During emerging infectious disease outbreaks, such as the current novel coronavirus (COVID-19) pandemic, mathematical models are important tools to help inform public health recommendations and best utilization of limited resources. This research will develop and analyze data-driven mathematical models to predict the spread and evaluate the success of various public health intervention strategies to control COVID-19 in the US and abroad. The models will account for the characteristics of the pathogen, the variation of transmission that occur within community and in hospital settings, and geographical difference in transmission. The broader impacts from these models will provide real-time information to assist public health officials and decision-makers in making critical decisions on COVID-19 control policies and resource allocation.
Standard modeling approach such as compartmental population-based approach may not be suitable for modeling the spread of COVID-19, due to the high-level of heterogeneity of such systems, disease pathways, population makeup, host interactions on different levels of organization (household, workplace/school, social activities), and adaptive features of human behavior. The investigators will employ an individual-based modeling approach (IBM) that will accommodate such local heterogeneities. The investigators will use social, demographic, and epidemiological data of COVID-19 cases in the US and Korea, as well as hospital-level and city-level contact tracing data of COVID-19 in Wuhan, China, to parameterize their models. First, they will develop an IBM hospital-based model to explore different hospital-based interventions for mitigating the risk of nosocomial transmission of COVID-19 between patients and healthcare workers. Second, they will develop an IBM community-based model to evaluate and identify optimal non-pharmaceutical and potential pharmaceutical interventions for COVID-19 control in different local communities (city-county scale). The non-pharmaceutical interventions will include, amongst others: case isolation at home or hospitals, voluntary self-quarantine, stopping mass gathering, closure of schools, universities, or workplaces, and social distancing such as reduction of contacts, wearing of protective masks, and reduction of individuals' movements. Pharmaceutical interventions will include novel vaccines and antiviral therapies.
This RAPID award is made by the Ecology and Evolution of Infectious Diseases Program in the Division of Environmental Biology, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act
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.
