The use of health geography modeling to understand early dispersion of COVID-19 in Sao Paulo, Brazil

Author(s)

Fortaleza, Carlos Magno Castelo Branco ^[1] ; Guimaraes, Raul Borges ^[2] ; Catao, Rafael de Castro ^[3] ; Ferreira, Claudia Pio ^[4] ; Berg de Almeida, Gabriel ^[1] ; Nogueira Vilches, Thomas ^[5] ; Pugliesi, Edmur ^[2]

Affiliation

^[1] Sao Paulo State Univ UNESP, Botucatu Med Sch, Dept Infect Dis, Botucatu, SP - Brazil

^[2] Sao Paulo State Univ UNESP, Fac Sci & Technol, Dept Geog, Presidente Prudente, SP - Brazil

^[3] Univ Fed Espirito Santo, Dept Geog, Vitoria, ES - Brazil

^[4] Sao Paulo State Univ UNESP, Inst Biosci, Botucatu, SP - Brazil

^[5] Univ Campinas UNICAMP, Inst Math Stat & Sci Computat, Campinas, SP - Brazil

• Document type: Journal article
• Source: PLoS One; v. 16, n. 1 JAN 7 2021.
• Web of Science Citations: 3

Abstract

Public health policies to contain the spread of COVID-19 rely mainly on non-pharmacological measures. Those measures, especially social distancing, are a challenge for developing countries, such as Brazil. In Sao Paulo, the most populous state in Brazil (45 million inhabitants), most COVID-19 cases up to April 18th were reported in the Capital and metropolitan area. However, the inner municipalities, where 20 million people live, are also at risk. As governmental authorities discuss the loosening of measures for restricting population mobility, it is urgent to analyze the routes of dispersion of COVID-19 in Sao Paulo territory. We hypothesize that urban hierarchy is the main responsible for the disease spreading, and we identify the hotspots and the main routes of virus movement from the metropolis to the inner state. In this ecological study, we use geographic models of population mobility to check for patterns for the spread of SARS-CoV-2 infection. We identify two patterns based on surveillance data: one by contiguous diffusion from the capital metropolitan area, and the other hierarchical with long-distance spread through major highways that connects Sao Paulo city with cities of regional relevance. This knowledge can provide real-time responses to support public health strategies, optimizing the use of resources in order to minimize disease impact on population and economy. (AU)

• FAPESP's process: 18/24811-1 - Mathematical modelling for the transmission of schistosomiasis in low-prevalence areas
• Grantee: Thomas Nogueira Vilches
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 18/24058-1 - Arboviroses: dynamics and vector control
• Grantee: Cláudia Pio Ferreira
• Support Opportunities: Regular Research Grants