Abstract
We evaluate the impact of oral polio vaccines on the incidence of all disabilities (locomotor, hearing, visual, speech, and mental) in India, focusing on polio-related disability, which constitutes the largest fraction of locomotor disabilities. Polio was hyperendemic in India even as recently as the early 1990s, but the country was declared wild polio virus-free in 2014. Intent-to-treat effects from difference-in-differences with multiple time period models that condition on demographic and socio-economic characteristics reveal that access to oral polio vaccines in the year of birth reduced the incidence of any disability, locomotor disability, and polio-related disability by 20.5%, 11.6%, and 7.2%, respectively, signaling substantial gains. Impacts on any disability underline that polio vaccines had positive spillover effects on other disability categories as well. The eradication of polio in India, while relatively late, brought significant health benefits and is a notable health economics success story in a develo** context.
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Data availability
The NSSO disability modules from 2002 and 2018 are available from the National Statistical Office at the Government of India’s Ministry of Statistics and Program Implementation at https://www.mospi.gov.in/national-sample-survey-officensso. The National Family Health Surveys are publicly available at https://dhsprogram.com/data/available-datasets.cfm. The Family Planning Statistics of India manuals are publicly available at https://nhm.gov.in/index1.php?lang=1&level=3&sublinkid=957&lid=405. The usual disclaimer applies.
Change history
24 February 2024
The correct email should be svsubram@hsph.harvard.edu and not svsubra@hsph.harvard.edu.
Notes
Notable research in this area includes Daramola et al. (2022), Meyer (2021), Butikofer and Salvanes (2020), Egedeso et al. (2020), Alsan and Goldin (2019), Mauricio and Noymer (2019), Gensowski et al. (2019), Serratos-Sotelo et al. (2019), Beach et al. (2016), Barreca (2010), Bleakley and Lange (2009), Currie et al. (2008), Cutler and Miller (2007), Bleakley (2007), and Almond (2006).
A reason for this was that at independence in 1947, India invested in control of tuberculosis, malaria and leprosy, ignoring polio as a low priority disease with a high cost of eradication (John and Vashishtha 2013).
The majority of individuals (99%) report only one disability, either locomotor, visual, hearing, speech, or mental, in our sample.
District Level Household and Facility Survey (DLHS) data track the presence of cold-storage facilities which might be used to proxy for vaccine access. However, the NFHS data are widely considered to be more reliable in its immunization measures as compared to the DLHS.
We cannot use the month information as NSSO does not report an individual’s month of birth.
This is the procedure used to minimize measurement error. Moreover, given panel B of Fig. 1 that shows almost universal adoption from mid 1990s on, we are less concerned with selection bias in take-up (or lack of it). See Huang and Danovaro-Holliday (2021) for a review of the literature that collects immunization information from the DHS surveys.
In our data, there were 382 districts in 25 states and union territories in the earliest time period and 640 districts in 36 states and union territories in the latest time period.
The 12.6%, 50.6%, and 21.5% measures for any locomotor and polio disability, respectively, are weighted averages of proportional estimates. That is, if we take the ratio of those with any disability to the number of people in the sample, the weighted mean of that ratio is 12.6%. Similarly, for the other two estimates. These proportions are not used in any of the regressions in the paper; they are reported for descriptive purposes mainly and their unweighted counterparts are depicted in panel A of Fig. 1.
An advantage of this relatively younger age group is that we are more confident that their current district of residence is also likely to be their district of birth. While Munshi and Rosenzweig (2009) note that permanent migration rates in India are relatively low, the average age group of our sample gives us additional confidence that we are tracking district-level exposure at the time of birth relatively accurately.
We include the i subscript because even though the analysis conditions on districts and year, exposure to OPVs can differ by individual and household level characteristics as noted in Hajizadeh (2018), Pande and Yazbek (2003), and Shrivastwa et al. (2015) (please see discussion in Section 4.2. of the paper). Consequently, our main results reported in Table 2 include the controls in panels C, D, E, and F of Appendix Table 1 which are individual and household specific.
This might lead us to underestimate average treatment effects on the treated, that is, we find a lower bound for this measure since we potentially include some people who might not have received the vaccine.
Note that tests show that pre-treatment (pre-OPV access) health and socio-economic characteristics in districts that received OPVs relatively early do not differ from those in districts that received them relatively late, as reported in Appendix Table 2 and discussed below.
We collected additional socio-economic variables at the state level in the initial period including per capita net state domestic product in 1990, the literacy rate in 1991 and per capita expenditures on health at the state level in 1991 from the National Health Profile of India published by the Ministry of Health and Family Welfare, and the Handbook of Statistics on Indian States published by the Reserve Bank of India. We then included these variables interacted with time trends in the main results reported in Table 2 to find that if anything, our results become even larger. For example, the coefficient on any disability implies an 84.9% decline on average after the district gains access to OPVs. These results are available on request as we are reluctant to include directly in the paper because the sample size is about 7000 observations lower in this case. That is because we have a lot of missing values in these variables for relatively big states that did not exist in the late 1980s and 1990s (like Uttarakhand, Jharkhand, and Chhattisgarh), which do, however, exist in our disability data from 2002 and 2018.
These results are available on request (locomotor-related disability results are reported in the paper).
Changes in parental behavior may also play a complementary role. Unfortunately, our disability data does not contain any health-related information specific to parents and children beyond that which we already include. We are thus unable to examine this channel closely. There is some evidence that years of exposure is positively correlated to completion of primary/middle school and to an indicator variable that the individual is married. These factors may have a protective influence on diverse disability types, thus possibly accounting for some of the positive externalities of OPVs.
We could have used the amount of land owned instead, but not every household in our sample owns land.
We lack data to examine in this aspect in detail.
Focusing on the estimated ITT coefficient of −0.075 for polio-related disability in Table 2 which implies a 7.2% decline on average when a district gains access, and using Nandi et al. (2016) which notes a pre-vaccine polio incidence rate of 15 per 100,000 people, and based on the district average population of about 1.8 million people from the (2011) Census of India, this ITT coefficient translates to about 20.4 fewer people on average per district contracting polio after the vaccination campaign. The associated economic productivity value based on estimates in Nandi et al. (2016) (which calculates the number of paralytic cases averted and the associated productivity gain based on a value of statistical life method) is approximately 2011 USD $8.9 million per district. Since India had 640 districts in the 2011 Census year, this is a total benefit of about 2011 USD 5.6 billion (2022 USD 6.9 billion). On the cost side, Prinja et al. (2014) note that the cost of the Pulse Polio campaign over the relevant years was $28.80 per child. Given that the 2011 census counts about 164.5 million children in the vaccine eligible group of 0–6 years, this is an approximate total cost of about 2011 USD 4.7 billion or 2022 USD 5.8 billion (the 2011 census does not report statistics for only the 0–5-year age group; the total cost is thus likely to be somewhat of an over-estimate).
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Acknowledgements
Thanks to editor ** Chen, three anonymous reviewers, Terence Cheng, Sara Curran, Laxmi Kant Dwivedi, David W. Johnston, Kalle Hirvonen, Albert Ma, Shiko Maruyama, Sanjay Mohanty, Fernando Rios-Avila, Abhishek Singh, Tom Vogl, and to participants at the Asian Meeting of the Econometric Society, South Central and Western Asia, and the PAA Applied Demography Conference. Zi Long provided excellent research assistance.
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Ambade, M., Menon, N. & Subramanian, S.V. The impact of early-life access to oral polio vaccines on disability: evidence from India. J Popul Econ 37, 23 (2024). https://doi.org/10.1007/s00148-024-01006-x
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DOI: https://doi.org/10.1007/s00148-024-01006-x
Keywords
- Polio
- Locomotor
- Disability
- Acute flaccid paralysis
- Oral polio vaccines
- Early-life
- Childhood
- Difference-in-differences with multiple time period models