.9 - 94.2 58.2 48.9 - 66.9 222

Low density 68.1 60.7 - 74.7 87.0 78.9 - 92.3 42.5 35.8 - 49.5 51.6 43.6 - 59.5 27.8 22.2 - 34.2 88.0 84.0 - 91.1 56.5 48.6 - 64.0 503Medium/high density 66.9 62.2 - 71.4 83.0 78.3 - 86.8 37.9 33.3 - 42.7 47.5 42.2 - 52.8 29.7 24.8 - 35.2 74.5 69.3 - 79.0 43.2 38.3 - 48.3 795

Occupational Category 

Doctor/clinical 

technician/specialist 

61.6 53.5 - 69.0 76.8 67.9 - 83.8 34.9 27.5 - 43.0 82.4 74.7 - 88.1 48.3 40.3 - 56.4 95.5 90.4 - 98.0 59.7 52.9 - 66.2 227

Nurse/midwife/other 68.2 63.9 - 72.1 87.1 82.9 - 90.4 40.3 36.3 - 44.4 43.5 39.2 - 48.0 24.4 21.1 - 28.1 78.6 75.3 - 81.6 48.1 43.7 - 52.4 1,293

Years of education 

<14 62.8 46.1 - 77.0 70.6 51.8 - 84.3 26.0 15.0 - 41.1 41.9 26.9 - 58.6 17.8 9.7 - 30.5 65.6 48.0 - 79.8 34.1 21.4 - 49.5 70

14-16 67.3 62.8 - 71.5 85.4 81.1 - 88.8 39.0 34.9 - 43.3 48.3 43.4 - 53.2 26.2 22.6 - 30.1 83.7 81.1 - 86.0 50.9 46.3 - 55.5 1,13617+ 67.6 60.8 - 73.7 89.6 83.4 - 93.7 44.2 37.8 - 50.9 54.9 48.5 - 61.2 36.8 30.1 - 43.9 75.5 66.6 - 82.6 49.4 41.9 - 56.9 314

Salary type 

None 67.1 63.3 - 70.6 86.8 83.5 - 89.5 39.0 35.2 - 42.9 50.0 45.7 - 54.2 27.1 23.7 - 30.9 80.6 77.0 - 83.7 49.0 44.9 - 53.1 1,312Monthly or daily salary 84.4 64.4 - 94.2 75.7 40.3 - 93.5 55.8 32.0 - 77.3 51.3 28.8 - 73.3 37.8 20.0 - 59.7 89.2 78.2 - 95.0 73.3 53.8 - 86.7 31No regular salary but 

other pay 64.0 49.5 - 76.3 78.0 60.9 - 89.0 39.6 28.5 - 51.9 43.7 32.2 - 56.0 32.2 22.4 - 44.0 83.5 76.6 - 88.7 50.9 38.4 - 63.3 173

Gender

Male 68.1 61.2 - 74.3 84.6 78.7 - 89.1 40.5 34.5 - 46.8 56.7 49.8 - 63.3 33.1 28.0 - 38.6 89.8 85.6 - 92.9 60.8 54.4 - 66.8 478

Female 66.7 62.1 - 71.0 86.0 81.3 - 89.7 39.0 34.7 - 43.6 46.0 41.3 - 50.7 25.7 21.6 - 30.2 77.2 73.3 - 80.7 44.8 40.0 - 49.7 1,043

Total in Kenya 

(N =1520) 

67.2 63.4 - 70.7 85.6 82.1 - 88.5 39.5 35.9 - 43.2 49.3 45.3 - 53.4 28.0 24.6 - 31.6 81.2 78.0 - 83.9 49.8 45.9 - 53.7 1,520

Note: Recent training is within the last 36 months. Excludes providers at stand-alone facilities. 
67

Appendix Table 3b. Provision of care and training in infectious disease services among providers who provide ANC care, Malawi 

ANC PMTCT TB Malaria 

Ever trained 

in ANC 

Recent 

training in 

ANC 

Provide 

PMTCT 

services 

Provide 

PMTCT 

services & 

ever trained 

in PMTCT 

Provide 

PMTCT 

services & 

recently 

trained in 

PMTCT 

Provide TB 

services 

Provide TB 

services & 

ever trained 

in TB 

Provide TB 

services & 

recently 

trained in TB 

Provide TB 

services & 

recently 

trained 

TB/HIV coinfection 

Provide 

Malaria 

services 

Provide 

Malaria 

services & 

ever trained 

in Malaria 

Provide 

Malaria 

services & 

recently 

trained in 

Malaria 

All ANC 

providers

% 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI N 

Type of Facility 

Hospital/Health Center/Maternity 

Clinic 

44.8 41.5 - 48.1 22.3 19.7 - 25.1 91.7 89.1 - 93.7 75.7 72.3 - 78.7 48.1 44.7 - 51.6 56.7 53.1 - 60.2 31.4 28.4 - 34.7 17.6 15.2 - 20.2 6.2 5.3 - 7.3 87.9 84.6 - 90.5 66.7 63.5 - 69.7 33.2 30.1 - 36.5 1,039 

Dispensary/Clinic/Other 42.6 34.6 - 51.0 14.2 9.1 - 21.6 84.3 76.9 - 89.7 71.4 62.9 - 78.5 29.9 22.9 - 37.8 46.0 37.4 - 54.7 25.0 19.3 - 31.9 8.1 4.2 - 15.0 0.8 0.3 - 1.8 90.0 81.6 - 94.8 73.8 63.8 - 81.8 25.3 18.6 - 33.5 99 

Managing Authority 

Public 47.0 43.2 - 50.9 23.1 20.1 - 26.4 92.5 89.5 - 94.6 76.7 72.5 - 80.4 49.3 45.2 - 53.5 56.7 52.3 - 61.0 33.0 29.4 - 36.9 18.5 15.6 - 21.8 6.1 5.1 - 7.3 87.4 83.2 - 90.7 66.4 62.5 - 70.0 33.3 29.6 - 37.2 736 Private/Other 40.2 35.0 - 45.6 18.8 15.0 - 23.4 88.4 84.1 - 91.7 72.8 68.1 - 77.1 41.4 36.5 - 46.5 54.2 48.9 - 59.3 26.9 22.6 - 31.8 13.6 10.5 - 17.3 3.5 2.6 - 4.8 89.2 84.9 - 92.4 69.0 64.1 - 73.5 31.1 26.3 - 36.3 402 

Region 

North 45.7 39.0 - 52.6 22.0 16.7 - 28.4 95.7 93.0 - 97.4 79.4 70.2 - 86.3 44.6 36.3 - 53.2 56.6 48.4 - 64.4 26.2 20.5 - 32.9 15.1 10.2 - 21.8 5.0 3.3 - 7.4 91.3 79.2 - 96.6 66.0 59.0 - 72.3 27.9 22.2 - 34.3 182 Central 47.3 41.9 - 52.7 23.2 19.2 - 27.7 91.5 87.7 - 94.2 75.4 70.5 - 79.6 47.7 42.8 - 52.7 57.8 51.9 - 63.5 34.4 29.7 - 39.4 18.9 15.4 - 22.9 6.1 4.8 - 7.6 85.6 80.8 - 89.3 72.8 67.8 - 77.3 40.5 35.2 - 46.1 474 South 41.6 37.2 - 46.1 19.9 16.5 - 23.8 88.8 84.5 - 92.0 73.7 68.8 - 78.1 46.1 41.5 - 50.8 53.5 48.9 - 58.0 29.2 25.0 - 33.8 15.3 12.2 - 19.0 4.0 3.1 - 5.2 89.3 84.7 - 92.6 62.4 57.8 - 66.7 26.4 22.6 - 30.6 482 

Population Density 

Lowest density 42.7 36.8 - 48.9 19.8 15.4 - 25.0 93.3 88.9 - 96.0 77.1 70.9 - 82.3 46.9 40.8 - 53.2 59.2 52.9 - 65.3 33.8 28.1 - 40.0 20.9 15.7 - 27.3 5.6 4.1 - 7.6 86.3 79.3 - 91.2 63.4 57.4 - 69.1 32.2 26.7 - 38.3 233 Low density 43.9 39.8 - 48.1 21.6 18.5 - 25.1 90.5 87.0 - 93.2 74.8 70.5 - 78.7 46.1 42.0 - 50.2 57.2 52.5 - 61.7 30.7 26.9 - 34.8 16.8 14.0 - 19.9 5.7 4.6 - 7.1 88.0 84.0 - 91.1 66.7 62.6 - 70.5 30.5 27.2 - 34.2 685 Medium/high density 48.9 41.9 - 55.8 23.6 18.4 - 29.7 90.2 85.1 - 93.6 74.9 67.2 - 81.3 47.8 39.5 - 56.3 48.2 40.4 - 56.1 28.7 22.4 - 36.0 12.6 8.6 - 17.9 2.8 1.8 - 4.2 89.9 81.3 - 94.8 72.9 65.4 - 79.3 38.9 30.3 - 48.1 216 

Occupational Category 

Doctor/clinical technician/specialist 37.6 33.0 - 42.5 18.6 15.1 - 22.8 94.1 91.5 - 95.9 80.9 76.6 - 84.6 55.6 50.5 - 60.5 84.0 80.2 - 87.2 45.6 41.0 - 50.3 28.2 24.1 - 32.7 10.7 8.8 - 12.9 99.6 97.1 - 99.9 71.6 67.1 - 75.7 40.0 35.4 - 44.9 287 Nurse/midwife/other 47.0 43.3 - 50.7 22.6 19.7 - 25.8 90.0 86.9 - 92.4 73.4 69.6 - 76.9 43.5 39.8 - 47.3 46.2 42.2 - 50.4 25.9 22.5 - 29.6 12.9 10.5 - 15.8 3.4 2.6 - 4.3 84.1 80.4 - 87.3 65.8 62.1 - 69.4 30.0 26.5 - 33.7 850 

Years of education 

<14 42.4 32.6 - 52.8 15.1 9.5 - 23.0 72.7 61.4 - 81.7 55.9 44.5 - 66.8 26.9 17.9 - 38.3 55.2 44.5 - 65.4 37.6 28.4 - 47.8 14.6 8.8 - 23.4 1.4 0.7 - 3.1 55.4 44.3 - 66.0 60.0 48.5 - 70.4 25.6 18.1 - 35.0 183 14-16 43.3 39.9 - 46.7 22.0 19.4 - 24.9 94.1 92.1 - 95.6 77.3 74.3 - 80.1 49.9 46.3 - 53.4 56.6 53.0 - 60.2 29.7 26.5 - 33.0 18.1 15.5 - 21.0 7.3 6.1 - 8.6 93.3 90.6 - 95.3 65.9 62.9 - 68.8 33.2 30.1 - 36.3 717 17+ 50.4 43.8 - 56.9 25.3 20.4 - 31.0 95.9 93.2 - 97.6 84.1 79.4 - 87.9 51.7 45.5 - 57.8 53.8 47.5 - 60.0 29.3 24.4 - 34.8 14.4 10.9 - 18.7 5.3 3.7 - 7.4 97.4 94.6 - 98.8 77.1 71.3 - 82.0 35.9 30.1 - 42.2 237 

Salary type 

None 37.3 29.7 - 45.7 13.5 8.6 - 20.5 85.3 77.1 - 91.0 64.0 55.3 - 71.9 35.4 26.1 - 46.1 44.1 35.1 - 53.4 22.7 15.1 - 32.5 11.8 7.1 - 19.0 2.6 1.4 - 4.7 89.8 81.4 - 94.7 57.9 48.8 - 66.5 22.9 16.5 - 30.8 168 Monthly or daily salary 44.7 40.2 - 49.4 21.3 17.8 - 25.3 92.8 89.0 - 95.4 77.6 72.6 - 81.9 50.0 45.2 - 54.8 55.8 50.8 - 60.6 31.5 27.2 - 36.1 14.8 11.7 - 18.5 4.9 3.6 - 6.5 85.4 80.1 - 89.5 68.2 63.3 - 72.8 33.2 28.9 - 37.8 417 No regular salary but other pay 46.7 42.6 - 50.9 24.3 20.9 - 28.0 91.4 88.0 - 93.9 77.0 72.8 - 80.7 47.3 42.7 - 52.0 59.3 55.1 - 63.4 32.9 29.0 - 37.1 19.8 16.5 - 23.5 6.3 5.1 - 7.8 89.5 85.3 - 92.6 69.4 65.4 - 73.2 35.0 31.0 - 39.2 553 

Gender 

Male 40.1 35.4 - 45.0 21.2 17.6 - 25.2 88.3 84.0 - 91.6 73.1 68.4 - 77.3 48.6 44.0 - 53.2 70.9 65.9 - 75.5 41.8 37.3 - 46.3 23.9 19.9 - 28.3 5.9 4.8 - 7.2 84.0 78.9 - 88.1 63.2 58.4 - 67.8 33.5 29.2 - 37.9 517 Female 48.4 44.5 - 52.3 22.0 19.0 - 25.3 93.3 90.9 - 95.1 77.2 73.4 - 80.5 44.8 40.6 - 49.0 43.1 38.9 - 47.4 21.8 18.7 - 25.3 10.8 8.8 - 13.2 3.8 2.9 - 4.8 91.4 88.2 - 93.8 70.7 67.3 - 73.9 31.8 27.9 - 35.9 620 

Total in Malawi (N = 1137) 44.6 41.5 - 47.7 21.6 19.2 - 24.2 91.0 88.7 - 92.9 75.3 72.2 - 78.2 46.5 43.4 - 49.7 55.8 52.4 - 59.1 30.9 28.0 - 33.9 16.8 14.6 - 19.2 5.0 4.3 - 5.9 88.0 85.0 - 90.5 67.3 64.3 - 70.2 32.5 29.6 - 35.6 1,137 

Note: Recent training is 24 months in Malawi. 
68

Appendix Table 3c. Provision of care and training in infectious disease services among providers who provide ANC care, Tanzania

ANC PMTCT TB Malaria 

Ever trained in 

ANC 

Recent 

training in 

ANC 

Provide 

PMTCT 

services 

Provide 

PMTCT 

services & 

ever trained in 

PMTCT 

Provide 

PMTCT 

services & 

recently 

trained in 

PMTCT 

Provide TB 

services 

Provide TB 

services & 

ever trained 

in TB 

Provide TB 

services & 

recently 

trained in TB 

Provide TB 

services & 

recently 

trained 

TB/HIV coinfection 

Provide 

Malaria 

services 

Provide 

Malaria 

services & 

ever trained in 

Malaria 

Provide Malaria 

services & 

recently trained 

in Malaria 

All ANC 

providers 

% 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI % 95% CI N 

Type of Facility 

Hospital/Health 

Center/Maternity Clinic 

37.8 36.0 - 39.8 13.8 12.4 - 15.3 89.3 87.8 - 90.7 57.6 55.6 - 59.6 32.2 30.1 - 34.3 35.6 33.4 - 37.8 18.4 16.8 - 20.1 8.3 7.1 - 9.7 2.8 2.4 - 3.4 69.8 67.3 - 72.1 43.9 42.0 - 45.7 21.4 19.9 - 23.0 1,535 

Dispensary/Clinic/ 

Other 

34.3 31.1 - 37.7 11.8 9.6 - 14.4 89.3 85.9 - 91.9 59.3 55.4 - 63.0 38.7 35.3 - 42.2 16.0 12.7 - 20.0 6.8 5.0 - 9.3 2.1 1.2 - 3.8 0.4 0.1 - 1.2 90.0 86.7 - 92.6 48.8 45.6 - 52.0 21.3 18.8 - 24.0 2,660 

Managing Authority 

Public 36.4 33.9 - 38.9 12.3 10.6 - 14.2 91.9 89.9 - 93.5 60.6 57.8 - 63.2 38.1 35.5 - 40.8 24.6 21.7 - 27.8 11.3 9.6 - 13.3 4.5 3.5 - 5.8 1.6 1.1 - 2.2 86.5 84.3 - 88.5 49.6 47.1 - 52.2 22.2 20.2 - 24.4 3,192 

Private/Other 33.2 29.0 - 37.6 13.3 10.2 - 17.1 81.1 74.9 - 86.0 52.7 46.8 - 58.5 30.6 26.1 - 35.6 18.7 15.3 - 22.5 10.1 7.9 - 12.8 4.1 2.9 - 5.8 1.0 0.8 - 1.4 70.1 64.4 - 75.2 38.5 34.6 - 42.7 18.5 15.5 - 21.9 1,003 

Zones 

Central 38.6 33.5 - 44.0 18.7 14.8 - 23.4 83.4 73.5 - 90.1 49.4 42.5 - 56.3 31.4 25.5 - 37.9 17.2 12.4 - 23.4 8.4 5.9 - 11.8 4.4 2.7 - 7.1 1.9 1.1 - 3.3 74.3 66.3 - 80.9 39.6 33.9 - 45.6 14.6 11.0 - 19.3 528 Northern 35.5 30.1 - 41.2 11.0 7.5 - 15.8 91.0 87.0 - 93.9 63.6 57.2 - 69.5 42.0 36.0 - 48.2 25.4 20.4 - 31.2 13.3 9.8 - 17.8 5.2 3.6 - 7.5 1.8 1.3 - 2.6 84.1 80.3 - 87.2 46.5 40.6 - 52.4 17.4 13.0 - 23.0 741 Coastal 36.2 31.4 - 41.3 11.4 8.6 - 15.0 90.4 84.8 - 94.0 59.2 52.9 - 65.3 31.3 26.5 - 36.4 19.2 14.8 - 24.4 11.1 8.2 - 14.7 5.2 3.2 - 8.3 1.0 0.6 - 1.7 73.2 67.4 - 78.3 46.7 42.8 - 50.6 25.1 21.9 - 28.6 972 Southern Highlands 37.6 32.7 - 42.8 13.4 10.2 - 17.4 90.9 85.9 - 94.3 60.0 54.9 - 64.8 37.2 32.6 - 42.1 20.9 16.1 - 26.6 9.1 7.0 - 11.7 2.7 1.9 - 4.0 1.2 0.8 - 1.6 91.7 88.9 - 93.9 47.6 42.7 - 52.5 14.1 11.5 - 17.3 866 Lake 29.8 25.8 - 34.2 10.7 7.7 - 14.6 90.2 86.4 - 93.0 58.5 53.6 - 63.2 40.4 35.9 - 45.0 30.9 25.0 - 37.4 12.4 9.0 - 16.7 4.4 2.6 - 7.3 1.5 0.7 - 3.2 89.5 85.6 - 92.4 49.8 45.5 - 54.0 28.3 24.4 - 32.5 980 Zanzibar 52.8 45.2 - 60.3 13.6 9.6 - 18.8 75.7 66.4 - 83.0 57.0 49.0 - 64.7 23.2 16.0 - 32.2 22.1 16.5 - 29.1 12.1 8.4 - 17.1 5.2 3.0 - 8.8 0.2 0.1 - 0.8 62.5 51.1 - 72.7 59.0 51.3 - 66.3 41.1 33.9 - 48.7 108 

Population Density 

Lowest density 35.2 32.0 - 38.4 13.6 11.4 - 16.1 91.1 88.4 - 93.2 59.9 56.4 - 63.3 39.4 36.2 - 42.7 21.7 18.4 - 25.4 9.8 8.0 - 11.9 3.9 2.9 - 5.3 1.7 1.1 - 2.5 89.2 86.9 - 91.0 50.8 47.7 - 53.9 22.7 20.1 - 25.4 2,325 

Low density 38.9 35.2 - 42.8 12.8 10.1 - 16.2 89.6 85.3 - 92.8 58.0 52.8 - 62.9 35.9 31.7 - 40.4 31.7 26.9 - 36.9 15.2 12.1 - 18.9 6.3 4.4 - 8.9 1.8 1.2 - 2.5 80.8 77.2 - 84.0 45.2 41.3 - 49.2 22.7 19.4 - 26.3 994 Medium/high density 33.9 29.4 - 38.7 9.7 7.0 - 13.2 83.8 76.7 - 89.0 57.0 50.6 - 63.2 27.2 22.9 - 31.9 16.9 13.1 - 21.5 9.9 7.1 - 13.4 3.7 2.3 - 6.1 0.7 0.5 - 1.1 64.7 56.8 - 71.8 38.7 33.7 - 44.0 15.3 12.3 - 18.8 789 

Occupational Category 

Doctor/clinical 

technician/specialist 27.6 23.1 - 32.6 10.6 8.0 - 14.0 83.6 79.3 - 87.1 52.0 46.7 - 57.3 28.9 24.2 - 34.0 43.5 38.6 - 48.6 26.8 22.7 - 31.3 9.0 7.0 - 11.3 3.1 2.4 - 3.9 98.8 97.2 - 99.5 66.9 62.0 - 71.5 32.2 27.7 - 37.1 853 

Nurse/midwife/other 37.6 35.2 - 40.2 13.0 11.3 - 15.0 90.8 88.6 - 92.6 60.4 57.6 - 63.1 38.2 35.6 - 40.9 18.0 15.6 - 20.6 7.0 5.7 - 8.7 3.2 2.4 - 4.4 0.8 0.5 - 1.3 78.5 75.8 - 80.9 41.9 39.4 - 44.4 18.5 16.7 - 20.5 3,342 

Years of education 

<14 33.6 30.5 - 36.8 11.6 9.6 - 13.9 89.3 86.7 - 91.5 57.1 53.5 - 60.6 36.3 32.9 - 39.8 16.1 13.3 - 19.3 5.6 4.2 - 7.6 2.3 1.4 - 3.6 0.5 0.3 - 0.8 82.8 79.9 - 85.4 41.7 38.4 - 45.1 17.9 15.5 - 20.6 2,323 

14-16 37.0 33.3 - 40.9 13.8 11.3 - 16.7 89.8 87.0 - 92.1 61.4 57.7 - 64.9 38.1 34.4 - 42.0 29.8 26.4 - 33.5 15.4 13.1 - 18.1 6.0 4.7 - 7.7 2.2 1.6 - 3.0 83.1 80.2 - 85.6 52.6 48.8 - 56.3 25.6 22.8 - 28.6 1,487 17+ 42.2 35.9 - 48.8 13.6 10.4 - 17.6 87.2 82.1 - 91.0 57.9 51.2 - 64.4 29.5 24.4 - 35.3 40.5 34.4 - 46.8 26.7 21.3 - 32.9 10.8 8.2 - 14.2 3.1 2.3 - 4.2 79.4 74.2 - 83.7 57.4 51.2 - 63.3 25.3 20.6 - 30.6 386 

Salary type 

None 26.1 21.8 - 31.0 9.5 6.9 - 13.1 86.4 82.2 - 89.8 47.3 41.8 - 52.9 28.5 23.6 - 33.9 17.2 13.4 - 21.8 5.2 3.5 - 7.7 2.5 1.4 - 4.7 0.4 0.1 - 0.9 79.8 74.8 - 84.0 33.6 28.9 - 38.6 15.6 12.1 - 19.9 938 Monthly or daily salary 38.4 34.2 - 42.8 14.3 11.4 - 17.7 89.4 85.2 - 92.5 59.0 54.6 - 63.3 37.4 33.4 - 41.5 20.8 17.4 - 24.6 11.3 9.0 - 14.1 3.9 2.6 - 5.9 1.2 0.8 - 1.7 78.9 74.9 - 82.3 48.7 44.7 - 52.6 23.3 20.4 - 26.4 1,287 No regular salary but 

other pay 

38.3 35.0 - 41.6 12.8 10.8 - 15.2 90.6 88.0 - 92.7 63.9 60.5 - 67.1 39.4 36.2 - 42.7 27.6 24.3 - 31.1 13.6 11.4 - 16.2 5.6 4.3 - 7.2 2.1 1.5 - 2.9 86.4 84.0 - 88.5 52.2 48.9 - 55.6 22.8 20.2 - 25.6 1,971 

Gender 

Male 26.0 22.1 - 30.3 12.6 9.8 - 16.0 86.1 82.3 - 89.2 51.6 47.1 - 56.1 32.7 28.4 - 37.2 33.2 29.1 - 37.5 18.9 15.8 - 22.3 6.3 4.9 - 8.1 1.8 1.4 - 2.3 94.5 92.7 - 95.8 55.1 50.5 - 59.6 30.0 25.8 - 34.5 959 

Female 38.4 35.8 - 41.2 12.5 10.8 - 14.5 90.3 87.9 - 92.2 60.8 57.9 - 63.6 37.4 34.8 - 40.1 20.2 17.7 - 23.0 8.7 7.3 - 10.4 3.8 2.9 - 5.0 1.1 0.8 - 1.7 79.1 76.4 - 81.5 44.6 42.1 - 47.1 18.7 16.9 - 20.8 3,236 

Total in Tanzania 

(N=4,195) 

35.6 33.4 - 37.8 12.5 11.0 - 14.2 89.3 87.2 - 91.1 58.7 56.1 - 61.2 36.3 34.1 - 38.7 23.2 20.8 - 25.7 11.0 9.6 - 12.6 4.4 3.6 - 5.4 1.4 1.1 - 1.7 82.6 80.5 - 84.5 47.0 44.9 - 49.1 21.3 19.6 - 23.1 4,195 
69 

Appendix Table 4a. Overall integration of ANC with infectious disease services, by facility 

background characteristics, Kenya

PMTCT TB/HIV Malaria 

All ANC 

facilities

 Mean 95% CI p-value Mean 95% CI p-value Mean 95% CI p-value N 

Type of Facility <.001 <.001 <.001 

Hospital/Health 

Center/Maternity Clinic 

66.3 63.28 - 69.29 59.0 55.01 - 62.90 68.6 66.42 - 70.80 126 

Dispensary/Clinic/Other 40.3 36.27 - 44.37 18.8 14.67 - 22.94 60.9 58.23 - 63.55 383 

Managing Authority 0.241 0.046 <.001 

Public 47.8 43.92 - 51.73 30.9 26.25 - 35.57 66.6 64.11 - 69.03 306 

Private/Other 45.2 39.78 - 50.58 25.6 20.01 - 31.11 57.2 53.75 - 60.58 204 

Region <.001 0.008 <.001 

Nairobi 43.3 33.90 - 52.63 34.1 24.25 - 43.86 45.4 39.06 - 51.64 33 

Central 47.5 38.71 - 56.33 28.0 19.87 - 36.10 57.9 52.82 - 62.89 71 

Coast 50.2 38.94 - 61.41 33.5 21.76 - 45.16 64.5 58.13 - 70.90 57 

Eastern 48.8 42.15 - 55.50 27.0 18.90 - 35.13 69.6 65.10 - 74.07 84 

North Eastern 25.9 16.48 - 35.40 20.6 7.25 - 33.87 51.5 45.11 - 57.96 17 

Nyanza 54.9 48.28 - 61.47 36.2 27.76 - 44.60 67.4 63.04 - 71.66 78 

Rift Valley 40.2 32.22 - 48.13 21.4 13.81 - 29.03 61.4 56.10 - 66.74 130 

Western 53.3 47.73 - 58.77 35.5 28.85 - 42.19 69.4 64.57 - 74.25 41 

Population Density 0.004 <.001 0.027 

Lowest density 40.3 33.03 - 47.55 19.8 13.32 - 26.30 62.8 57.90 - 67.66 111 

Low density 46.9 41.48 - 52.39 28.8 22.76 - 34.79 65.2 61.58 - 68.74 190 

Medium/high density 50.1 45.04 - 55.10 33.6 27.53 - 39.59 60.7 57.51 - 63.85 208 

Total 46.8 43.56 - 49.97 28.8 25.36 - 32.18 62.8 60.72 - 64.90 509 

Appendix Table 4b. Overall integration of ANC with infectious disease 

services, by facility background characteristics, Malawi 

PMTCT TB/HIV Malaria 

All ANC 

facilities 

 Mean Mean Mean N 

Type of Facility 

Hospital/Health Center/Maternity Clinic 77.1 21.8 62.7 548 

Dispensary/Clinic/Other 42.5 4.2 44.7 84 

Managing Authority 

Public 76.8 22.3 62.4 399 

Private/Other 65.2 14.4 56.8 233 

Region 

Northern 67.6 13.0 55.4 118 

Central 74.0 22.3 65.2 235 

Southern 73.3 19.8 58.3 280 

Population Density 

Lowest density 67.1 11.6 54.4 194 

Low density 76.1 22.6 63.6 352 

Medium/high density 70.2 24.8 60.6 83 

Total 72.5 19.4 60.3 632 

 
70 

Appendix Table 4c. Overall integration of ANC with infectious disease services, by facility 

background characteristics, Tanzania 

PMTCT TB/HIV Malaria 

All ANC 

facilities

 Mean 95% CI p-value Mean 95% CI p-value Mean 95% CI p-value N 

Type of Facility <.001 <.001 <.001 

Hospital/Health 

Center/Maternity Clinic 

79.6 77.94 - 81.16 37.8 35.46 - 40.22 54.7 52.91 - 56.52 160 

Dispensary/Clinic/Other 64.4 61.97 - 66.76 6.2 4.63 - 7.69 39.6 37.71 - 41.54 845 

Managing Authority 0.001 0.439 <.001 

Public 67.9 65.66 - 70.07 11.0 9.44 - 12.50 40.9 39.08 - 42.72 823 

Private/Other 61.9 56.79 - 66.97 12.2 9.21 - 15.22 47.1 43.34 - 50.84 182 

Zones <.001 0.023 <.001 

Central 60.2 55.39 - 65.06 7.2 5.23 - 9.14 30.1 26.01 - 34.11 131 

Northern 71.3 66.21 - 76.31 12.8 8.98 - 16.69 42.6 37.53 - 47.76 164 

Coastal 71.0 67.18 - 74.85 12.1 8.86 - 15.37 47.4 44.24 - 50.59 210 

Southern Highlands 68.5 63.56 - 73.37 9.0 6.53 - 11.47 42.8 39.58 - 46.08 228 

Lake 63.9 59.43 - 68.30 13.2 10.20 - 16.25 41.2 37.69 - 44.69 241 

Zanzibar 52.3 45.99 - 58.60 13.5 10.10 - 16.91 53.1 49.27 - 56.91 31 

Population Density 0.049 <.001 <.001 

Lowest density 65.4 62.89 - 68.00 8.5 7.01 - 10.01 39.9 37.79 - 41.90 645 

Low density 69.9 64.75 - 74.98 17.2 13.32 - 21.08 46.3 42.15 - 50.44 195 

Medium/high density 67.9 62.96 - 72.86 15.4 10.87 - 19.84 46.6 42.41 - 50.84 139 

Total 66.8 64.74 - 68.82 11.2 9.86 - 12.53 42.0 40.39 - 43.66 1,005 

 
71 

Appendix Table 5. Background characteristics of women observed in ANC visits, percent 

distribution, Kenya, Malawi, and Tanzania 

 Kenya Malawi Tanzania 

 % 95% CI N % 95% CI N % 95% CI N 

Education 

None 7.5 5.4 - 10.4 105 14.0 12.0 - 16.1 289 23.3 20.9 - 26.0 935

Primary 54.7 50.9 - 58.5 767 61.3 58.6 - 63.9 1,268 60.3 57.6 - 62.9 2,415

Secondary or Higher 37.8 33.9 - 41.8 529 24.7 22.3 - 27.4 512 16.4 14.7 - 18.3 657

Age <20 14.0 11.8 - 16.5 195 19.7 17.7 - 21.8 407 19.0 17.2 - 20.9 761

20-35 67.2 63.8 - 70.4 939 53.0 50.7 - 55.2 1,096 53.8 51.5 - 56.0 2,155

36+ 18.9 16.3 - 21.6 264 27.4 25.2 - 29.6 566 27.2 25.4 - 29.2 1,091

Weeks pregnant 

 4-13 1.6 1.0 - 2.7 21 4.2 3.1 - 5.6 86 4.5 3.6 - 5.7 180

 14-27 30.8 27.0 - 34.8 388 45.8 42.3 - 49.2 934 46.5 44.0 - 49.0 1,846

 28-40 67.6 63.5 - 71.4 851 50.0 46.5 - 53.6 1,022 49.0 46.4 - 51.5 1,943

First Pregnancy Yes 68.4 64.6 - 72.0 964 75.6 73.3 - 77.8 1,564 74.5 72.4 - 76.5 2,979

No 31.6 28.0 - 35.4 445 24.4 22.2 - 26.7 505 25.5 23.5 - 27.6 1,020

Visit 

First visit 39.4 35.0 - 44.1 556 42.2 38.2 - 46.3 873 46.1 43.3 - 48.9 1,847

Second visit 27.6 23.9 - 31.5 389 24.0 21.6 - 26.6 497 25.4 23.3 - 27.7 1,019

Third visit 19.2 16.3 - 22.4 270 18.9 16.6 - 21.5 392 18.1 16.0 - 20.4 725

Fourth or higher 13.8 11.8 - 16.1 194 14.8 12.7 - 17.2 307 10.4 9.1 - 11.8 416

Type of Facility Hospital/Health Center/Maternity Clinic 63.2 59.8 - 66.5 890 97.2 95.2 - 98.4 2,011 34.0 31.8 - 36.3 1,362

Dispensary/Clinic/Other 36.8 33.5 - 40.2 519 2.8 1.6 - 4.8 57 66.0 63.7 - 68.2 2,645

Managing Authority 

Public 75.2 70.5 - 79.4 1,060 73.7 68.3 - 78.4 1,523 81.1 77.5 - 84.2 3,249

Private/Other 24.8 20.6 - 29.5 349 26.3 21.6 - 31.7 545 18.9 15.8 - 22.5 758

Population Density Lowest density 16.3 11.7 - 22.1 229 18.2 14.6 - 22.4 376 54.3 49.6 - 58.8 2,115

Low density 35.7 29.6 - 42.3 503 65.8 59.4 - 71.7 1,361 26.1 21.9 - 30.7 1,016

Medium/high density 48.0 42.1 - 54.0 677 16.0 11.0 - 22.7 331 19.7 15.9 - 24.1 768

Provider Occupational Category 

Doctor/clinical technician/specialist 4.4 2.9 - 6.7 62 4.0 2.6 - 6.2 83 5.9 4.1 - 8.6 238

Nurse/midwife/other 95.6 93.3 - 97.1 1,347 96.0 93.8 - 97.4 1,985 94.1 91.4 - 95.9 3,769

Provider Years of Education <14 4.3 2.4 - 7.7 60 6.6 4.5 - 9.7 130 58.6 54.5 - 62.7 2,343

14-16 79.1 74.0 - 83.3 1,092 69.5 63.1 - 75.2 1,364 35.3 31.1 - 39.6 1,408

17+ 16.6 12.8 - 21.3 230 23.9 18.3 - 30.5 468 6.1 4.6 - 8.1 244

Provider Salary Type 

None 92.4 88.1 - 95.2 1,275 11.2 7.8 - 15.7 231 22.5 18.6 - 27.0 903

Monthly or daily salary 0.5 0.1 - 2.3 7 35.8 30.4 - 41.6 741 25.8 22.5 - 29.5 1,035

No regular salary but other pay 7.1 4.4 - 11.3 98 53.0 46.9 - 59.0 1,097 51.6 46.9 - 56.3 2,069

Provider Gender Male 25.6 20.1 - 32.0 361 25.1 20.9 - 29.7 518 15.4 12.3 - 19.1 617

Female 74.4 68.0 - 79.9 1,048 74.9 70.3 - 79.1 1,550 84.6 80.9 - 87.7 3,390

Total 1,409 2,068 4,007

 Mean 95% CI Mean 95% CI Mean 95% CI 

Malaria Facility Integration Score 63.1 60.4 - 65.8 82.7 80.6 - 84.9 69.7 67.3 - 72.0 

PMTCT Facility Integration Score 68.5 66.7 - 70.4 68.6 66.5 - 70.7 45.3 43.4 - 47.2 

Note: Clients with missing background or provider information were excluded from the distribution. 

 
72 

Appendix Table 6. Mean integration score by services provided during ANC, Kenya, Malawi, and 

Tanzania 

Kenya Malawi Tanzania 

Mean 95% CI p-value Mean 95% CI p-value Mean 95% CI p-value

PMTCT Score 

Did not receive HCT 63.5 58.65 - 68.31 0.626 83.7 80.94 - 86.44 0.898 63.9 58.93 - 68.89 <.001 Received HCT 65.2 59.99 - 70.40 84.4 74.25 - 94.44 76.2 73.69 - 78.77

Malaria Score 

Did not receive ITN or 

counseling 62.1 58.15 - 66.04 <.001 65.2 60.36 - 69.97 0.078 44.5 42.05 - 46.97 0.733 

Received ITN or counseling 72.8 70.28 - 75.29 69.8 66.99 - 72.67 46.1 37.61 - 54.54

Did not receive SP 66.2 63.68 - 68.67

<.001 

68.2 65.62 - 70.70

0.518 

40.3 38.04 - 42.59

Received SP <.001 72.5 70.27 - 74.65 69.0 66.36 - 71.69 58.2 55.27 - 61.02