Fermat's Library | Improving immunisation coverage in rural India: clustered randomised controlled evaluation of immunisation campaigns with and without incentives annotated/explained version.

BMJ, published in the UK, is a premier medical journal, and not a t...

Esther Duflo and Abhijit Banerjee shared the 2019 Nobel prize in Ec...

Randomized controlled trials became a popular tool for policy evalu...

These numbers have not improved significantly since this was publis...

This programs are what they sound like: the treatment is to give ca...

Banerjee and Duflo are both part of JPAL (The Abdul Latif Jameel Po...

The incentives (lentils in this case) are a key treatment that they...

With any survey, particularly health-related surveys, there are man...

Clustered randomized controlled trials are different than individua...

This is key. If the measurement error was correlated with the treat...

Many of the RCTs for development are longitudinal studies that take...

This is a key visual presentation of the results. Note that the ...

The program with incentives pays for itself on a per child basis.

The ultimate goal of JPAL and development economics is to evaluate ...

RESEARCH

Improving immunisation coverage in rural India: clustered

randomised controlled evaluation of immunisation

campaigns with and without incentives

Abhijit Vinayak Banerjee, Ford foundation international professor of economics,

Esther Duflo, Abdul Latif

Jameel professor of poverty alleviation and development economics,

Rachel Glennerster, executive

director,

Dhruva Kothari, medical student

ABSTRACT

Objective To assess the efficacy of modest non-financial

incentives on immunisation rates in children aged 1-3 and

to compare it with the effect of only improving the

reliability of the supply of services.

Design Clustered randomised controlled study.

Setting Rural Rajasthan, India.

Participants 1640 children aged 1-3 at end point.

Interventions 134 villages were randomised to one of

three groups: a once monthly reliable immunisation camp

(intervention A; 379 children from 30 villages); a once

monthly reliable immunisation camp with small

incentives (raw lentils and metal plates for completed

immunisation; intervention B; 382 children from 30

villages), or control (no intervention, 860 children in 74

villages). Surveys were undertaken in randomly selected

households at baseline and about 18 months after the

interventions started (end point).

Main outcome measures Proportion of children aged 1-3

at the end point who were partially or fully immunised.

Results Among children aged 1-3 in the end point survey,

rates of full immunisation were 39% (148/382, 95%

confidence interval 30% to 47%) for intervention B

villages (reliable immunisation with incentives), 18%

(68/379, 11% to 23%) for intervention A villages (reliable

immunisation without incentives), and 6% (50/860, 3%

to 9%) for control villages. The relative risk of complete

immunisation for intervention B versus control was 6.7

(4.5 to 8.8) and for intervention B versus intervention A

was 2.2 (1.5 to 2.8). Children in areas neighbouring

intervention B villages were also more likely to be fully

immunised than those from areas neighbouring

intervention A villages (1.9, 1.1 to 2.8). The average cost

per immunisation was $28 (1102 rupees, about

16 or

€

19) in intervention A and $56 (2202 rupees) in

intervention B.

Conclusions Improving reliability of services improves

immunisation rates, but the effect remains modest. Small

incentives have large positive impacts on the uptake of

immunisation services in resource poor areas and are

more cost effective than purely improving supply.

Trial registration IRSCTN87759937.

INTRODUCTION

Immunisation is a highly cost effective way of improv-

ing survival in children in developing countries.

Every year throughout the world, however, an esti-

mated 27 million children and 40 million pregnant

women do not receive the basic package of immunisa-

tions(asdefinedby WHO andUnicef), and two to three

million people die from diseases that can be prevented

with vaccines.

Immunisation rates are in part based

on official statistics and might be over-reported.

India, immunisation services are offered free in public

health facilities, but, despite rapid increases, the immu-

nisation rate remains low in some areas. According to

the National Family Health survey (NFHS-3), in India

only 44% of children aged 1-2 years have received the

basic package.

That drops to 22% in rural Rajasthan,

the setting of the present study, and was less than 2% in

our study area (a disadvantaged population in rural

Udaipur) at baseline (according to a more detailed sur-

vey instrument than the NFHS-3, that was less likely to

overestimate full immunisation rates). Understanding

how to improve the uptake of immunisation is impor-

tant, not only for existing vaccines but also to maximise

the uptake of any new vaccine.

Reliable supply of free immunisation services and

incentives to improve the demand for these services

could improve immunisation rates. Previous studies

have assessed the effectiveness of financial and non-

financial incentives to encourage immunisation and

other preventive health behaviours. Non-randomised

studies of the measles campaign in Africa suggest that

coupling the distribution of vaccines and bed nets

increases ownership of bed nets by more than 40 per-

centage points,

but the studies did not estimate the

programme’s impact on measles vaccination rates. In

Nicaragua, attendance at an immunisation campaign

increased from 77% to 94% when food incentives

equivalent to about three to five days of wages were

introduced to encourage vaccination in 1985.

That

study, however, was an observational study in which

the treatments were sequential rather than contem-

poraneous. Conditional cash transfer programmes,

Department of Economics,

Massachusetts Institute of

Technology, 50 Memorial Drive,

E52-391, Cambridge, MA 02142,

USA

Abdul Latif Jameel Poverty Action

Lab, Massachusetts Institute of

Technology, Cambridge, MA

630 West 168th Street,

Columbia University Physici ans

and Surgeons Mailbox #67, New

York, NY 10032, USA

Correspondence to: E Duflo

eduflo@mit.edu

Cite this as:

BMJ

2010;340:c2220

doi:10.1136/bmj.c2220

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popular in Latin American countries, have been effec-

tive in promoting the use of certain preventive health-

care services and have also had a positive impact on

health outcomes for women and children.

10-13

These

programmes, however, did not have a large impact

on immunisation rates.

The lack of impact might be

because of high initial immunisation rates in the areas

where the programmes were carried out. Most condi-

tional cash transfer programmes have been implemen-

ted in countries with existing adequate local health

infrastructure so evaluations of their impact cannot

shed light on the relative cost effectiveness of establish-

ing incentive based interventions (versus improving

quality of health infrastructure only) in more resource

poor settings.

We assessed the relative efficacy and cost effectiveness

of improving the supply of infrastructure for immunisa-

tion only compared with improving supply and simulta-

neously increasing demand through the use of incentives.

The study was a partnership between the Abdul Latif

Jameel Poverty Action Lab (J-Pal) at the Massachusetts

Institute of Technology and Seva Mandir, a non-govern-

mental organisation in Udaipur district.

METHODS

We used a clustered randomised controlled trial to

evaluate two interventions in rural Rajasthan, India.

In one intervention (A), regular, well publicised immu-

nisation clinics (referred to as “camps”) were held,

while in the second intervention (B), similar camps

were held and parents were also offered small incen-

tives to immunise their children. A third set of villages

formed the control group. We used a cluster level

design because individual level randomisation could

have generated resentment against the non-govern-

mental organisation.

Selection and description of sample

The main sample comprised 134 villages randomly

selected from a Seva Mandir catchment area in Udai-

pur by using a computer generated random variable

and over-sampling villages far away from a road. We

also randomly selected one village within 6 km of each

intervention village to measure potential spillover of

the interventions.

Within each village, a household census was con-

ducted, and 30 households containing children aged

0-5 years were randomly selected with a random num-

ber generator to be part of the sample. The same house-

holds were surveyed again at the end point. The

criterion for inclusion of a child in this study was to

belong to a sampled household and to be aged 1-3 at

the end point of the study (main sample) or to have

been aged 0-6 months at baseline (baseline cohort).

As Seva Mandir works in poorer and more tribal

villages, the villages selected are not representative of

Udaipur in general but are representative of Seva Man-

dir’s catchment area, an impoverished area where

health status is poor.

The public facilities serving

these areas are characterised by high absenteeism:

weekly visits during the year preceding the

intervention showed that 45% of the health staff in

charge of immunisations (auxiliary nurse midwives)

were absent from their village level health centre (and

could not be found anywhere in the village) on any

given workday, and there was no predictable pattern

to their absence.

Interventions

In this study children received the WHO/Unicef

extended package of immunisation, provided by the

Indian government. This includes one dose of BCG

vaccine, three doses of DPT (diphtheria-pertussis, teta-

nus) vaccine, three doses of oral polio vaccine, and one

dose of measles vaccine.

A child should be fully

immunised (that is, have received all the vaccines in

the extended package) by the age of 1 year.

Given that a full immunisation course requires at

least five visits to a public health facility, the unreliabil-

ity of the auxiliary nurse midwives might deter families

from taking their children to the centre to complete the

full immunisation schedule. Therefore, intervention A

(“immunisation camps”) focused on establishing regu-

lar availability of immunisation services. It consisted of

a mobile immunisation team, including a nurse and

assistant (both hired by Seva Mandir), who conducted

monthly immunisation camps in the villages. The

nurse and assistant held the camp on a fixed date

every month at a fixed time (11 am to 2 pm). The pre-

sence of the nurse and assistant was verified by the

requirement of timed and dated pictures of them in

the villages and by regular monitoring. Review of

records showed that of 1336 planned camps, 95%

(1269) took place. In addition, in each village a social

worker was responsible for identifying children,

informing mothers about the availability of the immu-

nisation camps, and educating them about the benefits

of immunisation. Seva Mandir has been active in the

area for over 50 years and is trusted in villages. While

this programme was new, and Seva Mandir had not

been engaged in any effort to provide immunisation

before, the health unit of the organisation had been

conducting several programmes in these villages or in

neighbouring villages, most notably an effective pro-

gramme of training traditional birth attendants for

delivery. Many villages also already had health social

workers, responsible for general health advice, infor-

mation on prenatal and other preventive care, referral

to health centres, and help with the DOT (directly

observed therapy) programme. The organisation thus

benefits from a high level of trust among villagers,

which might have ameliorated issues of mistrust that

surround immunisation programmes in India.

Intervention B used the same infrastructure as inter-

vention A but in addition offered parents 1 kg of raw

lentilsperimmunisation administeredanda set of thalis

(metal plates used for meals) on completion of a child’s

full immunisation. The value of the lentils was about 40

rupees (about $1), equivalent to three quarters of one

day’s wage, and the value of the thalis was about 75

rupees. Seva Mandir decided to provide lentils, rather

than cash, as this was useful to the family and also

RESEARCH

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immediate had nutritional value. The amount roughly

corresponds to the opportunity cost of time for the

mother. The thalis were chosen as a tangible sign of

achievement, while also being of immediate use.

At the first immunisation, every child was given an

official immunisation card indicating their name, the

name of their parent/s, and the date and type of each

immunisation performed. The nurse also kept a

detailed logbook. Following standard guidelines,

when a child arrived at a camp without an immunisa-

tion card and it could not be ascertained whether he or

she had received a given immunisation, the child was

immunised.

Study and evaluation design

We evaluated the impact of the interventions using a

clustered randomised control trial. Using the random

number generator in the statistical package Stata (ver-

sion 9), and after stratification by geographical block

(the administrative unit above the village), one author

(ED) randomly selected 30 of the 134 study villages to

receive intervention A and 30 to receive intervention

B. The 74 remaining villages were control villages and

received no additional intervention. Naturally, given

the context and the intervention, the allocation of vil-

lages to treatment or control was not blind. In most

control villages, a Seva Mandir health worker was pre-

sent and encouraging uptake of preventive services,

including immunisation, was part of their mission. Vil-

lagers were to obtain immunisation in the closest

health centre. In all villages, the government nurse

continued to provide immunisation services for the

duration of the study. When a camp was established

in a village, any non-immunised child younger than

5, from any village, was eligible for immunisation in

the camp. All children younger than 2 were eligible

for the lentils in intervention B camps, irrespective of

the village they came from. (Villages from all three

treatment groups were sufficiently far from each

other (over 20 km) so we expected no contamination

between the villages.) Children who began the immu-

nisation course before turning 2 remained eligible for

the incentives until the completion of the immunisa-

tion course. Therefore children included in the study

sample were aged 1-3 at the end point survey.

Data sources

Our primary outcome was the receipt of all or part of

the extended package of immunisation. Most house-

holds in the areas did not have immunisation cards so

we ascertained the immunisation rate during inter-

views with the mother. Mothers were surveyed about

the immunisation status of all children aged under 7 at

the end point and about her immunisation status dur-

ing her pregnancy with each child.

We developed our survey instrument to elicit accu-

rate reporting of immunisation status, regardless of

where the immunisation was obtained (camp, health

centres, private doctor). Because a parent might con-

fuse immunisation with other injections (injection of

antibiotics is common in India) and might not realise

the difference between different vaccinations, the

instrument asked in detail about each injection

received by the child, including whether it was admi-

nistered to cure a sickness, in which facility it was admi-

nistered, and where on the body it was injected. In

addition, at the end of the survey, the field officer

examined the child to ascertain whether they had the

distinctive scar left by the BCG vaccine. If the family

had a vaccination card for the child researchers also

recorded the information on the card.

Self report can be influenced by recall bias (mothers,

who are often illiterate, might not remember) and

potentially by social desirability bias, which might be

affected by their intervention group. We carried out

several validation exercises in which we compared

the self reports with the BCG scar, the immunisation

card (available for 343 children), and a sample of chil-

dren from intervention villages. The immunisation

camp records were matched with the survey data.

BCG self report seemed to be accurate (see appendix

1 on bmj.com). Immunisation status elicited from the

survey instrument corresponded to within one injec-

tion of the status indicated on the card 79% of the

time and to within one injection of the status indicated

in the logbook 74% of the time. The mis-measurement

was not correlated with the treatment statusor the num-

ber of immunisations reported and was not systemati-

cally over-reported or under-reported and should

therefore increase noise but not necessarily introduce

bias (as measurement error is the dependent variable

and is not differential in different treatment groups).

While self reports of immunisation from mothers

who do not have an immunisation card is not perfect,

a meta-analysis of several validation studies has shown

that they are generally of acceptable quality and that

they represent “the best available independent mea-

sure of DPT3 coverage.”

Nevertheless, to verify that theresults were not biased

by the use of self reported data, we carried out two addi-

tional analyses: an analysis of the presence of BCG scar

(observed by the field officer at the end of the mother’s

interview) and an analysis based on the administrative

data maintained in intervention A and intervention B

villages. For these children, a complete computerised

record of immunisation received in the camp and else-

where is maintained. This allows a comparison of inter-

vention A and B villages for childrenwhohave received

at least one immunisation in the camp. For this analysis,

we also focused on children aged 1-3.

The baseline survey took place between June 2004

and February 2005 and covered all children aged 0-5

in the sample households. The intervention started in

each geographical block after the baseline investiga-

tions. The end point survey took place between July

2006 and February 2007, about 18 months after the

interventions started in a particular village. It used the

same survey instrumentsand coveredall children age 0-

7 in the same households to identify eligible children (1-

3 at end point, or 0-6 monthsat end point). Bothsurveys

were blind: interviewers did not know which villages

belonged to which intervention (or control) group.

RESEARCH

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Data entry, cleaning, and validation were completed in

September 2007 and analysis and report write up took

place between October 2007 and May 2008. The paper

was revised a first time between September 2009 and

November 2009 and a second time in March 2010.

End points

In the household sample, our main analysis focused on

children aged 1- 3 at the end point (that is, eligible and

old enough to be fully immunised). The outcomes

include the probability of receiving at least one immu-

nisation (excluding oral polio vaccine, which almost all

children have received and therefore does not affect the

statistics); the presence of the BCG scar; the number of

immunisations received; and the probability of receiv-

ing the complete extended package of immunisation.

We also analysed the administrative data collected in

the camp: the outcomes were the number of immuni-

sations received by children who received at least one

immunisation in the camp, and the probability of

receiving all the vaccines in the extended package of

immunisation.

Complementary analysis reports the impact of the

interventions on neighbouring villages. We report the

probability of being immunised in villages neighbour-

ing intervention A and intervention B camps, differ-

ences between these two groups of neighbouring

villages and the control group, and relative risks.

Costs

We carried out a cost effectiveness analysis of both

interventions (see appendix 2 on bmj.com for details).

Statistical analysis

Taking into account correlation of the end point within

a village and clustering of the treatment at that level (a

intracluster correlation of 0.25 was assumed based on a

preliminary survey) and given a baseline immunisation

rate of 2% in the control group, we determined that a

sample of 30 villages per treatment arm, with a random

sample of 30 households per village (assuming about

1.4 children aged 1-3 years surveyed in each house-

hold), was sufficient to obtain 80% power for a 5%

level testof a differenceof at least five percentage points

in the probability of being fully immunised between

any two groups (treatmentA, treatmentB, and compar-

ison). The larger control group increases power.

We used intention to treat analysis

—

that is, all house-

holds were analysed with the assumption that they

remained in the treatment group to which they were

initially assigned. For the binary variables, we report

proportion in each group, difference in proportions

across groups, and relative risks. For the count vari-

ables (number of immunisation), we report values in

the treatment group, difference across groups, and rela-

tive risks. The analysis adjusts for clustering at the vil-

lage and the family level. For the difference in

proportion, we used a multilevel mixed effect linear

model of the probability of being immunised on the

treatment indicator, with a hierarchical error structure

that allows cluster level heterogeneity (random effect)

at the village and at the family level. For the relative

risk, we used a multilevel mixed effect Poisson model

with the same hierarchical error structure. We did not

include any control variables. In all the analyses we

used Stata version 10.

Assessed for eligibility (n=134 villages, each with 30 households with children aged 0-7 years at end point)

Randomised

Allocated to intervention A (n=453

households in 30 villages)

All received allocated intervention

Lost from baseline to end point (n=71

households)

Allocated to intervention B (n=481

households in 30 villages)

All received allocated intervention

Lost from baseline to end point (n=82

households)

Allocated to control (n=1224 households

in 74 villages)

All received control

Lost from baseline to end point (n=210

households)

Enrolment

Allocation

Followed up to end point (n=379 children

aged 1-3 in 30 villages)

Estimated loss to follow-up (n=22 children;

household moved, unable to find child,

child died)

Discontinued intervention (n=0)

Followed up to end point (n=382 children

aged 1-3 in 29 villages)

Estimated loss to follow-up (n=13 children;

household moved, unable to find child,

child died)

Discontinued intervention (n=0)

Followed up to end point (n=866 children

aged 1-3 in 69 villages)

Lost to lack of covariates (n=6 children)

Estimated loss to follow-up (n=44 children;

household moved, unable to find child,

child died)

Discontinued intervention (n=0)

Follow-up

Analysed (n=379 children, none excluded) Analysed (n=382 children, none excluded) Analysed (n=860 children, none excluded)

Analysis

Excluded (n=4246):

Did not meet inclusion criteria (too old or too young at end point) (n=4246)

Refused to participate (n= 0)

Other reasons (n=0)

(randomisation occurred at village level; all villages assigned to receive treatment did so)

Fig 1

Flow of participants through study

RESEARCH

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RESULTS

The final sample in the household surveys included

2188 children aged 1-3 years at the end point from

2898 households in five groups of villages: 74 control

villages (n=860 children), 30 villages in intervention

group A (n=379), 30 in intervention group B (n=382),

27 neighbouring an intervention group A village

(n=265), and 26 neighbouring an intervention group

B village (n=302) (fig 1).

Baseline characteristics of children across the treat-

ment arms were comparable (table 1). There were no

differences in proportions of children partially or fully

immunised at baseline or in the covariates. Immunisa-

tion rates were less than 2% among 1-3 year olds. The

intracluster correlation at baseline was 0.28.

The final sample with logbook data included 2106

children aged 1-3 who received at least one immunisa-

tion in the camps: 407 in 30 villages in intervention A

and 725 in 30 villages in intervention B.

Primary end point: impact on immunisation in treatment

village

The highest rate of full immunisation was observed for

intervention B (table 2, fig 2). In intervention B vil-

lages, 148/382 (mean 39%, 95% confidence interval

30% to 47%) children were completely immunised

compared with 68/379 (18%, 11% to 23%) in inter-

vention A villages and 50/860 (6%, 3% to 9%) in con-

trol villages (fig 2). The relative risk of being

completely immunised was 3.1 (2.0 to 4.2) for inter-

vention A versus control, 6.7 (4.5 to 8.8) for inter-

vention B versus control, and 2.2 for intervention B

versus intervention A (1.5 to 2.8). Compared with the

control group, immunisation rates more than doubled

in intervention A villages and increased by more than

six times in the intervention B villages. There were no

adverse events (severe reaction to immunisation)

reported in either intervention groups.

The difference between intervention B and inter-

vention A was more marked for full immunisation

than for the number of immunisations received and dis-

appeared for the probability of receiving at least one

injection. Specifically, 78% (70% to 85%) of children in

intervention A villages received at least one injection

compared with 74% (67% to 82%) of children in inter-

vention B villages. Similarly, 50% (41% to 59%) of chil-

dren in intervention A villages and 50% (41%to 59%) of

children in intervention B villages had a BCG scar (v

28% (21% to 36%) in control villages) (fig 3), showing

that the impact of the incentivewasmainly to reduce the

number of children dropping out after three injections.

Over half (52%, 43% to 62%) of children who were

reported as receiving at least one injection in inter-

vention B villages were completely immunised com-

pared with 23% (15% to 32%) in intervention A.

The analysis of the logbooks confirms these results.

Of the children who received at least one injection in

the camps, 485/700 (67%, 59% to 74%) were fully

immunised in intervention B and 197/407 (48%, 38%

to 59%) were fully immunised in intervention A. The

relative risk of being completely immunised in inter-

vention B compared with intervention A for children

who received at least one injection was 1.4 (1.1 to 1.7).

The propensity for children to drop out before com-

pleting the full course, particularly in intervention A

villages, was not because the camps became less popu-

lar over time: children who received their first immu-

nisation later received on average the same number of

immunisations as children who received their first

immunisation earlier.

Impact on neighbouring villages

Table 3 shows immunisation rates in villages neigh-

bouring the intervention villages. In villages within a

few kilometres of an intervention B camp, 61/302 chil-

dren (20%, 10% to 31%) were completely immunised

compared with 36/265 children (11%, 5% to 16%) in

villages bordering an intervention A camp. These con-

fidence intervals overlap, but the relative risk is signifi-

cantly greater than one. The relative risk of being

completely immunised for villages neighbouring inter-

Table 1

Baseline characteristics by allocated group*. Figures are percentages of children

unless stated otherwise

Control group Treatment A Treatment B

Mean age (months) 10.2 (9.2 to 11.3) 10.4 (8.8 to 12.0) 11.06 (9.72 to

12.40)

Mean household size (No of people) 6.7 (6.5 to 7.0) 6.7 (6.3 to 7.1) 6.74 (6.46 to 7.03)

Male 0.5 (0.5 to 0.6) 0.5 (0.4 to 0.6) 0.50 (0.44 to 0.57)

Member of scheduled castes/scheduled

tribes (disadvantaged group)

0.9 (0.8 to 1.0) 0.9 (0.8 to 1.0) 0.96 (0.8 to 1.02)

Literate head of household 0.4 (0.3 to 0.4) 0.4 (0.3 to 0.5) 0.37 (0.27 to 0.47)

Monthly household income

†

2858.70 (2433.17

to 3284.23)

3196.57 (2743.95

to 3649.18)

2729.09 (2374.79

to 3083.39)

Land size owned by family (in bighas

‡

) 3.9 (3.5 to 4.3) 4.0 (3.5 to 4.5) 3.51 (2.98 to 4.04)

Below poverty line 0.5 (0.5 to 0.6) 0.5 (0.4 to 0.6) 0.50 (0.42 to 0.59)

No of rooms in house 2.0 (1.8 to 2.2) 2.1 (1.8 to 2.4) 1.90 (1.74 to 2.06)

House has electricity 0.2 (0.1 to 0.2) 0.2 (0.1 to 0.3) 0.06 (0 to 0.12)

Treats water 1.1 (1.1 to 1.2) 1.1 (1.0 to 1.1) 1.08 (1.03 to 1.12)

No of immunisations 0.6 (0.5 to 0.8) 0.8 (0.5 to 1.1) 0.45 (0.25 to 0.65)

Completely immunised 0.01 (0 to 0.01) 0.02 (0 to 0.04) 0.00 (0 to 0.02)

At least one injection 0.3 (0.3 to 0.4) 0.4 (0.3 to 0.5) 0.30 (0.19 to 0.4)

reliable immunisation camps, 30 villages; B

reliable immunisation camps with incentives, 30 villages;

control

no treatment, 74 villages.

†

In rupees (1000 rupees

about

15,

€

17, $23).

‡

Generally <1 acre (0.4 hectare).

Fully immunised (%)

Control

villages

Intervention

A villages

(reliable

camps)

Intervention

B villages

(reliable

camps)

Villages

neighbouring

intervention

A camps

Villages

neighbouring

intervention

B camps

Fig 2

Percentage of children aged 1-3 years fully immunised

by treatment status

RESEARCH

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vention B camps versus those neighbouring inter-

vention A camps was 1.9 (1.1 to 2.8) (table 3).

This analysis is confirmed in the logbook data,

where results are more precise. In villages within a

few kilometres of an intervention B camp, 452/700

children who received at least one immunisation

(65%, 58% to 72%) were completely immunised com-

pared with 69/208 children (33%, 23% to 44%) in vil-

lages bordering an intervention A camp.

Costs

The average cost to Seva Mandir of fully immunising a

child was $27.94 (1102 rupees, about £16 or €19) in the

reliable camp with incentives and $55.83 (2202 rupees)

in the reliable camp without incentives (see appendix 2

on bmj.com for further details). The difference comes

from the fact that camps had to be open from 11 am to

2 pm, regardless of the number of children present.

Thus, the higher average number of children in the

camps with incentives spread the daily fixed cost

(mainly, the salary of the nurse and assistant) over

more children. The marginal cost of an extra child

being fully immunised with and without incentive in a

given camp is, respectively, $6.60 and $1.30. The sal-

aries of the nurse and assistant represent about half of

the cost of the camp without incentives. Monitoring

that the camps are regularly held is another important

part of the cost, which is necessary in light of high

absenteeism.

When we calculated the cost that would

be incurred by a government able to use an existing

health infrastructure, the average cost of fully immunis-

ing a child was estimated at $25.18 in camps without

incentives and $17.35 in camps with incentives.

DISCUSSION

Summary of results

This randomised controlled study of immunisation

camps shows that offering modest incentives to

families in resource poor settings can significantly

increase uptake of immunisation services, when reli-

able services are available. In our study, reliable

camps with incentives achieved significantly higher

rates of full immunisation for children aged 1-3 com-

pared with control areas where no camps were made

available and compared with reliable camps without

incentives. While control villages had a full immunisa-

tion rate of nearly 6%, villages in which a reliable camp

was held showed rates of around 18%, and adding the

incentive pushed rates to nearly 40%, a significant

increase. The rate achieved with incentives represents

a more than sixfold increase over the rate in control

villages, in a particularly poor and hard to reach popu-

lation. It is, however, still too low to achieve herd

immunity.

Surprisingly,despite that fact that the family received

a set of plates for the last immunisation, the biggest

increasebetweeninterventionA and interventionB vil-

lages was for the third and fourth immunisation. This

might indicatethat parents are more sensitivetothe fact

that there is an incentive than to the level of the incen-

tive, a finding consistent with the results that in condi-

Percentage

No of immunisations

≥1 ≥2 ≥3 ≥4 ≥5

Intervention A main villages

Intervention B main villages

Fig 3

Number of immunisations received by children aged

1-3 years

Table 2

Effects of group allocation (A

immunisation, B

immunisation plus incentive). Numbers are in absolute values

Mean (95% CI) Difference* (95% CI) Relative risk

†

(95% CI)

Control A B A

−

control B

−

control B

−

AAv control B v control B v A

End point cohort (aged 1-3 years)

No in group 860 379 382

——— —— —

No of immunisations 1.20

(0.94 to 1.46)

2.35

(1.99 to 2.71)

2.85

(2.44 to 3.25)

1.15

(0.95 to 1.35)

1.70

(1.48 to 1.92)

0.55

(0.26 to 0.83)

2.14

(1.84 to 2.44)

2.66

(2.28 to 3.05)

1.22

(1.08 to 1.36)

≥

1immunisation 0.49

(0.40 to 0.57)

0.78

(0.70 to 0.85)

0.74

(0.67 to 0.82)

0.29

(0.23 to 0.35)

0.26

(0.20 to 0.33)

−

0.03

(

−

0.09to0.04)

1.59

(1.35 to 1.83)

1.52

(1.29 to 1.75)

0.96

(0.80 to 1.11)

Has BCG scar

‡

0.28

(0.21 to 0.36)

0.50

(0.41 to 0.59)

0.50

(0.41 to 0.59)

0.22

(0.15 to 0.28)

0.22

(0.15 to 0.28)

0.00

(

−

0.08to0.08)

1.76

(1.41 to 2.12)

1.76

(1.41 to 2.12)

1.00

(0.79 to 1.21)

Completely immunised 0.06

(0.03 to 0.09)

0.18

(0.11 to 0.25)

0.39

(0.30 to 0.47)

0.13

(0.09 to 0.16)

0.34

(0.30 to 0.38)

0.21

(0.15 to 0.28)

3.09

(1.96 to 4.21)

6.66

(4.53 to 8.80)

2.16

(1.54 to 2.78)

Logbook cohort (aged 1-3 years)

No in group

—

407 725

——— —— —

Total No of immunisations

—

3.70

(3.39 to 4.01)

4.18

(3.99 to 4.37)

——

0.59

(0.25 to 0.93)

——

1.15

(1.05 to 1.25)

Completely immunised

—

0.48

(0.38 to 0.59)

0.67

(0.59 to 0.74)

——

0.22

(0.10 to 0.33)

——

1.43

(1.12 to 1.73)

*Estimated by fitting multilevel mixed effect linear model, with clustering at hamlet and household level.

†

Estimated by fitting multilevel mixed effect Poisson regression, with clustering at hamlet and household level.

‡

For analysis with BCG scar as outcome, there were 790 observations in control group, 334 in treatment A group, and 336 in treatment B group.

RESEARCH

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tional cash transfer programme, the size of the transfer

does not seem to matter beyond the fact that there is a

positive transfer,

19 20

and suggests that larger incentives

mightnotincrease the immunisationratemuchbeyond

what was found here. Moreover, while a camp without

incentives increased immunisation rates only in the vil-

lage where it took place, camps with incentives also

increased rates in neighbouring villages.

Comparison with other studies

Several previous studies have shown that uptake of pre-

ventive behaviours is sensitive to small incentives or

small costs, suggesting that incentives can play a role in

promoting preventive health services.

9192122

Other

researchers have suggested that in resource poor set-

tings, ensuring a reliable supply of health services and

educating parents about the benefits of preventive care

are more important than providing incentives.

923

Our

findings contrast with those of a study in Timor Leste,

which found that food incentives did not increase the

completion of tuberculosis treatment.

This difference

might be attributable to various factors: the frequency of

the treatment (vaccines versus daily treatment); the fact

thatadults weretargetedinthetuberculosisintervention;

the relatively high initial compliance rate; and the differ-

ence in demand for treatment and prevention. More stu-

dies are needed to understand in what conditions

incentives for parents or patients have a positive impact.

Limitations of study

We relied in part on self reported data on immunisa-

tion, though the results were robust when we used the

BCG scar or the immunisation reported in the logbook

as outcomes. The study was not blind from the point of

view of the villagers, who might have been motivated

to attend the camp to ensure that Seva Mandir would

not cancel the programme. The study was also con-

ducted in an environment with low density where

initial immunisation rates were extremely low. In

areas where initial immunisation rates are higher, simi-

lar interventions might not produce as dramatic an

increase. On the other hand, the impacts might be

much higher and the costs much lower in more densely

populated regions. Finally, we could look only at the

joint effect of improving supply and incentivising

demand. Because it would have been impossible to

administer in practice, we could not introduce an

incentive programme without simultaneously making

the supply more reliable.

Policy implications

The magnitude of our results shows that, in this setting,

holding regular immunisation camps combined with

incentives improves immunisation rates, even though

the rate of full immunisation remained low. Moreover,

providing incentives and improving the supply of ser-

vices was also more cost effective than improving the

supply of services alone. The cost of immunising with

incentive (around $17.35) is higher than the cost cur-

rently in the Indian budget (about $4 per immunisa-

tion, according to the healthcare budget

), but it is of

an order of magnitude comparable with the payment

from the Global Alliance for Vaccines and Immunisa-

tion (GAVI) to member countries of $20 per “extra

child” who would not have been immunised otherwise.

This is a relevant comparison as these kinds of pro-

gramme would target “difficult to reach” children

who are not already immunised under India’s standard

programme. A review of interventions to improve

immunisation found that the cost of most interventions

is about $10-20 per newly immunised child.

More-

over, while the lentils represented a cost to Seva Man-

dir, their distribution could have led to improved

nutrition for the family in an environment where mal-

nutrition and anaemia are endemic, and it is not clear

they should be considered as a cost.

Table 3

Effects of treatment in villages adjacent to intervention or control villages (A

immunisation, B

immunisation plus incentive)

Mean in group (95% CI) Difference* (95% CI) Relative risk

†

(95% CI)

Control Treat A B A

−

control B

−

control B

−

AAv control B v control B v A

End point cohort (aged 1-3 years)

No in group 860 265 302

——— —— —

No of immunisations 1.20

(0.94 to 1.46)

1.41

(0.94 to 1.88)

1.70

(1.18 to 2.22)

0.23

(0.00 to 0.46)

0.58

(0.35 to 0.82)

0.36

(0.02 to 0.69)

1.18

(0.92 to 1.43)

1.48

(1.18 to 1.77)

1.26

(0.93 to 1.60)

≥

1immunisation 0.49

(0.40 to 0.57)

0.49

(0.34 to 0.64)

0.51

(0.39 to 0.63)

0.01

(

−

0.06to0.09)

0.05

(

−

0.02to0.12)

0.03

(

−

0.06to0.12)

1.00

(0.80 to 1.19)

1.05

(0.86 to 1.24)

1.05

(0.81 to 1.30)

Has BCG scar

‡

0.28

(0.21 to 0.36)

0.28

(0.16 to 0.41)

0.30

(0.18 to 0.41)

0.01

(

−

0.06to0.08)

0.03

(

−

0.04to0.10)

0.02

(

−

0.07to0.10)

1.00

(0.73 to 1.28)

1.05

(0.78 to 1.32)

1.05

(0.70 to 1.39)

Completely immunised 0.06

(0.03 to 0.09)

0.11

(0.05 to 0.16)

0.20

(0.10 to 0.31)

0.05

(0.01 to 0.09)

0.16

(0.12 to 0.20)

0.11

(0.05 to 0.18)

1.83

(0.93 to 2.73)

3.47

(2.18 to 4.77)

1.91

(1.06 to 2.77)

Logbook cohort (aged 1-3 years)

No in group

—

208 700

——— —— —

Total No of immunisations

—

3.23

(2.91 to 3.55)

4.15

(3.95 to 4.35)

——

0.92

(0.50 to 1.35)

——

1.28

(1.14 to 1.42)

Completely immunised

—

0.33

(0.23 to 0.44)

0.65

(0.58 to 0.72)

——

0.30

(0.15 to 0.45)

——

1.91

(1.36 to 2.45)

*Estimated by fitting multilevel mixed effect linear model, with clustering at village and household level.

†

Estimated by fitting multilevel mixed effect Poisson regression, with clustering at village and household level.

‡

For the analysis with BCG scar as outcome, there were 790 observations in control group, 239 in treatment A group, and 252 in treatment B group.

RESEARCH

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One implication of the increased immunisation rates

in the villages with camps with incentives (and in the

surrounding villages) is that they were busier than

those without incentives. Inspection of the logbook

showed that for any given camp, each day an average

of 4.5 immunisations were given without incentives

and 13.4 with incentives.

Interpretation, unanswered questions, and future research

Our results also suggest reasons that immunisation has

not been more widely embraced in developing coun-

tries. Previous work has emphasised the need to

strengthen health systems to achieve the millennium

development goals.

Our results suggest that to

achieve this strengthening, improving the supply

alone might not be enough: even a fully reliable supply

system has a relatively modest effect on uptake of

immunisation. In intervention A, even when access

was good and a social worker constantly reminded

parents of the benefits of immunisation, more than

80% did not get their children fully immunised. Never-

theless, more than 75% obtained the first injection

without the incentive and stopped attending the

camps only after two or three injections. This shows

that the parents do not have strong objections or fears

about immunisation, but that they are not persuaded

enough about its benefits to overcome the natural ten-

dency to delay a slightly costly activity (immunisation

is free, but it takes some time and effort to go to the

centre and get the child immunised, and the child

might have a fever afterwards). This fits the findings

of sociological research in India, where nurses describe

parents forgetting to bring their children to the immu-

nisation day, and where they are particularly careful to

manage even benign side effects of immunisation to

avoid discouraging parents from coming back.

also explains the tendency for children not to complete

the whole course of immunisation. Providing the len-

tils helps to overcome this procrastination because the

lentils make the occasion a small “plus” rather than a

small “minus.” Thus, in the case of preventive care,

small barriers might turn out to have large implica-

tions. Finding effective ways to overcome small bar-

riers might hold the key to large improvements in

immunisation rates and uptake of other preventive

health behaviours. In the case of immunisation, small

incentives coupled with regular delivery of services

seem to have the potential to play this role.

While we primarily examined the effect of small

incentives and supply improvement when they are cor-

rectly implemented, we need to know whether and

how such an incentive programme could be general-

ised. Under the National Rural Health Mission, the

government of India now has a health worker in each

village who is responsible for encouraging uptake of

preventive care. Furthermore, several Indian states,

including those with comparatively low immunisation

rates (Orissa, Bihar, Rajasthan), are already imple-

menting a “ camp” approach, where the regular auxili-

ary nurse midwife immunises children in villages on a

rotating schedule. We are hoping to conduct an impact

evaluation of the addition of small incentives to parents

in this structure, in collaboration with the state govern-

ment in India, to evaluate the potential of these types of

intervention to be adopted as large scale policies and

the challenges that would need to be overcome.

We tha nk Je nnifer Tobin for her help in editing this manus cript for

publication. She was funded by the Abdul Lati f Jameel Poverty Action lab.

Contributors: AVB, ED, and RG participa ted in the study design. ED a nd DK

completed the data analysis. All authors participated in data collection,

data interpret ation, a nd drafting of the manuscript. E D is guarantor.

Funding: T his study was funded by the Mac Arthur Fo undation. All

researchers declare that the research was entirely independent f rom the

funders. The funders had no involvement in t he design and conduct of the

study; collection, management, analysis, and interpretation of the data;

and preparation , review, or approval of the manuscript. The intervention

was funde d by the Evangelischer E ntwicklungdi enst (Germany), I nter

Church Cooperation for Development Cooperation (Netherlands), and

Plan International, through Seva Mandir comprehensive plan. None of the

funding organ isations participated in the design of the study (although

the MacAr thur Foun dation reviewed the design before making the

funding de cision), the data collection or analysis, or the decision to su bmit

the paper for publication.

Competi ng interests: All authors have completed the Unified Competing

Interest form at www.icmje.org/coi_disclosure.pdf (available on request

from the corresponding author) and declare that they have no competing

interests relevant to this work.

Ethical approval: This study was approved by the health ministry of the

government of Rajasthan, the office on the use of human su bjects at

Massachusetts Ins titute of Technology, and the ethics committee of

Vidhya Bhawan, the university which hosted the project in Udaipur.

Informed consent was first obt ained orally at the community level fro m

the research villages through village meeti ngs to which all adult members

of the village were invited. Individua l level informed consent was then

obtained orally from every family participating in the study.

Data sharing: Statistical code an d full dataset available from the

corresponding author at eduflo@mit.edu. Consen t was not obtained, but

the presented data are a nonymised a nd risk of identification is ext remely

low.

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Financial incentives, such as in conditional cash transfer programmes, can be effective in

promoting the use of certain preventive healthcare services

In settings with reliable immunisation services and a high pre-existing immunisation rate

such programmes have little impact on immunisation

WHAT THIS STUDY ADDS

In a setting with a low immunisation rate (under 6%), improving the reliability of services

modestly improved uptake of immunisation

Small non-financial incentives, combined with improved reliability, had large positive

impacts on the uptake of immunisation and were more cost effective

RESEARCH

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Accepted: 11 April 2010

RESEARCH

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Discussion

Banerjee and Duflo are both part of JPAL (The Abdul Latif Jameel Poverty Action Lab). JPAL's "mission is to reduce poverty by ensuring that policy is informed by scientific evidence. They do this through research, policy outreach, and training." JPAL's website: https://www.povertyactionlab.org/ These numbers have not improved significantly since this was published in 2010. 19.4 million children under the age of one year still do not receive basic vaccines, and 2-3 million people still die from diseases that can be prevent with vaccines. Source WHO: https://www.who.int/news-room/fact-sheets/detail/immunization-coverage This programs are what they sound like: the treatment is to give cash to individuals conditional on an objective (I️.e. getting immunized). The incentives (lentils in this case) are a key treatment that they are evaluating in this case, which is why Intervention A and B are identical, save for the addition of an incentive in Intervention B. This is key. If the measurement error was correlated with the treatment outcome or dependent variable, statistical analysis and drawing conclusions from the results of the trial would be difficult. This is a key visual presentation of the results. Note that the impact on neighboring village is a real example of the spillover effects of treatments. Many of the RCTs for development are longitudinal studies that take many years to complete. This study (where the baseline survey was administered in 2004 and the paper was not submitted in 2010) is not atypical for the field. The ultimate goal of JPAL and development economics is to evaluate different policies/treatments, and recommend the policies that work (based on scientific evidence from RCTs). The authors found that immunization camps with modest incentives do a great job of improving immunization rates in their trial, so they're recommending it! The program with incentives pays for itself on a per child basis. With any survey, particularly health-related surveys, there are many forms of bias that can creep into the results. In the case of recall bias: people can retrieve recollections regarding events or experiences differently (source: JPAL). Here is a list of different kinds of measurement error in surveys provided by JPAL: Completeness; Vagueness; Negatives; Overlapping Categories; Presumptions; Framing effect; Recall bias; Anchoring bias; Telescoping bias; Social desirability bias. Here is discussion of these biases in a JPAL presentation. Slides 46-70 are relevant: https://www.povertyactionlab.org/sites/default/files/documents/L2_Measurement_0.pdf Randomized controlled trials became a popular tool for policy evaluation in the US beginning in the 1970s, and the first well known trials happened in development in the 1990s (I️.e. Kremer et al, studies on Kenya (1994)). This approach, which is the gold standard of clinical trials and was developed for evaluating medical studies, involves randomly assigning subjects into two or more groups, treating the groups differently (i.e. treatment vs. control) and comparing their outcomes. They are the gold standard because they control for many sources of bias when testing how effective treatments are. Background presentation given by Duflo about randomized controlled trials (RCTs): http://pubdocs.worldbank.org/en/394531465569503682/Esther-Duflo-PRESENTATION.pdf BMJ, published in the UK, is a premier medical journal, and not a typical place for economists to publish their studies. However, for this policy paper on immunization, BMJ readers are the target audience for Banerjee, Duflo, et al. Clustered randomized controlled trials are different than individually randomized controlled trials in that rather than the randomization occurring at the individual participant level, there is a different unit of randomization. In this study, the unit of randomization occurs at the village level. This study design is popular in public health and education where it is difficult to randomize treatments to individuals. For more context on the invention of randomized double blind trials you should take a look at this annotated paper: [Inventing the randomized double-blind trial: the Nuremberg salt test of 1835](https://fermatslibrary.com/s/inventing-the-randomized-double-blind-trial-the-nuremberg-salt-test-of-1835) Esther Duflo and Abhijit Banerjee shared the 2019 Nobel prize in Economics along with Michael Kremer. Here is a press conference at MIT with them speaking about their research. To see more about this specific paper, tune in to around minute 27: http://news.mit.edu/2019/esther-duflo-abhijit-banerjee-win-2019-nobel-prize-economics-1014

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