A Case Study on the Practical Use of Low-Fidelity Modeling to Mitigate the Spread of COVID-19 Amongst the Underserved Farmworker Community.

Abstract

In March of 2020, with the full magnitude of the COVID-19 pandemic yet to be seen, Costa and Martin released a report through the Economic Policy Institute noting that "To prevent infections and the spread of COVID-19 on farms, farm employers should be planning and implementing safety measures to protect their employees" (Costa D, Martin P, Coronavirus and farmworkers: farm employment, safety issues, and the H-2A guestworker program, Economic Policy Institute, https://www.epi.org/publication/coronavirus-and-farmworkers-h-2a/, 2020). The report goes on to provide multiple observations recognizing the seasonal nature of farm work, effects increased unemployment may have on the workforce, industry dependence on H-2A visa farm workers, impact school closings would have on worker availability, and includes recommendations for safety equipment, social distancing, as well as worker housing and transportation. This paper focuses on the worker housing component of those recommendations and describes an effort to rapidly develop and deploy a computationally efficient, web-based, low-fidelity mathematical model of COVID-19 spread in dormitory style housing to support education and mitigation strategies for the historically underserved farmworker community.