Started in December 2019, the novel coronavirus (known to cause a respiratory disease known as COVID-19) has spread rapidly and broadly and is proving to be one of the most devastating events that affect the health and well-being of humans all around the world. A key scientific goal concerning COVID-19 is to develop mathematical models that help in understanding and predicting its spreading behavior, as well as supporting guidelines on what can be done to limit its spread. In this project, the PIs aim to achieve these goals by applying their recent findings on a new epidemic model to the spread of COVID-19. The PIs will work on a model that considers the possibility of COVID-19 mutating into different strains with different spreading characteristics. By also considering changes in the spreading behavior of COVID-19 due to environmental factors and changes in human behavior (seasonal changes, travel bans, etc.), they aim to obtain results that will help assess the effectiveness of countermeasures that can be taken against the spread of the virus and to help better prepare for different mutation scenarios, including worst-cases. Most existing models of epidemics assume that an infectious individual passes the same pathogen strain that she was infected with to a susceptible individual in her contact network. This assumption may not hold in real-life as pathogens often evolve over time, and the ways a pathogen evolves might lead to significant changes in its spreading dynamics. This project aims to improve the state-of-the-art mathematical and computational models for predicting the spread of COVID-19 to incorporate the effects of evolution and mutations. This will be done by leveraging recent work of the PIs in which they developed a mathematical model to predict the spreading dynamics for multiple-strain epidemics models with mutations. By incorporating the potential changes in the reproduction number R0 (due to countermeasures or mutations), the PIs aim to obtain a better understanding of the future progress of the COVID-19 spread; obtain different predictions of the spread of COVID-19 under different scenarios including extensive bans on travel, school/shop closures, as well as potential evolution into different strains; and add to the public discourse on the expected effectiveness of various countermeasures that can be taken to slow down the spread of COVID-19. Project outcomes will be disseminated broadly and incorporated into teaching curricula. The project will also engage students from underrepresented groups.
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.
