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A multivariate analysis on spatiotemporal evolution of Covid-19 in Brazil
Marcio Luis Ferreira Nascimento1,2
1Nano Group @ UFBA, Department of Chemical Engineering, Polytechnic School, Federal University of Bahia, Rua Aristides Novis 2, Federação, 40210 - 630, Salvador, BA, Brazil.
Infectious Disease Modelling
|September 14, 2020
Summary
This study analyzed COVID-19 spread in Brazil using health, geographic, and economic data. Five clusters of states emerged, highlighting critical hotspots and correlations between cases, deaths, and GDP.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- The COVID-19 pandemic presented unprecedented challenges to public health systems globally.
- Understanding the spatiotemporal distribution of cases and deaths is crucial for effective control strategies.
Purpose of the Study:
- To analyze and classify the spatiotemporal distribution of COVID-19 in Brazilian states.
- To identify distinct clusters of states based on epidemiological, geographic, and socioeconomic indicators.
Main Methods:
- Utilized multivariate statistical methods, including k-means clustering and factor analysis.
- Analyzed data from April 3rd to August 8th, 2020, encompassing health, geographic, and socioeconomic variables.
- Classified Brazilian states into five distinct clusters based on 10 key indicators.
Main Results:
- Identified five clusters representing different spatiotemporal patterns of COVID-19 spread across Brazilian states.
- Observed dynamic group changes between states and clusters over time.
- Found correlations between COVID-19 cases/deaths and Gross Domestic Product (GDP), identifying key hotspots.
Conclusions:
- The multivariate classification provides a comprehensive overview of the COVID-19 epidemic in Brazil.
- Findings can inform targeted public health interventions and future research on virus transmission control.
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