This presentation was made by Santanu Pramanik (Public Health Foundation of India)

1. Integrated Child Health and
Immunization Survey (INCHIS):
Objectives, Methodology and Challenges
Santanu Pramanik
Public Health Foundation of India
Delivering for Nutrition in India
Learnings from Implementation Research
November 9–10, 2016

2. Monitoring vaccination coverage
• Vaccination coverage is an important public
health indicator
– Levels and variation in coverage can influence
individual and collective immunity in the population
• High vaccination coverage is a good indicator of
accessibility and functionality of a health system
• The necessary condition in achieving coverage
goals is the ability to measure and monitor
coverage levels in the population at a regular
interval
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3. Methods to monitor coverage
• Administrative estimates: often unreliable due
to incomplete or inaccurate primary recording
of vaccinations, errors in compiling monthly
summary sheets, delayed or duplicate
reporting and inaccurate estimates of
population denominators
• Household surveys are often preferred over
administrative reports
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4. Accuracy of survey estimates
• Improperly designed sampling plan
• Insufficient sample size
• Poorly designed survey questionnaires
• Inaccurate (or absence of) sampling frame
• Lack of experience and commitment of field agencies
collecting data
• Limited involvement of research team during the training of
interviewers and monitoring of data collection activities
• Faulty interviewing techniques
• Inaccurate recording of vaccination details
• Erroneous digital data entry from paper questionnaire
• All these factors may contribute towards biased and/or
imprecise (unreliable) estimates
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5. Integrated Child Health and Immunization
Survey (INCHIS)
• Planned and designed by the Immunization
Technical Support Unit (ITSU) of the Ministry
of Health and Family Welfare (MoHFW)
• Objectives:
– Regular monitoring of immunization coverage
– Evaluation of a pan India immunization related
intervention termed as Mission Indradhanush (MI)
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6. Journey so far
• INCHIS is a nationally representative repeated
cross-sectional survey on different aspects of
immunization, including immunization
services at the health facility level
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Surveys State District Cluster Village Ward HHs
Sub-
centre
Planning
Unit
INCHIS-1 (Mar-
Apr 2015)
12 83 591 414 177 11,683 402 439
INCHIS-2 (Sep-
Oct 2015)
12 81 635 424 211 15,039 436 478
INCHIS-3 (Mar-
Apr 2016)
13 96 738 474 264 17,849 508 593

7. Methodology: Selection of states
• INCHIS was not designed as a one-time survey, rather a biannual
event, hence effective use of resources was crucial
• To achieve the goal of national representativeness in a resource-
effective way, a limited number of states were included in each
round selected through an appropriately stratified design
• All 29 states were stratified into six levels of development (based on
a composite index) and six geographic locations
• State level indicators used to construct the composite development
index:
– infant mortality rate
– female literacy rate
– proportion of stunted children
– full immunization coverage rate
– per capita net state domestic product
• Principal component analysis (PCA) technique was used to
construct the composite index
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8. Selection of states
• INCHIS collects data from a fixed set of states and adds new
states every round in order to cover the entire country in
four rounds
• In first two rounds, 12 states were included in the sample
– Six fixed states and six rotational states
• Fixed states: Bihar, Maharashtra, MP, Rajasthan, Telangana,
and UP
• Rotational states INCHIS-1: Tamil Nadu, Manipur,
Uttarakhand, Haryana, Odisha, and Andhra Pradesh
• Rotational states of INCHIS-2: Himachal Pradesh, Jammu &
Kashmir, Goa, Mizoram, West Bengal and Kerala
• The state selection method was designed to ensure
representation from each geographical region and
development category
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9. Sampling design
• Within a selected state, a three-stage
stratified sampling design was adopted
– At each stage, the sampling design was chosen to
select representative random sample
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10. Stage 1: Selection of Districts
• For the selection of districts, district-level data
from Census 2011 was considered as the
sampling frame
• Districts were stratified into 3 or 4 strata
• Strata were created based on a composite index
constructed using the following socioeconomic
characteristics: proportion of urban HHs,
percentage of SC/ST population, literacy rate,
proportion of HHs with latrine facility, and HHs
availing banking facility
• From each stratum 1-3 districts were selected
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11. Stratification of districts into four strata in Madhya Pradesh:
boxplot of socioeconomic indicators across strata
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12. Stage 2: Selection of Clusters
(villages/urban wards)
• For the selection of clusters, cluster-level 2011
Census data were considered as sampling frame
• Within a selected district, sampling frame of
villages and wards (separately) was arranged by
female literacy rate and clusters were drawn
using systematic sampling
• This design guarantees inclusion of clusters
covering the whole range of female literacy rate
within a district
• Number of clusters required within a state was
determined based on the sample size calculation
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13. Stage 3: Household and Health Facility
Selection
• A separate houselisting exercise was crucial for
implementing a probability sampling technique for HH
selection
• Complete listing of all eligible households in the selected
clusters was used as the sampling frame for selection of
HHs
• HHs with at least one child in the age group 0-23 months
were eligible for selection
• Children in the 0-23 month age group were considered as
opposed to the 12-23 used in other immunization surveys
• Selection of health facilities was linked to the sampled
clusters
– Sub-centres
– Planning units
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14. Survey Implementation
• Ethics approval for the study was obtained from the IEC
of PHFI
• Data collection for INCHIS was conducted by the field
agency Nielsen India Pvt. Ltd.
– Public Development & Sustainability unit
• Pen and paper interviewing (PAPI) method was used to
collect data
• Data collection involved two key components: 1)
houselisting of selected clusters and 2) administering
the household and health facility survey questionnaires
to selected household and health facilities
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15. Descriptive analysis using survey weights
• INCHIS adopts a three-stage stratified sampling design
which leads to unequal selection probabilities of
ultimate sampling units
• If individuals in certain subgroups are sampled at a
lower rate than individuals in other subgroups, then
their data can be thought to represent more individuals
in the population
– Otherwise, any estimation based on the sample may be
biased
• Survey weights incorporate differential selection
probabilities as well as adjustments for nonresponse
and incomplete sampling frame and/or mismatch
between sampling and population distributions
through poststratification
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16. Discussion
• Coverage error and measurement errors contribute to the
non-sampling error of survey estimates which is hard to
quantify
• Their magnitude can be controlled through a well-designed
and executed survey
• In the absence of readily available sampling frame of HHs, a
separate houselisting exercise was carried out for
implementing a probability sampling for HH selection
• This procedure guaranteed that each HH had a positive
probability of being selected and reduced coverage bias
that could have arisen from incomplete sampling frame
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17. Minimizing selection bias
• Upon receiving houselisting data in electronic
format from Nielsen, the INCHIS team did the
selection of HHs for all sampled clusters and
shared with Nielsen for conducting the main
survey
• This back and forth between Nielsen and ITSU
minimizes selection bias and prevents from
adopting convenient sampling in the field
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18. Minimizing measurement errors
• To define vaccination coverage rate, we
combined information from vaccination card
(if available) and mother’s recall in order to
reduce instances of misclassification
• In the absence of valid date in the card, the
rationale behind going back to recall is that
card may also be incomplete
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19. • Acknowledgement: INCHIS team
Thank You!
Questions/Comments
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