RAPID: Joint Epidemiological and Macroeconomic Outcomes from Non-Pharmaceutical Interventions in Response to the COVID-19 Pandemic
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: unknown
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$196,620Funder
National Science Foundation (NSF)Principal Investigator
James StockResearch Location
United States of AmericaLead Research Institution
Harvard UniversityResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease transmission dynamics
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
Abstract
The initial shutdown of the US economy in March 2020 resulted in a peak and a slow decline in the death rate from COVID-19, but at a tremendous cost to the economy, with the April 2020 seeing the highest rate of unemployment since the Great Depression. Urgent questions now concern how to reopen the economy in a way that gets workers back to work while controlling the spread of the disease. While intuition might suggest general directions, ultimately a quantitative understanding of the effects of proposed reopening plans is needed to guide a safe and durable reopening. This project will provide a granular, integrated modeling system capable of providing internally consistent joint paths for epidemiological and economic outcomes. Doing so entails merging epidemiological models and sectoral economic models at a sufficient level of detail to provide quantitative assessments of detailed non-pharmaceutical interventions (NPIs), such as sectoral-level reopening strategies, testing and quarantine, school closings, and the use of masks and gloves at the workplace, which has immediate substantial broader impacts for the economy and the society.
At a technical level, the research will merge an age-based epidemiological SEIRD (Susceptible, Exposed, Infectious, Recovered and Dead) model with a nonlinear input-output model of the US economy. Closure and reopening paths are specified at a granular sector level, where sectors are characterized by different age distributions of workers and different degrees of proximity and contacts at the workplace. NPIs affect infections, quarantine, and deaths, which, along with direct labor supply and other shocks from the NPIs, feed into the economic model. The age structure of the SEIRD model allows examination of detailed age-specific and activity-specific NPIs. The research will extend the existing nonlinear input-output structure to labor market frictions and to endogenous shifts in labor supply and consumption demand in response to the epidemic. The result will be a quantitative framework for assessing the joint path of the epidemic and the economy at a level of granularity currently not available.
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.
The initial shutdown of the US economy in March 2020 resulted in a peak and a slow decline in the death rate from COVID-19, but at a tremendous cost to the economy, with the April 2020 seeing the highest rate of unemployment since the Great Depression. Urgent questions now concern how to reopen the economy in a way that gets workers back to work while controlling the spread of the disease. While intuition might suggest general directions, ultimately a quantitative understanding of the effects of proposed reopening plans is needed to guide a safe and durable reopening. This project will provide a granular, integrated modeling system capable of providing internally consistent joint paths for epidemiological and economic outcomes. Doing so entails merging epidemiological models and sectoral economic models at a sufficient level of detail to provide quantitative assessments of detailed non-pharmaceutical interventions (NPIs), such as sectoral-level reopening strategies, testing and quarantine, school closings, and the use of masks and gloves at the workplace, which has immediate substantial broader impacts for the economy and the society.
At a technical level, the research will merge an age-based epidemiological SEIRD (Susceptible, Exposed, Infectious, Recovered and Dead) model with a nonlinear input-output model of the US economy. Closure and reopening paths are specified at a granular sector level, where sectors are characterized by different age distributions of workers and different degrees of proximity and contacts at the workplace. NPIs affect infections, quarantine, and deaths, which, along with direct labor supply and other shocks from the NPIs, feed into the economic model. The age structure of the SEIRD model allows examination of detailed age-specific and activity-specific NPIs. The research will extend the existing nonlinear input-output structure to labor market frictions and to endogenous shifts in labor supply and consumption demand in response to the epidemic. The result will be a quantitative framework for assessing the joint path of the epidemic and the economy at a level of granularity currently not available.
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.