mHealth-Assisted Conditional Cash Transfers to Improve Timeliness of Childhood Vaccinations
Phase: NA
Conditions: Immunization
Sponsor: Duke University

NCT03252288 – 2017-08-11 
 Page 1 of 29 
mHealth-Assisted Conditional Cash Transfers to Improve 
Timeliness of Vaccinations (MINT) 
ClinicalTrials.gov ID NCT03252288 

2 
Do mobile phone-based reminders and conditional financial transfers improve the 
timeliness of childhood vaccinations in Tanzania? Study protocol
Globally, childhood vaccinations are estimated to prevent 2.5 million deaths annually. [1] Yet, 
19.7 million children under the age of 1 year have missed receiving basic vaccinations. [1] The 
majority of un- or under-vaccinated children reside in low- and middle-income countries 
(LMICs), with those from rural, remote, and poorer households being disproportionately less 
likely to receive all recommended vaccines in their first year of life. [1-3] In Tanzania, for 
example, 1 in 4 children has not received all recommended vaccines in the first year of life, 
compared to 1 in 10 globally. [4, 5] Significant regional variation in vaccination coverage has 
been reported in Tanzania, with several regions failing to meet the 80% coverage target set 
forth in the Global Vaccine Action Plan. [5-7] Furthermore, numerous reports indicate low 
timeliness of vaccinations in LMICs, including in Tanzania. [8-10] In a study in rural Tanzania, 
vaccination delays were reported in 69% of children for the third dose of the diphtheria-
pertussis-tetanus (DPT) vaccine, and in 46% of children for the measles-containing vaccine 
(MCV). [10] In the quest for universal immunization, innovative strategies are needed to 
improve vaccination coverage for the “last mile”, and to reduce vaccination delays that leave 
children susceptible to unnecessary morbidity and mortality from vaccine-preventable infections.  
Barriers to timely immunization are multifaceted and include immunization system constraints 
(e.g., vaccine stock-outs, limited availability of health care providers), poor access to health 
facilities (e.g., transport cost, opportunity cost), lack of information (e.g., about the vaccination 
schedule or community mobilizations), and negative parental attitudes and inadequate 
knowledge (e.g., lack of trust in vaccinators, poor knowledge of vaccination benefits, fear of 
vaccination side effects). [3, 11, 12] In recent years, many groups have leveraged the global 
pervasiveness of mobile phones for alleviating some of these barriers in order to improve 
vaccination coverage and timeliness in LMICs. [13, 14] Implementations of mobile phone-based 
(“mHealth”) strategies in the context of vaccinations include birth notification and newborn 
surveillance for early identification of children eligible for vaccination services; [15-17] 
development of digital vaccination registries to longitudinally track the vaccination status of 
children and rapidly identify those who are un- or under-vaccinated; [17-23] use of text 
messages (SMS) or simple voice communication to deliver health promotion messages and 
reminders about upcoming vaccination appointments; [17, 24-26] delivery of incentives for 
timely vaccinations; [27-29] digital aids to assist vaccinators in counseling parents, [23] for work 
planning and scheduling, [17, 18, 23] or for vaccine stock management; [30] and curation of 

5 
performance indicators at the regional and national levels. [31] Despite these numerous 
instantiations, the evidence-base on the efficacy of mHealth strategies for improving childhood 
vaccination coverage and timeliness is limited, with the need for rigorous evaluations identified 
in several systematic reviews. [14, 32, 33] 
With support from the National Immunization and Vaccines Development (IVD) program of the 
Tanzanian National Ministry of Health, Community Development, Gender, Elderly and Children, 
we are evaluating the efficacy of mobile phone-based vaccination reminders and incentives in 
the form of conditional financial transfers (CFTs) for offsetting demand-side barriers to timely 
vaccination. Per the recently released WHO classification of digital health interventions, the two 
key interventions in this study correspond to 1.1 Targeted client communication (specifically, 
1.1.3 Transmit targeted alerts and reminders to clients), and 1.7 Client financial transactions 
(specifically, 1.7.3 Transmit or manage incentives to clients for health services.) [34] Our 
hypothesis is that reminders and incentives will increase timeliness of vaccinations relative to 
the status quo. The design and protocol of the evaluation are described below.  
Methods/Design 
Study aim 
The aim of the study is to assess the efficacy of (1) mobile phone-based reminders, and (2) 
mobile phone-based reminders combined with incentives in the form of CFTs, for improving 
vaccination timeliness among children at 6, 10 and 14 weeks after birth, compared to the 
standard of care. 
Outcome measures 
The recommended schedule for vaccinations by age 1 year is presented in Table 1. The 
primary study outcome is whether or not a child received an on-time vaccination; the outcome is 
measured for vaccinations scheduled at 6, 10 and 14 weeks after birth. Secondary outcomes 
include vaccination coverage, in aggregate and for each of the vaccinations due at 6, 10 and 14 
weeks after birth. Timeliness is defined as vaccination within 28 days of the scheduled 
vaccination due date. Coverage is defined as the percentage of children vaccinated. 

6 
 
Study design 
The study design represents a quasi-randomized controlled trial that includes three phases, 
each corresponding to one study arm: 1) standard of care (no reminders or incentives); 2) 
mobile phone-based reminders; and 3) mobile phone-based reminders combined with 
incentives in the form of CFTs. Arm 1 serves as the control arm; arms 2 and 3 are intervention 
arms. The trial is enfolded by base- and end-line assessments (Figure 1). 
Assignment to study arms and transitions between arms 
Assignment to study arms is implemented at the level of the vaccination event, with all 
vaccination events scheduled during a phase assigned to the corresponding arm. T1, the 
beginning of Phase 1, denotes the time of participants’ enrollment into the control arm. At time 
T2, the beginning of Phase 2, all participants are rolled over to the arm with reminders; at time 
T3, the beginning of Phase 3, all participants are rolled over to the arm with reminders combined 
with incentives.  While T2 and T3 denote fixed points in calendar time, variation in delivery dates 
across participants results in between- and within-individual variation in the assignment of 
vaccination events across the three arms. Table 2 shows all possible combinations of 
vaccination event assignments to study arms at the level of the participant. With dates of birth 
exogenously determining children’s vaccination schedules, shifts in T2 and T3 directly affect the 
number of vaccination events that may be observed in each study phase. Based on the 
distributions of expected delivery and vaccination due dates, T2 and T3 are chosen such that the 
expected number of vaccination events is approximately equal across the three arms. With T2 
and T3 being random in relation to mothers’ delivery dates, and thus children’s vaccination 
schedules, the assignment of vaccination events across arms may be considered quasi-
random. Loss to follow-up and other reasons for non-delivery of vaccination reminders result in 
exposure indistinguishable from the control condition. 
The assignment to study arms based on scheduled vaccination dates, and the simultaneous 
transition of all participants between study arms, address concerns that the individual 
randomization into, and co-existence of, incentive and non-incentive arms are not considered 
viable within closely-knit communities. While cluster randomization was considered as an 
alternative approach, the heterogeneity of clusters suggests that this approach would confound 
the effects of settings with the effects of reminders and incentives.  

7 
 
Study setting 
The study is conducted in two adjacent districts, one urban district (Mtwara Municipality) and 
one rural district (Mtwara District Council), in Mtwara Region in Southeastern Tanzania. In 2017, 
Mtwara Municipality had an estimated population of 115,132; Mtwara District Council had an 
estimated population of 130,757.[35] Owing to logistical considerations, the study area in the 
rural district is limited to a 30 kilometer (km) radius around the urban district. 
Study participants 
Eligible study participants are women, ages 16 or older, who are in the third trimester of 
pregnancy and have access to a mobile phone. The target enrollment is 400 women. 
Recruitment 
Participants are recruited from at least 4 urban and at least 8 rural health facilities and the 
surrounding communities. Eligible health facilities regularly provide childhood vaccinations. A 
combination of purposive and snowball sampling strategies is used for recruitment as follows: 
Eligible women presenting for antenatal care at participating facilities are approached by trained 
study personnel and offered enrollment in the study. To minimize biases from facility-based 
enrollment, participating women and local community leaders (balozis) are asked to identify 
other pregnant women in their community, who, if eligible, are also offered enrollment in the 
study.  
Enrollment and informed consent 
All individuals contacted for participation in the study are informed of the study purpose and 
procedures, as well as risks and benefits, during the informed consent process by study staff. 
Women are approached in person and are provided study information orally and in writing using 
an informed consent script in Kiswahili. Only consenting women are included in the study. Some 
women may access mobile phones via relatives, friends, or other designees: these persons are 
considered authorized agents for the purpose of this study. Authorized agents are not 
considered research subjects and, thus, are not independently consented. By designating 
authorized agents, participating women are considered to be providing implied consent for these 
agents to receive information on their behalf.  

8 
 
Since the study includes participants ages 16 years and older, the Institutional Review Board 
(IRB) granted a waiver of parental consent for pregnant women ages 16 and 17 years old. 
Tanzanian national policy indicates that adolescents under age 18 who are sexually active are 
considered “mature minors”, have the right to access reproductive health services without 
parental or spousal consent, and can make associated medical decisions on their own behalf. 
[36] Given that sexually active adolescents have this “adult” right to medical decision-making, it 
was determined that pregnant adolescents ages 16 and 17 years are also able to consent to 
research participation for themselves without parental or spousal consent.  
No blinding 
The nature of the interventions, mobile phone-based reminders and incentives in the form of 
CFTs, precludes blinding of study participants.  
Intervention components and implementation 
For the delivery of the study interventions, we developed an mHealth system comprising the 
following components: 
Scheduling system: Upon enrollment, a participant’s name, contact information, and EDD are 
stored in a database, and participants are added to a process queue.  For each participant, the 
process awaits inputs (e.g., date of birth of the child, vaccination dates) and executes tasks 
according to a pre-specified schedule. Tasks include sending reminder SMS, tracking SMS 
delivery, and alerting study staff to call participants when follow-up action is required. When 
event-related inputs (e.g. dates of completed or rescheduled vaccinations) are received by the 
system, the database and the schedule of tasks are updated. For example, a delay in one 
vaccination shifts the remaining schedule by the length of the delay. 
USSD notification system: Participants can notify the scheduling system of events (e.g., birth 
of child, vaccinations received) using an Unstructured Supplementary Service Data (USSD) 
dialog. USSD dialogs, which can be accessed free of charge by dialing a short code from any 
mobile phone, allow for a two-way exchange of data. In this case, the USSD dialog is 
implemented analogously to a short survey. Participants are guided through text-based menus 
which prompt them for information related to the event they are reporting. The information is 
passed to the scheduling system, which updates the schedule of upcoming tasks. 

9 
 
Mobile phone reminder system: Participants in Arms 2 and 3 receive reminders for upcoming 
vaccination appointments 1 week and 1 day before the vaccination due date. No reminders are 
associated with the EDD or the vaccination due at birth. Reminders are issued in the form of 
text messages to the mobile phone numbers of study participants or their designees. Prior to 
study implementation, messages were tested for comprehension using a structured template, 
and revised based on feedback received. The timing of messages is based on findings from a 
cross-sectional survey of 134 Tanzanian mothers of children ages 12-23 months. In that survey, 
54% of women who indicated any mobile phone use wanted to receive reminders one week 
before the due date, 40% one day before the due date, and 6% on the due date. Data on 
comprehension are collected in the end-line survey to inform future implementations. 
Incentive disbursement system: For each timely vaccination for which a reminder with an 
incentive offer was sent to a mobile phone, a payment in the form of a mobile phone airtime 
recharge voucher code (worth either TSH 1000 or TSH 2000) is sent to a mobile phone number 
specified by the participant. The two-tiered incentive amount, which was chosen ad hoc by the 
study team as appropriate to ‘nudge’ participants toward timely vaccinations without significantly 
changing their economic incentives, [37] is conditional upon the timing of vaccination (see 
below). 
Technical implementation:  The scheduling and sending of SMS messages and incentives is 
implemented via a custom-built task scheduling, execution, and event tracking application called 
mParis (“mobile phone assisted reminder and incentive system”). mParis, which was developed 
for another NIH-funded study (R01MH106388), is built using Flowable, a flexible, open source, 
Java-based, workflow engine (https://www.flowable.org). [38] The system is based at the 
Kilimanjaro Clinical Research Institute, in Moshi, Tanzania.  
Study activities 
Key events and related study activities are summarized in Figure 1 and Table 3.  
Women providing informed consent are enrolled in the study.  At the time of enrollment, a 
baseline survey is conducted with all participants to assess socio-demographic characteristics, 
mobile phone ownership and use, reproductive history, EDD for the current pregnancy, and 
vaccination knowledge, history of vaccinations in a prior child, if applicable, and previously 
experienced or anticipated barriers to vaccinations. Mobile phone numbers are obtained for 
mothers and any authorized agents. Surveys are implemented electronically on tablet devices 

10 
 
and conducted by study staff at health facilities, participants’ homes, or other mutually agreed-
upon locations. 
Toward the end of Phase 1, all women are contacted by phone to ascertain birth dates and 
outcomes, and information on past and scheduled vaccinations. The information is used to 
generate child-specific vaccination schedules. In Phases 2 and 3, reminder messages are sent 
to registered mobile phone numbers 1 week and 1 day prior to each scheduled vaccination, 
and, if no vaccination confirmation is received, 2 weeks after the vaccination due date. Uniquely 
numbered cards, given to participants at each completed or rescheduled vaccination, allow 
participants to report vaccination dates via the USSD system. When no vaccination report is 
received via the USSD system, SMS, or phone calls from participants, study staff contact the 
participant by phone to verify whether and when a vaccination was received, and ascertain the 
due date for the next vaccination, if applicable. Recorded vaccination dates are used to 
iteratively update vaccination schedules and to re-schedule reminders.  
During Phase 3, reminder messages offer an incentive for each timely vaccination. The full 
incentive amount (TSH 2000; approximately $0.90) is paid when a vaccination is received within 
2 weeks (14 days) of the due date; half the incentive is paid if the vaccination is completed more 
than 2 weeks but within 4 weeks (28 days) after the vaccination due date. Incentive amounts 
are paid if the mother, despite going to the health facility as reminded, is asked to return for a 
vaccination at a later date. Payments for timely vaccinations are made via an SMS message 
that includes a network-specific mobile phone airtime recharge voucher code and is sent to a 
phone number specified by the mother. An in-person end-line survey, conducted 12 months 
after enrollment, assesses barriers to vaccinations, receipt and acceptability of reminders (Arms 
2 and 3) and incentives (Arm 3), and records vaccination dates from participants’ government-
issued vaccination cards, allowing for comparisons with the data recorded in the mHealth 
system. 
Data management 
Password protected tablet devices are used to collect survey data from participants. Data 
transfer agreements (DTAs), signed by all participating institutions, guide the secure sharing of 
data between Tanzania and foreign collaborators. To ensure confidentiality, identifying 
information are collected, transferred, and stored separately from survey data. On-site study 
monitoring, performed by the Principal Investigators or their designees, is used to verify 

11 
 
compliance with human subjects and other research regulations and guidelines, assess 
adherence to the study protocol, and confirm the quality and accuracy of information collected 
and entered into the study database. All collaborators have access to the final data. 
Statistical analysis 
For each participant, outcomes are observed at three time points (corresponding to timely 
vaccinations at 6, 10 and 14 weeks, respectively). The probability of timely vaccinations and its 
association with reminders and incentives will be analyzed using a random effects logistic 
regression model. The outcome variable is 1 if the vaccination was received on-time, and 0 if 
early, delayed, or not received at all. The primary covariates of interest are indicator variables 
for the receipt of reminders only (“reminder”) and the receipt of reminders with an incentive offer 
(“reminder+incentive”). For arm 1 the value of both covariates is 0 for all three time points. For 
outcomes in arm 2, the value for reminder (and for arm 3 the value for reminder+incentive) is 1 
if the mHealth system confirmed delivery of the reminder, and 0 for all other observations. 
Additional covariates (e.g. mother’s education, rural vs. urban residence, recruitment from 
health facilities vs. the community) will control for differences in participant characteristics 
between study arms and their association with vaccination timeliness. Interactions of reminder 
and reminder+incentive with these covariates describe systematic variation in the effects of 
reminders and incentives on vaccination timeliness. Models will control for the number of phone-
based contacts prior to or within the timeliness window for any given vaccination, and standard 
errors will be adjusted to account for clustering at the level of the health facility catchment area.  
Statistical power 
Across 400 participants we expect up to 1,200 data points on vaccination timeliness. Assuming 
(a) that these data points are distributed equally across the 3 study arms (standard of care; 
reminders only; reminders and incentive); (b) a 10% attrition rate; (c) equal cluster sizes of 10 
women per health facility catchment area, with an intra-cluster correlation of 0.02; (d) 3 
observations per child, with a within-child correlation of 0.2; (e) a baseline rate of vaccination 
timeliness of 65% in the control condition; and (f) a 10 (15) percentage point difference 
associated with reminders (reminders and incentives), the power (α=.05, 2-tailed) to detect such 
difference is 72% (98%).   
Dissemination  

12 
 
Results will be shared with stakeholders at the regional and national levels, presented at 
national and international conferences, and published in high impact academic journals.  
Data sharing 
Efforts will be made to develop a data repository for the storage of de-identified study data. 
Investigators wishing to use study data to answer new research questions may submit data 
analysis concept proposals for consideration by the Principal Investigators. The Principal 
Investigators will review the proposal and will provide those submitting scientifically rigorous and 
promising proposals access to the data repository to address their research questions.  
Discussion 
This study examines the efficacy of mobile phone-based reminders and incentives in the form of 
conditional financial transfers for offsetting demand-side barriers to timely childhood 
vaccinations in Tanzania. Our implementation strategy has several unique components, 
including the use of a USSD-based birth and vaccination event notification system, an adaptive 
schedule for vaccination reminders which is derived from the date of the preceding event, a 
tiered incentive system, and the automated disbursement of mobile phone credit for eligible 
timely vaccinations.  
The study is subject to several limitations: First, feasibility considerations limit the study area to 
include only health facilities and their catchment areas within approximately 30 km of Mtwara 
municipality. More remote populations may face additional barriers that cannot be evaluated in 
this study. Second, only women with access to mobile phones are included in the study. To 
minimize selection bias, women could designate anyone with a mobile phone to be their study 
contact. However, for women relying on such authorized agents, receipt of messages and 
payments for timely vaccinations could remain a challenge. Third, reminder schedules and 
payments for timely vaccinations are based on client-reported birth and vaccination dates. The 
dependence on client reports may introduce delays, affect schedule accuracy, and motivate 
inaccurate reporting of vaccination dates. Comprehensive quality control, including automated 
alerts to study staff for participant follow-up, algorithms that identify inconsistencies in near real 
time, and an in-person end-line survey with a review of government-issued vaccination cards, 
will be used to assess and/or mitigate these concerns. Fourth, it is plausible that follow-up 
phone calls by study staff to ascertain birth outcomes, the timing of past vaccinations, and/or the 

13 
timing of the next scheduled vaccination, may themselves function as an intervention. Fifth, 
temporal changes that coincide with the points of transition between study arms could influence 
results. Finally, while the primary focus of the study is on demand-side barriers to timely 
vaccinations, participating health facilities may encounter vaccine stock outs and power 
outages, resulting in vaccination activities being deferred until vaccine stocks are received or 
power is restored. We plan to monitor these events along with mHealth system and mobile 
network metrics (e.g., message transmission errors, calls dropped) during the study period. By 
characterizing, and if possible, addressing the limitations of our study, we will provide critical 
information for the feasibility of scaling up reminders and/or incentives to the regional or national 
levels in low-resource settings such as Tanzania. 
With the continuing diffusion of mobile phones and the ongoing development of mHealth 
technologies, adaptive programming in the form of dynamic reminder systems and variable 
incentive structures has become a feasible reality even in low-resource settings. Our study 
sheds light on the demand-side barriers to vaccinations and the synergistic potential of 
combining mHealth reminders and incentives for improving vaccination coverage and 
timeliness. The results have implications for the design and potential efficacy of other subsidy or 
incentive programs aimed at improving health and health seeking behaviors. 

18 
References 
1.
World Health Organization. Immunization coverage. 2016 September 2016 [cited 2016
November 07]; Available from: http://www.who.int/mediacentre/factsheets/fs378/en/.
2.
World Health Organization, Global Vaccine Action Plan 2011-2020. 2013, World Health
Organization: Geneva, Switzerland.
3.
Global Immunization Division, Centers of Disease Control and Prevention, and World
Health Organization, Epidemiology of the unimmunized child: Findings from the peer-reviewed
published literature, 1999-2009. 2009.
4.
World Health Organization. Immunization, Vaccines and Biologicals. 2017  [cited 2017
October 26]; Available from: http://www.who.int/immunization/en/.
5.
The DHS Program. Demographic and Health Survey, and Malaria Indicator Survey,
Tanzania. 2015-16  [cited 2017 June 09]; Available from:
https://dhsprogram.com/pubs/pdf/FR321/FR321.pdf.
6.
Kruger, C., et al., Immunisation coverage and its associations in rural Tanzanian infants.
Rural Remote Health, 2013. 13(4): p. 2457.
7.
Semali, I.A., Trends in immunization completion and disparities in the context of health
reforms: the case study of Tanzania. BMC Health Serv Res, 2010. 10: p. 299.
8.
Akmatov, M.K. and R.T. Mikolajczyk, Timeliness of childhood vaccinations in 31 low and
middle-income countries. J Epidemiol Community Health, 2012. 66(7): p. e14.
9.
Clark, A. and C. Sanderson, Timing of children's vaccinations in 45 low-income and
middle-income countries: an analysis of survey data. Lancet, 2009. 373(9674): p. 1543-9.
10.
Le Polain de Waroux, O., et al., Timeliness and completeness of vaccination and risk
factors for low and late vaccine uptake in young children living in rural southern Tanzania. Int
Health, 2013. 5(2): p. 139-47.
11.
Sridhar, S., et al., A systematic literature review of missed opportunities for immunization
in low- and middle-income countries. Vaccine, 2014. 32(51): p. 6870-9.
12.
Cobos Munoz, D., L. Monzon Llamas, and X. Bosch-Capblanch, Exposing concerns
about vaccination in low- and middle-income countries: a systematic review. Int J Public Health,
2015. 60(7): p. 767-80.
13.
International Telecommunications Union, ICT Facts and Figures. 2016.
14.
Oliver-Williams, C., et al., Using Mobile Phones to Improve Vaccination Uptake in 21
Low- and Middle-Income Countries: Systematic Review. JMIR Mhealth Uhealth, 2017. 5(10): p.
e148.

19 
 
15. 
Xeuatvongsa, A., et al., Improving hepatitis B birth dose in rural Lao People's 
Democratic Republic through the use of mobile phones to facilitate communication. Vaccine, 
2016. 34(47): p. 5777-5784. 
16. 
Government of India, H., D. Family Welfare, and M. National Rural Health, Mother and 
Child Tracking System. 
17. 
Uddin, M.J., et al., Use of mobile phones for improving vaccination coverage among 
children living in rural hard-to-reach areas and urban streets of Bangladesh. Vaccine, 2016. 
34(2): p. 276-83. 
18. 
THRIVE consortium. Open Smart Register Platform (OpenSRP). 2017  [cited 2017 Mar 
14]; Available from: http://smartregister.org/index.html. 
19. 
Nguyen, N.T., et al., Digital immunization registry: evidence for the impact of mHealth on 
enhancing the immunization system and improving immunization coverage for children under 
one year old in Vietnam. Mhealth, 2017. 3: p. 26. 
20. 
PATH. Better Immunization Data (BID) Initiative. 2017  [cited 2017 October 26]; 
Available from: http://bidinitiative.org/. 
21. 
Jandee, K., et al., Effectiveness of Using Mobile Phone Image Capture for Collecting 
Secondary Data: A Case Study on Immunization History Data Among Children in Remote Areas 
of Thailand. JMIR Mhealth Uhealth, 2015. 3(3): p. e75. 
22. 
Kaewkungwal, J., et al., Application of mobile technology for improving expanded 
program on immunization among highland minority and stateless populations in northern 
Thailand border. JMIR Mhealth Uhealth, 2015. 3(1): p. e4. 
23. 
Chen, L., et al., Effectiveness of a smart phone app on improving immunization of 
children in rural Sichuan Province, China: study protocol for a paired cluster randomized 
controlled trial. BMC Public Health, 2014. 14: p. 262. 
24. 
Rand, C.M., et al., Effects of Phone and Text Message Reminders on Completion of the 
Human Papillomavirus Vaccine Series. J Adolesc Health, 2017. 60(1): p. 113-119. 
25. 
Department of Health and Republic of South Africa. MomConnect. 2014  [cited 2017 
March 14]; Available from: http://www.health.gov.za/index.php/mom-connect. 
26. 
Health Compass. Wazazi Nipendeni - Love Me, Parents. June 16, 2016 [cited 2017 
October 26]; Available from: http://www.thehealthcompass.org/sbcc-spotlights/wazazi-
nipendeni-love-me-parents. 
27. 
Gibson, D.G., et al., Mobile phone-delivered reminders and incentives to improve 
childhood immunisation coverage and timeliness in Kenya (M-SIMU): a cluster randomised 
controlled trial. Lancet Glob Health, 2017. 5(4): p. e428-e438. 
28. 
Wakadha, H., et al., The feasibility of using mobile-phone based SMS reminders and 
conditional cash transfers to improve timely immunization in rural Kenya. Vaccine, 2013. 31(6): 
p. 987-93. 

20 
 
29. 
Chandir, S., et al., Evaluation of Small Amount Mobile Conditional Cash Transfers 
(mCCTs) to Improve Immunization Coverage and Timeliness. iproc, 2017. 3(1): p. e47. 
30. 
VaxTrac. What is VaxTrac.  [cited 2017 October 26]; Available from: http://vaxtrac.com/. 
31. 
World Health Organization, Assisting community health workers in Rwanda: MOH's 
RapidSMS and mUbuzima. 2013: Geneva. 
32. 
Watterson, J.L., J. Walsh, and I. Madeka, Using mHealth to Improve Usage of Antenatal 
Care, Postnatal Care, and Immunization: A Systematic Review of the Literature. Biomed Res 
Int, 2015. 2015: p. 153402. 
33. 
Lee, S.H., et al., Effectiveness of mHealth interventions for maternal, newborn and child 
health in low- and middle-income countries: Systematic review and meta-analysis. J Glob 
Health, 2016. 6(1): p. 010401. 
34. 
World Health Organization. Classification of digital health interventions v1.0: A shared 
language to describe the uses of digital technology for health. 2018  [cited 2018 April 08]; 
Available from: http://www.who.int/reproductivehealth/publications/mhealth/classification-digital-
health-interventions/en/. 
35. 
Tanzania National Bureau of Statistics. Tanzania Total Population by District - Regions -
2016-2017. 2018  [cited 2018 December 02]; Available from: 
https://www.nbs.go.tz/nbstz/index.php/english/statistics-by-subject/population-and-housing-
census/844-tanzania-total-population-by-district-regions-2016. 
36. 
Fox, K., et al., Adolescent consent to HIV testing: A review of current policies and issues 
in sub-Saharan Africa., in HIV and adolescents: guidance for HIV testing and counselling and 
care for adolescents living with HIV. 2013, World Health Organization  
37. 
Thaler, R.H. and C.R. Sunstein, Nudge - Improving Decisions About Health, Wealth, and 
Happiness. 2008, New Haven, CT: Yale University Press. 
38. 
Ostermann, J., Mobile Phone Assisted Reminder and Incentive System (mParis): 
Combining mHealth reminders and conditional cash transfers to improve the timeliness of 
vaccinations in Tanzania, in National Institutes of Health mHealth Technology Showcase 2018: 
Natcher Auditorium and Atrium, National Institutes of Health Campus, Bethesda, MD.