Health impact evaluation of Aspirational Districts Program in India: Evidence from National Family Health Survey.

The Aspirational District Program (ADP) is a unique initiative of Government of India launched in 2018 that aims to reduce inter-district multidimensional inequality. ADP aims to bring the least developed districts to catch up with the rest of the other districts in the country. The program is comprehensive in its scope as it targets improvement of several key development indicators spanning health and nutrition, education, agriculture and water resources, financial inclusion and skill development and basic infrastructure indicators. Aspirational districts (ADs) are eligible for enhanced funding and priority allocation of various initiatives undertaken by the central and the state governments. Our research estimates the causal impact of ADP on the targeted health and nutrition indicators using a combination of propensity score matching and difference-in-differences (PSM-DID). We use the fourth and fifth rounds of National Family Health Survey (NFHS) data collected in 2015-16 and 2019-21 respectively which serve as the pre and post-treatment data for our analysis. Moreover, we take advantage of the transparent mechanism outlined for the identification of ADs under ADP, which we use for propensity score matching for our PSM-DID. While we observe negative impact of ADP on early initiation of breastfeeding, we believe that the impact is confounded with the effects of Covid-19 since part of NFHS-5 data was collected during the pandemic. However, the negative impact of ADP on early initiation of breastfeeding disappears when we only use pre-covid data (i.e. data for districts from states surveyed before the pandemic). Additionally, using pre-covid data we find a reduction in the prevalence of underweight children younger than 5 years to an extent of 2 to 4 percentage points in ADs as an impact of ADP, which is robust across multiple specification. We do not find evidence of a positive or a negative impact of ADP on any other health and nutrition indicators. Future research efforts should be made towards impact evaluation of all the targeted indicators in order to get a comprehensive unbiased evaluation of ADP.

COVID-19 Vaccine Coverage in India: A District-Level Analysis.

India implemented the largest COVID-19 vaccination drive in the world, through which it vaccinated the majority of its population. Lessons from the Indian COVID-19 vaccination experience can be invaluable for other LMICs as well as for preparedness for future outbreaks. Our study is designed to explore the factors associated with COVID-19 vaccination coverage in India at the district level. We used data from COVID-19 vaccination in India combined with several other administrative data to create a unique data set that facilitated a spatio-temporal exploratory analysis by uncovering the factors associated with vaccination rates across different vaccination phases and districts. We found evidence that past reported infection rates were positively correlated with COVID-19 vaccination outcomes. Past cumulative COVID-19 deaths as a proportion of district populations were associated with lower COVID-19 vaccination, but the percentage of past reported infection was positively correlated with first-dose COVID-19 vaccination, which might indicate a positive role of higher awareness created by a higher reported infection rate. Districts that on average had a higher population burden per health centre were likely to have lower COVID-19 vaccination rates. Vaccination rates were lower in rural areas relative to urban areas, whereas the association with literacy rate was positive. Districts with a higher percentage of children with complete immunisation were associated with higher COVID-19 vaccination, whereas low vaccination was observed in districts that had higher percentages of wasted children. COVID-19 vaccination was lower among pregnant and lactating women. Higher vaccination was observed among populations with higher blood pressure and hypertension (which were a few of the co-morbidities associated with COVID-19 infection).