Disease Modeling of COVID-19: Beira and Sebastião 2021 (an analysis)
Hope Hahn, Name Redacted, Name Redacted
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Introduction
Disease modeling is of significant importance during this day and age due to the virus SARS-CoV-2 which has caused the ongoing pandemic of coronavirus disease 2019 (COVID-19). With all the uncertainty around its dynamics, many scientists have been attempting to produce models that will allow us to understand future spread and dynamics. COVID-19 is modeled by many papers using some variation of a susceptible, exposed, infected, recovered, and dead (SEIRD) model (Bae et al. 2020, Selvamuthu et al. 2021, Wen et al. 2020). However, as we are actively living through this pandemic, we observe human behaviors and government mandates that appear to affect the spread of the disease, so it is important to incorporate this knowledge when modeling COVID-19. Beira and Sebastião 2021 uses a slightly different model than the SEIRD model, which they modified to account for human behavior. They used the PSEIRD(S) model - which was presented by Beira et al. 2020 - in which a protected group (P) is added, given that people can try to actively avoid disease through different behaviors such as social distancing.
After seeing a huge outbreak of COVID-19 after Christmas in Portugal, the authors used data from Portugal to produce a model to understand multi-wave dynamics taking into account social activities and government mandates. The goal of this paper was to be able to predict the patterns of outbreaks given human behavior, and they aimed to create a model that is able to fit data from any country to project disease dynamics.