Articles

Eﬀect of a cash transfer programme for schooling on
prevalence of HIV and herpes simplex type 2 in Malawi:
a cluster randomised trial
Sarah J Baird, Richard S Garfein, Craig T McIntosh, Berk Özler

Summary
Background Lack of education and an economic dependence on men are often suggested as important risk factors for
HIV infection in women. We assessed the eﬃcacy of a cash transfer programme to reduce the risk of sexuallytransmitted infections in young women.
Methods In this cluster randomised trial, never-married women aged 13–22 years were recruited from 176 enumeration
areas in the Zomba district of Malawi and randomly assigned with computer-generated random numbers byenumeration area (1:1) to receive cash payments (intervention group) or nothing (control group). Intervention
enumeration areas were further randomly assigned with computer-generated random numbers to conditional (school
attendance required to receive payment) and unconditional (no requirements to receive payment) groups. Participantsin both intervention groups were randomly assigned by a lottery to receive monthly payments ranging from US$1 to$5, while their parents were independently assigned with computer-generated random numbers to receive $4–10.
Behavioural risk assessments were done at baseline and 12 months; serology was tested at 18 months. Participants
were not masked to treatment status but counsellors doing the serologic testing were. The primary outcomes wereprevalence of HIV and herpes simplex virus 2 (HSV-2) at 18 months and were assessed by intention-to-treat analyses.
The trial is registered, number NCT01333826.
Findings 88 enumeration areas were assigned to receive the intervention and 88 as controls. For the 1289 individuals
enrolled in school at baseline with complete interview and biomarker data, weighted HIV prevalence at 18 monthfollow-up was 1·2% (seven of 490 participants) in the combined intervention group versus 3·0% (17 of
799 participants) in the control group (adjusted odds ratio [OR] 0·36, 95% CI 0·14–0·91); weighted HSV-2 prevalence
was 0·7% (ﬁve of 488 participants) versus 3·0% (27 of 796 participants; adjusted OR 0·24, 0·09–0·65). In theintervention group, we noted no diﬀerence between conditional versus unconditional intervention groups forweighted HIV prevalence (3/235 [1%] vs 4/255 [2%]) or weighted HSV-2 prevalence (4/233 [1%] vs 1/255 [<1%]). For
individuals who had already dropped out of school at baseline, we detected no signiﬁcant diﬀerence between
intervention and control groups for weighted HIV prevalence (23/210 [10%] vs 17/207 [8%]) or weighted HSV-2
prevalence (17/211 [8%] vs 17/208 [8%]).

Published Online
February 15, 2012
DOI:10.1016/S01406736(11)61709-1
See Online/Comment
DOI:10.1016/S01406736(12)60036-1
The World Bank, Development
Research Group, Washington,
DC, USA (B Özler PhD);
Department of Medicine,
Division of Global Public Health(Prof R S Garfein PhD), andSchool of International
Relations and Paciﬁc Studies(C T McIntosh PhD), Universityof California at San Diego, San
Diego, CA, USA; andDepartment of Global Health,George Washington University,
Washington, DC, USA(S J Baird PhD)
Correspondence to:
Dr Berk Özler, The World Bank,
Development Research Group,
Washington, DC 20433, USAbozler@worldbank.org

Interpretation Cash transfer programmes can reduce HIV and HSV-2 infections in adolescent schoolgirls in lowincome settings. Structural interventions that do not directly target sexual behaviour change can be importantcomponents of HIV prevention strategies.
Funding Global Development Network, Bill & Melinda Gates Foundation, National Bureau of Economic Research
Africa Project, World Bank’s Research Support Budget, and several World Bank trust funds (Gender Action Plan,
Knowledge for Change Program, and Spanish Impact Evaluation fund).

Introduction
Two-thirds of HIV-infected people worldwide live in subSaharan Africa and 68% of new infections in adults occur
in the region.1 Women and girls are at particularly highrisk; 60% of people living with HIV in sub-Saharan Africa
are women. Furthermore, people aged 15–24 years
account for an estimated 45% of new infections worldwide.2 In this age group, women are more than twice as
likely to be infected than are men. In Malawi, HIVprevalence in 2007 was 9·1% in young women, comparedwith 2·1% in young men.3 Prevention of HIV in girls is
one of the most essential challenges to reach a turning
point in the epidemic.4

Schooling has been suggested to be a social vaccine toprevent the spread of HIV.5 Although cross-sectional data6,7
suggest a correlation between school attendance and HIV
status, only two studies8,9 have identiﬁed a possible causal
link between school attendance and reduced risky sexual
behaviour. Furthermore, although poverty, especiallypoverty of women, has been suggested as a major risk
factor for HIV, evidence is mixed.10–13 We are aware of only
one cluster randomised trial14 with biological outcomes ofa structural intervention to prevent HIV in women. The
Intervention with Microﬁnance for AIDS and Gender
Equity (IMAGE) study14 assessed a structural intervention
that combined a microﬁnance programme with a gender

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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and HIV training curriculum and showed no eﬀect on
HIV incidence. No studies causally link increased
schooling or income with a reduction in HIV risk.
However, this absence of clear and credible evidence is not
restricted to interventions in education or social protection.
A review of behaviour change interventions has shownthat “the reality that current behavior change interventions,by themselves, have been limited in their ability to control
HIV infection in women and girls in low- and middleincome countries”.15 No randomised controlled trial
assessing a behavioural intervention has shown asigniﬁcant eﬀect on HIV incidence.16
Conditional cash transfer programmes aim to reduce
current poverty and, by investment in the education ofchildren, future poverty. As such, they have been popularin development economics since the late 1990s,
especially in Latin America.17,18 The programmes provide
cash transfers to poor households with school-aged
children (generally aged 6–18 years), often with therequirement that the children attend school regularly.
Conditional cash transfer programmes can be an
important component of social protection policy andevidence suggests that they have improved the lives ofpoor people.19
Because conditional cash transfer programmes increasehousehold income and school enrolment, they areparticularly suitable for investigation of the importanceof education and poverty as risk factors for HIV. We
assess the eﬀectiveness of cash transfers in Malawi for
reduction of the risk of HIV and herpes simplex virus
type 2 (HSV-2) infections in never-married girls aged
13–22 years.

Methods
Study design and participants
We undertook this cluster randomised trial in Zomba
district, which like most of southern Malawi ischaracterised by poverty, low school enrolment, and ahigh prevalence of HIV.3,20 Zomba district contains
550 enumeration areas deﬁned by the National
Statistical Oﬃce of Malawi. Each enumeration area
contains an average of 250 households spanning several
villages. Zomba city includes 50 enumeration areas; theEligibility criteria

remaining 500 are in seven traditional authorities.
Before the start of the trial we selected 176 enumeration
areas from three diﬀerent geographical strata: urban(Zomba city, 29 enumeration areas), near rural (<16 km
from Zomba city, 119 enumeration areas), and far rural(≥16 km from Zomba city, 28 enumeration areas). The
use of a 16 km radius was arbitrary and based mainlyon transport costs. Of the 50 enumeration areas inZomba city, 21 were excluded on the basis of advice
from local experts who deemed these areas to be too
aﬄuent for the proposed intervention. In each of thetwo rural strata, with the exception of one traditional
authority that was unsafe for ﬁeld work, the study
enumeration areas were randomly selected from all
enumeration areas.
In the 176 sampled enumeration areas, each dwelling
was visited to take a census of all never-married girls
aged 13–22 years, which was used to deﬁne two cohorts:
those enrolled in school at baseline (baseline schoolgirls),
and those not enrolled in school at baseline (baseline
dropouts). Because of their small number (about ﬁve
per enumeration area), all eligible baseline dropouts
were sampled to participate in the overall study. In thecohort of baseline schoolgirls, a subset of eligible
individuals was randomly selected for the study. The
sampling percentages for this cohort diﬀered bygeographical stratum and age group and varied from
14% to 45% in urban areas and 70% to 100% in rural
areas. This sampling procedure yielded a baseline study
sample of 4051 individuals of whom 3796 (94%) wereenrolled and completed a baseline interview at the endof 2007. Of these study participants, 889 were baseline
dropouts and 2907 were baseline schoolgirls. Table 1
shows eligibility criteria.
All participants provided written informed consent. We
obtained additional consent from parents or legal
guardians of all unmarried girls younger than 18 years.
Informed consent for HIV, HSV-2, and syphilis testing
was obtained separately at the time of specimen
collection. The study design was approved by ethics
review committees at the National Health Sciences
Research Council (Malawi) and the University ofCalifornia at San Diego (USA).

Household survey follow-up criteria

Voluntary counselling and testing follow-up

Intervention enumeration areas

Control enumeration areas

N

PeriodCriteria(months)

PeriodCriteria(months)

Baselineschoolgirls

Enrolled in school at baseline;
eligible to return to standard 7 toform 2*

Enrolled in school at baseline;
eligible to return to standard 7 toform 22907

12

All individuals successfullyinterviewed at baseline

18

Randomly selected subsample of baseline
participants successfully interviewed insecond household survey

Baseline
dropouts

Not enrolled in school at baseline

Not enrolled in school at baseline

889

12

All individuals successfullyinterviewed at baseline

18

Randomly selected subsample of baseline
participants successfully interviewed insecond household survey*Primary school year groups in Malawi are from standard 1 to standard 8 (generally for children aged 6–13 years); secondary school year groups are from form 1 to form 4 (generally for children aged 14–17 years).

Table 1: Eligibility and follow-up criteria

2

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

Articles

88 treatment enumeration areas
15 no cash
Cohort 1(baseline schoolgirls)

Within-village
control

Cohort 2(baseline dropouts)

Conditionaltransfer

88 control
enumeration areas

27 unconditional
Unconditionaltransfers

46 conditional

Within-village
control

Conditionaltransfers

Conditional transfer

Within-village
control

Conditional transfer

No transfer

No transfer

88 conditional enumeration areas
Groups used in the analysis

Figure 1: Intervention groups

Randomisation and masking
After baseline surveys were completed, the 176 geographic enumeration areas were randomly assigned(1:1) to intervention (cash transfer programme) orcontrol groups (no programme). To reduce thepossibility of crossover from the intervention group to
the control group, participants were assigned to trial
groups on the basis of the random assignment of theenumeration areas that they lived in. Randomisation
within each geographical stratum ensured the assignment of equal proportions of enumeration areas from
Zomba city, near rural, and far rural areas in theintervention and control groups. Within each of thethree geographical strata, enumeration areas wereassigned numbers from a computer-generated list of
random numbers (with Stata, version 9.2). Each of thethree lists of enumeration area identiﬁcation numbers
were sorted in ascending order and the enumeration
areas in the ﬁrst half of the list were assigned to theintervention group and the rest were assigned to thecontrol group.
To assess whether any eﬀects were simply due toincreased household income baseline schoolgirls fromthe enumeration areas in the intervention group were
further randomly assigned with computer-generated
random numbers to one of two groups: one received
conditional cash transfer oﬀers and the other unconditional
cash transfer oﬀers. Baseline dropouts were assigned toreceive conditional cash transfer oﬀers in all intervention
enumeration areas irrespective of the treatment status of
the baseline schoolgirls within those areas.
To measure potential eﬀects of the programme on
untreated schoolgirls in treatment enumeration areas,
the percentage of baseline schoolgirls invited toparticipate in the cash transfer programme in theintervention enumeration areas was randomly assignedwith computer-generated random numbers to be equal
to 0% (15 enumeration areas), 33% (15 conditional
cash transfer enumeration areas, nine unconditional cashtransfer enumeration areas), 66% (16 conditional
cash transfer enumeration areas, nine unconditional cashtransfer enumeration areas), or 100% (15 conditional
cash transfer enumeration areas, nine unconditional cashtransfer enumeration areas). In the 15 intervention
enumeration areas where this share was 0%, no baselineschoolgirls were oﬀered cash transfers, meaning that the
only spillover of baseline schoolgirls would be from thebaseline dropouts who were oﬀered conditional cashtransfers (ﬁgure 1). Analysis of secondary outcomes withthe 12 month follow-up survey data, such as school
enrolment, marriage and pregnancy, and sexual
behaviour, showed no eﬀects in this group of participants
who did not receive cash transfer oﬀers despite living inintervention enumeration areas (data not shown), andbiological data were not collected from these study
participants at the 18 month follow-up. Therefore, we did
not include this group of 623 girls in the analysis of direct
programme eﬀects on HIV and HSV-2. The remaining
1225 sampled individuals in the 88 intervention
enumeration areas (789 baseline schoolgirls and436 baseline dropouts) were invited to participate in the
cash transfer programme.
Codes for randomisation of the enumeration areas
into trial groups, and for random assignment ofbaseline schoolgirls to participate in the cash transfer
programme in the cash transfer enumeration areas,
were written by one of the study investigators (SJB).
These programmes were run by the programme ﬁeld
manager with Stata (version 9.2). The resultant
enumeration area identiﬁcation numbers and basic
information about individuals selected to participate in
the cash transfer programme in each intervention
enumeration area were then provided to study staﬀ,
who enrolled participants.
Study participants were not masked to their assignment,
but did not know what the comparison groups were
because they were assigned at the enumeration arealevel. Trained counsellors who did home-based
counselling and rapid testing for HIV, HSV-2, andsyphilis were masked to the participant’s group. Statisticalanalyses were done by the investigators who were notmasked to the treatment status of the participants.
However, the analysis was done according to the research
design of primary outcomes, comparison groups, andcovariates (age group and geographical strata) used for
regression analysis. Because the primary outcomes werewww.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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measurable and objective (HIV and HSV-2 test results)
and regression adjustments were small, bias in analyses
due to no masking was reduced.

Procedures

See Online for webappendix

Panel 1 shows key features of the intervention design.
Participants in the conditional cash transfer group received
oﬀers of monthly cash transfers dependent on regularschool attendance during the previous month. In theunconditional cash transfer group, the oﬀers were identical
except that school attendance was not required. Participantsin the control group received nothing. The intervention issummarised in the webappendix and described in detailelsewhere.21 No other cash transfer programme existed in
Zomba district before or during the study.
The primary outcomes were the prevalences of HIV
and HSV-2 at 18 months, which were collected by homebased voluntary counselling and testing (VCT).
Secondary outcomes included syphilis prevalence,school enrolment, self-reported marriage, pregnancy,
sexual behaviour, and knowledge of HIV/AIDS. Data forthe behavioural outcomes were collected at both baseline
and 12 month follow-up (webappendix). We expectedthat school enrolment and HIV awareness would
increase as a result of the intervention and that rates ofmarriage, fertility, and sexual activity would decrease.
Data for biological outcomes were collected at followup at 18 months in 104 randomly selected enumeration
areas with computer-generated random numbers. A
detailed description of the VCT protocols is provided in
the webappendix. Cost of voluntary counselling andStatistical analysis

Panel 1: Intervention details
Intervention
The Zomba cash transfer programme took place between January, 2008, andDecember, 2009. In both years, transfers were made on a monthly basis for a total often transfers per year.
Treatment groups
In the conditional group (baseline schoolgirls and baseline dropouts), each payment wasreceived if the girl attended school for 80% of the days that school was in session during
the previous month.
In the unconditional group (baseline schoolgirls only) payment was received if the girlattended the cash transfer points.
Split
Cash transfers split between guardian and girl.
Amounts
Household amount varied randomly (by use of computer-generated random numbers) byenumeration area, with monthly values of US$4, $6, $8, or $10. Girl amount varied
randomly between individuals, with monthly values of $1, $2, $3, $4, or $5, decided bydrawing numbers from an envelope.
Programme eﬀects on untreated girls in treatment areas
Within treatment enumeration areas, a random subsample of baseline schoolgirls was
not treated. The size of the subsample ranged from 0% to 100% per enumeration area.

4

testing was the main reason to reduce the number ofenumeration areas in which biological data werecollected. We expected that the intervention would
reduce prevalence of HIV and HSV at follow-up. All
behavioural and biological endpoints were pre-speciﬁed.
Biological data were not collected at baseline for two
reasons. First, because HIV testing in Malawi was fairlyrare at the start of our study (fewer than one in ﬁve
baseline schoolgirls in control enumeration areas had
ever been tested for HIV at baseline), and learning
one’s HIV status could change subsequent school
enrolment decisions, we decided that HIV testing atbaseline would have precluded the assessment of theeﬀect of only the cash transfer programme on school
enrolment and self-reported risk behaviours at
12 months.22,23 Second, one of the primary aims of thestudy was to assess whether an intervention that aimed
to increase school attendance could indirectly decrease
exposure to HIV. To achieve this aim, the study
participants could not think that the cash transfers wereintended to reduce risky sexual behaviour and HIV orthat they were tied to good behaviour in terms of sexual
activity. Therefore, we judged that rapid testing atbaseline would likely constitute a separate intervention
and make it harder to argue that the study ﬁndings
would be valid for a standard conditional cash transfer
programme that promotes schooling exclusive of HIV
counselling and testing. Thus, biological data were only
measured 6 months after the 12 month follow-up
surveys, but while the cash transfer programme wasstill ongoing.

Power calculations were done to establish the number ofenumeration areas (and the number of participants ineach enumeration area) needed to detect signiﬁcantdiﬀerences in school enrolment with 90% conﬁdence
and 80% power. Optimal Design software24 was used for
power calculations to account for the study’s randomised,cluster design that aimed to assess eﬀects for continuousand binary outcome variables. Separate power calculations were done for programme eﬀects on HIV. With
the assumption of a 4% prevalence (on the basis ofanalysis of data for unmarried women younger than
25 years in southern Malawi3) in baseline schoolgirls in
the 52 control enumeration areas selected for collectionof biological data, and with a 95% CI and an 80% power
for analysis of the intervention’s eﬀect on HIV prevalence,
we selected a sample size that would allow us to detect atleast a 66% decreased HIV prevalence (2·3 percentage
points) in the combined conditional and unconditional
cash transfer programme groups versus the group
receiving no cash transfers. The minimum detectableeﬀect size was higher (3 percentage points) for eachintervention group separately than for the control group
because of the fewer clusters. The study was not powered
to detect eﬀects on HIV prevalence in baseline dropouts

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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550 enumeration areas in Zomba

Enrolment

176 randomly selected4051 eligible individuals sampled
3796 successfully interviewed
255 refused

88 enumeration areas allocated to intervention(n=1848)

88 enumeration areas allocated to control(n=1948)

15 enumerationareas
201 participants not
oﬀered cash

436 baseline
dropouts(cohort 2)

1495 baselineschoolgirls(cohort 1)

453 baseline
dropouts(cohort 2)

46 enumeration areas (conditional)
15 with 33% of participants oﬀered cash
16 with 66% of participants oﬀered cash
15 with 100% of participants oﬀered cash

88 enumeration
areas
436 participants
oﬀered cash

88 enumeration
areas
1495 control

88 enumerationareas
453 control

283 participants
oﬀered cash

506 participants
oﬀered cash

40 participants
lost tohouseholdsurveyfollow-up
1 died3 refused
36 not locatedat follow-up

89 participants
lost tohouseholdsurveyfollow-up
1 died13 refused
75 not locatedat follow-up

46 participants
lost tohouseholdsurveyfollow-up
1 died3 refused
42 not locatedat follow-up

243 participants
not oﬀered
cash

179 participants
not oﬀeredcash

26 participants lost to household survey
follow-up
1 died1 refused
24 not located at follow-up

27 enumeration areas chosen for biologicaltesting (n=265)

25 enumeration areas chosen for biologicaltesting (n=236)

52 enumeration
areas chosen
for biologicaltesting (n=226)

52 enumeration
areas chosen
for biologicaltesting (n=827)

52 enumeration
areas chosen
for biologicaltesting (n=223)

10 participants lost to follow-up
8 refused
2 not located at follow-up

1 participant lost to follow-up
1 not located at follow-up

16 participants lost
to follow-up
1 died11 refused
4 not locatedat follow-up

28 participants lost
to follow-up
1 died20 refused
7 not locatedat follow-up

16 participants lost
to follow-up
12 refused
4 not locatedat follow-up

27 enumeration areas analysed
255 participants successfully tested

25 enumeration areas analysed
235 participants successfully tested

52 enumeration
areas analysed
210 successfully
tested52 enumeration
areas analysed
799 successfully
tested52 enumeration
areas analysed
207 successfully
testedAnalysis

18 participants lost to household survey
follow-up
1 died17 not located at follow-up

Follow-up

27 enumeration areas (unconditional)
9 with 33% of participants oﬀered cash
9 with 66% of participants oﬀered cash
9 with 100% of participants oﬀered cash

Allocation

1412 baselineschoolgirls(cohort 1)

Figure 2: Trial proﬁleor heterogeneity of eﬀects between the conditional andunconditional cash transfer programme groups.
We assessed, by intention to treat analysis, whether
study outcome measures diﬀered between theintervention (conditional and unconditional cashtransfer programmes combined) and control groups;
we analysed separately baseline schoolgirls and baseline
dropouts. We also tested heterogeneity of programme
eﬀects on the prevalence of HIV and HSV-2 in theconditional and unconditional cash transfer groups bywww.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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cash transfer size. We calculated unadjusted odds ratios(ORs) by ﬁtting logistic regression models to individual
follow-up data with treatment status as the only
independent variable. We calculated robust standard
errors, allowing for intracluster correlation. We usedsampling weights to account for the fact that theprobability of inclusion in the study varied by age andenumeration area geographical stratum. We calculated
adjusted ORs with the same regression model withbinary indicators for age (13–14 years vs 15–22 years)
and geographical location as additional independent
variables. Adjustments for baseline values wereControl group

Enumeration areas sampled forbiological data collection

Intervention group
PooledConditional
cash transfer
programme

Unconditional
cash transfer
programme

52

52

25

27

Baseline schoolgirls
Number of individuals

827

501

236

265

Ever had sexual intercourse

182 (19%)130 (22%)70 (22%)60 (22%)

Ever pregnant

21 (3%)

16 (3%)

9 (3%)

7 (3%)

Age (years)

15·3 (1·9)

15·1 (1·9)

14·9 (1·8)

15·4 (1·9)

Age at sexual debut (years)

15·7 (1·7)

15·8 (1·8)

15·7 (2·0)

15·9 (1·7)

Highest grade attended

7·6 (1·6)

7·4 (1·7)

7·1 (1·7)

7·9 (1·6)

Mother alive

707 (85%)423 (84%)

198 (85%)

222 (83%)

Father alive

601 (74%)367 (75%)

176 (74%)191 (76%)

Female-headed household

275 (32%)141 (25%)

63 (26%)78 (24%)

Household owns a radio

479 (59%)309 (58%)

143 (53%)

166 (65%)

Household owns a television

130 (24%)110 (30%)40 (27%)70 (34%)

Household has access to a mobile
telephone464 (61%)303 (60%)145 (60%)

158 (61%)

Electricity available in dwelling

86 (20%)80 (26%)31 (28%)49 (24%)

Piped water available in dwelling

277 (47%)183 (49%)

48 (41%)135 (60%)

Number of individuals

223

226

··

··

Ever had sexual intercourse

151 (68%)

154 (68%)····

Ever pregnant

98 (44%)90 (40%)····Age (years)

17·6 (2·2)

16·8 (2·4)····

Age at sexual debut (years)

16·4 (1·8)

15·9 (2·2)····

Highest grade attended

6·2 (2·9)5·8 (2·9)

··

··
··

Baseline dropouts

Mother alive

175 (78%)

180 (80%)··

Father alive

146 (66%)

144 (65%)····

Female-headed household

93 (42%)90 (39%)····Household owns a radio

118 (53%)

107 (47%)····

Household owns a television

16 (7%)

24 (11%)····

Household has access to a mobile
telephone

103 (46%)110 (49%)····

Electricity available in dwelling

16 (7%)

24 (11%)····

Piped water available in dwelling

64 (29%)63 (25%)····

Data are n (weighted %) or mean (SD). Sampling weights were used to account for variation in the probability ofinclusion in the study according to age and stratum. All baseline dropouts received the conditional cash transfer
intervention irrespective of the treatment status of baseline schoolgirls in their enumeration areas; thus, theconditional and unconditional cash transfer columns are not applicable to this cohort.

Table 2: Baseline characteristics of participants

6

included for behavioural outcome measures. Stata(version 10.1) was used for the statistical analyses. The
trial is registered, number NCT01333826.

Role of funding source
The sponsors of the study had no role in study design,
data collection, analysis, and interpretation, or writing of
the report. BÖ, SJB, and CTM had full access to all thedata, and had ﬁnal responsibility for the decision tosubmit the report for publication.

Results
Figure 2 shows the trial proﬁle. At baseline 3796 individuals were successfully interviewed. Although 133 (7%)
baseline schoolgirls and 86 (10%) baseline dropouts werelost to follow-up at 12 months, none of the enumeration
areas had complete loss to follow-up. Rates were similar at
the 18-month visit (ﬁgure 2). Of the 1777 individuals
selected for biological testing, 71 (4%) were lost to followup because of either refusal to get tested (n=51) or not
being located by the data collection teams (n=20). The
number of participants lost to follow-up at 18 months did
not diﬀer signiﬁcantly between the intervention andcontrol groups (ﬁgure 2). All analyses of intervention
eﬀects on primary outcomes were done only in the1706 individuals with both 12 month follow-up survey data
and 18 month biomarker data. Table 2 shows the baselinecharacteristics of the participants selected for biological
data collection for each cohort. Baseline characteristics in
the intervention and control groups were similar (table 2).
In the cohort of baseline schoolgirls, weighted
prevalence of HIV was 1·2% (seven of 490) in the
combined intervention group versus 3·0% (17 of 799) inthe control group at 18 month follow-up (adjusted
OR 0·36, 95% CI 0·14–0·91; table 3). Weighted HSV-2
prevalence was 0·7% (ﬁve of 488) in the intervention
group versus 3·0% (27 of 796) in the control group (0·24,
0·09–0·65; table 3). Self-reported sexual activity at
12 month follow-up was signiﬁcantly lower in theintervention group for intercourse at least once a weekwith at least one partner, and for having a sexual partner
aged 25 years or older (table 3). Individuals in theintervention group were also more likely to be enrolled inschool during the 2008 school year than were those incontrol enumeration areas (table 3). The adjusted point
estimates for the likelihood of marriage, pregnancy,
sexual debut, and intercourse without consistent use of
condoms with at least one partner did not diﬀer
signiﬁcantly between intervention and control groups.
Intervention and comparison groups did not diﬀer
signiﬁcantly at follow-up for the prevalence of syphilis,
HIV knowledge, having had an HIV test, or having
received any health training about HIV/AIDS (table 3).
For baseline dropouts, although school re-enrolment
was substantially higher and the likelihood of having beenmarried at 12 month follow-up was lower in the intervention
group than in the comparison group, the prevalence of

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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Baseline

Follow-up

Intervention group Control group

Intervention group Control group

Unadjusted odds
ratio (95% CI)

Adjusted odds
ratio (95% CI)

Baseline schoolgirls
Enrolled during 2008 school year····

419/484 (90%)

669/801 (84%)

1·67 (1·09–2·56)

1·62 (1·07–2·45)

Ever married

0/501 (0%)

0/827 (0%)

19/501 (3%)

45/827 (4%)

0·63 (0·31–1·28)

0·68 (0·37–1·28)

Currently pregnant

3/501 (<1%)

2/827 (<1%)

15/501 (3%)

35/827 (4%)

0·66 (0·33–1·30)

0·71 (0·35–1·41)

Sexual debut*····

39/371 (8%)

100/645 (13%)

0·59 (0·33–1·05)

0·64 (0·38–1·07)

Had unprotected sexual intercourse

91/500 (16%)

107/825 (11%)

49/500 (8%)

63/826 (7%)

1·28 (0·78–2·09)

1·08 (0·67–1·75)

Had sexual intercourse once per week

16/500 (3%)

22/825 (2%)

22/299 (3%)

62/826 (7%)

0·44 (0·23–0·85)

0·46 (0·26–0·82)

4/502 (<1%)

20/827 (3%)

0·20 (0·07–0·59)

0·21 (0·07–0·62)

Had an HIV test

Had a sexual partner aged ≥25 years†

121/501 (22%)

174/827 (19%)

307/501 (54%)

470/826 (52%)

1·12 (0·74–1·68)

1·18 (0·83–1·69)

Knows that a healthy looking person
can have HIV

443/501 (88%)

752/827 (90%)

454/501 (91%)

768/826 (92%) 0·94 (0·58–1·53)

1·00 (0·61–1·62)

Knows that HIV can be transmitted
through breastfeeding466/500 (93%)

785/827 (95%)

481/501 (97%)

786/827 (96%)

1·70 (0·84–3·43)

1·72 (0·89–3·34)398/501 (78%)

657/827 (80%) 0·89 (0·61–1·30)

0·90 (0·63–1·30)

Received health training about
HIV/AIDS†

··

··

··

··

HIV prevalence†,‡····

7/490 (1%)

17/799 (3%)

0·39 (0·15–1·02)

0·36 (0·14–0·91)

HSV-2 prevalence†,‡····

5/488 (<1%)

27/796 (3%)

0·23 (0·08–0·66)

0·24 (0·09–0·65)

Syphilis prevalence†,‡····

1/491 (<1%)

4/800 (<1%)

1·20 (0·15–9·68)

0·92 (0·12–6·85)
8·77 (5·08–15·1)

Baseline dropouts
Enrolled during 2008 school year····

124/219 (57%)

27/220 (12%)

9·31 (5·31–16·3)Ever married

0/226 (0%)

0/223 (0%)

37/226 (17%)

64/223 (29%)

0·50 (0·29–0·83)

0·48 (0·29–0·80)

Currently pregnant

11/226 (5%)

10/223 (5%)

16/226 (7%)

26/223 (12%)

0·59 (0·28–1·25)

0·55 (0·27–1·13)

18/72 (26%)

27/72 (38%)

0·57 (0·28–1·16)

0·70 (0·34–1·45)

Had unprotected sexual intercourse

Sexual debut*

133/222 (61%)

128/223 (57%)

59/225 (25%)

64/222 (29%)

0·75 (0·46–1·22)

0·74 (0·44–1·23)

Had sexual intercourse once per week

31/222 (14%)

28/223 (13%)

43/225 (19%)

66/223 (30%)

0·56 (0·34–0·91)

0·53 (0·32–0·86)

Had a sexual partner aged ≥25 years†····

20/225 (8%)

23/223 (10%)

0·73 (0·40–1·34)

0·79 (0·42–1·50)

Had an HIV test

98/225 (43%)

104/223(47%)

163/225 (72%)

169/223 (76%)

0·84 (0·51–1·38)

1·00 (0·64–1·57)

Knows that a healthy looking person
can be infected with HIV

198/225 (88%)

201/223 (90%)

204/226 (90%)

212/223 (95%)

0·45 (0·19–1·05)

0·51 (0·23–1·15)

Knows that HIV can be transmitted
through breastfeeding

198/223 (89%)

210/223 (94%)

213/226 (94%)

214/223 (96%) 0·63 (0·25–1·56)

0·69 (0·26–1·81)··

130/226 (57%)

94/223 (42%)

1·91 (1·29–2·83)

Received health training about
HIV/AIDS†

··

··

··

1·82 (1·23–2·69)

HIV prevalence†,‡····

23/210 (10%)

17/207 (8%)

1·30 (0·69–2·48)

1·37 (0·72–2·61)

HSV-2 prevalence†,‡····

17/211 (8%)

17/208 (8%)

0·99 (0·46–2·10)

1·03 (0·47–2·23)

Syphilis prevalence†,‡····

3/211 (2%)

2/208 (1%)

1·59 (0·27–9·50)

1·63 (0·27–9·95)

Data are n/N (weighted %) unless otherwise stated. Sampling weights were used to account for variation in the probability of inclusion in the study according to age andstratum. Adjusted odds ratios calculated with a logistic regression model of individual data with independent variables that include treatment status, age group, indicatorsfor near rural and far rural strata, and baseline measure unless otherwise stated. HSV=herpes simplex virus. *Cumulative risk measure, so no adjustment made for baseline
status. †No adjustment for baseline measure because data not collected at baseline. ‡Measured at 18 months, all others were measured at 12 months.

Table 3: Eﬀects of cash transfer intervention on outcome measures

HIV or HSV-2 did not diﬀer signiﬁcantly between the twogroups (table 3). For self-reported sexual activity at 12 monthfollow-up, only intercourse at least once a week with atleast one partner was signiﬁcantly lower in the intervention
group than in the control group (table 3).
Table 4 shows programme eﬀects separately in theconditional and unconditional cash transfer programmegroups, calculated with a subset of the outcomes included
in table 3. These comparisons were of smaller treatmentgroups and therefore have less statistical power to detecteﬀects for each of these intervention groups. Althoughsome outcomes were signiﬁcantly diﬀerent comparedwith the control group in the conditional cash transfergroup (HIV prevalence and had a sexual partner aged
25 years or older) and others in the unconditional transfergroup (currently pregnant, had sexual intercourse once
per week, and HSV-2 prevalence; table 4), only forcurrently pregnant do treatment eﬀects diﬀer signiﬁcantly
between the two intervention groups (table 4). In separate
tests, we also analysed heterogeneity in programme
eﬀects on the prevalence of HIV, HSV-2, and syphilis bytransfer size. The treatment eﬀect did not vary by the

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

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UCT vs control(adjusted odds
ratio [95% CI])

Heterogeneityof odds ratios*(p value)

2·08 (1·14–3·82)

1·22 (0·77–1·96)

0·14

0·93 (0·47–1·86)

0·36 (0·12–1·07)

0·11

Control group

CCT group

UCT group

Enrolled during the 2008 school year

669/801 (84%)

207/229 (92%)

212/255 (87%)

Ever married

45/827 (4%)

14/236 (4%)

5/265 (2%)

Currently pregnant

35/827 (4%)

13/236 (4%)

2/265 (1%)

1·17 (0·56–2·43)

0·16 (0·04–0·68) 0·0121

Sexual debut†

100/645 (13%)

18/166 (7%)

21/205 (10%)

0·58 (0·29–1·15)

0·72 (0·37–1·40)

Unprotected sexual intercourse

63/826 (7%)

30/235 (9%)

19/265 (8%)

1·17 (0·67–2·05)

0·96 (0·50–1·83) 0·59

Had sexual intercourse once per week

62/826 (7%)

14/235 (3%)

8/264 (3%)

0·53 (0·26–1·07)

0·37 (0·16–0·85)

Had a sexual partner aged ≥25 years‡

20/826 (3%)

1/235 (<1%)

3/265 (1%)

0·08 (0·01–0·60)

0·36 (0·11–1·19)

0·19

HIV prevalence‡

17/799 (3%)

3/235 (1%)

4/255 (2%)

0·29 (0·09–0·98) 0·47 (0·14–1·59)

0·57

HSV-2 prevalence‡

27/796 (3%)

4/233 (1%)

1/255 (<1%)

0·37 (0·13–1·03)

0·08 (0·01–0·58) 0·16

Syphilis prevalence‡

4/800 (1%)

1/235 (1%)

0/256 (0%)

1·37 (0·20–9·41)

Undeﬁned

CCT vs control(adjusted odds
ratio [95% CI])

0·62
0·49

··

Data are n/N (weighted %) unless otherwise stated. Adjusted odds ratios calculated with a logistic regression model of individual data with independent variables that include
treatment status, age group, indicators for near rural and far rural strata, and baseline measure unless otherwise stated. Sampling weights were used to account for variationin the probability of inclusion in the study according to age and stratum. HSV=herpes simplex virus. CCT=conditional cash transfer. UCT=unconditional cash transfer. *Waldtest of equality of adjusted odds ratios for the conditional and unconditional cash transfer interventions. †Cumulative risk measure, therefore no adjustment made forbaseline status. ‡No adjustment for baseline measure because data not gathered at baseline.

Table 4: Eﬀect of conditional or unconditional cash transfers on baseline schoolgirls by outcome measuresamount of cash transfers oﬀered to programmeparticipants (data not shown).

Discussion
The cash transfer programme decreased the prevalencesof HIV and HSV-2 infection after 18 months in girls aged
13–22 years who were enrolled in school at baseline.
These eﬀects are supported by changes in self-reported
sexual behaviour; we detected no eﬀects on age of sexual
debut or unprotected sex, but individuals in theintervention group chose younger partners than did
those in the control group and sexual activity was lessfrequent with those partners.
Few randomised controlled trials have assessed
behavioural interventions with biological outcomes, andnone have recorded a signiﬁcant eﬀect on HIV(panel 2).16 Our trial shows that an intervention without
direct focus on sexual behaviour change can lead tomeaningful reductions in HIV and HSV-2 infections. The
cluster randomised study design ensured that crossover
between treatment groups was minimised, and the datacollected for a wide range of self-reported behavioural
measures allowed us to verify and contextualise eﬀects on
biological outcomes. The percentage of study participants
lost to follow-up did not diﬀer between control,
conditional, and unconditional groups, and was lower
than that reported in similar studies.25
Our study had some limitations. The absence ofbaseline data for HIV and HSV-2 makes comparison ofincidences between trial groups impossible. Thus, theprogramme eﬀects on the 18 month prevalences of these
infections are subject to scrutiny. However, several factors
increase our conﬁdence in the ﬁndings. First, participantsin the intervention and control groups had similar
characteristics at baseline. Although residual confounding due to unmeasured factors could have caused
8

spurious ﬁndings, the balance across several baselinevariables known to be associated with HIV infection
makes this scenario unlikely. Second, block randomisation
by geographical stratum helps to prevent bias that might
be caused by diﬀerences in the underlying prevalence of
HIV.26 Third, the diﬀerences in biological outcomes
between trial groups at follow-up are supported bychanges in behavioural factors. Thus, the reported
diﬀerences in the prevalences of HIV and HSV-2 arelikely to be real rather than a result of selection bias.
The low event rate for biological outcomes, especiallyfor HIV infection (seven in the combined intervention
group vs 17 in the comparison group), means that the
programme eﬀects should be interpreted with caution.
Furthermore, the study was not powered to detect
heterogeneity of eﬀects on biological outcomes between
the conditional and unconditional cash transfer
interventions, and had suﬃcient power to detect only
very large eﬀects on HIV in baseline dropouts becauseof the small size of this cohort. Further studies of cashtransfer programmes are needed to conﬁdently establish
these eﬀects and the channels through which theymight operate.
The intervention was implemented for only 2 school
years. The short duration of the programme mightmean that the eﬀects noted after 18 months might not
be durable. However, the ﬁnding that cash transfers toschool-aged girls and their families can reduce theirrisk of HIV infection while that support is ongoing is
still important.
We did not collect data for men or for women older
than 22 years. The risk of infection in older womenmight have increased in the intervention enumeration
areas. However, survey data at 12 month follow-up
showed no diﬀerences in behavioural outcomes between
untreated girls in treatment enumeration areas and the

www.thelancet.com Published online February 15, 2012 DOI:10.1016/S0140-6736(11)61709-1

Articles

Panel 2: Research in context
Systematic review
We searched PubMed for full articles, systematic reviews, andmeta-analyses published up to July 22, 2011, in any languagewith the search terms “HIV prevention” and “cash transfer” or“microﬁnance”. Our search identiﬁed 17 results. Only one othercluster randomised trial of a structural intervention to prevent
HIV in women with biological outcomes was identiﬁed. The
Intervention with Microﬁnance for AIDS and Gender Equity(IMAGE) study14 assessed a structural intervention thatcombined a microﬁnance programme with a sex and HIV
training curriculum and noted no eﬀect on HIV incidence.
Interpretation
Poor education, poverty, and gender inequalities are
postulated to be important determinants of young women’svulnerability to HIV infection. However, to date, norandomised controlled trial of a structural intervention has
shown a signiﬁcant eﬀect on HIV incidence.16 The Zomba cashtransfer programme reduced the prevalence of HIV and
HSV-2 infection at 18 month follow-up in school-age girls
who were enrolled in school at baseline. These eﬀects aresupported by changes in self-reported sexual behaviour. The
ﬁndings suggest that ﬁnancially empowering school-age girls
and their families can have substantial eﬀects on their sexualand reproductive health.

control group, which suggests that the risk of infectionin this group is unlikely to have increased as a result of
the intervention.
Undetected misclassiﬁcation of HSV-2 status could
have occurred, since no supplemental testing was done
to conﬁrm the results of the HSV-2 rapid tests. However,
because counsellors were masked to the participants’intervention status at the time of testing, any misclassiﬁcation of the test result would be non-diﬀerential bytrial group and tend to bias results towards the null
hypothesis of no diﬀerence in HSV-2.
The prevalence of HIV (3·7%) in unmarried women
younger than 25 years in southern Malawi3 was nearly
identical to the overall HIV prevalence (3·8%) in thecontrol group. Therefore, our sample of school-aged
girls seems to be representative of the population in the
study area. A valid question is whether our ﬁndings canbe generalised to other areas in Malawi or othercountries in southern Africa. Zomba district ischaracterised by high poverty, HIV, and school dropout
in young women. Matrilocality is common in the study
area, with married couples living with or near the wives’families. Transactional sex was also common in ourstudy: roughly a quarter of participants who were
sexually active at baseline reported that they started
their relationship with their partner because they“needed his assistance” or “wanted gifts or money”.
Future studies are needed to assess whether cashtransfer programmes can protect girls of this age fromacquiring HIV in other settings.
By use of the average household transfer size (US$10 per
month) and the high administrative costs of our cashtransfer experiment, we calculated that the cost of
averting a primary HIV infection is $12 500 in 2009 dollars.
However, because intervention eﬀect did not diﬀer bytransfer amount, we suspect that the minimum transfer
amount of $5 per month would be equally eﬀective.
Combination of this amount with a more realistic
administrative cost of about 15% of total programmecosts for a scaled up cash transfer programme would
yield a cost of only $5000 per HIV infection averted.
This study shows that a simple intervention thatprovided cash to unmarried schoolgirls (and theirparents) decreased risky sexual activity and reduced theirlikelihood of being infected with HIV and HSV-2. Ourﬁndings suggest that ﬁnancially empowering schoolaged girls might have beneﬁcial eﬀects on their sexualand reproductive health. Our results indicate that cashtransfer programmes could be attractive to policy makers
in sub-Saharan Africa when they consider the full arrayof beneﬁts that they might provide.
Contributors
CTM, BÖ, and SJB oversaw the design of the study and analysed thedata. RSG, BÖ, and SJB oversaw the collection of biological data. All
authors interpreted the data, prepared the report, and approved theﬁnal version.
Conﬂicts of interest
We declare that we have no conﬂicts of interest.
Acknowledgments
Findings from this study have been presented at the 3rd Biennial
Conference of the American Society of Health Economists (Ithaca, NY,
USA), June 20–23, 2010, and the 18th International AIDS Conference(Vienna, Austria), July 18–23 2009. We thank the study participants, thesurvey enumerators, the voluntary counselling and testing counsellors,
the data entry teams, our ﬁeld staﬀ, the two non-governmentalorganisations who implemented the cash transfer programme, and theDistrict Oﬃcers for Education, Health, and Planning in Zomba for theircooperation. The ﬁndings and conclusions in this report are those of theauthors and do not necessarily represent the views of the International
Bank for Reconstruction and Development or World Bank and its
aﬃliated organisations, or those of the Executive Directors of the WorldBank or the governments they represent.
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