Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data

Oliveira, Silvano Barbosa de; Pôrto, Victor Bertollo Gomes; Ganem, Fabiana; Mendes, Fabio Macedo; Almirón, María; Oliveira, Wanderson Kleber de; Fantinato, Francieli Fontana Sutile Tardetti; Almeida, Walquíria Aparecida Ferreira de; Borges, Abel Pereira de Macedo; Pinheiro, Hector N. B.; Oliveira, Raíza dos Santos; Andrews, Jason R.; Faria, Nuno Rodrigues; Lopes, Marcelo Barreto; Araújo, Wildo Navegantes de; Díaz-Quijano, Fredi Alexander; Nakaya, Helder I.; Croda, Júlio

doi:10.1101/2020.04.30.20082172

Cited by 17 publications

(13 citation statements)

References 38 publications

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“…Strategies to evaluate and control transmission should consider differential assess to COVID-19 diagnosis for lower-income populations, changes in reporting systems and delays in reporting, which are key to accurately determining rates of epidemic growth 35 . Innovative infectious disease surveillance approaches such as those obtained from aggregated mobility data, when used properly, could help support public health actions across the COVID-19 epidemic [36][37][38][39] .…”

Section: Discussionmentioning

confidence: 99%

Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

Buss²,

et al. 2020

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OVID-19 is a severe acute respiratory infection (SARI) that emerged in early December 2019 in Wuhan, China 1. The outbreak was declared a public health emergency of international concern by the World Health Organization on 30 January 2020. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), an enveloped, single-stranded positive-sense RNA virus that belongs to the Betacoronavirus genus and Coronaviridae family 2. SARS-CoV-2 is closely related genetically to bat-derived SARS-like coronaviruses 3. Human-to-human transmission occurs primarily via respiratory droplets and direct contact, similar to human influenza viruses, SARS-CoV and Middle East respiratory syndrome coronavirus 4. The most commonly reported clinical symptoms are fever, dry cough, fatigue, dyspnoea, anosmia, ageusia, or some combination of these 1,4,5. As of 16 June 2020, more than 7.9 million cases have been confirmed worldwide, resulting in 434,796 deaths 6. Brazil declared COVID-19 a national public health emergency on 3 February 2020 7. After the development of a national emergency plan and the early establishment of molecular diagnostic facilities across Brazil's network of public health laboratories, the country reported its first confirmed COVID-19 case on 25 February 2020, in a traveller returning to São Paulo from northern Italy 8. São Paulo is the largest city in South America and no other Brazilian city receives a greater proportion of international flights 9. Currently, Brazil has one of the fastest-growing COVID-19 epidemics in the world, now accounting for 1,864,681 cases and 72,100 deaths, comprising over 55% of the total number of reported cases in Latin America and the Caribbean (as of 14 July 2020) 6. About 21% of Latin American and Caribbean populations are estimated to be at risk of severe COVID-19 illness 10. The region has been experiencing large outbreaks, with growing epidemics in Brazil,

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Section: Discussionmentioning

confidence: 99%

Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

Buss²,

et al. 2020

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“…Climate and socioeconomic characteristics were only weakly associated 5 . Another study found a strong negative correlation (r < -0.7) between the proportion of people staying at home and R t 6 . The "social isolation index" calculated by In Loco was also incorporated into an elasticity model which showed that, on average, every 10% increase in the isolation index was associated with 26% fewer cases of Covid-19 and 18% fewer deaths 7 .…”

Section: Introductionmentioning

confidence: 93%

“…Clima e características socioeconômicas apresentaram associação fraca 5 . Outro estudo mostrou correlação negativa forte (r < –0,7) entre a proporção de pessoas ficando em casa e R t 6 . O índice de isolamento social calculado pela In Loco também foi utilizado em um modelo de elasticidade que mostrou que um índice 10% maior implicou em 26% menos casos de Covid-19, em média.…”

Section: Introductionunclassified

Social distancing patterns in nine municipalities of Rio Grande do Sul, Brazil: the Epicovid19/RS study

et al. 2020

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OBJECTIVE: To describe social distancing practices in nine municipalities of the state of Rio Grande do Sul, Brazil, stratified by gender, age, and educational attainment. METHODS: Two sequential cross-sectional studies were conducted in the municipalities of Canoas, Caxias do Sul, Ijuí, Passo Fundo, Pelotas, Porto Alegre, Santa Cruz do Sul, Santa Maria, and Uruguaiana to estimate the population prevalence of COVID-19. The study was designed to be representative of the urban population of these municipalities. A questionnaire including three questions about social distancing was also administered to the participants. Here, we present descriptive analyses of social distancing practices by subgroups and use chi-square tests for comparisons. RESULTS: In terms of degree of social distancing, 25.8% of the interviewees reported being essentially isolated and 41.1% reported being quite isolated. 20.1% of respondents reported staying at home all the time, while 44.5% left only for essential activities. More than half of households reported receiving no visits from non-residents. Adults aged 20 to 59 reported the least social distancing, while more than 80% of participants aged 60 years or older reported being essentially isolated or quite isolated. Women reported more stringent distancing than men. Groups with higher educational attainment reported going out for daily activities more frequently. CONCLUSIONS: The extremes of age are more protected by social distancing, but some groups remain highly exposed. This can be an important limiting factor in controlling progression of the COVID-19 pandemic.

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“…However, several factors, including delays in reporting, changes in notification, and heterogeneous access to testing across populations, obfuscate the real-time assessment of virus transmission using SARS-CoV-2 case counts (15). Consequently, a more accurate measure of SARS-CoV-2 transmission in Brazil is the number of reported deaths caused by severe acute respiratory infections (SARIs), which is provided by the Sistema Único de Saúde (SUS) (18). Changes in the opportunity for SARS-CoV-2 transmission are strongly associated with changes in average mobility (18)(19)(20) and can typically be measured by calculating the effective reproduction number, R, defined as the average number of secondary infections caused by an infected person.…”

Section: Challenges Of Real-time Assessment Of Transmissionmentioning

confidence: 99%

“…Consequently, a more accurate measure of SARS-CoV-2 transmission in Brazil is the number of reported deaths caused by severe acute respiratory infections (SARIs), which is provided by the Sistema Único de Saúde (SUS) (18). Changes in the opportunity for SARS-CoV-2 transmission are strongly associated with changes in average mobility (18)(19)(20) and can typically be measured by calculating the effective reproduction number, R, defined as the average number of secondary infections caused by an infected person. R > 1 indicates a growing epidemic, whereas R < 1 is needed to achieve a decrease in transmission.…”

Section: Challenges Of Real-time Assessment Of Transmissionmentioning

confidence: 99%

Evolution and epidemic spread of SARS-CoV-2 in Brazil

Cândido

Claro

Jesus

et al. 2020

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Brazil currently has one of the fastest growing SARS-CoV-2 epidemics in the world. Owing to limited available data, assessments of the impact of non-pharmaceutical interventions (NPIs) on virus spread remain challenging. Using a mobility-driven transmission model, we show that NPIs reduced the reproduction number from >3 to 1–1.6 in São Paulo and Rio de Janeiro. Sequencing of 427 new genomes and analysis of a geographically representative genomic dataset identified >100 international virus introductions in Brazil. We estimate that most (76%) of the Brazilian strains fell in three clades that were introduced from Europe between 22 February11 March 2020. During the early epidemic phase, we found that SARS-CoV-2 spread mostly locally and within-state borders. After this period, despite sharp decreases in air travel, we estimated multiple exportations from large urban centers that coincided with a 25% increase in average travelled distances in national flights. This study sheds new light on the epidemic transmission and evolutionary trajectories of SARS-CoV-2 lineages in Brazil, and provide evidence that current interventions remain insufficient to keep virus transmission under control in the country.

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Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data

Cited by 17 publications

References 38 publications

Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil

Social distancing patterns in nine municipalities of Rio Grande do Sul, Brazil: the Epicovid19/RS study

Evolution and epidemic spread of SARS-CoV-2 in Brazil

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