Many low- and middle-income countries face limited supply of vaccines. In such situations it is imperative to devise vaccination rollout strategies that maximize the cost-effectiveness of these limited vaccine stocks. For instance, it may seem that selectively targeting regions with lower seroprevalence (e.g., rural areas) may be more effective in protecting more susceptible individuals than regions with higher seroprevalence (e.g., urban areas) that have fewer susceptible individuals. However, these areas may also have different reproduction rates which are the core drivers of different seroprevalence. Similarly, cost of supplying vaccines to these regions may be different. As a result, it is not obvious if, and when, such seroprevalence driven strategies may be more effective than uniform vaccine rollout. We develop a modeling framework that combines transmission modeling with supply chain modeling to answer this question and illustrate its utility using data on COVID-19 pandemic for the state of Punjab.
