87
Views
0
CrossRef citations to date
0
Altmetric
Research Article

COVID-19 mortality rates in South America related to environmental factors

, , ORCID Icon, , , , , & ORCID Icon show all

References

  • Zhou, P., Yang, X.-L., Wang, X.-G., Hu, B., Zhang, L., Zhang, W., et al., 2020, A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579(7798), 270–273. doi: 10.1038/s41586-020-2012-7
  • Taubenberger, J.K. and Morens, D.M., 2006, 1918 influenza: The mother of all pandemics. Emerging Infectious Diseases 12(1), 15–22. doi: 10.3201/eid1209.05-0979
  • Dong, E., Du, H., and Gardner, L., 2020, An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases 20(5), 533–534. doi: 10.1016/S1473-3099(20)30120-1
  • Chan, K.H., Peiris, J.S.M., Lam, S.Y., Poon, L.L.M., Yuen, K.Y., and Seto, W.H., 2011, The effects of temperature and relative humidity on the viability of the SARS coronavirus. Advances in Virology 2011, 1–7. doi: 10.1155/2011/734690
  • Coccia, M., 2021;, The effects of atmospheric stability with low wind speed and of air pollution on the accelerated transmission dynamics of COVID-19. International Journal of Environmental Studies 78(1), 1–27. doi: 10.1080/00207233.2020.1802937
  • Paynter, S., Ware, R.S., Sly, P.D., Williams, G., and Weinstein, P., 2015, Seasonal immune modulation in humans: Observed patterns and potential environmental drivers. Journal of Infection 70(1), 1–10. doi: 10.1016/j.jinf.2014.09.006
  • Sajadi, M.M., Habibzadeh, P., Vintzileos, A., Shokouhi, S., Miralles-Wilhelm, F., and Amoroso, A., 2020, Temperature and latitude analysis to predict potential spread and seasonality for COVID-19. SSRN Electronic Journal. doi: 10.2139/ssrn.3550308.
  • Wang, J., Tang, K., Feng, K., and Lv, W., 2020, High temperature and high humidity reduce the transmission of COVID-19. SSRN Electronic Journal. Available online at: https://www.cebm.net/study/covid-19-high-temperature-and-high-humidity-reduce-the-transmission-of-covid-19/ (accessed 23 March 2022).
  • Araujo, M.B. and Naimi, B., 2020, Spread of SARS-CoV-2 Coronavirus likely to be constrained by climate. medRxiv. doi: 10.1101/2020.03.12.20034728
  • Bukhari, Q. and Jameel, Y., 2020, Will coronavirus pandemic diminish by summer? SSRN Electronic Journal. doi: 10.2139/ssrn.3556998.
  • Xie, J. and Zhu, Y., 2020, Association between ambient temperature and COVID-19 infection in 122 cities from China. Science of the Total Environment 724, 138201. doi: 10.1016/j.scitotenv.2020.138201
  • Jiang, X.-Q., Mei, X.-D., and Feng, D., 2016, Air pollution and chronic airway diseases: What should people know and do? Journal of Thoracic Disease 8(1), E31–E40. doi: 10.3978/j.issn.2072-1439.2015.11.50
  • Hadley, M.B., Baumgartner, J., and Vedanthan, R., 2018, Developing a clinical approach to air pollution and cardiovascular health. Circulation 137(7), 725–742. doi: 10.1161/CIRCULATIONAHA.117.030377
  • Conticini, E., Frediani, B., and Caro, D., 2020, Can atmospheric pollution be considered a co-factor in extremely high level of SARS-CoV-2 lethality in Northern Italy? Environmental Pollution 261, 114465. doi: 10.1016/j.envpol.2020.114465
  • Mittal, R., Ni, R., and Seo, J.-H., 2020, The flow physics of COVID-19. Journal of Fluid Mechanics 894, F2. doi: 10.1017/jfm.2020.330
  • Asadi, S., Bouvier, N., Wexler, A.S., and Ristenpart, W.D., 2020, The coronavirus pandemic and aerosols: Does COVID-19 transmit via expiratory particles? Aerosol Science and Technology 54(6), 635–638. doi: 10.1080/02786826.2020.1749229
  • Morawska, L. and Cao, J., 2020, Airborne transmission of SARS-CoV-2: The world should face the reality. Environment International 139, 105730. doi: 10.1016/j.envint.2020.105730
  • Tang, J.W., Bahnfleth, W.P., Bluyssen, P.M., Buonanno, G., Jimenez, J.L., Kurnitski, J., et al., 2021, Dismantling myths on the airborne transmission of severe acute respiratory syndrome coronavirus (SARS-CoV-2). Journal of Hospital Infection 110, 89–96. 10.1016/j.jhin.2020.12.022
  • Miller, S.L., Nazaroff, W.W., Jimenez, J.L., Boerstra, A., Buonanno, G., Dancer, S.J., et al., 2021, Transmission of SARS‐CoV‐2 by inhalation of respiratory aerosol in the Skagit Valley Chorale superspreading event. Indoor Air 31(2), 314–323. doi: 10.1111/ina.12751
  • Liu, Y., Ning, Z., Chen, Y., Guo, M., Liu, Y., Gali, N.K., et al., 2020, Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature 582(7813), 557–560. doi: 10.1038/s41586-020-2271-3
  • Setti, L., Passarini, F., De Gennaro, G., Barbieri, P., Perrone, M.G., Borelli, M., et al., 2020, SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy: First evidence. Environmental Research 188, 109754. 10.1016/j.envres.2020.109754
  • Travaglio, M., Yu, Y., Popovic, R., Selley, L., Leal, N.S., and Martins, L.M., 2021 Jan, Links between air pollution and COVID-19 in England. Environmental Pollution 268, 115859. doi: 10.1016/j.envpol.2020.115859
  • Wu, X., Nethery, R.C., Sabath, M.B., Braun, D., and Dominici, F., 2020, Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Science Advances 6(45), eabd4049. doi: 10.1126/sciadv.abd4049
  • Vasquez-Apestegui, V., Parras-Garrido, E., Tapia, V., Paz-Aparicio, V., Rojas, J., Sánchez-Ccoyllo, O., et al., 2021, Association between air pollution in lima and the high incidence of COVID-19: Findings from a post hoc analysis. BMC Public Health 21(1), 1161. doi: 10.1186/s12889-021-11232-7
  • Jiang, Y., Wu, X.-J., and Guan, Y.-J., 2020, Effect of ambient air pollutants and meteorological variables on COVID-19 incidence. Infection Control & Hospital Epidemiology 41(9), 1011–1015. doi: 10.1017/ice.2020.222
  • Bontempi, E., 2020, First data analysis about possible COVID-19 virus airborne diffusion due to air particulate matter (PM): The case of Lombardy (Italy). Environmental Research 186, 109639. doi: 10.1016/j.envres.2020.109639
  • Zoran, M.A., Savastru, R.S., Savastru, D.M., and Tautan, M.N., 2020, Assessing the relationship between ground levels of ozone (O3) and nitrogen dioxide (NO2) with coronavirus (COVID-19) in Milan, Italy. Science of the Total Environment 740, 140005. doi: 10.1016/j.scitotenv.2020.140005
  • Adhikari, A. and Yin, J., 2020, Short-Term effects of ambient ozone, PM2.5, and meteorological factors on COVID-19 confirmed cases and deaths in queens, New York. International Journal of Environmental Research and Public Health 17(11), 4047. doi: 10.3390/ijerph17114047
  • Copat, C., Cristaldi, A., Fiore, M., Grasso, A., Zuccarello, P., Signorelli, S.S., et al., 2020, The role of air pollution (PM and NO2) in COVID-19 spread and lethality: A systematic review. Environmental Research 191, 110129. 10.1016/j.envres.2020.110129
  • Kupferschmidt, K. and Cohen, J., 2020, Can China’s COVID-19 strategy work elsewhere? Science 367(6482), 1061–1062. doi: 10.1126/science.367.6482.1061
  • Giani, P., Castruccio, S., Anav, A., Howard, D., Hu, W., and Crippa, P., 2020, Short-term and long-term health impacts of air pollution reductions from COVID-19 lockdowns in China and Europe: A modelling study. The Lancet Planetary Health 4(10), e474–82. doi: 10.1016/S2542-5196(20)30224-2
  • Freitas, E.D., Ibarra-Espinosa, S.A., Gavidia-Calderón, M.E., Rehbein, A., Abou Rafee, S.A., Martins, J.A., et al., Mobility restrictions and air quality under COVID-19 pandemic in São Paulo, Brazil. Preprints 2020, 2020040515. doi: 10.20944/preprints202004.0515.v1
  • Dantas, G., Siciliano, B., França, B.B., da Silva Cm and Arbilla, G., 2020, The impact of COVID-19 partial lockdown on the air quality of the city of Rio de Janeiro, Brazil. Science of the Total Environment 729, 139085. doi: 10.1016/j.scitotenv.2020.139085
  • Nakada, L.Y.K. and Urban, R.C., 2020, COVID-19 pandemic: Impacts on the air quality during the partial lockdown in São Paulo state, Brazil. Science of the Total Environment 730, 139087. doi: 10.1016/j.scitotenv.2020.139087
  • Zalakeviciute, R., Vasquez, R., Bayas, D., Buenano, A., Mejia, D., Zegarra, R., et al., 2020, Drastic Improvements in Air Quality in Ecuador during the COVID-19 Outbreak. Aerosol and Air Quality Research 20(8), 1783–1792. doi: 10.4209/aaqr.2020.05.0254
  • BuenosAiresCiudad. Casos COVID-19 [Internet]. 2020 [cited 2020 Aug 19]. Available from: https://data.buenosaires.gob.ar/dataset/casos-covid-19
  • Brasil, I.O. COVID-19, dados por município [Internet]. 2020 [cited 2020 Aug 16]. Available from: https://brasil.io/covid19/
  • Chile. Datos COVID-19 [Internet]. Ministerio de Ciencia, Tecnología, Conocimiento e Innovación. 2020 [cited 2020 Sep 2]. Available from: https://covid19.soporta.cl/pages/descarga
  • Peru. Plataforma Nacional de Datos Abiertos [Internet]. 2020 [cited 2020 Aug 28]. Available from: https://www.datosabiertos.gob.pe/group/datos-abiertos-de-covid-19
  • Wu, S.L., Mertens, A.N., Crider, Y.S., Nguyen, A., Pokpongkiat, N.N., Djajadi, S., et al., 2020, Substantial underestimation of SARS-CoV-2 infection in the United States. Nature Communications 11(1), 4507. doi: 10.1038/s41467-020-18272-4
  • Krotkov, N.A., Lamsal, L.N., Celarier, E.A., Swartz, W.H., Marchenko, S.V., Bucsela, E.J., et al., 2017, The version 3 OMI NO2standard product. Atmospheric Measurement Techniques 10(9), 3133–3149. doi: 10.5194/amt-10-3133-2017
  • Krotkov, N.A., Lamsal, L.N., Marchenko, S.V., Celarier, E.A., J.Bucsela, E., Swartz, W.H., et al., 2019, OMI/Aura NO2 Cloud-Screened Total and Tropospheric Column L3 Global Gridded 0.25 Degree X 0.25 Degree V3 (NASA Goddard Space Flight Center, Goddard Earth Sciences Data and Information Services Center (GES DISC)). doi: 10.5067/Aura/OMI/DATA3007
  • Anand, J.S. and Monks, P.S., 2017, Estimating daily surface NO2 concentrations from satellite data –a case study over Hong Kong using land use regression models. Atmospheric Chemistry and Physics 17(13), 8211–8230. doi: 10.5194/acp-17-8211-2017
  • Bechle, M.J., Millet, D.B., and Marshall, J.D., 2013, Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area. Atmospheric Environment 69, 345–353. doi: 10.1016/j.atmosenv.2012.11.046
  • Lamsal, L.N., Krotkov, N.A., Celarier, E.A., Swartz, W.H., Pickering, K.E., Bucsela, E.J., et al., 2014, Evaluation of OMI operational standard NO2 column retrievals using in situ and surface-based NO2 observations. Atmospheric Chemistry and Physics 14(21), 11587–11609. doi: 10.5194/acp-14-11587-2014
  • INMET. Instituto Nacional de Meteorologia, Brasil [Internet]. 2020 [cited 2020 Aug 20]. Available from: https://portal.inmet.gov.br/
  • SENAMHI. Servicio Nacional de Meteorología e Hidrología, Peru [Internet]. 2020 [cited 2020 Aug 20]. Available from: https://www.senamhi.gob.pe/?&p=estaciones
  • SMM. Servicio Meteorológico Nacional, Argentina [Internet]. 2020 [cited 2020 Aug 20]. Available from: https://www.smn.gob.ar/
  • DGAC. Dirección Meteorológica de Chile - Servicios Climáticos [Internet]. Dirección Meteorológica de Chile. 2020 [cited 2020 Aug 10]. Available from: https://climatologia.meteochile.gob.cl/
  • Gelaro, R., McCarty, W., Suárez, M.J., Todling, R., Molod, A., Takacs, L., et al., 2017, The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate 30(14), 5419–5454. doi: 10.1175/JCLI-D-16-0758.1
  • IBGE. Cidades@ [Internet]. Instituto Brasileiro de Geografia e Estatística. 2020 [cited 2020 Aug 18]. Available from: https://cidades.ibge.gov.br/
  • INEI. Censos Nacionales. 2017.
  • INE, 2017, Censos Nacionales de Población y de Vivienda. Available online at: https://www.ine.cl/estadisticas/sociales/censos-de-poblacion-y-vivienda (accessed 25 March 2022).
  • INDEC, 2010, Censo Nacional de Población, Hogares y Viviendas. Available online at: https://www.indec.gob.ar/indec/web/Nivel4-Tema-2-41-135 (accessed 25 March 2022).
  • GlobalDataLab, 2020, Subnational Human Development Index. Available online at: https://globaldatalab.org/shdi/shdi/ (accessed 25 March 2022).
  • IBGE, 2013, Pesquisa nacional de saúde. Brasil. Available online at: https://biblioteca.ibge.gov.br/visualizacao/livros/liv94074.pdf (accessed 25 March 2022).
  • Brasil, 2018, Vigitel: Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico.
  • INDEC, 2018, 4° Encuesta Nacional de Factores de Riesgo. Available online at: https://www.indec.gob.ar/ftp/cuadros/publicaciones/enfr_2018_resultados_definitivos.pdf (accessed 25 March 2022).
  • Chile. Encuesta Nacional de Salud 2016-2017. 2017.
  • de Cde C, S.-P.S.H., de Azevedo-silva Lj, Bonato, R.C.S., de Cde C, S.-P.M., da S, P.A.C., and Santiago Junior, J.F., 2020, Coronavirus (SARS-CoV-2) and the risk of obesity for critically illness and ICU admitted: Meta-analysis of the epidemiological evidence. Obesity Research & Clinical Practice 14(5), 389–397. doi: 10.1016/j.orcp.2020.07.007
  • Cuschieri, S. and Grech, S., 2020, COVID-19 and diabetes: The why, the what and the how. Journal of Diabetes and Its Complications 34(9), 107637. doi: 10.1016/j.jdiacomp.2020.107637
  • Niquini, R.P., Lana, R.M., Pacheco, A.G., Cruz, O.G., Coelho, F.C., Carvalho, L.M., et al., 2020, SRAG por COVID-19 no Brasil: Descrição e comparação de características demográficas e comorbidades com SRAG por influenza e com a população geral. Cadernos de Saúde Pública 36(7). doi: 10.1590/0102-311x00149420
  • Wang, B., Li, R., Lu, Z., and Huang, Y., 2020, Does comorbidity increase the risk of patients with COVID-19: Evidence from meta-analysis. Aging 12(7), 6049–6057. doi: 10.18632/aging.103000
  • Google. COVID-19 community mobility reports [internet]. 2020 [cited 2020 Aug 18]. Available from: https://www.google.com/covid19/mobility/
  • Cameron, A.C. and Trivedi, P.K., 2013, Regression Analysis of Count Data (Cambridge University Press). Available online at: http://faculty.econ.ucdavis.edu/faculty/cameron/racd2/ (accessed 25 March 2022).
  • Byers, A.L., Allore, H., Gill, T.M., and Peduzzi, P.N., 2003, Application of negative binomial modeling for discrete outcomes: A case study in aging research. Journal of Clinical Epidemiology 56(6), 559–564. doi: 10.1016/S0895-4356(03)00028-3
  • Lloyd-Smith, J.O., 2007, Maximum likelihood estimation of the negative binomial dispersion parameter for highly overdispersed data, with applications to infectious diseases. In: M. Rees (Ed.) PLoS ONE Vol. 2. 2, pp. e180. doi:10.1371/journal.pone.0000180
  • Chun, S.Y. and Shapiro, A., 2009, Normal versus noncentral chi-square asymptotics of misspecified models. Multivariate Behavioral Research 44(6), 803–827. doi: 10.1080/00273170903352186
  • Freitas, S.R., Longo, K.M., Silva Dias, M.A.F., Silva Dias, P.L., Chatfield, R., Prins, E., et al., 2005, Modeling the transport of biomass burning emissions in South America. Environmental Fluid Mechanics 5(1–2), 135–167. doi: 10.1007/s10652-005-0243-7
  • Martins, L.D., Hallak, R., Alves, R.C., de Almeida, D.S., Squizzato, R., Moreira, C.A.B., et al., 2018, Long-range transport of aerosols from biomass burning over Southeastern South America and their implications on air quality. Aerosol and Air Quality Research 18(7), 1734–1745. doi: 10.4209/aaqr.2017.11.0545
  • Debone, D., da Costa, M.V., and Sgek, M., 2020, 90 days of COVID-19 social distancing and its impacts on air quality and health in Sao Paulo, Brazil. Sustainability 12(18), 7440. doi: 10.3390/su12187440
  • CDC, 2020, United States centers for disease control and prevention. Covid Data Tracker. Available online at: https://covid.cdc.gov/covid-data-tracker/#datatracker-home (accessed 25 March 2022).
  • Hallal, P.C., Hartwig, F.P., Horta, B.L., Silveira, M.F., Struchiner, C.J., Vidaletti, L.P., et al., 2020, SARS-CoV-2 antibody prevalence in Brazil: Results from two successive nationwide serological household surveys. The Lancet Global Health 8(11), e1390–8. doi: 10.1016/S2214-109X(20)30387-9
  • Buss, L.F., JrJr, Abrahim, C.A.P., Cmm, A.M., Jr, Salomon, T., Almeida-Neto, C., et al., 2020, COVID-19 herd immunity in the Brazilian Amazon. medRxiv. doi: 10.1101/2020.09.16.20194787
  • The Lancet, 2020, COVID-19 in Africa: No room for complacency. The Lancet 395(10238), 1669. doi:10.1016/S0140-6736(20)31237-X
  • Kucirka, L.M., Lauer, S.A., Laeyendecker, O., Boon, D., and Lessler, J., 2020, Variation in false-negative rate of reverse transcriptase polymerase chain reaction–based SARS-CoV-2 tests by time since exposure. Annals of Internal Medicine 173(4), 262–267. doi: 10.7326/M20-1495
  • Castro, R., Luz, P.M., Wakimoto, M.D., Veloso, V.G., Grinsztejn, B., and Perazzo, H., 2020, COVID-19: A meta-analysis of diagnostic test accuracy of commercial assays registered in Brazil. Brazilian Journal of Infectious Diseases 24(2), 180–187. doi: 10.1016/j.bjid.2020.04.003
  • Cohen, J. and Kupferschmidt, K., 2020, Labs scramble to produce new coronavirus diagnostics. Science 367(6479), 727. doi: 10.1126/science.367.6479.727
  • Freitas, A.R.R., de, M.N.M., Frutuoso, L.C.V., Beckedorff, O.A., de, M.L.M.A., de M, C.M.M., et al., 2020, Tracking excess deaths associated with the COVID-19 epidemic as an epidemiological surveillance strategy-preliminary results of the evaluation of six Brazilian capitals. Revista da Sociedade Brasileira de Medicina Tropical 53, 1–8. 10.1590/0037-8682-0558-2020
  • Woolf, S.H., Chapman, D.A., Sabo, R.T., Weinberger, D.M., Hill, L., and Dsdh, T., 2020, Excess deaths from COVID-19 and other causes, March-July 2020. JAMA - Journal of the American Medical Association 324(15), 1562–1564. doi: 10.1001/jama.2020.19545
  • Grillo Rojas, P.F. and Romero Onofre, R., 2020, Estimate of the excess of the total deaths reported in 2020 versus the reported deaths from COVID-19 (SARS-CoV2) in Peru during the months of March, April and May 2020. Revista de la Facultad de Medicina Humana 20(4), 646–650. doi: 10.25176/RFMH.v20i4.3220
  • Baud, D., Qi, X., Nielsen-Saines, K., Musso, D., Pomar, L., and Favre, G., 2020, Real estimates of mortality following COVID-19 infection. The Lancet Infectious Diseases 20(7), 773. doi: 10.1016/S1473-3099(20)30195-X
  • Prata, D.N., Rodrigues, W., and Bermejo, P.H., 2020, Temperature significantly changes COVID-19 transmission in (sub)tropical cities of Brazil. Science of the Total Environment 729, 138862. doi: 10.1016/j.scitotenv.2020.138862
  • Wu, Y., Jing, W., Liu, J., Ma, Q., Yuan, J., Wang, Y., et al., 2020, Effects of temperature and humidity on the daily new cases and new deaths of COVID-19 in 166 countries. Science of the Total Environment 729, 139051. 10.1016/j.scitotenv.2020.139051
  • Zhang, Z., Xue, T., and Jin, X., 2020, Effects of meteorological conditions and air pollution on COVID-19 transmission: Evidence from 219 Chinese cities. Science of the Total Environment 741, 140244. doi: 10.1016/j.scitotenv.2020.140244
  • Auler, A.C., Cássaro, F.A.M., da Silva Vo and Pires, L.F., 2020, Evidence that high temperatures and intermediate relative humidity might favor the spread of COVID-19 in tropical climate: A case study for the most affected Brazilian cities. Science of the Total Environment 729, 139090. doi: 10.1016/j.scitotenv.2020.139090
  • Khazaei, S., Rezaeian, S., Khazaei, S., and Nematollahi, S., 2016, Relation between the prevalence of diabetes mellitus and human development index: A global ecological study. Health Scope 6(2). doi: 10.5812/jhealthscope.40212
  • Zeng, Z., Chen, J., Xiao, C., and Chen, W., 2020, A global view on prevalence of hypertension and human develop index. Annals of Global Health 86(1). doi: 10.5334/aogh.2591
  • Pereira, A.M., Dos Santos Silva, R., and Silva, P.R., 2019, Desigualdades na informalidade: Uma análise das Regiões Nordeste e Sudeste do Brasil. Revista Desenvolvimento Social 134, 33–46.
  • Ataguba, O.A. and Ataguba, J.E., 2020, Social determinants of health: The role of effective communication in the COVID-19 pandemic in developing countries. Global Health Action 13(1), 1788263. doi: 10.1080/16549716.2020.1788263
  • Bruns, D.P., Kraguljac, N.V., and Bruns, T.R., 2020, COVID-19: Facts, cultural considerations, and risk of stigmatization. Journal of Transcultural Nursing 31(4), 326–332. doi: 10.1177/1043659620917724
  • Pareek, M., Bangash, M.N., Pareek, N., Pan, D., Sze, S., Minhas, J.S., et al., 2020, Ethnicity and COVID-19: An urgent public health research priority. The Lancet 395(10234), 1421–1422. doi: 10.1016/S0140-6736(20)30922-3

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.