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

population, health, and nutrition programs. Additional information about the MEASURE DHS project can 

be obtained by contacting ICF International, 11785 Beltsville Drive, Suite 300, Calverton, MD 20705 

(telephone: 301-572-0200; fax: 301-572-0999; e-mail: reports@measuredhs.com; 

www.measuredhs.com).

The main objectives of the MEASURE DHS project are: 

 to provide decision makers in survey countries with information useful for informed policy 

choices; 

 to expand the international population and health database; 

 to advance survey methodology; and 

 to develop in participating countries the skills and resources necessary to conduct high-quality 

demographic and health surveys. 
DHS Methodological Reports No. 7 

Measuring Concurrent Sexual Partnerships: 

Experience of the MEASURE DHS Project to Date 

Joy D. Fishel 

Ladys Ortiz 

Bernard Barrère 

ICF International 

Calverton, Maryland USA 

February 2012 

Corresponding author: Joy D. Fishel, International Health and Development Division, ICF International, 11785 

Beltsville Drive, Suite 300, Calverton, MD 20705; Phone: 301-572-0200; Fax: 301-572-0999; Email: 

jfishel@icfi.com 
Editor: Bryant Robey 

Document Production: Yuan Gu 

This report was written with support provided by the United States Agency for International Development 

(USAID) through the MEASURE DHS project (#GPO-C-08-00008-00). The views expressed are those of 

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

Recommended citation: 

Fishel, Joy D., Ladys Ortiz, and Bernard Barrère. 2012. Measuring Concurrent Sexual Partnerships: 

Experience of the MEASURE DHS Project to Date. DHS Methodological Reports No. 7. Calverton, 

Maryland, USA: ICF International. 
iii 

Contents 

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

Figures ........................................................................................................................................................ vii

Preface ......................................................................................................................................................... ix

Acknowledgments ...................................................................................................................................... xi

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

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

2. Rationale and Definitions for Indicators of Concurrent Sexual Partnerships .............................. 3

2.1 Rationale ....................................................................................................................................... 3 

2.2 Definitions ..................................................................................................................................... 3 

3. Calculation of Indicators of Concurrent Sexual Partnerships in DHS and AIS Surveys ............ 5

3.1 Data collection .............................................................................................................................. 5 

3.2 Preparing the data to generate variables on point and cumulative prevalence in DHS and 

AIS datasets .................................................................................................................................. 7 

3.3 Creation of recode variables and calculation of concurrency indicators....................................... 7 

4. Results ................................................................................................................................................ 15

4.1 Point and cumulative prevalence of concurrent sexual partnerships .......................................... 15 

4.2 Concurrent sexual partnerships and HIV status in individuals ................................................... 18 

4.3 Concurrent sexual partnerships and HIV status in couples ......................................................... 20 

5. Challenges in Collecting, Tabulating, and Interpreting Indicators on Concurrent Sexual 

Partnerships ...................................................................................................................................... 23

5.1 Challenges in collection .............................................................................................................. 23 

5.2 Challenges in tabulation .............................................................................................................. 23 

5.3 Challenges in interpretation ........................................................................................................ 24 

6. Conclusions ........................................................................................................................................ 27

References ......................................................................................................................................................... 29

v 

Tables 

Table 1. Point prevalence and cumulative prevalence of concurrent sexual partnerships .......................... 16 

Table 2. HIV prevalence by sexual behavior .............................................................................................. 19 

Table 3. HIV prevalence among couples .................................................................................................... 21 

Table 4. Completeness of data .................................................................................................................... 25 

vii 

Figures 

Figure 1. Sexual history questions in the DHS core women’s questionnaire ............................................... 6 

Figure 2. Coding of the point prevalence recode variable ............................................................................ 8 

Figure 3. Concurrent and non-concurrent partners ..................................................................................... 10 

Figure 4. Logic to tabulate cumulative prevalence of concurrent sexual partnerships ............................... 12 

Figure 5. Concurrency and polygyny among men age 15-49 ..................................................................... 18

ix 

Preface 

The Demographic and Health Surveys (DHS) program has become one of the principal sources of 

international data on fertility, family planning, maternal and child health, nutrition, mortality, and 

HIV/AIDS. The quality of these data is of utmost importance to researchers worldwide. 

Because survey methodology has a major impact on data quality, one of the objectives of the MEASURE 

DHS project is to advance the methodology and procedures used to carry out national-level surveys. This 

will improve the accuracy and depth of information relied on by policymakers and program managers in 

developing countries. 

The topics in the DHS Methodological Reports series are selected by MEASURE DHS staff in 

consultation with the U.S. Agency for International Development. While data quality is a main topic of 

the reports, they also examine issues of sampling, questionnaire comparability, survey procedures, and 

methodological approaches. 

This report summarizes recommendations for defining and measuring indicators on concurrent sexual 

partnerships that have been developed by the UNAIDS Reference Group on Estimates, Modeling and 

Projections. It explains the procedures used by MEASURE DHS to calculate the standard indicators, 

presents the data available at this time, and discusses some of the challenges and limitations to describing 

concurrency. 

It is hoped that the DHS Methodological Reports series will be useful to researchers and survey 

specialists, particularly those engaged in work in developing countries. 

Ann A. Way 

Project Director

xi 

Acknowledgments 

The authors would like to acknowledge the contributions of Trevor Croft, who participated in the development of 

protocols for processing concurrency data, and of Sunita Kishor and Ann Way, who reviewed the report and 

provided valuable feedback. 

xiii 

Executive Summary 

In April 2009, the UNAIDS Reference Group on Estimates, Modeling and Projections convened a meeting in 

Nairobi, Kenya, to discuss the definition and measurement of concurrent sexual partnerships. Concurrent sexual 

partnerships, that is, those that overlap in time, have become a topic of increasing interest for understanding HIV 

epidemics. During this meeting, the Reference Group recommended three standard indicators for measuring the 

prevalence of concurrent sexual partnerships in population-based surveys. The standard indicators are: point 

prevalence of concurrent partnerships, cumulative prevalence of concurrent partnerships, and the proportion of 

multiple partnerships that are concurrent in the past year, in detail. 

The purpose of the report is to summarize the Reference Group recommendations, to explain the specific procedures 

the MEASURE DHS project uses to calculate the standard indicators, to present the data on concurrency available at 

the present time, and to discuss some of the challenges and limitations. 

It is possible to measure the three recommended indicators in Demographic and Health Surveys (DHS) and AIDS 

Indicator Surveys (AIS) with minor alterations of the standard questionnaires; however, there are challenges to 

collect accurate and complete data as well as limitations to their interpretation. 

Five countries have collected and released data on concurrent sexual partnerships: Congo Brazzaville, Lesotho, 

Malawi, Mozambique, and Tanzania. Among women, the point prevalence of concurrency ranges from well under 1 

percent in Malawi to 3 percent in Congo. Among men, point prevalence ranges from 4 percent in Malawi to 10 

percent in Congo. Cumulative prevalence of concurrency ranges from less than 1 percent in Malawi to 5 percent in 

Congo and Lesotho among women, and from 7 percent in Malawi to 23 percent in Congo among men. 

Challenges in data collection include possible underreporting of concurrency due either to a reluctance of 

respondents to reveal pre-marital or extra-marital sexual partners or to recall errors. Tabulation of the concurrency 

indicators is exceedingly complex, and requires some assumptions to be taken (see Section 3). Finally, although the 

data collected in DHS and AIS surveys can estimate the national prevalence of concurrent sexual partnerships, the 

data have limited value in analyzing the association between concurrency and HIV transmission. Low numbers of 

cases of women who report having concurrent sexual partners in DHS and AIS surveys, and the fact that the surveys 

use a cross-sectional, population-based design limits the analytical value of the concurrency data they collect (see 

Section 5). 

1 

1. Introduction 

Concurrent sexual partnerships, that is, partnerships that overlap in time, have become a topic of increasing interest 

in the field of HIV/AIDS. A debate has developed over the premise that differences in levels of concurrent sexual 

partnerships help to explain why the HIV epidemic grew much more quickly in some countries than in others; 

however, the debate has been muddied by inconsistent definitions of concurrency and a lack of comparable data. 

In April 2009, the UNAIDS Reference Group on Estimates, Modeling and Projections convened a meeting in 

Nairobi, Kenya, to discuss the definition and measurement of concurrent sexual partnerships. Through this meeting, 

the Working Group on Measuring Concurrent Sexual Partnerships generated a set of recommendations with respect 

to indicators for assessing the prevalence of concurrent partnerships and the questions that should be added to 

surveys to provide the data for measuring these concurrency indicators. 

This report summarizes the Reference Group’s recommendations, provides detail on how the MEASURE DHS 

Project collects and tabulates data to measure these indicators, and shows the results for the prevalence of 

concurrency in five Demographic and Health Surveys (DHS) and AIDS Indicator Surveys (AIS). The report also 

describes challenges and limitations in collecting data on concurrency, calculating the indicators, and interpreting 

the results.

3 

2. Rationale and Definitions for Indicators of Concurrent Sexual 

Partnerships 

2.1 Rationale 

Mathematical modeling has shown that even small increases in concurrency can result in large increases in HIV 

transmission (Morris and Kretzchmar, 1997). The increase in risk of HIV transmission associated with concurrency 

is believed to occur through two different mechanisms: (1) by generating an interconnected sexual network, 

increasing the velocity with which HIV infection passes from one person to the next; and (2) by allowing HIV 

infection to travel both “forward” and “backward” among an individual’s sexual partners (Ghys, 2009).

In serial monogamous partnerships, a newly infected individual cannot transmit the virus to another person until the 

current partnership dissolves and he or she acquires a new partner. In contrast, in concurrent partnerships the virus 

can spread quickly along the pathways of interconnected sexual networks. The period of high viremia and 

transmissibility that follows initial HIV infection amplifies the effect of concurrency on HIV transmission; having 

concurrent sexual partners makes it more likely that a newly infected individual will expose additional partners to 

infection during this time. 

In addition, concurrency removes the “protective sequencing” of serial monogamy. In serial monogamous 

partnerships, HIV infection can only move “forward” through an individual’s sexual partners. An individual’s 

earlier partner is “protected” from acquiring the infection of a later partner. However, if an individual begins a 

second partnership while continuing the first partnership, then the first partner is at risk of acquiring an infection that 

the individual acquires from the second partner. In other words, HIV infection can move both “forward” and 

“backward” through an individual’s sexual partners. 

Although there is a theoretical link between concurrent sexual partnerships and the size and spread of HIV 

epidemics, few data are available to test for an empirical association. One of the challenges to generating a body of 

evidence on concurrency has been the lack of consensus on an operational definition and recommended data 

collection methodologies. In addition to providing evidence to support or refute an association between concurrency 

and HIV transmission, standardized indicators and data collection methodologies are also needed to facilitate 

evaluation of several emerging HIV prevention programs that aim to reduce the number of concurrent sexual 

partnerships. 

2.2 Definitions 

According to the UNAIDS Reference Group, concurrent sexual partnerships are defined as “overlapping sexual 

partnerships in which sexual intercourse with one partner occurs between two acts of intercourse with another 

partner.”1

 

The Working Group on Measuring Concurrent Sexual Partnerships also recommended one primary and two 

alternate indicators: 

Primary indicator: Point prevalence of concurrent partnerships, defined as the proportion of 

women and men age 15-49 with more than one ongoing sexual partnership at the point in time six 

months before the interview. 

Alternate indicator: Cumulative prevalence of concurrent partnerships, defined as the 

proportion of women and men age 15-49 with overlapping sexual partnerships at any point in the 

past year. 

 

1

 Ghys, 2009; UNAIDS, 2009; and UNAIDS, 2010. 
4 

Alternate indicator: Proportion of multiple partnerships that are concurrent in the past 

year, defined as follows: Among women and men age 15-49 who had multiple sexual 

partnerships in the previous year, the proportion who had concurrent partnerships in the previous 

year. 

The point prevalence of concurrent sexual partnerships, by virtue of requiring that partnerships start before and end 

after a given cutoff, excludes those that last only one day. It was chosen as the primary indicator because it 

emphasizes sustained overlapping sexual partnerships, which are theorized to have a stronger association with HIV 

transmission than concurrent sexual partnerships involving one long-term partnership and occasional one-time 

sexual encounters. The possibility of acquiring HIV through a single coital act with an HIV-positive individual is 

relatively low.2

 If an individual does not acquire an infection through a one-time sexual encounter, then their other 

concurrent sexual partners are not at increased risk of infection. An individual’s risk of acquiring HIV from an HIVpositive partner is higher if their partnership is sustained over a period of time. The cumulative prevalence indicator, 

however, does include concurrent partnerships that consist of a longer-term partnership and a one-time sexual 

encounter. 

The UNAIDS Reference Group recommendations took into account two other issues in defining concurrency: 

(1) If one sexual partnership ends during the same month/week/day as another sexual partnership 

begins, the two partnerships should not be considered concurrent. 

(2) The relationship of the sexual partner is not taken into account. Partnerships are treated the same 

if they are with a wife, a non-cohabiting long-term partner, a casual acquaintance, a sex worker, 

etc. One implication of this recommendation is that polygynous men who have overlapping 

sexual partnerships with their wives are considered to have concurrent partnerships. 

The Reference Group also recommended a specific series of questions for measurement of these indicators: 

“When was the last time you had sexual intercourse with this person?” 

[Answer in days/weeks/months ago (and years for the most recent partner)] 

“When was the first time you had sexual intercourse with this person?”

[Answer in days/weeks/months ago] 

“Are you still having sex with this person?”

 

2

 Three studies have estimated the chance of infection per coital act (of penile vaginal intercourse) at around 1 in 

1,000: Gray et al., 2001; Wawer et al., 2005; and Hira et al., 1997.
5 

3. Calculation of Indicators of Concurrent Sexual Partnerships in 

DHS and AIS Surveys 

3.1 Data collection 

The MEASURE DHS Project has incorporated the recommendations of the UNAIDS Reference Group on Estimates 

Modeling and Projections (with the exception of the question about whether the sexual partnership is ongoing) into 

the core DHS questionnaires and final report tabulation plan.3

 The rest of Section 3 provides detailed information on 

the indicator definitions and how they are tabulated in the DHS and AIS surveys. Data from surveys in five 

countries—three DHS and two AIS—are currently available and are presented in Section 4 of this report. 

The standard DHS and AIS core questionnaires for women and men include a section on the respondent’s sexual 

behavior in the past 12 months. Figure 1 shows the 12-month sexual history questions from the DHS core women’s 

questionnaire; the men’s version is nearly identical, except for the necessary modifications in coding categories and 

filters to adapt it for use with men. 

In collecting the sexual history data, the surveys ask all respondents who have ever had sex when was the last time 

they had sexual intercourse. Respondents who reported having had sexual intercourse in the past 12 months are 

asked how long ago they last had sex, and how long ago they first had sex with each of their most recent three 

sexual partners in the past 12 months. Each of these questions is used in the calculation of both point and cumulative 

prevalence of concurrent sexual partnerships. 

 

3

 The project did not include the question on whether the sexual partnership is ongoing because it requires the 

respondent to speculate about future events. It may be difficult for a respondent to know whether or not a 

partnership will continue into the future, especially for casual sexual partnerships. In addition, this question is not 

needed to calculate the recommended point and cumulative prevalence indicators. 
6 

Figure 1. Sexual history questions in the DHS core women’s questionnaire

615

DAYS AGO . . . . . . . . . . . . 1

IF LESS THAN 12 MONTHS, ANSWER MUST BE RECORDED

IN DAYS, WEEKS OR MONTHS. WEEKS AGO . . . . . . . . . 2

IF 12 MONTHS (ONE YEAR) OR MORE, ANSWER MUST BE

RECORDED IN YEARS. MONTHS AGO . . . . . . . 3

YEARS AGO . . . . . . . . . 4 627

When was the last time you had sexual intercourse?

616 DAYS DAYS

AGO 1 AGO 1

WEEKS WEEKS

AGO 2 AGO 2

MONTHS MONTHS

AGO 3 AGO 3

617 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1

NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2

(SKIP TO 619) (SKIP TO 619) (SKIP TO 619)

618 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1

NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2

619 HUSBAND . . . . . . . . . 1 HUSBAND . . . . . . . . . 1 HUSBAND . . . . . . . . . 1

LIVE-IN PARTNER . . . 2 LIVE-IN PARTNER . . . 2 LIVE-IN PARTNER . . . 2

BOYFRIEND NOT BOYFRIEND NOT BOYFRIEND NOT 

LIVING WITH LIVING WITH LIVING WITH 

IF BOYFRIEND: RESPONDENT . . . 3 RESPONDENT . . . 3 RESPONDENT . . . 3

CASUAL CASUAL CASUAL 

ACQUAINTANCE . . . 4 ACQUAINTANCE . . . 4 ACQUAINTANCE . . . 4

IF YES, CIRCLE '2'. CLIENT/PROSTITUTE 5 CLIENT/PROSTITUTE 5 CLIENT/PROSTITUTE 5

IF NO, CIRCLE '3'. OTHER ______________ 6 OTHER ______________ 6 OTHER ______________ 6

(SPECIFY) (SPECIFY) (SPECIFY)

(SKIP TO 622) (SKIP TO 622) (SKIP TO 622)

620 CHECK 609: MARRIED MARRIED MARRIED MARRIED MARRIED MARRIED

ONLY MORE ONLY MORE ONLY MORE

ONCE THAN ONCE THAN ONCE THAN 

ONCE ONCE ONCE

(SKIP (SKIP (SKIP

TO 622) TO 622) TO 622)

621 CHECK 613: FIRST TIME WHEN FIRST TIME WHEN FIRST TIME WHEN

STARTED LIVING STARTED LIVING STARTED LIVING

WITH FIRST WITH FIRST WITH FIRST

HUSBAND OTHER HUSBAND OTHER HUSBAND OTHER

(SKIP TO 623) (SKIP TO 623) (SKIP TO 623)

622 DAYS DAYS DAYS

AGO 1 AGO 1 AGO 1

WEEKS WEEKS WEEKS

AGO 2 AGO 2 AGO 2

MONTHS MONTHS MONTHS

AGO 3 AGO 3 AGO 3

YEARS YEARS YEARS

AGO 4 AGO 4 AGO 4

623 NUMBER OF NUMBER OF NUMBER OF 

TIMES TIMES TIMES

IF NON-NUMERIC ANSWER,

PROBE TO GET AN ESTIMATE.

IF NUMBER OF TIMES IS 95 OR

MORE, WRITE '95'.

624 AGE OF AGE OF AGE OF

PARTNER PARTNER PARTNER

DON'T KNOW . . . . . 98 DON'T KNOW . . . . . 98 DON'T KNOW . . . . . 98

625 YES . . . . . . . . . . . . . . 1 YES . . . . . . . . . . . . . . 1

(GO BACK TO 616 (GO BACK TO 616

IN NEXT COLUMN) IN NEXT COLUMN)

NO . . . . . . . . . . . . . . 2 NO . . . . . . . . . . . . . . 2

(SKIP TO 627) (SKIP TO 627)

626 NUMBER OF

PARTNERS

LAST 12 

IF NON-NUMERIC ANSWER, . . . 

PROBE TO GET AN ESTIMATE.

IF NUMBER OF PARTNERS IS DON'T KNOW . . . 

95 OR MORE, WRITE '95'.

How old is this person?

Apart from (this person/these two 

people), have you had sexual 

intercourse with any other person in 

the last 12 months?

SECOND-TO-LAST

SEXUAL PARTNER

98

MONTHS

THIRD-TO-LAST

SEXUAL PARTNER

In total, with how many different 

people have you had sexual 

intercourse in the last 12 months? 

LAST

How long ago did you first have 

sexual intercourse with this 

(second/third) person?

How many times during the last 12 

months did you have sexual 

intercourse with this person?

SEXUAL PARTNER

When was the last time you had 

sexual intercourse with this person?

The last time you had sexual 

intercourse (with this second/third 

person), was a condom used? (2)

Was a condom used every time you 

had sexual intercourse with this 

person in the last 12 months?

What was your relationship to this 

person with whom you had sexual 

intercourse?

Were you living together as if 

married?
7 

3.2 Preparing the data to generate variables on point and cumulative 

prevalence in DHS and AIS datasets

In DHS and AIS surveys, time since first/last sex is recorded in number of days, weeks, months or years before the 

survey. Each of these responses is first converted to a number of days, for ease of comparison. Because all responses 

are recorded in completed units, an adjustment of half the length of the unit is applied to each response. 

e.g. “4 months ago” is treated as 4.5 months = (365 days/12 months) * 4.5 months = 137 days ago

e.g. “4 weeks ago” is treated as 4.5 weeks = (7 days/week) * 4.5 weeks = 31.5 days ago

3.3 Creation of recode variables and calculation of concurrency indicators 

Creating the recode variable for point prevalence of concurrency 

As mentioned above (see Definitions), point prevalence of concurrency is defined as having two or more sexual 

partnerships ongoing at the point in time six months before the survey. The cutoff of six months is converted to 182 

days (6*(365/12)). A sexual partnership is considered to be ongoing six months before the survey if the time since 

first sex with the partner is greater than 182.5 days and the time since last sex with the partner is less than 182.5 

days.4

 

The first step in creating the recode variable for point prevalence of concurrency is to tally the number of sexual 

partnerships that are ongoing at the point in time six months before the survey for each respondent who had more 

than one sexual partner in the past 12 months. The possible outcomes are 0, 1, 2, or 3, because the questionnaire 

collects time since first and last sex only for the last three sexual partners in the past 12 months. The recode variable 

for point prevalence of concurrent sexual partnerships is then defined as followed: 

Respondents who had multiple sexual partnerships in the past 12 months but who had no sexual 

partnerships or only one sexual partnership that met the criteria of beginning before the six-month 

cutoff and continuing after the six-month cutoff (i.e., those with a value of 0 or 1 on the tally 

variable described above) are assigned a value of 0. (Respondents 1 and 2 in Figure 2, below). 

Respondents who had two or three sexual partnerships in the past 12 months that began before the 

cutoff and continued after the cutoff (i.e., those with a value of 2 or 3 on the tally variable) are 

assigned a value of 1. (Respondents 3 and 4 in Figure 2). 

Respondents who had no sexual partners in the past 12 months or who had exactly one sexual 

partner during this time are assigned a value of ‘not applicable’ in CSPro. This gets translated 

into a value of ‘system missing’ in most analysis software. 

 

4

 Due to the half-unit adjustment, responses for time since first/last sex cannot equal exactly 180 days. 
8 

Figure 2. Coding of the point prevalence recode variable 

Respondent 1:

0 partnerships at 6 months

Point prevalence variable=0

Respondent 2:

1 partnership at 6 months

Point prevalence variable=0

Respondent 3:

2 partnerships at 6 months

Point prevalence variable=1

Respondent 4:

3 partnerships at 6 months

Point prevalence variable=1

Months before the interview

12 11 10 9 8 7 6 5 4 3 2 1 0

Calculating the indicator for point prevalence of concurrency using the recode variable 

Using the recode variable for point prevalence of concurrency, the indicator is calculated by placing respondents 

with a value of 1 in the numerator, and all respondents (i.e., those with a value of 0, 1 and ‘not applicable’) in the 

denominator. 

Numerator: 

Number of respondents age 15-49 who had two or more sexual 

partnerships during the past 12 months in which the first sexual 

intercourse with a partner occurred prior to a cutoff of six 

months before the survey and the most recent sexual 

intercourse with the same partner occurred after a cutoff of six 

months before the survey 

Denominator: All respondents age 15-49 

In other words, a person is counted as having point prevalence of concurrency if they have two or three sexual 

partnerships ongoing at the point in time six months before the survey. The point prevalence of concurrency 

indicator intentionally excludes partnerships lasting only one day. The relationship of each partner to the respondent 

is not taken into account in calculating point prevalence of concurrency. 
9 

Creating the recode variable for cumulative prevalence of concurrency 

As mentioned above (see Definitions), cumulative prevalence of concurrency is defined as having any overlapping 

sexual partnerships in the 12 months preceding the survey. Overlapping sexual partnerships are those in which an 

individual has sexual intercourse with one partner between two acts of intercourse with another partner. 

As in the recode variable for point prevalence, in the recode variable for cumulative prevalence respondents who did 

not have multiple sexual partners in the past 12 months are assigned a value of ‘not applicable’. Next, all 

respondents with two or more sexual partners in the past 12 months are assigned a default value of 0, indicating no 

concurrent partnerships in the past 12 months. Each respondent is then checked to determine whether or not any of 

their partnerships are concurrent. Any respondent who is found to have concurrent partners, by satisfying one of the 

conditions described below, is recoded from 0 to 1, indicating concurrent sexual partnerships in the past 12 months. 

As shown in Figure 1, the information on the last three sexual partners in the past 12 months is collected using a 

table with three columns, with the first column including information on the most recent sexual partner (the last 

person the respondent had sex with), the second column including information on the second-to-last sexual partner, 

and the third column including information on the third-to-last sexual partner. If a respondent has only two partners 

in the past 12 months, only one comparison is needed to check whether or not any two partners overlap (that is, a 

comparison between the most recent partner and the second-to-last partner). However, if a respondent has three or 

more sexual partners in the past 12 months, three comparisons must be made: between the most recent partner and 

the second-to-last partner, between the second-to-last partner and the third-to-last partner, and between the most 

recent partner and the third-to-last partner. If any two partnerships are concurrent according to the conditions below, 

then the respondent is assigned a value of 1 on the recode variable for cumulative prevalence of concurrent sexual 

partnerships. 

In checking whether or not any two of the various combinations of sexual partnerships are concurrent, four data 

points are involved. Figure 3 illustrates how the information on time since first sex and time since last sex with the 

most recent partner and the time since first sex and time since last sex for the second-to-the last partner are checked 

for concurrency. 

1. Last sex with the most recent partner - call this ‘a’

2. First sex with the most recent partner - call this ‘b’

3. Last sex with the second-to-the last partner - call this ‘c’

4. First sex with the second-to-the last partner - call this ‘d’
10 

Figure 3. Concurrent and non-concurrent partners 

Not concurrent

Concurrent

Months before the interview

Greater | Lesser

12 11 10 9 8 7 6 5 4 3 2 1 0

b a

d

d c

c

b a

Partner 1

Partner 2

Overlap

Partner 1

Partner 2

For the vast majority of respondents in the five surveys analyzed, any two sexual partnerships can be correctly 

classified as concurrent or not concurrent simply by determining whether the first sex with the first partner in the 

pair being checked for concurrency (data point ‘b’) occurred before or after the last sex with second partner in the 

pair (data point ‘c’). As Figure 3 shows, if data point ‘b’ is after data point ‘c’ the partnerships are not concurrent; if 

data point ‘b’ is before data point ‘c’ the partnerships are concurrent. However, two data quality issues affecting a 

small percentage of partnerships may prevent this simple check from working correctly for every pair of partners: 

(1) partners being recorded out of order on the questionnaire; and (2) missing data. 

Although sexual partners are supposed to be recorded in the three columns in the questionnaire in order, from most 

recent to least recent according to the time since last sex with each partner, it is possible for the timing of last sex for 

a supposedly earlier partner to be reported as later than the timing of last sex with the supposed later partner. In this 

situation, we assume that the data for time since last sex is correct, and the partners are out of order in the 

questionnaire. To ensure that the cumulative prevalence variable correctly classifies partnerships as concurrent or 

not, we employ a logic for checking partnerships that is equally effective whether the partners are in order or out of 

order. The logic is also designed to minimize the impact of missing data on the indicator calculation. In many (but 

not all) pairs of partnerships, it is possible to correctly classify the partnerships as concurrent or not concurrent even 

when one of the four data points is missing. The logic used to classify partnerships performs multiple checks on 

each pair of partners, so that a lack of information on any specific data point does not prevent correct classification 

of the partnerships when sufficient information is available to make a conclusion. 

The following logic rules are used to classify any two partnerships as concurrent or not concurrent (see Figure 4): 

Condition 1: If b>c and b<d, then the partners are concurrent 

Condition 2: If a>c and a<d, then the partners are concurrent 

Condition 3: If a<d and b>d, then the partners are concurrent 
11 

Condition 4: If a<c and b>c, then the partners are concurrent 

Condition 5: If a is missing and b>d, then assume that the partners are in order, and the two partners are 

considered concurrent by condition 3 

Condition 6: If c is missing and b≥12 months, then the two partners are concurrent

Condition 7: If a=c and b=d and a is not equal to b, then the partners are concurrent 

The date of first/last sex is recorded in time before the interview, so a larger number signifies an earlier event, while 

a smaller number signifies a later event. 

For the purpose of illustrating the basic mechanics of the seven conditions, Figure 4 is simplified and does not show 

all possible configurations of partnerships. For example, Condition 1 would also classify two partnerships as 

concurrent if ‘a’ occurred at the same time as ‘c’, if ‘a’ occurred in between ‘b’ and ‘c’, or if ‘a’ and ‘b’ had the 

same value, as in a one-time casual encounter. 
12 

Figure 4. Logic to tabulate cumulative prevalence of concurrent sexual partnerships 

Months before the interview

Greater | Lesser

12 11 10 9 8 7 6 5 4 3 2 1 0

d c

b a

Condition 1

Condition 3

Condition 2

Condition 4

d c

b a

d c

b a

d c

b a

d c?

b a

Condition 7

d c

b a?

Condition 6

d c

b a

Condition 5
13 

If at least one of these seven conditions is true, then the respondent is recoded from 0 to 1 on the cumulative 

prevalence of concurrency recode variable. The program to calculate the variable first compares the most recent and 

second-to-last partners. If none of the seven conditions is satisfied for that pair of partners, the program then loops 

through and compares the second-to-last partner and third-to-last partners. If none of the conditions is satisfied, the 

program then compares the most recent partner and the third-to-last partner. If at least one condition is found to be 

true in any of the three comparisons, the respondent is recoded from 0 to 1 on the cumulative prevalence of 

concurrency variable. 

If none of the conditions is true for any pair of partners, then the respondent maintains the default value of 0 on the 

cumulative concurrency variable. Respondents with a value of 0 on the cumulative prevalence of concurrency 

variable include two groups: (1) respondents whose information confirms that none of their partners in the past 12 

months were concurrent; and (2) respondents whose information is insufficient to determine whether or not any of 

their partners were concurrent.5

In summary, for the recode variable on cumulative prevalence of concurrency, a respondent is given a value of 1 if 

any two of their last three sexual partnerships in the past 12 months satisfy at least one of the seven conditions 

specified above. All other respondents who had multiple partners in the past 12 months retain a default value of 0. 

Respondents who did not have sex in the past 12 months and those who had exactly one sexual partner are assigned 

a value of ‘not applicable’. 

Calculating the indicator for cumulative prevalence of concurrency using the recode variable 

Using the recode variable for cumulative prevalence of concurrency, the indicator is calculated by placing 

respondents with a value of 1 in the numerator, and placing all respondents (i.e., those with a value of 0, 1 and ‘not 

applicable’) in the denominator. The relationship of each partner to the respondent is not taken into account in 

calculating point prevalence of concurrency. 

Numerator: Number of respondents age 15-49 who had two or more 

overlapping sexual partners in the past 12 months (as 

determined by satisfying at least one of the seven conditions 

outlined above) 

Denominator: All respondents age 15-49 

Calculation of point and cumulative prevalence of concurrency, further detail 

The following steps are taken to clean the data collected for time since first sex (TFS) and time since last sex (TLS) 

before any of the calculations on concurrency are made: 

If TLS (with any sexual partner in the past 12 months) is reported earlier than TFS with the same 

partner, then the two values are reversed. 

If TFS (with any sexual partner in the past 12 months) is missing and TLS with the same partner 

is valid, and the number of times the respondent had sex with this partner is 1, then TFS is set 

equal to TLS. 

If TLS (with any sexual partner in the past 12 months) is missing and TFS with the same partner 

is valid, and the number of times the respondent had sex with this partner is 1, then TLS is set 

equal to TFS. 

 

5 Information on the proportion of cases that lack sufficient information is provided in Table 4, for each of the five 

countries examined.
14 

If the TFS (for any partner in the past 12 months) has code ‘4’ for the unit, indicating ‘years ago’, 

and the number of years is missing, then set time since first sex for this partner equal to 1 year. 

This allows the application to establish that first sex with this partner occurred before last sex 

with any other partner in the sexual history table, because last sex with any partner must have 

occurred within the past 12 months in order for the partner to be recorded in this section of the 

questionnaire. 
15 

4. Results 

4.1 Point and cumulative prevalence of concurrent sexual partnerships 

DHS or AIS data on concurrent sexual partnerships are currently available from five countries (Congo Brazzaville, 

Lesotho, Malawi, Mozambique and Tanzania)6

 and are presented in Table 1. In the five countries, data were 

collected from nationally representative samples, varying widely in size, from 5,674 women in Mozambique to 

23,020 in Malawi, and from 2,527 men in Tanzania to 6,818 in Malawi. 

Table 1 first presents the proportion of women and men who reported multiple partners in the past 12 months. In 

Malawi, about one in ten men reported two or more sexual partners; in Lesotho, Tanzania and Mozambique, this 

proportion is twice as high; and in Congo one in three men reported multiple partners. Among women, these 

proportions are much lower: less than 1 percent of women reported multiple partners in Malawi, about 3 percent in 

Mozambique and Tanzania, 6 percent in Lesotho, and 7 percent in Congo. 

In each country, both the point and cumulative concurrency prevalence measures are markedly higher for men than 

women. Among women, point prevalence ranges from 0.1 percent in Malawi to 3 percent in Congo. Cumulative 

prevalence ranges from 0.3 percent in Malawi to 5 percent in Congo and Lesotho. Among men, point prevalence 

ranges from 4 percent in Malawi to 10 percent in Congo. Cumulative prevalence ranges from 7 percent in Malawi to 

23 percent in Congo. Cumulative prevalence of concurrent sexual partners appears to be about twice as high as point 

prevalence, for both women and men in all countries. 

 

6

 Congo AIS 2009 (Centre National de la Statistique et des Études Économiques and ICF Macro, 2009); Lesotho 

DHS 2009 (Ministry of Health and Social Welfare and ICF Macro, 2010); Malawi DHS 2010, (National Statistical 

Office and ICF Macro, 2011); Mozambique AIS 2009 (INS, INE, and ICF Macro, 2010); and Tanzania DHS 2010 

(National Bureau of Statistics and ICF Macro, 2011).
16 

Table 1. Point prevalence and cumulative prevalence of concurrent sexual partnerships 

Percentage of all respondents age 15-49 who had overlapping sexual partnerships six months before the survey 

(point prevalence1

), and percentage of all respondents age 15-49 who had any overlapping sexual partnerships during the 12 months before the survey (cumulative prevalence2

), and among respondents age 15-49 who had 

multiple sexual partners during the past 12 months, percentage who had concurrent sexual partnerships 

Among all respondents age 15-49 

Among respondents who had 

multiple partners during the 

12 months before the survey 

Background 

characteristic 

Percentage with 2+ 

partners in the 

past 12 months 

Point 

prevalence of 

concurrent 

sexual partners1 

Cumulative 

prevalence of 

concurrent 

sexual partners2 Number 

Percentage who 

had concurrent 

sexual partners2 Number 

CONGO 2009

Women 6.9 2.6 5.2 6,550 77.0 446 

 Not in union 12.1 3.9 8.5 2,658 72.0 315 

 In Union 3.4 1.6 3.0 3,892 89.1 131 

Men 28.6 9.9 22.6 5,863 79.5 1,667 

 Not in union 23.1 4.5 14.8 2,855 64.2 658 

 In Union 33.8 15.0 30.0 3,008 89.5 1,009 

 Polygynous 91.7 69.7 86.2 192 94.0 176 

 Non-polygynous 29.7 11.0 26.0 2,795 88.4 822 

LESOTHO 2009 

Women 6.4 2.4 5.2 7,624 81.6 488 

 Not in union 5.2 1.3 3.6 3,575 69.0 186 

 In Union 7.5 3.3 6.7 4,049 89.5 302 

Men 21.9 7.7 16.2 3,008 74.0 659 

 Not in union 21.0 4.9 13.2 1,839 62.9 385 

 In Union 23.4 12.0 21.0 1,169 89.7 274 

 Polygynous * * * 17 * 5 

 Non-polygynous 23.4 11.9 20.9 1,152 89.5 269 

MALAWI 2010

Women 0.7 0.1 0.3 23,020 45.8 151 

 Not in union 1.0 0.2 0.4 7,492 39.7 73 

 In Union 0.5 0.1 0.3 15,528 51.5 78 

Men 9.2 3.8 7.2 6,818 78.5 627 

 Not in union 6.7 0.7 3.9 2,923 58.3 195 

 In Union 11.1 6.0 9.7 3,895 87.7 432 

 Polygynous 68.8 54.7 63.8 295 92.7 203 

 Non-polygynous 6.3 2.0 5.3 3,592 83.2 227 

MOZAMBIQUE 2009

Women 3.0 0.8 2.1 5,674 70.3 169 

 Not in union 5.9 1.5 3.7 1,516 63.3 90 

 In Union 1.9 0.5 1.5 4,157 78.2 79 

Men 19.8 9.0 16.0 4,168 80.7 824 

 Not in union 15.1 3.8 9.2 1,458 60.8 220 

 In Union 22.3 11.8 19.6 2,710 87.9 604 

 Polygynous 73.9 52.4 71.1 311 96.3 230 

 Non-polygynous 15.6 6.5 12.9 2,377 83.0 370 

TANZANIA 2010

Women 3.5 1.1 2.1 10,139 59.8 357 

 Not in union 5.0 1.0 2.3 3,727 47.4 185 

 In Union 2.7 1.1 2.0 6,412 73.2 173 

Men 20.7 7.8 15.4 2,527 74.5 523 

 Not in union 12.3 2.1 5.7 1,210 46.5 149 

 In Union 28.3 13.1 24.3 1,317 85.6 373 

 Polygynous 85.5 63.9 80.6 128 94.3 109 

 Non-polygynous 22.2 7.7 18.2 1,189 82.1 264 

Notes: Two sexual partners are considered to be concurrent if the date of the most recent sexual intercourse with the 

earlier partner is after the date of the first sexual intercourse with the later partner. Information on type of union is missing for 21 men in Congo, 8 men in Malawi, and 21 men in Mozambique. 1

 The percentage of respondents who had two (or more) sexual partners that were concurrent at the point in time six 

months before the survey 2

 The percentage of respondents who had two (or more) sexual partners that were concurrent anytime during the 12 months preceding the survey 
17 

The countries rank in more or less the same order for prevalence of concurrency, regardless of whether one looks at 

the point prevalence indicator or the cumulative prevalence indicator. However, concurrency among men is not 

consistently correlated with concurrency among women across the countries. Malawi has the lowest levels of 

concurrency for both women and men, Congo has the highest levels among men and women, and Mozambique and 

Tanzania fall in the middle. In Lesotho, however, the level of concurrency among women is similar to the higher 

level in Congo while among men, the level of concurrency is similar to the moderate levels in Tanzania and 

Mozambique. 

Considering current marital status, in Congo and Mozambique women who are not in union are more likely to have 

concurrent sexual partners (by either definition), but in Lesotho they are less likely to have concurrent partners, and 

in Malawi and Tanzania they are roughly equally likely to have concurrent sexual partners compared with women in 

union. 

Given that the definitions of point and cumulative prevalence of concurrency include multiple wives as concurrent 

partners, it is not surprising that polygynous men are most likely to report concurrent sexual partnerships in the past 

12 months. Men with one wife are more likely than men who are not in union to have had concurrent sexual 

partnerships in the past 12 months but are less likely than polygynous men to have had concurrent sexual 

partnerships (by either the point or cumulative indicator). It is also interesting to note that the percent of men in 

polygynous union who report having concurrent sexual partnerships in the past 12 months is low in some countries 

(64 percent in Malawi and 71 percent in Mozambique, versus 86 percent in Congo, according to the cumulative 

prevalence indicator). 

However, the prevalence of concurrency is not directly associated with the prevalence of polygyny in these five 

countries, which all have relatively low levels of polygyny. Figure 5 shows the percentage of all men age 15-49 with 

more than one wife/partner. Malawi, with 4 percent of men currently married to more than one woman, has a 

cumulative prevalence of concurrent sexual partnerships of 7 percent. In contrast, Congo, with 3 percent of men 

currently in polygynous union, has a cumulative prevalence of concurrent sexual partnerships of 23 percent. In 

another set of countries with higher levels of polygyny, a stronger relationship between polygyny and concurrency 

may be observed. 

Table 1 also shows the second UNAIDS-recommended alternate indicator: the proportion of multiple partnerships 

that are concurrent in the past year. In considering these results, note that relatively small numbers of respondents, 

especially women, report having multiple partners. Among women and men age 15-49 who had multiple sexual 

partnerships in the previous year, the proportions that had concurrent partnerships in the previous year is high in all 

five countries—among women from 46 percent in Malawi to 82 percent in Lesotho, and among men from 74 

percent in Lesotho to 81 percent in Mozambique. As might be expected, among women with multiple partners in the 

past 12 months, in each of the five countries the percentage that had concurrent partners is higher among women in 

union than those who are not in union. Among men with multiple partners in the past 12 months, the percentage that 

had concurrent partners is highest among men in polygynous union, followed by men with one wife and then men 

who are not in union. 
18 

Figure 5. Concurrency and polygyny among men age 15-49 

8

10

4

8

9

16

23

7

15 16

1

3

4 5

8

0

5

10

15

20

25

Lesotho Congo Malawi Tanzania Mozambique

Point prevalence Cumulative prevalence % polygynous

4.2 Concurrent sexual partnerships and HIV status in individuals 

Table 2 shows HIV prevalence by number of sexual partners in the past 12 months, and whether or not the 

individual had concurrent partnerships in the past 12 months according to both point prevalence and cumulative 

prevalence definitions. Concurrency and HIV prevalence are available for only four of the countries because the 

2010 Tanzania DHS did not include HIV testing. One limitation to these data is that although the sexual behavior 

data applies to the past 12 months, there is no information on when HIV+ individuals became infected. Obviously, 

sexual behavior in the past 12 months cannot have a causal relationship with HIV infection that was acquired more 

than 12 months ago. 

For men in all countries, HIV prevalence increases with the number of sexual partners in the past 12 months. For 

women, by contrast, there is no consistent pattern across countries. In Lesotho, Malawi and Mozambique, women 

with multiple partners in the past 12 months have the highest HIV prevalence. In Congo, however, women with no 

sexual partners in the past 12 months have the highest HIV prevalence. In Congo, Malawi and Mozambique, women 

with no sexual partners in the past 12 months have higher HIV prevalence than those with one sexual partner during 

this time. 
19 

Table 2. HIV prevalence by sexual behavior 

Percentage HIV-positive among women and men age 15-49 who ever had sex and were tested for HIV, by sexual 

behavior characteristics 

Women Men 

Sexual behavior characteristic 

Percentage 

HIV-positive Number 

Percentage 

HIV-positive Number 

CONGO 2009 

Number of sexual partners in last 12 months

0 5.7 506 1.0 248 

1 3.9 5,070 2.1 3,332 

2+ 4.3 440 2.4 1,613 

Missing * 2 * 3 

Concurrent sexual partners at 6 months before the survey1

Multiple, concurrent 2.4 168 3.3 558 

Multiple, non-concurrent 5.5 272 1.9 1,055 

Concurrent sexual partners anytime in past 12 months1

Multiple, concurrent 3.5 339 2.2 1,283 

Multiple, non-concurrent 7.0 101 3.1 331 

 

Total age 15-49 4.1 6,019 2.1 5,196 

LESOTHO 2009 

Number of sexual partners in last 12 months

0 28.4 418 12.6 287 

1 29.8 2,514 20.2 1,488 

2+ 39.4 261 23.8 651 

Missing (49.3) 46 (16.4) 41 

Concurrent sexual partners at 6 months before the survey1

Multiple, concurrent 42.5 95 29.9 229 

Multiple, non-concurrent 37.6 165 20.4 422 

Concurrent sexual partners anytime in past 12 months1

Multiple, concurrent 38.2 215 26.6 480 

Multiple, non-concurrent (45.1) 45 15.8 171 

 

Total age 15-49 30.7 3,239 20.2 2,468 

MALAWI 2010

Number of sexual partners in last 12 months

0 24.7 831 4.9 783 

1 12.7 5,262 9.7 4,137 

2+ 31.8 64 11.8 614 

Missing * 8 * 7 

Concurrent sexual partners at 6 months before the survey1

Multiple, concurrent * 13 10.9 248 

Multiple, non-concurrent (25.5) 51 12.4 366 

Concurrent sexual partners anytime in past 12 months1

Multiple, concurrent * 26 12.1 482 

Multiple, non-concurrent (26.6) 38 10.5 132 

 

Total age 15-49 14.5 6,166 9.3 5,541 

MOZAMBIQUE 2009

Number of sexual partners in last 12 months

0 15.6 663 7.9 187 

1 12.9 4,175 9.6 2,538 

2+ 23.1 164 11.1 777 

Missing nc 0 * 2 

Concurrent sexual partners at 6 months before the survey1

Multiple, concurrent (30.4) 41 10.6 351 

Multiple, non-concurrent 20.7 123 11.5 426 

Concurrent sexual partners anytime in past 12 months1

Multiple, concurrent 21.3 115 10.5 627 

Multiple, non-concurrent 27.4 49 13.7 149 

 

Total age 15-49 13.6 5,003 9.8 3,503 

Note: Figures in parentheses are based on 25-49 unweighted cases; an asterisk indicates that a figure is based on 

fewer than 25 unweighted cases and has been suppressed. nc = No cases 

1

 Restricted to those respondents with 2+ partners in the past 12 months 
20 

There is no theoretical basis for an association between an individual’s own HIV status and whether or not his or her 

sexual partnerships are concurrent, and Table 2 shows no consistent pattern between an individual’s HIV status and 

whether his/her multiple partners in the past 12 months were concurrent or sequential. The point and cumulative 

prevalence indicators do not always have the same direction of association with HIV status—across countries, 

within a country, or between women and men in the same country. 

Out of 16 comparisons of individuals with concurrent partners versus individuals with multiple non-concurrent 

partners (for point and cumulative prevalence indicators for men and women in four countries), 5 comparisons show 

higher HIV prevalence among those who had concurrent partners, 9 show higher HIV prevalence among those with 

multiple partners that were not concurrent, and 2 lack a sufficient number of cases on which to draw a conclusion. 

Several of these differences are likely to be within sampling error. 

4.3 Concurrent sexual partnerships and HIV status in couples 

If having concurrent sexual partnerships affects partners’ risk of HIV infection, it seems plausible that the data on 

couples available from DHS and AIS surveys would be useful in analyzing this association. Table 3 presents HIV 

prevalence according to the two indicators of concurrency, for cohabiting couples for whom an HIV test result was 

available. 

There are several limitations to using couples data for this type of analysis. These limitations include having 

information on HIV status for only the cohabiting partner rather than all sexual partners, and not knowing whether 

the concurrency behavior or the HIV infection came first. These limitations are described in greater detail in Section 

5 (see “Challenges in interpretation”). They make it difficult to determine what the expected relationship should be 

between concurrency and HIV status. 

Even if there were a clear expected association, the results in Table 3 show that in the four countries the number of 

cases in which women had concurrent sexual partners (by either definition) is too small to analyze. Thus, the only 

robust comparison to make is between couples in which neither member had concurrent partnerships and couples in 

which the man had concurrent partnerships and the woman did not. In both Congo and Lesotho, couples in which 

the man had concurrent sexual partners and the woman did not are less likely to have both partners be HIV-negative 

and more likely to have both partners be HIV-positive compared with couples in which neither partner had 

concurrent sexual partnerships. In Malawi and Mozambique, couples’ HIV status does not differ much by whether 

or not the members in the couple had concurrent partners. 
21 

Table 3. HIV prevalence among couples 

Percent distribution of couples living in the same household, both of whom were tested for HIV, by the HIV status, 

according to concurrent sexual partnership 

Concurrency 

Both HIVpositive 

Man HIVpositive, woman 

HIV-negative 

Woman HIVpositive, man 

HIV-negative 

Both HIVnegative Total Number 

CONGO 2009 

Concurrent sexual partners at 6 months before the survey

Both no 0.8 1.8 2.3 95.1 100.0 1,885 

Man yes, woman no 2.0 1.4 5.7 90.9 100.0 361 

Woman yes, man no * * * * 100.0 23 

Both yes * * * * 100.0 6 

Concurrent sexual partner in past 12 months

Both no 0.9 1.8 2.3 94.9 100.0 1,534 

Man yes, woman no 1.2 1.4 4.0 93.3 100.0 695 

Woman yes, man no (3.8) (8.6) (4.9) (82.7) 100.0 22 

Both yes * * * * 100.0 24 

Total 1.0 1.8 2.9 94.3 100.0 2,275 

LESOTHO 2009 

Concurrent sexual partners at 6 months before the survey

Both no 18.5 8.9 7.3 65.3 100.0 729 

Man yes, woman no 22.2 13.0 8.4 56.4 100.0 90 

Woman yes, man no * * * * 100.0 16 

Both yes * * * * 100.0 8 

Concurrent sexual partner in past 12 months

Both no 18.1 8.8 7.0 66.0 100.0 642 

Man yes, woman no 21.6 11.0 9.6 57.9 100.0 148 

Woman yes, man no (18.6) (12.2) (13.1) (56.1) 100.0 38 

Both yes * * * * 100.0 15 

Total 18.9 9.5 7.6 64.0 100.0 843 

MALAWI 2010 

Concurrent sexual partners at 6 months before the survey

Both no 6.4 4.6 3.6 85.4 100.0 3,208 

Man yes, woman no 5.2 5.5 4.8 84.5 100.0 245 

Woman yes, man no * * * * 100.0 4 

Both yes * * * * 100.0 4 

Concurrent sexual partner in past 12 months

Both no 6.3 4.4 3.7 85.6 100.0 3,060 

Man yes, woman no 6.1 7.0 3.7 83.2 100.0 387 

Woman yes, man no * * * * 100.0 10 

Both yes * * * * 100.0 4 

Total 6.3 4.7 3.8 85.3 100.0 3,462 

MOZAMBIQUE 2009

Concurrent sexual partners at 6 months before the survey

Both no 4.9 5.1 5.2 84.7 100.0 2,267 

Man yes, woman no 4.5 4.7 4.5 86.4 100.0 374 

Woman yes, man no * * * * 100.0 4 

Both yes * * * * 100.0 3 

Concurrent sexual partner in past 12 months

Both no 4.6 5.0 5.1 85.3 100.0 2,057 

Man yes, woman no 5.7 4.9 4.9 84.5 100.0 559 

Woman yes, man no (10.3) (17.2) (10.5) (62.0) 100.0 21 

Both yes * * * * 100.0 11 

Total 4.9 5.1 5.2 84.9 100.0 2,648 

Note: Table based on couples for which a valid HIV test result (positive or negative) is available for both partners. 

Figures in parentheses are based on 25-49 unweighted cases; an asterisk indicates that a figure is based on fewer 

than 25 unweighted cases and has been suppressed. 

23 

5. Challenges in Collecting, Tabulating, and Interpreting Indicators 

on Concurrent Sexual Partnerships

5.1 Challenges in collection 

There are several challenges in collecting the data needed to tabulate point and cumulative prevalence indicators. As 

mentioned, the data come from six questions about time since the respondent first and last had sexual intercourse 

with their sexual partners. Accurate classification of an individual’s concurrency status requires information for all 

of the partners to be internally consistent and externally valid. It is very difficult to assess the external validity of 

respondents’ answers. It is also a challenge to get internally consistent responses on up to six questions asking for 

information that is both sensitive to report and difficult to remember. 

Specific sources of bias or error include: 

Normative response bias: In many societies, having sexual partners before or outside of 

marriage is not an acceptable behavior, especially for women. Paid sex is also stigmatized. 

Respondents may choose not to report ‘socially undesirable’ sexual partners, which would lead to 

an underestimation of multiple partnerships and consequently of concurrency. 

Recall error: It may be difficult for respondents to accurately recall when they first had sex and 

last had sex with all of their sexual partners, especially for respondents with many partners. 

Interviewers are trained in how to probe respondents who say that they cannot remember. 

Nonetheless, some respondents will be unable (or in some cases unwilling) to report the needed 

information. In thinking about the care that is needed to obtain optimal information on the 

questions used to calculate concurrency, it is also important to keep in mind that these questions 

come from only one page of a very long and complex individual questionnaire. 

5.2 Challenges in tabulation 

Challenges in collecting data for the questions used to measure concurrency introduce two key issues in the process 

of tabulating the indicators: (1) the possibility of partners being recorded out of order; and (2) missing data. 

Problems in remembering time since first/last sex or preferential reporting of the spouse in the first column, even 

when he/she is not the last sexual partner, can result in partners being recorded out of order on the questionnaire. If 

the interviewer does not correct this error at the time of the interview, correct calculation of the cumulative 

prevalence indicator requires either that the partners be reversed during the data cleaning stage or that the logic used 

to tabulate the indicator accommodate the possibility that partners may be recorded out of order. Conditions 2 and 3 

shown in Figure 3 are included in the logic for cumulative prevalence of concurrency specifically to check for 

overlap in partners that are recorded out of order. However all conditions include an additional layer of complexity 

(two logic statements instead of one) to allow for correct classification of partnerships regardless of the order in 

which they are recorded in the questionnaire. 

The possibility of having missing data on any of the six questions also affects the logic that must be used to tabulate 

the cumulative prevalence indicator. Additional conditions must be included in order to catch all cases that can be 

identified as concurrent even when some of the questions have missing responses. There is redundancy in 

Conditions 1-4 (shown in Figure 4) in that the same pair of overlapping partners will satisfy two of the conditions 

when all four data points are present (that is, a, b, c, and d). The redundancy is required because each condition 

(except condition 5) is designed to work even if a specific data point is missing: 

Condition 1 still works when data point ‘a’ is missing and the partners are in order 

Condition 2 still works when data point ‘b’ is missing and the partners are out of order 

Condition 3 still works when data point ‘c’ is missing and the partners are out of order 
24 

Condition 4 still works when data point ‘d’ is missing and the partners are in order 

Conditions 6 and 7 capture overlapping sexual partnerships in special cases when data points ‘a’ 

and ‘c’ are missing, respectively

5.3 Challenges in interpretation 

There are several challenges in interpreting the concurrency data collected in DHS and AIS surveys. First, missing 

data and imprecise recording of timing of events (i.e., in completed units) prevent accurate classification of the 

concurrency status of some respondents. Second, low reported prevalence of concurrency, especially among women, 

limits the possibility of analyzing characteristics of respondents with concurrent partners. Third, the research design 

of cross-sectional population-based surveys such as the DHS and AIS is not appropriate to addressing many of the 

most salient questions regarding concurrency and the spread of HIV. 

Missing data and imprecise recording of timing. In many cases, missing data makes it impossible to classify two 

sexual partners as overlapping or not. For point prevalence of concurrency, missing data on first or last sex for a 

given partner sometimes makes it impossible to determine whether or not that partnership straddles the six-month 

cutoff. Such a partnership is treated as if it does not straddle the six-month cutoff. Thus, in some cases the missing 

data could result in an underestimation of concurrent partnerships. 

Missing data can also result in underestimation of the cumulative prevalence of concurrency. When time since last 

sex with the prior partner or time since first sex with the later partner is missing, it is impossible to determine 

whether or not the partners overlapped. 

Moreover, in cases where one partnership ended during the same day/week/month that another started, whether the 

earlier partnership ended before or after the later partnership started is ambiguous. As recommended by the 

UNAIDS Reference Group, such partnerships are classified as not concurrent; however, this assumption results in 

some underestimation of concurrency. This challenge is not easy to address: more precise accounting of time is not 

necessarily more accurate, and a directed question such as “Did you first have sex with [later partner] before or after 

you last had sex with [earlier partner]” is difficult for the respondent to understand and may be prone to normative 

response bias. 

Table 4 shows respondents for whom it cannot be determined whether or not they had concurrent sexual 

partnerships (according to the cumulative prevalence indicator) as a percentage of all respondents, and as a 

percentage of respondents who had multiple partnerships in the past 12 months. It appears that missing data and 

imprecision in the start and stop dates of partnerships do not have a large impact on the overall estimates of point 

and cumulative prevalence of concurrency. In each of the five countries, the number of cases with missing data or in 

which two partnerships end and begin during the same unit of time is low. Such cases account for well under 1 

percent of women in each of the five countries, less than 1 percent of men in Tanzania, Lesotho and Malawi, and 

less than 2 percent of men in Congo and Mozambique. 

Although the impact of missing data on the point prevalence indicator has not been assessed, we anticipate these 

issues in tabulation would have a similar impact on point prevalence of concurrency as on cumulative prevalence. 

In sum, respondents with undetermined concurrency status do not appear to have a strong impact on the point and 

cumulative prevalence indicators. For these indicators, the denominator includes all women and men interviewed. 

However, respondents with undetermined concurrency status have a more notable impact on the third concurrency 

indicator: proportion of multiple partnerships that are concurrent in the past year. The denominator in this indicator 

is restricted to individuals who had multiple partners in the past 12 months. In each of the five countries, 

concurrency status was uncertain for less than 7 percent of women and men with multiple partners, with the 

exception of women in Malawi. In Malawi, there are 18 women whose concurrency status (cumulative prevalence) 

could not be determined. As shown in Table 4, these 18 women make up only 0.1 percent of all women but make up 

14 percent of women with multiple partners, because the percentage of women with multiple partners in Malawi is 

low. 
25 

Table 4. Completeness of data 

Among all women and men, the percentage for whom concurrency status could not be determined from the available 

data; and among women and men with multiple partners in the past 12 months, the percentage for whom concurrency 

status could not be determined from the available data (unweighted)

Women Men 

Country 

Among all women 

Among women with 2+ 

partners in the past 12 

months Among all men 

Among men with 2+ 

partners in the past 12 

months 

% with 

concurrency 

status 

unknown 

Number of 

women 

% with 

concurrency 

status 

unknown 

Number of 

women 

% with 

concurrency 

status 

unknown 

Number of 

men 

% with 

concurrency 

status 

unknown 

Number of 

men 

Congo 0.3 6,550 5.7 388 1.5 5,863 5.1 1,763 

Lesotho 0.2 7,624 3.2 496 0.7 3,317 3.4 707 

Malawi 0.1 23,020 13.5 133 0.5 7,175 5.6 692 

Mozambique 0.1 6,413 4.9 183 1.4 4,799 6.8 971 

Tanzania 0.2 10,139 6.9 291 0.8 2,527 4.4 474 

Notes: Concurrency status is unknown for the cumulative prevalence indicator. Data for women for age 15-49 in 

Congo, Lesotho, Malawi and Tanzania, and age 15-64 in Mozambique. Data for men are for age 15-49 in Congo and 

Tanzania, age 15-54 in Malawi, age 15-59 in Lesotho and age 15-64 in Mozambique. In this table, respondents with 

concurrency status unknown include those with one partnership beginning at the same time that another ends and 

those for whom missing data made it impossible to determine whether or not any of the respondents’ partners were 

concurrent. 

Low reported prevalence. Low prevalence of reported concurrency is another factor that can impede analysis to 

identify factors associated with concurrency or to test for an association between HIV prevalence and concurrency. 

In Malawi, Mozambique and Tanzania, point prevalence is at or below 1 percent of the general population of 

women age 15-49. In Malawi, with a sample of over 20,000 women, there are only around 20 women classified as 

having concurrent sexual partnerships according to the point prevalence indicator. In Mozambique, with a sample of 

over 5,000 women, fewer than 50 women have concurrent partners according to the point prevalence indicator, and 

in Tanzania, with a sample of over 10,000 women, only around 100 women have concurrent sexual partners 

according to the point prevalence indicator. As Table 3 shows, low reported prevalence of concurrency among 

women and relatively low HIV prevalence in some countries results in low numbers of cases in much of the table. 

Research design. The final challenge to data interpretation is related to a mismatch between the research design 

employed in DHS and AIS surveys and the kind of research design that is best suited for answering questions about 

the association between concurrency and HIV transmission. This mismatch introduces limitations particularly in 

interpreting couples data. 

First, in testing the theoretical association between concurrency status of one member of a couple and the HIV status 

of the other member in the couple, it is important to know the order in which an individual and his or her partners 

became infected with HIV, but this information is not available from cross-sectional surveys. Consider for a moment 

John and Jane, a married couple. John began a concurrent partnership with Carol after he married Jane. At the time 

of the survey, all three are HIV-positive. Whether or not Jane’s HIV status has anything to do with John’s 

concurrent sexual partnership depends on which of John’s two partners was the source of his HIV infection. If Carol 

was infected first, and she transmitted the virus to John who then transmitted the infection to Jane, then John’s 

concurrent sexual partnership caused Jane’s infection. However, if Jane was infected first (i.e., before John), then 

Jane’s HIV status is unrelated to whether or not John had any concurrent sexual partnerships. In the data files, it is 

impossible to distinguish between those couples in which a concurrent sexual partnership introduced a ‘backward 

path’ for infection (i.e. from Carol to Jane) and thus posed additional risk for HIV transmission, and those couples in 

which a concurrent sexual partnership did not introduce a backward path. This limitation dilutes the association at 

the aggregate level between an individual’s practice of concurrency and his or her principle partner’s HIV status. It 

also presents a serious challenge for any research using couples as the unit of analysis. 

Second, DHS and AIS surveys cannot link sexual partners who live in separate households. In terms of the example 

above, the data can only link John with Jane. If Carol lives in a separate household, then she is most likely not in the 
26 

survey sample, but even if her household is included in the sample it is still impossible to link her with John. In 

order to make a meaningful association between concurrency and partners’ status, it is necessary to have the status 

of all of the partners. Assume that John ends his sexual partnership with Jane before beginning his sexual 

partnership with Carol. If Jane is the partner who infects John, then Carol is at increased risk of acquiring HIV. But 

if John acquires HIV from Carol, then Jane is at no increased risk of infection. On the other hand, if John has 

concurrent sexual partnerships with Jane and Carol, then Carol is still at risk if John is infected by Jane, just as she 

would be in the case of sequential relationships, but now Jane would be at risk of acquiring HIV if John is infected 

by Carol. For HIV-positive individuals, fewer of their sexual partners on average will be HIV-positive if none of 

their partnerships are concurrent than if any of their partnerships are concurrent, but it is necessary to have the HIVstatus of all of the partners in order to see this association. 
27 

6. Conclusions 

The indicators on point and cumulative prevalence of concurrent sexual partnerships were designed by the Working 

Group on Measuring Concurrent Sexual Partnerships, an ad hoc working group of the UNAIDS Reference Group on 

Estimates, Modeling and Projections. From the experience to date of the MEASURE DHS project with these 

indicators, we can conclude the following: 

1. Although the DHS and AIS questionnaires could be fairly easily modified to ask for the information needed 

to measure the recommended concurrency indicators, there are challenges to collect accurate data. 

The standard questionnaires required little adjustment to be able to provide the data needed to measure the three 

recommended indicators. Exactly the same questions are required to measure both point and cumulative prevalence 

indicators. However, there are challenges to collecting complete and correct data. Recall error, normative response 

bias, and the general sensitivity of asking about these kinds of sexual behaviors all impact data quality. Due to the 

nature of the data collection challenges, adding additional or more detailed questions is unlikely to greatly improve 

data quality. 

2. It is possible but challenging to calculate the three recommended indicators from the data collected in DHS 

and AIS surveys. 

Both point and cumulative prevalence of concurrency require complex calculations and a number of assumptions to 

be made. As illustrated in Section 3, the logic required to calculate the point prevalence indicator of concurrent 

sexual partnerships is somewhat simpler than the logic required to calculate the cumulative prevalence indicator. 

The data quality issues mentioned in conclusion 1 above, in addition to others detailed in Section 3, markedly 

complicate the process of calculating both indicators. 

3. DHS findings to date do not support recommending any one indicator over the others. 

The three indicators measure different aspects of concurrent sexual partnerships and have different interpretations. 

Point prevalence emphasizes long-term overlapping sexual partnerships, cumulative prevalence measures the total 

magnitude of overlapping sexual partnerships, and the final indicator provides information on the proportion of 

multiple partnerships that are concurrent. The UNAIDS Reference Group concluded that it is important to know all 

three of these things. The Reference Group made the point prevalence indicator the primary indicator because 

concurrency theory suggests that this may be the indicator most closely linked to HIV transmission; however, the 

empirical data remain inconclusive. In addition, point prevalence of concurrent sexual partners is always lower than 

cumulative prevalence, and there are often too few cases to allow further analysis. 

4. Data on both point prevalence and cumulative prevalence of concurrency are of limited analytical value in 

cross-sectional population-based surveys such as the DHS and AIS. 

Although data collected in DHS and AIS surveys can be used to calculate levels of concurrency, there are numerous 

limitations to how much the surveys can contribute to the body of evidence on the theorized association between 

concurrency and transmission of HIV. At the national level, DHS and AIS surveys can measure the association 

between prevalence of concurrent sexual partnerships and prevalence of HIV, but knowing the extent of this 

association is not very meaningful, as a stronger association is expected between HIV incidence and concurrency. At 

the level of respondents and their sexual partners, DHS and AIS surveys cannot be used to map sexual networks, and 

the DHS and AIS surveys do not have information on the HIV status or timing of infection of all of the respondent’s 

sexual partners. Moreover, the small numbers of women reporting concurrent sexual partnerships prevent drawing 

robust conclusions about concurrency and HIV in couples. 

29 

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