NSF Award
2210382
This project will develop a mathematical model of SARS-CoV-2 transmission that takes into account the use of several types of vaccines, genetic variation in the virus, and multiple age groups. The COVID-19 pandemic has produced immense suffering throughout the world, with over 5 million deaths as of January 2022, but low- and middle-income countries have carried an increased burden both from the health crisis and from the economic crisis arising from the pandemic. While high-income countries have vaccinated the majority of their eligible populations, less than 2.3% of the population of low-income countries have been immunized. This is expected to change in the following months, as more vaccines will be available to these countries. As more vaccines become available to them, public health officials in these countries will likely develop vaccine allocation strategies based on a mix of vaccines (there are currently over 20 vaccines available worldwide) that differ in effectiveness against circulating variants, arriving at different times, and in different quantities. However, these countries usually lack resources to develop models to guide vaccine allocation. This project will develop a free, user-friendly online tool that will simulate country-specific multi-strain COVID-19 epidemics in conjunction with vaccination campaigns with multiple vaccines. By simulating the epidemic and producing key outcomes including expected numbers of deaths, hospitalizations, and cases, this tool will allow decision-makers in up to 177 countries around the world to compare scenarios of vaccine allocation.<br/> <br/>This project will develop a multi-strain, multi-vaccines mathematical model of SARS-CoV-2 transmission and vaccination that will then be used to develop an open-source, online, free, user-friendly comparative tool for vaccine allocation. This tool has the potential to to evaluate in-silico different vaccine allocations with country- or region-specific characteristics. The tool will allow users to input a variety of country-specific parameters including: the type, effectiveness and quantities (coverage, number of doses, distribution) of vaccines; co-circulating variants with different transmissibility, virulence, and cross-protection; social distancing interventions, demographics; and variable time horizons. It will simulate different vaccine allocation scenarios and project for each of them key outcomes (expected numbers of deaths, hospitalizations, and cases). <br/><br/>This project was funded in collaboration with the CDC to support rapid-response research projects to further advance federal infectious disease modeling capabilities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
