The first vertical dotted line marks the introduction of São Paulo’s stay-at-home order. The second marks the federal government’s recommendation to wear face coverings. The left-hand axis represents average weekly growth in the number of confirmed cases of COVID-19 in cities across the state of São Paulo (image: CeMEAI)

Published on 03/19/2021

By Elton Alisson  |  Agência FAPESP – In the first few weeks of the coronavirus pandemic, social isolation and face covering reduced transmission of SARS-CoV-2 by 15% in São Paulo, Brazil’s largest city, and by 25% in Brasília, the nation’s capital. São Paulo was the first epicenter of the COVID-19 epidemic in Brazil.

The findings come from a study published on the preprint platform medRxiv and are not yet peer-reviewed. The authors are researchers affiliated with the Center for Research in Mathematical Sciences Applied to Industry (CeMEAI), one of the Research, Innovation and Dissemination Centers (RIDCs) funded by FAPESP. CeMEAI is hosted by the University of São Paulo’s Institute of Mathematics and Computer Sciences (ICMC-USP) in São Carlos.

“We found that the imposition of lockdowns and social isolation by state governments, in conjunction with the federal government’s advice to wear face coverings, were effective public health measures that contributed to a reduction in transmission of the coronavirus in the initial phase of the COVID-19 epidemic in Brazil, when contagion rates were rising exponentially,” Zhao Liang, one of the authors of the study, told Agência FAPESP. Zhao is a professor at the University of São Paulo’s Ribeirão Preto School of Philosophy, Science and Letters (FFCLRP-USP).

To reach these conclusions, the researchers analyzed the available data using a mathematical model to estimate contagion rates per city around Brazil. Developed as part of a project supported by FAPESP, the model is based on the SIR (susceptible-infectious-recovered) epidemiological model and the spectral network approach.

Cities were represented as network nodes or vertices and possible transmission of the virus between cities as links, using actual data for each of the cities concerned. Nodes and links were calculated by machine learning algorithms and complex network analysis.

Using the model, the researchers analyzed and quantitatively compared the effectiveness of two public health measures implemented successively to contain transmission of COVID-19 at the start of the epidemic in Brazil. The first measure was the imposition of confinement or lockdown regimes by state governments in late March. The second was the recommendation to wear face masks issued by the federal government in early April.

The results showed that the stay-at-home order in São Paulo, the first in Brazil to announce a confinement regime, reduced the average rate of growth in confirmed cases in cities across the state. The measure came into force on March 24, seven days after the first death from COVID-19 was reported in Brazil, by which time São Paulo was the epicenter of the epidemic in Brazil, with 745 confirmed cases and 30 deaths.

However, the most substantial reduction occurred after the federal government recommended face covering. The fall in transmission rates was especially steep in cities that did not impose strict lockdowns at the start of the epidemic.

“This may have been because there was more contact between people in these cities, so wearing face masks played a key role in limiting transmission of the virus,” Zhao said.

The researchers simulated counterfactual scenarios to predict what would have happened without stay-at-home orders and mask wearing. The simulations also used the SIR model and spectral networking. The results showed significant differences in the effectiveness of these measures from one city to another, given the differences in viral transmission and mortality rates.

Based on confirmed case data for over 2,700 cities (approximately half the national total) until May 8, the model indicated that social confinement and mask wearing resulted in a reduction of 15% on average at the time the epidemic was peaking in the city of São Paulo, for example, and a reduction of 25% in Brasília.

“We hope this methodology for quantifying the effectiveness of public health policies will contribute to awareness by government and society of the importance of social isolation and face covering to contain the pandemic,” Zhao said.

Controversy

Some countries have been reluctant to impose stay-at-home or social isolation regimes because they consider such measures ineffectual. The same controversy explains discrepancies in the policies followed by cities, states and the federal government in Brazil.

“We continue to face these disagreements about social isolation in Brazil, where there’s been a lot of pressure for economic reopening and relaxation of confinement,” said Zhao, a naturalized Brazilian citizen born in China. In 1988, he graduated in computer science from the University of Wuhan, where the coronavirus outbreak began.

For Zhao, China’s lockdown was effective because of the country’s system of strict social control and the use of big data technologies to keep check on community transmission by tracking every new case, tracing everyone who had contact with the infected individual and isolating them to slow the spread.

“China is a very different country and implemented controls that would not be feasible in Brazil,” he said. “However, there’s no question that tight control and social isolation plus the use of big data technologies enabled China to contain the outbreak in its initial phase.”

The article “Quantitative analysis of the effectiveness of public health measures on COVID-19 transmission” (doi: 10.1101/2020.05.15.20102988) by Thiago Christiano Silva, Leandro Anghinoni and Liang Zhao can be downloaded from medRxiv at: www.medrxiv.org/content/10.1101/2020.05.15.20102988v1.

 

Source: https://agencia.fapesp.br/33684