Author: Rajan Gupta; Gaurav Pandey; Poonam Chaudhary; Saibal Kumar Pal
Title: SEIR and Regression Model based COVID-19 outbreak predictions in India Document date: 2020_4_3
ID: hf0jtfmx_6
Snippet: Mathematical models can be designed to stimulate the effect of disease within many levels. These models can be used to evaluate disease from within the host model i.e. influence interaction within the cells of the host to metapopulation model i.e. how its spread in geographically separated populations. The most important part of this model is to calculate the R0 value. The value of R0 tells about the contagiousness of disease. It is the fundament.....
Document: Mathematical models can be designed to stimulate the effect of disease within many levels. These models can be used to evaluate disease from within the host model i.e. influence interaction within the cells of the host to metapopulation model i.e. how its spread in geographically separated populations. The most important part of this model is to calculate the R0 value. The value of R0 tells about the contagiousness of disease. It is the fundamental goal of epidemiologists studying a new case. In simple terms R0 determines an average of what number of people can be affected by a single infected person over a course of time. If the value of R0 < 1, this signifies the spread is expected to stop. If the value of R0 = 1, this signifies the spread is stable or endemic. If the value of R0 >, 1 this signifies the spread in increasing in the absence of intervention as shown in Figure 1 . Equation (1) calculates the percentage of the population needed to be vaccinated to stabilize the spread of disease.
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