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

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 São 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 São 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 São 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.

The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil

“…For example, the concept of a super-spreader city can be refined to account for epidemiological hotspots encompassing several interconnected metropolitan territories that are common in several states, such as São Paulo, Rio de Janeiro and Minas Gerais. Indeed, the contiguous diffusion among highly interconnected cities within metropolitan areas has been shown to act as a complementary spreading mechanism shaping geographical patterns of COVID-19 cases along with the hierarchical propagation via long-distance trips involving cities of regional relevance 34 .…”

The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population

“…In the case of infectious diseases, previous research suggests that large metropolitan areas experience greater spread due to the larger number of people, their closer proximity and increased movement [ 5 , 29 , 42 – 44 ]. Fortaleza et al [ 45 ] observed hierarchical diffusion of COVID-19 from the largest cities to smaller settlements in Brazil. Similarly, Sirkeci and Yüceşahin [ 34 ] observe hierarchical diffusion of COVID-19 infection in countries including the United States, the United Kingdom, South Korea and Italy among others.…”

A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil

“…We widely analyze the general situation of the COVID-19 pandemic in the 26 Brazilian states and their capitals and the Federative Unit. Furthermore, because several interfering and interventional measures, including social distancing/isolating (quarantine and lockdown), mandatory use of face masks, and other government decisions about people lives and economic activities (reopening, flexibilization, and school returning) have been considered fundamental strategies to combat the COVID-19 pandemic 28 – 30 , we also correlated these measures with the epidemic curve in each state and capital.…”