Las bajas temperaturas, la alta humedad relativa y las mayores precipitaciones se asocian a un mayor número de muertes por COVID-19

Autores/as

DOI:

https://doi.org/10.33448/rsd-v11i4.27616

Palabras clave:

Pandemias; SARS-CoV-2; Coronavirus; Meteorología; Clima.

Resumen

Introducción: Las variables meteorológicas desempeñan un papel importante en la transmisión de enfermedades infecciosas como la enfermedad por coronavirus 2019 (COVID-19). Objetivo: Analizar la correlación entre las variables meteorológicas y las muertes/casos diarios de COVID-19. Metodología: Estudio exploratorio-descriptivo basado en datos secundarios sobre muertes, casos de COVID-19 y variables climáticas de marzo de 2020 a mayo de 2021 en Fortaleza, Brasil. Se utilizaron datos del sistema de vigilancia COVID-19 del Ministerio de Sanidad. Los indicadores climáticos se extrajeron del Instituto Nacional de Meteorología. Las variables estudiadas fueron la temperatura (mínima, media y máxima en °C), la humedad relativa (%), la precipitación total (mm) y la insolación diaria total (h). Para el análisis estadístico se utilizaron la correlación de Pearson y el modelo de regresión lineal. Las correlaciones se consideraron significativas cuando P ≤ 0,05 y se adoptó un intervalo de confianza del 95%. Resultados: Todas las variables meteorológicas estaban correlacionadas con las muertes por COVID-19, la temperatura mínima (r = -0,126; P < 0,01), la temperatura media (r = -0,146; P < 0,05), la temperatura máxima (r = -0,190; P < 0,001), la insolación (r = -0,214; P < 0,001), las precipitaciones (r = 0,216; P < 0,001) y la humedad relativa (r = 0,348; P < 0,001). En cuanto a los nuevos casos de COVID-19, sólo la temperatura máxima (r = -0,116; P < 0,05), la insolación (r = -0,141; P < 0,01) y la humedad relativa (r = 0,231; P < 0,001) estaban significativamente correlacionadas. Conclusión: Hubo correlaciones significativas entre las variables meteorológicas y las muertes/casos diarios de COVID-19. Se comprobó que las variables meteorológicas fueron las que más influyeron en las muertes por COVID-19.

Citas

Alvares, C. A., Stape, J. L., Sentelhas, P. C., De Moraes Gonçalves, J. L., & Sparovek, G. (2013). Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift, 22(6), 711–728. https://doi.org/10.1127/0941-2948/2013/0507

Alves, M. R., de Souza, R. A. G., & Caló, R. D. S. (2021). Poor sanitation and transmission of covid-19 in Brazil. Sao Paulo Medical Journal, 139(1), 72–76. https://doi.org/10.1590/1516-3180.2020.0442.r1.18112020

Auler, A. C., Cássaro, F. A. M., da Silva, V. O., & 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(January), 2020–2022. https://doi.org/10.1016/j.scitotenv.2020.139090

Benseñor, I. M., & Lotufo, P. A. (2020). Some lessons from the covid-19 pandemic virus. Sao Paulo Medical Journal, 138(3), 174–175. https://doi.org/10.1590/1516-3180.2020.138320052020

Chen, B., Liang, H., Yuan, X., Hu, Y., Xu, M., Zhao, Y., Zhang, B., Tian, F., & Zhu, X. (2020). Roles of meteorological conditions in COVID-19 transmission on a worldwide scale. BMJ Open. https://doi.org/10.1101/2020.03.16.20037168

Coelho, M. T. P., Rodrigues, J. F. M., Medina, A. M., Scalco, P., Terribile, L. C., Vilela, B., Diniz-Filho, J. A. F., & Dobrovolski, R. (2020). Exponential phase of covid19 expansion is driven by airport connections. MedRxiv. https://doi.org/10.1101/2020.04.02.20050773

Cucinotta, D., & Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta Biomedica, 91(1), 157–160. https://doi.org/10.23750/abm.v91i1.9397

Guan, W., Ni, Z., Hu, Y., Liang, W., Ou, C., He, J., Liu, L., Shan, H., Lei, C., Hui, D. S. C., Du, B., Li, L., Zeng, G., Yuen, K.-Y., Chen, R., Tang, C., Wang, T., Chen, P., Xiang, J., … Zhong, N. (2020). Clinical Characteristics of Coronavirus Disease 2019 in China. New England Journal of Medicine, 382(18), 1708–1720. https://doi.org/10.1056/nejmoa2002032

Instituto Brasileiro de Geografia e Estatística (IBGE). (2020). Estimativas da população residente para os municípios e para as unidades da federação brasileiros com data de referência em 1o de julho de 2020. 26. https://www.ibge.gov.br/estatisticas/sociais/populacao/9109-projecao-da-populacao.html?=&t=o-

Instituto de Pesquisa e Estratégia Econômica do Ceará (IPECE). (2018). Perfil Municipal de Fortaleza - 2017. https://www.ipece.ce.gov.br/wp-content/uploads/sites/45/2018/09/Fortaleza_2017.pdf

Kaplin, A., Junker, C., Kumar, A., Ribeiro, M. A., Yu, E., Wang, M., Smith, T., Rai, S. N., & Bhatnagar, A. (2021). Evidence and magnitude of the effects of meteorological changes on SARS-CoV-2 transmission. PLoS ONE, 16(2 February), e0246167. https://doi.org/10.1371/journal.pone.0246167

Karapiperis, C., Kouklis, P., Papastratos, S., Chasapi, A., Danchin, A., Angelis, L., & Ouzounis, C. A. (2021). A strong seasonality pattern for covid-19 incidence rates modulated by UV radiation levels. Viruses, 13(4), 1–17. https://doi.org/10.3390/v13040574

Kodera, S., Rashed, E. A., & Hirata, A. (2020). Correlation between COVID-19 morbidity and mortality rates in Japan and local population density, temperature, and absolute humidity. International Journal of Environmental Research and Public Health, 17(15), 1–14. https://doi.org/10.3390/ijerph17155477

Ma, Yiqun, Pei, S., Shaman, J., Dubrow, R., & Chen, K. (2021). Role of meteorological factors in the transmission of SARS-CoV-2 in the United States. Nature Communications, 12(1), 1–9. https://doi.org/10.1038/s41467-021-23866-7

Ma, Yueling, Zhao, Y., Liu, J., He, X., Wang, B., Fu, S., Yan, J., Niu, J., Zhou, J., & Luo, B. (2020). Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China. Science of the Total Environment, 724, 138226. https://doi.org/10.1016/j.scitotenv.2020.138226

Mecenas, P., da Rosa Moreira Bastos, R. T., Rosário Vallinoto, A. C., & Normando, D. (2020). Effects of temperature and humidity on the spread of COVID-19: A systematic review. PLoS ONE, 15(9 September), e0238339. https://doi.org/10.1371/journal.pone.0238339

Meo, S. A., Abukhalaf, A. A., Alomar, A. A., Aljudi, T. W., Bajri, H. M., Sami, W., Akram, J., Akram, S. J., & Hajjar, W. (2020). Impact of weather conditions on incidence and mortality of COVID-19 pandemic in Africa. European Review for Medical and Pharmacological Sciences, 24(18), 9753–9759. https://doi.org/10.26355/eurrev_202009_23069

Omer, S., Iftime, A., & Burcea, V. (2021). COVID-19 mortality: positive correlation with cloudiness and sunlight but no correlation with latitude in Europe. MedRxiv, 2021.01.27.21250658. https://www.medrxiv.org/content/10.1101/2021.01.27.21250658v1%0Ahttps://www.medrxiv.org/content/1 0.1101/2021.01.27.21250658v1.abstract

Prata, D. N., Rodrigues, W., & Bermejo, P. H. (2020). Temperature significantly changes COVID-19 transmission in (sub)tropical cities of Brazil. The Science of the Total Environment, 729(January), 138862. https://doi.org/10.1016/j.scitotenv.2020.138862

Ratnesar-Shumate, S., Williams, G., Green, B., Krause, M., Holland, B., Wood, S., Bohannon, J., Boydston, J., Freeburger, D., Hooper, I., Beck, K., Yeager, J., Altamura, L. A., Biryukov, J., Yolitz, J., Schuit, M., Wahl, V., Hevey, M., & Dabisch, P. (2020). Simulated Sunlight Rapidly Inactivates SARS-CoV-2 on Surfaces. Journal of Infectious Diseases, 222(2), 214–222. https://doi.org/10.1093/infdis/jiaa274

Secretarias Estaduais de Saúde. (2021). Painel de casos de doença pelo coronavírus 2019 (COVID-19) no Brasil pelo Ministério da Saúde. https://covid.saude.gov.br

Walrand, S. (2021). Autumn COVID-19 surge dates in Europe correlated to latitudes, not to temperature-humidity, pointing to vitamin D as contributing factor. Scientific Reports, 11(1), 1–9. https://doi.org/10.1038/s41598-021-81419-w

Wang, Y., Wang, Y., Chen, Y., & Qin, Q. (2020). Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID-19) implicate special control measures. Journal of Medical Virology, 92(6), 568–576. https://doi.org/10.1002/jmv.25748

Wu, Y., Jing, W., Liu, J., Ma, Q., Yuan, J., Wang, Y., Du, M., & Liu, M. (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. https://doi.org/10.1016/j.scitotenv.2020.139051

Yang, X.-D., Li, H.-L., & Cao, Y.-E. (2021). Influence of Meteorological Factors on the COVID-19 Transmission with Season and Geographic Location. International Journal of Environmental Research and Public Health, 18(2), 1–13. https://doi.org/10.3390/ijerph18020484

Yuan, J., Wu, Y., Jing, W., Liu, J., Du, M., Wang, Y., & Liu, M. (2021). Non-linear correlation between daily new cases of COVID-19 and meteorological factors in 127 countries. Environmental Research, 193, 110521. https://doi.org/10.1016/j.envres.2020.110521

Descargas

Publicado

24/03/2022

Cómo citar

SOUZA JÚNIOR, S. A. de .; FREITAS, P. V. C. de .; HAMBERGER, Y. do V. .; BISOL, L. W. .; SOUZA, F. G. de M. e . Las bajas temperaturas, la alta humedad relativa y las mayores precipitaciones se asocian a un mayor número de muertes por COVID-19. Research, Society and Development, [S. l.], v. 11, n. 4, p. e49111427616, 2022. DOI: 10.33448/rsd-v11i4.27616. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/27616. Acesso em: 23 nov. 2024.

Número

Sección

Ciencias de la salud