A Statistical Learning Regression Model utilized to determine predictive factors of social distancing during COVID-19 pandemic

Timothy A. Smith; Albert J. Boquet; Matthew Chin

doi:https://doi.org/10.14445/22315373/IJMTT-V66I11P504

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 66 | Issue 11 | Year 2020 | Article Id. IJMTT-V66I11P504 | DOI : https://doi.org/10.14445/22315373/IJMTT-V66I11P504

A Statistical Learning Regression Model utilized to determine predictive factors of social distancing during COVID-19 pandemic

Timothy A. Smith, Albert J. Boquet, Matthew Chin

Citation :

Timothy A. Smith, Albert J. Boquet, Matthew Chin, "A Statistical Learning Regression Model utilized to determine predictive factors of social distancing during COVID-19 pandemic," International Journal of Mathematics Trends and Technology (IJMTT), vol. 66, no. 11, pp. 60-66, 2020. Crossref, https://doi.org/10.14445/22315373/IJMTT-V66I11P504

Abstract

In an application of the mathematical theory of statistics, predictive regression modelling can be used to determine if there is a trend to predict the response variable of social distancing in terms of multiple predictor input “predictor” variables. In this study the social distancing is measured as the percentage reduction in average mobility by GPS records, and the mathematical results obtained are interpreted to determine what factors drive that response. This study was done on county level data from the state of Florida during the COVID-19 pandemic, and it is found that the most deterministic predictors are county population density along with median income.

Keywords

Regression, statistical machine learning, theory of infectious disease transmission & control. AMS classification: 62P99.

References

[1] Unacast Social Distancing Scoreboard https://www.unacast.com/covid19/social-distancing-scoreboard
[2] T. Smith, MA Self-Contained Course in the Mathematical theory of Statistics for Scientists & Engineers with an emphasis on predictive regression modelling & financial applications.” Embry Riddle Aeronautical University Creative Commons, 2019.
[3] G. James, D. Witten, T. Hastie and R. Tibshirani, An Introduction to Statistical Learning: with Applications in R.” Springer, 2013.
[4] T. Smith, “A Statistical Learning Model utilized to validate a well-know market hypothesis of the moving average “death cross.”, 2019 international journal of mathematical trends and technology, International Journal of Mathematics Trends and Technology 65.11 (2019):72-82.
[5] Miami Dade County COVID project data site https://rwilli5.github.io/MiamiCovidProject/Trajectory/
[6] Wikipedia list of Florida counties https://en.wikipedia.org/wiki/List_of_counties_in_Florida
[7] Florida Survey of Income https://www.countyhealthrankings.org/app/florida/2020/measure/factors/63/data
[8] Florida University Study of Demographics http://edr.state.fl.us/Content/population-demographics/data/PopulationEstimates2019.pdf