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Air transportation, population density and temperature predict the spread of COVID-19 in Brazil.

ABSTRACT: There is evidence that COVID-19, the disease caused by the betacoronavirus SARS-CoV-2, is sensitive to environmental conditions. However, such conditions often correlate with demographic and socioeconomic factors at larger spatial extents, which could confound this inference. We evaluated the effect of meteorological conditions (temperature, solar radiation, air humidity and precipitation) on 292 daily records of cumulative number of confirmed COVID-19 cases across the 27 Brazilian capital cities during the 1st month of the outbreak, while controlling for an indicator of the number of tests, the number of arriving flights, population density, proportion of elderly people and average income. Apart from increasing with time, the number of confirmed cases was mainly related to the number of arriving flights and population density, increasing with both factors. However, after accounting for these effects, the disease was shown to be temperature sensitive: there were more cases in colder cities and days, and cases accumulated faster at lower temperatures. Our best estimate indicates that a 1 °C increase in temperature has been associated with a decrease in confirmed cases of 8%. The quality of the data and unknowns limit the analysis, but the study reveals an urgent need to understand more about the environmental sensitivity of the disease to predict demands on health services in different regions and seasons.

SUBMITTER: Pequeno P

PROVIDER: S-EPMC7275681 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Air transportation, population density and temperature predict the spread of COVID-19 in Brazil.

Pequeno Pedro P Mendel Bruna B Rosa Clarissa C Bosholn Mariane M Souza Jorge Luiz JL Baccaro Fabricio F Barbosa Reinaldo R Magnusson William W

PeerJ 20200603

There is evidence that COVID-19, the disease caused by the betacoronavirus SARS-CoV-2, is sensitive to environmental conditions. However, such conditions often correlate with demographic and socioeconomic factors at larger spatial extents, which could confound this inference. We evaluated the effect of meteorological conditions (temperature, solar radiation, air humidity and precipitation) on 292 daily records of cumulative number of confirmed COVID-19 cases across the 27 Brazilian capital citie ...[more]

PMID: 32547889

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Project description:Nationwide lockdown for COVID-19 created an urgent demand for public transportation among migrant workers stranded at different parts of India to return to their native places. Arranging transportation could spike the number of COVID-19 infected cases. Hence, this paper investigates the potential surge in confirmed and active cases of COVID-19 infection and assesses the train and bus fleet size required for the repatriating migrant workers. The expected to repatriate migrant worker population was obtained by forecasting the 2011 census data and comparing it with the information reported in the news media. A modified susceptible-exposed-infected-removed (SEIR) model was proposed to estimate the surge in confirmed and active cases of COVID-19 patients in India's selected states with high outflux of migrants. The developed model considered combinations of different levels of the daily arrival rate of migrant workers, total migrant workers in need of transportation, and the origin of the trip dependent symptomatic cases on arrival. Reducing the daily arrival rate of migrant workers for states with very high outflux of migrants (i.e., Uttar Pradesh and Bihar) can help to lower the surge in confirmed and active cases. Nevertheless, it could create a disparity in the number of days needed to transport all repatriating migrant workers to the home states. Hence, travel arrangements for about 100,000 migrant workers per day to Uttar Pradesh and Bihar, about 50,000 per day to Rajasthan and Madhya Pradesh, 20,000 per day to Maharashtra and less than 20,000 per day to other states of India was recommended. Highlights • Lower daily arrival of migrant workers preferred for Uttar Pradesh and Bihar.• Need a balanced number of days to repatriate all migrant workers from all states.• Daily arrival rate of migrant workers does not affect Rajasthan after May 31, 2020.• Repatriating migrant workers have a minimum implication on Maharashtra and Rajasthan.• Highest number of trains are needed to repatriate migrant workers to Bihar.

Dataset Information

Air transportation, population density and temperature predict the spread of COVID-19 in Brazil.

Publications

Air transportation, population density and temperature predict the spread of COVID-19 in Brazil.

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