In the era of the novel coronavirus disease of 2019, COVID- 19, there are many who have attempted to model various aspects of how the pandemic would play out, based on when hospitals and health care providers would be overwhelmed Others have attempted to model the relative effectiveness of various public health attempts to contain it such as social distancing, hand washing, and masking Still others have made models of the peaks and valleys of reopening the economy with spikes of new infection A robust approach to each of these applications is the Susceptible-Infected-Recovered (SIR) model that is presented in this manuscript: a simple, practical, and useful model albeit as imperfect as any such attempt at predicting an uncertain and unknown future Yet, the events can be modeled, predicted, and done within the noise of the situations that affect their validity [ABSTRACT FROM AUTHOR] Copyright of Texas Public Health Journal is the property of Texas Public Health Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )
Simple COVID-19 Susceptible-Infected-Recovered Model with Social Distancing Levels Across Time: A West Texas Example