Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases

Heather Z. Brooks; Mason A. Porter; Unchitta Kanjanasaratool; Yacoub H. Kureh

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Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases

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arxiv 2007.05495 v2 pith:DV5BSNLY submitted 2020-06-30 q-bio.OT math.DSmath.HOnlin.AOphysics.soc-ph

Heather Z. Brooks , Unchitta Kanjanasaratool , Yacoub H. Kureh , Mason A. Porter This is my paper

classification q-bio.OTmath.DSmath.HOnlin.AOphysics.soc-ph

keywords modelsspreaddiseasediseasesinfectiousmathematicalpandemicanalyzing

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The COVID-19 pandemic has led to significant changes in how people are currently living their lives. To determine how to best reduce the effects of the pandemic and start reopening societies, governments have drawn insights from mathematical models of the spread of infectious diseases. In this article, we give an introduction to a family of mathematical models (called "compartmental models") and discuss how the results of analyzing these models influence government policies and human behavior, such as encouraging mask wearing and physical distancing to help slow the spread of the disease.

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