MODELING COVID-19 WITH THE SUSCEPTIBLE-INFECTED-REMOVED MODEL

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https://hdl.handle.net/2142/125042

Title: MODELING COVID-19 WITH THE SUSCEPTIBLE-INFECTED-REMOVED MODEL
Author(s): Lim, Junyeob
Issue Date: 2020-05-01
Keyword(s): COVID-19, coronavirus, disease modeling, epidemiology, susceptible-infected-removed (SIR) model, suppression, public health countermeasures
Abstract: The susceptible-infected-removed (SIR) model characterizes an epidemic via a set of differential equations governing the change in the sizes of the susceptible, infected and removed portions of a population affected by the epidemic. The coronavirus disease 2019 (COVID-19) is a currently ongoing pandemic caused by a virus identified in Wuhan, China, in December 2019 that so far has infected millions and killed thousands of people globally. In this thesis, the trajectory of COVID-19 in three regions around the world is forecasted by fitting an SIR model to time series data of reported confirmed and recovered numbers of cases of COVID-19 in these regions. In addition, COVID-19 in the United States is forecasted using data before and after the enactment of suppression measures to contain the disease. Our findings validate the claims of public health officials on the effectiveness of suppression measures such as lockdown, social distancing and self-isolation at slowing down the spread of COVID-19.
Type of Resource: text
Language: eng

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