A Computational Model for Estimating the Progression of COVID-19 Cases in the US West and East Coasts

Yao Yu Yeo; Yao-Rui Yeo; Wan-Jin Yeo

One way to mitigate the spread of COVID-19 is to successfully isolate more infected people, i.e. to have a higher relative proportion of over . That outcome should be achieved when defective testing kits are replaced and more testing kits are allocated, so that more exposed people can be tested and isolated accordingly. For instance, if 50% more people had been tested ( = 0.15) since the start of the outbreak, the model would predict 40% of the projected severity However, the sudden onset of COVID-19 and the overall unpreparedness of the United States make these data inaccessible. It should also be noted that while the global mortality during COVID-19 is currently 3.8%, it is noticeably different across nations [24] . As a result, we chose a 5% mortality rate ( = 0.05) in our quasi-worst-case scenario prediction of COVID-19 in the US. Other factors at a molecular level can further modulate our variables. For instance, the actual 0 in the US might be different as the transmissibility and infectivity of CoVs have been shown to be modulated by abiotic factors such as temperature and humidity [1] , and the robustness of host immunity further affects the etiology, pathogenesis, and overall virulence of CoVs [9] . As . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.