Prioritising vaccines to people who need them the most is very important. There may be limits to vaccine supply due to manufacturing constraints as well as distribution constraints. It is important then to direct the distribution of vaccines towards people such that the benefit from the vaccine is maximized.
Vaccination serves multiple purposes. Firstly, and most importantly, it provides immunity to the recipient from the disease and reduces their risk of infection/death. Second, vaccines may also reduce the spread of the disease since immune persons are less likely to spread the disease. Third, vaccination and the subsequent reduction in infection can lead to a faster economic revival and increase people’s incomes. Hence we need to consider all these benefits from vaccination when determining the priority lists.
We build an epidemiological model to fit the dynamics of the infection across districts in India. The model is also used to generate projections of infections and deaths under different vaccination strategies. We also estimate the consumption per capita by district and age groups using data from monthly household surveys and estimate value of life years using models used in health economics.
There are two main levels at which prioritisation of vaccine delivery is important: across age groups and across geographies. In the visualisations below we focus on the prioritisation by geographies. There is a different value to vaccinating people in each district. This difference is due to the differences in current infection levels, the age composition of the district, urban-rural shares of the district and the economic condition of the district. For example, there will be more lives and life years saved by vaccinating the districts with a very high current and projected infection rate than a district where infection levels are projected to be low.
Consider vaccinating 25% of the population in a district in a short span of time. In the visualisations below we present the value from vaccinating 25% of the population in each district. The first measure is Life Years Saved (in years per million population). This measures the number of life years that would have been lost to the virus but were saved due to vaccination. It is reported in number of life years per million population and captures only the health benefits of vaccination. The second measure, Statistical Value of Life Years Saved (in Rs, per person), is an economic valuation of the health benefits of vaccines. This is measured in rupees and the reported value is per person. The third measure is the full Economic Value of Vaccination (in Rs, per person). This valuation measure accounts for the health and economic benefits of vaccines. This is measured in rupees and is reported per person.
Map interpretation: The districts with a higher number have a greater value of vaccination currently. Hence if a state government wishes to maximize any of these valuation measures, they can distribute more vaccines in districts with a higher valuation.
Note: The calculations presented here use publicly available data on infections, deaths, and other variables. If a state government wishes to share more data available with them, we’d be happy to run customized calculations by state.
Details of the model used will be shared shortly.
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