Applying SIR Modeling Data to Predict the Growth of COVID-19 Cases in Hidalgo County and Guide Public Policy Interventions
The results of this project demonstrate a practical application of the SIR (Susceptible, Infectious, or Recovered) epidemiological model to predict the growth of the COVID-19 case counts in Hidalgo County, TX. Using the standard SIR model with no stochastic variables considered, we looked at COVID-19 data from March 21, 2020, the day when the first positive case of COVID-19 was confirmed in Hidalgo County, through June 1, 2020. We considered plausible values for Hidalgo County for the probability of infection (pI) and contacts per day (cPD) by taking a survey from the current literature. Values for pI ranged from 0.0015 to 0.0703. While contacts per day ranged from 2.13 to 4.13. This resulted in corresponding infection rates (=pI×cPD) that ranged from 0.00319 to 0.219. Having such small pI, cPD, and 𝛽 values may be attributed to different reasons: (1) Hidalgo County has a low population density compared to other larger cities (2) The lifestyle and culture of the area (3) The majority of people were abiding by the Shelter-At-Home Order. To further reduce the spread of infection, it is necessary to continue to enact policies that preferably give the lowest statistically significant probability that the virus may be spread when people do need to be in public, such as being at least 9 or more feet apart, wearing a mask (preferably a surgical mask or an N95), wearing an eye shield, and properly washing hands <1 minute after touching something that may be contaminated with SARS-CoV-2 viral particles.
Reyes, Sidney Charm D., "Applying SIR Modeling Data to Predict the Growth of COVID-19 Cases in Hidalgo County and Guide Public Policy Interventions" (2020). MEDI 8127 Scholarly Activities Pre-Clerkship. 38.
Population Health and Biostatistics
Clinical Epidemiology Commons, Environmental Public Health Commons, Epidemiology Commons