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

To model the COVID-19 outbreak, we use a variant of the SEIR model (see [7, 18] for some examples). We mainly focus on the East and West Coast of the United States. We assume that there is no travel between the different population zones, and that the natural birth and death rates are equal. In Figure 1 , S represents the susceptible population, and E represents the exposed population (i.e. individuals who have been infected but are not yet themselves infectious). The infected population I divided into two groups, and , wherein the subscripts H and C stand for "hospital" and "community" respectively. represents those that are infected and isolated (such as those that have been pre-tested and found to carry the virus), and for those that are infected but not isolated (such as those with unreported cases or present mild symptoms that are overlooked). Thus, people in is unable to spread the virus whereas those in can spread the virus. As testing kits in the US are currently in low supply, the current model projects significantly higher levels of than at any given point in time. Once infected, there are two possibilities: either recovery or death. These outcomes are represented by the populations R and D above, with . 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.