Influence of climatic variables on COVID-19: how might the proximity of summer affect the pandemic results?

  • JEAN LUCAS POPPE URI

Resumo

The beginning of the summer in the south hemisphere has caused some optimism in the population about the flattening in the curve of new cases of COVID-19, resulting in a population behavior of relaxing the prevention measures against the SARS-CoV-2 outbreak. The present study aims to investigate the relationship among climatic and sociodemographic elements over the pandemic data in a subtropical countryside municipality where the temperatures are becoming high by the proximity of the summer. Data about confirmed cases of COVID-19 were obtained in the daily bulletins from the Municipal Health Secretariat and climatic data were obtained from the local meteorological station. Spearman correlation analyses were performed for verifying the relationship between daily average values of temperature, relative air humidity and wind speed with recorded cases of COVID-19. Most of infected people (41.8%) live in the downtown, which is the main trade area and presents high movement of people in the municipality, being it classified as a super spread region of SAR-CoV-2. The statistical correlations between daily cases of COVID-19 and the climatic variables were revealed as not significant. Thus, the summer climatic conditions probably will not flatten the pandemic curve as it has been waited for many people.

Referências

1. Zhou T, Liu QH, Yang ZM, Liao JY, Yang KX, Bai W, Lu X, Zhang W. Preliminary prediction of the basic reproduction number of the Wuhan novel coronavirus 2019-nCov. J Evid Based Med. 2020; 13: 3-7. doi.org/10.1111/jebm.12376
2. Zhang T, Wu Qunfu, Zhang Zhigang. Probable Pangolin Origin of SARS-CoV-2 Associated with the COVID-19 Outbreak. Current Biol. 2020; 30: 1346-1351. doi.org/10.1016/j.cub.2020.03.022.
3. Lescure F, Bouadma L, Nguyen D, Parisey M, Wicky P, Behillil S, et al. Clinical and virological data of the first cases of COVID-19 in Euripe: a case series. Lancet Infect Diseases. 2020; 20: 697-706. doi.org/10.1016/S1473-3099(20)30200-0.
4. Dhaval D. Urban Densities and the Covid-19 Pandemic: Upending the Sustainability Myth of Global Megacities. Observer Res Found. 2020; 244: 1-42.
5. Barreto Ml, Barros AJD, Carvalho MS, Codeço CT, Hallas PRC, Medronho RA, et al. O que é urgente e necessário para subsidiar as políticas de enfrentamento da pandemia de Covid-19 no Brasil? Rev Brasil Epidemiol. 2020; 23: 1-4. doi.org/10.1590/1980-549720200032.
6. Zheng J. SARS-CoV-2: an Emerging Coronavirus that Causes a Global Threat. Int J Biol Sci. 2020; 16(10): 1678–1685. doi.org/10.7150/ijbs.45053.
7. Wenham C, Smith J, Morgan R. COVID-19 Working Group. COVID-19: the gendered impacts of the outbreak. The Lancet. 2020; 395: 846-848.
8. Chen B, Liang H, Yuan X, Hu Y, Xu M, Zhao Y, et al. Roles of meteorological conditions inCOVID-19 transmission on a worldwide scale. medRxi. 2020; doi.org/10.1101/2020.03.16.20037168.
9. Auler AC, Cássaro FAM, Da Silva VO, Pires LF. 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. Sci Total Environ. 2020; 729 (2020): 139090. doi.org/10.1016/j.scitotenv.2020.139090.
10. Gupta R, Dhamija RK, Gaur K. Epidemiological transmition of Covid-19 in India from higher to lower HDI States and territories: implications for prevention and control. medRxiv. 2020. doi.org/10.1101/2020.05.05.20092593.
11. Suryawanshi DM, Venugopal R, Goyal R. Factors influencing COVID-19 case burden and fatality rates findings from secondary data analysis of major urban agglomerations in India. Int J Community Med Public Health. 2020; 7(8): 3284-3292. doi.org/10.18203/2394-6040.ijcmph20203415.
12. Alvi MM, Sivasankaran S, Singh M. Pharmacological and non-pharmacological efforts at prevention, mitigation, and treatment for COVID-19. J Drug Targeting. 2020. doi.org/10.1080/1061186X.2020.1793990.
13. Instituto Brasileiro de Geografia e Estatística – IBGE. Pesquisa Nacional do Índice de Desenvolvimento Humano (IDH) por município. [accessin jun 10th 2020]. Available in: https://cidades.ibge.gov.br/brasil/rs/sao-luiz-gonzaga/panorama.
14. Serviço de Apoio às Micro e Pequenas Empresas do Rio Grande do Sul – SEBRAE. Perfil das cidades gaúchas 2019 - São Luiz Gonzaga. [access in jun 10th 2020]; 21p. Available in: https://datasebrae.com.br/municipios/rs/Perfil_Cidades_Gauchas-Sao_Luiz_Gonzaga.pdf.
15. Mehl-Madrona LE, Bricaire F, Cuyugan A, Barac J, Parvaiz A, Jamil AB, Iqbal S, Koliali M, Vally R, Sellier MK. Understanding SARSCOV-2 propagation, impacting factors to derive possible scenarios and simulations. medRxiv, 2020; https://doi.org/10.1101/2020.09.07.20190066.
16. Hammer ∅, Harper DAT, Ryan PD. PAST: Palaeontological Statistics software for education and data analysis. Palaeontol Electronica. 2001; 4: 1-9.
17. Huang L, Zhang X, Zhang X, Wei Z, Zhang L, Xu J, et al. Rapid asymptomatic transmission of COVID-19 during the incubation period demonstrating strong infectivity in a cluster of youngsters aged 16-23 years outside Wuhan and characteristics of young patients with COVID-19: A prospective contact-tracing study. J Infec. 2020; 80(2020): e1–e13, 2020. doi.org/10.1016/j.jinf.2020.03.006.
18. Watson M., Gilmour R., Menzies R., Ferson M., McIntyre P. The Association of Respiratory Viruses, Temperature and Other Climatic Parameters with the Incidence of Invasive Pneumococcal Disease in Sydney, Australia. Clinic Infect Dis. 2006; 42: 211-215. doi.org/10.1086/498897.
19. Lowen AC, Mubareka S, Steel J, Palese P. Influenza virus transmission is dependent on relative humidity and temperature. PLoS Pathog 2007; 3(10): 1470-1476. doi.org/10.1371/journal.ppat.0030151.
20. Moriyama M, Hugentobler WJ, Iwasaki A. Seasinality of Respiratory Viral Infections. Annual rev Virol. 2020; 7, 83-101. doi.org/10.1146/annurev-virology-012420-022445.
21. Batistella C. Saúde, Doença e Cuidado: complexidade teórica e necessidade histórica. In: Fonseca AF, Corbo AMD'A. (orgs.). O território e o processo saúde-doença. Rio de Janeiro: EPSJV/FIOCRUZ. 2007; 25-50.
22. Azizi GG, Orsini M, Dortas Júnior SD, Vieira PC, Carvalho RS, Pires CSR, et al. COVID-19 e atividade física: qual a relação entre a imunologia do exercício e a atual pandemia? Rev Bras Fisiol Exerc. 2020; 19: 20-29. doi.org/10.33233/rbfe.v19i2.4115.
23. Azizi GG, Orsini M, Dortas Júnior SD, Cerbino SA. Obesidade e imunologia do exercício: implicações em tempos de pandemia de COVID-19. Rev Bras Fisiol Exerc. 2020; 19: 35-39. doi.org/10.33233/rbfe.v19i2.4023.
24. Lippi G, Henry BM, Sanchis-Gomar F. Physical inactivity and cardiovascular disease at the time of coronavirus disease 2019 (COVID-19). Eur J Prev Cardiol. 2020; 27(9): 906–908. doi.org/10.1177/2047487320916823.
25. Dalziel BD, Kissler S, Gog JR, Viboud C, Bjørnstad ON, Metcalf CJE, et al. Urbanization and humidity shape the intensity of influenza epidemics in U.S. cities. Science. 2018; 362: 75-79.
26. Yuan J, Yun H, Lan W, Wang W, Sullivan SG, Jia S, et al. A climatologic investigation of the SARS-CoV outbreak in Beijing, China. Am. J. Infect. Control 2006; 34: 234-236.
27. Anderson RM, Heesterbeek H, Klinkenberg D, Hollingsworth TD. How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancet. 2020; 395: 931-934.
28. Qualls N, Levitt A, Kanade N, Wright-Jegede N, Dopson S, Biggerstaff M, et al. Community Mitigation Guidelines to Prevent Pandemic Influenza - United States, 2017. MMWR Recommendations and Reports. 2017; 66: 1-34. doi.org/10.15585/mmwr.rr6601a1.
29. Wang J, DU G. COVID-19 may transmit through aerosol. Irish J Med Sci. 2020. doi.org/10.1007/s11845-020-02218-2.
30. Contini D, Costabile F. Does Air Pollution Influence COVID-19 Outbreaks? Atmosphere. 2020; 11: 377. doi:10.3390/atmos11040377.
31. Morawska L, Tang JW, Bahnfleth W, Bluyssen PM, Boerstra A, Buonanno G, et al. How can airborne transmission of COVID-19 indoors be minimised? Environ Int. 2020; 142 (2020) 105832. doi.org/10.1016/j.envint.2020.105832
32. Gupta M, Abdelmaksoud A, Jafferany M, Lotti T, Sadoughifar R, Goldust M. COVID-19 and economy. Dermatol Ther. 2020;e13329. doi.org/10.1111/dth.13329.
33. Tosepu R, Gunawan J, Effendy DS, Ahmad LOAI, Lestari H, Bahar H, Asfian P. Correlation between weather and Covid-19 pandemic in Jakarta, Indonesia. Sci Total Environ. 2020; 725: 138436. doi.org/10.1016/j.scitotenv.2020.138436.
34. Yuan J, Yun H, Lan W, Wang W, Sullivan SG, Jia S, et al. A climatologic investigation of the SARS-CoV outbreak in Beijing, China. Am J Infec Control. 2006; 34: 234-236.
35. Liu J, Zhou J, Yao J, Zhang X, Li L, Xu X, et al., Impact of meteorological factors on the COVID-19 transmission: A multicity study in China. Sci Total Environ. 2020; 726 (2020): 138513. doi.org/10.1016/j.scitotenv.2020.138513.
36. De Souza CDF, Santana GBA, Leal TC, De Paiva JPS, Da Silva LF, Santos LG, et al. Spatiotemporal evolution of coronavirus disease 2019 mortality in Brazil in 2020. J Bras Soc Trop Med. 2020; 53: e20200282. doi.org/10.1590/0037-8682-0282-2020.
37. Lima DLF, Dias AA, Rabelo RS, Cruz ID, Costa SC, Nigri FMN, Neri JR. COVID-19 no estado do Ceará, Brasil: comportamentos e crenças na chegada da pandemia. Cien Saude Colet. 2020; 25(5): 1575-1586. doi.org/10.1590/1413-81232020255.07192020.
38. Guerra-Shinohara E, Weber SS, Paniz C, Gomes GW, Shinohara EJ, Gandra TBR, et al. Overview on COVID-19 outbreak indicators across Brazilian federative units. medRxiv. doi.org/10.1101/2020.06.02.20120220.
Publicado
2021-03-01