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

PeerJ - Tập 8 - Trang e9322
Pedro Aurélio Costa Lima Pequeno1, Bruna Mendel2, Clarissa Rosa3, Mariane Bosholn1, Jorge Luiz Pereira Souza4, Fabrício Beggiato Baccaro5, Reinaldo Imbrózio Barbosa1, William E. Magnusson3
1Instituto Nacional de Pesquisas da Amazônia, Boa Vista, Brazil
2Universidade Federal de Roraima, Boa Vista, Brazil
3Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil
4Instituto Nacional da Mata Atlântica, Santa Teresa, Brazil
5Universidade Federal do Amazonas, Manaus, Brazil

Tóm tắt

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.

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Tài liệu tham khảo

ANAC, 2020, Agência Nacional de Aviação Civil

Anderson, 2020, How will country-based mitigation measures influence the course of the COVID-19 epidemic?, Lancet, 395, 931, 10.1016/S0140-6736(20)30567-5

Barreto, 2011, Successes and failures in the control of infectious diseases in Brazil: social and environmental context, policies, interventions, and research needs, Lancet, 377, 1877, 10.1016/S0140-6736(11)60202-X

Bartoń, 2019, MuMIn: multi-model inference

Bates, 2015, Fitting linear mixed-effects models using lme4, Journal of Statistical Software, 67, 1, 10.18637/jss.v067.i01

Breheny, 2017, Visualization of regression models using visreg, R Journal, 9, 56, 10.32614/RJ-2017-046

Chan, 2011, The effects of temperature and relative humidity on the viability of the SARS coronavirus, Advances in Virology, 2011, 734690, 10.1155/2011/734690

Ciencewicki, 2007, Air pollution and respiratory viral infection, Inhalation Toxicology, 19, 1135, 10.1080/08958370701665434

Ebrahim, 2020, Covid-19 and community mitigation strategies in a pandemic, BMJ, 368, m1066, 10.1136/bmj.m1066

Fasina, 2020, Novel coronavirus (2019-nCoV) update: what we know and what is unknown, Asian Pacific Journal of Tropical Medicine, 13, 97, 10.4103/1995-7645.277795

Ferguson, 2020, Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, 1

Fick, 2017, WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas, International Journal of Climatology, 37, 4302, 10.1002/joc.5086

Grant, 2020, Evidence that Vitamin D supplementation could reduce risk of influenza and COVID-19 infections and deaths, Nutrients, 12, E988, 10.3390/nu12040988

INMET, 2020, Estação Meteorológica de Observação de Superfície Automática

Lauer, 2020, The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application, Annals Internal Medicine, 172, 577, 10.7326/M20-0504

Lowen, 2007, Influenza virus transmission is dependent on relative humidity and temperature, PLOS Pathogens, 3, 1470, 10.1371/journal.ppat.0030151

Morais, 2020, The global population of SARS-CoV-2 is composed of six major subtypes, 10.1038/s41598-020-74050-8

Mortara, 2020, Coronabr: download de dados do coronavírus

Nelson, 2006, Stochastic processes are key determinants of short-term evolution in influenza a virus, PLOS Pathogens, 2, e125, 10.1371/journal.ppat.0020125

Paterno, 2020, covid19br: an r-package with updated data on the number of coronavirus (covid-19) cases in Brazil

Poole, 2020, Seasonal influences on the spread of SARS-CoV-2 (COVID19), causality, and forecastabililty

R Core Team, 2020, R: A language and environment for statistical computing

Ribeiro, 2020, Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil, 10.1101/2020.03.26.20044370

Rhodes, 2012, Intensive care provision: a global problem, Revista Brasileira de Terapia Intensiva, 24, 322, 10.1590/S0103-507X2012000400005

Roser, 2020, Coronavirus disease (COVID-19)—statistics and research

Sajadi, 2020, Temperature, humidity, and latitude analysis to predict potential spread and seasonality for COVID-19

Schoeman, 2019, Coronavirus envelope protein: current knowledge, Virology Journal, 16, 69, 10.1186/s12985-019-1182-0

Secretarias de Saúde das Unidades Federativas, 2020, Dados diários mais recentes do coronavírus por município brasileiro

Sidra, 2020, Pesquisa Nacional por Amostra de Domicílios Contínua Trimestral: Tabela 5918—População por grupo de idade

Van Doremalen, 2013, Stability of middle east respiratory syndrome coronavirus (MERS-CoV) under different environmental conditions, Eurosurveillance, 18, 20590, 10.2807/1560-7917.ES2013.18.38.20590

Viboud, 2006, Influenza in tropical regions, PLOS Medicine, 3, e89, 10.1371/journal.pmed.0030089

Walker, 2020, The Global Impact of COVID-19 and Strategies for Mitigation and Suppression, 1

Wang, 2020, High temperature and high humidity reduce the transmission of COVID-19, 10.2139/ssrn.3551767

Wilder-Smith, 2020, Isolation, quarantine, social distancing and community containment: pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak, Journal of Travel Medicine, 27, 727, 10.1093/jtm/taaa020

Xu, 2020, Pathological findings of COVID-19 associated with acute respiratory distress syndrome, Lancet Respiratory Medicine, 8, 420, 10.1016/S2213-2600(20)30076-X

Yang, 2020, The deadly coronaviruses: the 2003 SARS pandemic and the 2020 novel coronavirus epidemic in China, Journal of Autoimmunity, 109, 102434, 10.1016/j.jaut.2020.102434

Zhao, 2004, Moderate mutation rate in the SARS coronavirus genome and its implications, BMC Evolutionary Biology, 4, 21, 10.1186/1471-2148-4-21

Zuur, 2009, Mixed effects models and extensions in ecology with R, 10.1007/978-0-387-87458-6