Demographic, clinical-epidemiological and geospatial aspects of COVID-19 in Santiago de Cuba
Keywords:
COVID-19, Epidemia, Santiago de Cuba, Análisis demográfico, Clínico-epidemiológico, Geoespacial.Abstract
Background: Santiago de Cuba, like the rest of the Cuban provinces, was affected by COVID-19, although it is one of the territories with the lowest incidence of the disease.
Objective: to describe the demographic, clinical-epidemiological and geospatial aspects of COVID-19 in Santiago de Cuba.
Methods: an analytical observational study was carried out at the individual and population levels. At the individual level, the 49 confirmed cases of COVID-19 in the province are used as the study population. The frequency and distribution of cases were estimated, as well as hypothesis tests, with a 5% significance, to discover the differences between them. To analyze the geospatial aspect, the geo-referenced data from all the popular councils into which the province is divided were used as area data, the number of cases by territory and as aggregation units of the information. The exploratory analysis of the spatial data was performed, the spatial autocorrelation was estimated by popular councils, using the Moran global index I, and the formation of clusters was visualized using the local G* statistic from Getis-Ord.
Results: the frequency and distribution of the demographic, clinical and epidemiological characteristics were obtained, as well as the formation of spatial groupings by popular councils according to the number of COVID-19 cases and their significance.
Conclusions: the municipality of Santiago de Cuba marked the differences at the population level in the epidemic of this province. On the other hand, at an individual level, differences were observed between the confirmed cases in some demographic aspects, but not in the clinical or epidemiological ones.
DeCS: CORONAVIRUS INFECTIONS/epidemiology; EPIDEMICS; DEMOGRAPHIC DATA; GEOGRAPHIC INFORMATION SYSTEMS; OBSERVATIONAL STUDY.
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References
1. WHO. Coronavirus disease (COVID-19). Dashboard [Internet]. 2020 [citado 15 Jun 2020]. Disponible en: https://covid19.who.int/.
2. Covid19CubaData [Internet].La Habana: Postdata;c2020 [actualizado 15 Jun 2020; citado 15 Jun 2020]. Disponible en: https://covid19cubadata.github.io/#cuba
3. Díaz-Canel Bermúdez M, Núñez Jover J. Gestión gubernamental y ciencia cubana en el enfrentamiento a la COVID-19. Anales de la Academia de Ciencias de Cuba [Internet]. 2020 [citado 9 Jun 2020]; 10(2). Disponible en: http://www.revistaccuba.cu/index.php/revacc/article/view/881/886
4. Sagaró del Campo NM, Zamora Matamoros L, Valdés García LE, Bergues Cabrales LE, Rodríguez Valdés A, Morandeira Padrón HM. La COVID-19 en Santiago de Cuba desde un análisis estadístico implicativo. Rev Cubana Salud Pública [Internet]. 2020 [citado 10 Nov 2020];46(Suppl especial):[aprox. 21 p.]. Disponible en: http://www.revsaludpublica.sld.cu/index.php/spu/article/view/2578/1560
5. Zhou F, Guo HC, Ho YS, Wu CZ. Scientometric analysis of geostatistics using multivariate methods. Scientometrics [Internet]. 2007 [citado 09 Jun 2020];73(3):[aprox. 14 p.]. Disponible en: https://akjournals.com/view/journals/11192/73/3/article-p265.xml
6. Liao CH, Hung SC, Lee YT, Hung HC, Hsueh PR. How do we decide to de-isolate COVID-19 patients? J Microbiol Immunol Infect [Internet]. 2020 Jun [citado 09 Jun 2020];53(3):[aprox. 2 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194629/.
doi: 10.1016/j.jmii.2020.03.025
7. Bhat AI, Rao GP. Characterization of plant viruses: methods and protocols [Internet]. New York, NY: Humana Press; 2020 [citado 09 Jun 2020]. Disponible en: https://catalog.libraries.psu.edu/catalog/29989350
8. Moreno Serrano R, Vayá EV. Econometría espacial: nuevas técnicas para el análisis regional. Una aplicación a las regiones europeas. Investigaciones Regionales-Journal of Regional Research [Internet]. 2002 [citado 09 Jun 2020];(1):[aprox. 25 p.]. Disponible en: https://www.redalyc.org/pdf/289/28900104.pdf
9. Wen Y, Chen F, Zhang Q, Zhuang Y, Li Z. Detection of differentially methylated regions in whole genome bisulfite sequencing data using local Getis-Ord statistics. Bioinformatics [Internet]. 2016 Nov [citado 09 Jun 2020];32(22):[aprox. 7 p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/27493194/.
doi: 10.1093/bioinformatics/btw497
10. World Medical Association. Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA [Internet]. 2013 Nov [citado 09 Jun 2020];310(20):[aprox. 3 p.]. Disponible en: https://jamanetwork.com/journals/jama/fullarticle/1760318
11. Wei X, Xiao YT, Wang J, Chen R, Zhang W, Yang Y, et al. Sex Differences in Severity and Mortality Among Patients With COVID-19: Evidence from Pooled Literature Analysis and Insights from Integrated Bioinformatic Analysis [Internet]. 2020 [citado 09 Jun 2020]. Disponible en: https://arxiv.org/ftp/arxiv/papers/2003/2003.13547.pdf
12. Centro Cochrane Iberoamericano. Prevalencia de infección asintomática por SARS-CoV-2. Estudios COVID-19 [Internet]. Jun 2020 [citado 09 Jun 2020]. Disponible en: https://es.cochrane.org/es/prevalencia-de-infecci%C3%B3n-asintom%C3%A1tica-por-sars-cov-2
13. Heneghan C, Brassey J, Jefferson T. COVID-19: What proportion are asymptomatic? CEBM [Internet]. 2020 Abr [citado 15 Jun 2020]. Disponible en: https://www.cebm.net/covid-19/covid-19-what-proportion-are-asymptomatic/.
14. Oran DP, Topol EJ. Prevalence of Asymptomatic SARS-CoV-2 Infection: A Narrative Review. Ann Intern Med [Internet]. 2020 [citado 09 Sep 2020]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281624/. doi: 10.7326/M20-3012
15. Li J, Zhang Y, Wang F, Liu B, Li H, Tang G, et al. Sex differences in clinical findings among patients with coronavirus disease 2019 (COVID-19) and severe condition. medRxiv preprint [Internet]. Feb 2020 [citado 09 Jun 2020]. Disponible en: https://www.medrxiv.org/content/10.1101/2020.02.27.20027524v1.full.pdf
doi.org/10.1101/2020.02.27.20027524
16. Promislow DE. A Geroscience Perspective on COVID-19 Mortality. J Gerontol A Biol Sci Med Sci [Internet]. 2020 Sep [citado 09 Jun 2020];75(9):[aprox. 3 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184466/.
doi: 10.1093/gerona/glaa094
17. Onder G, Rezza G, Brusaferro S. Case-fatality rate and characteristics of patients dying in relation to COVID-19 in Italy. JAMA [Internet]. 2020 May [citado 09 Jun 2020];323(18):[aprox. 2 p.]. Disponible en: https://jamanetwork.com/journals/jama/fullarticle/2763667 doi:10.1001/jama.2020.4683
18. Mills JP, Kaye KS, Mody L. COVID-19 in older adults: clinical, psychosocial, and public health considerations. JCI Insight [Internet]. 2020 May [citado 09 Jun 2020];5(10):[aprox. 5 p.]. Disponible en: https://insight.jci.org/articles/view/139292/pdf doi.org/10.1172/jci.insight.139292.
19. Ruocco G, Feola M, Palazzuoli A. Hypertension prevalence in human coronavirus disease: the role of ACE system in infection spread and severity. Int J Infect Dis [Internet]. 2020 Jun [citado 09 Jun 2020];95:[aprox. 2 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180155/.
doi: 10.1016/j.ijid.2020.04.058
20. Ji D, Zhang D, Xu J, Chen Z, Yang T, Zhao P, et al. Prediction for Progression Risk in Patients with COVID‐19 Pneumonia: the CALL Score. Clin Inf Dis [Internet]. 2020 Sep [citado 09 Jun 2020];71(6):[aprox. 6 p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/32271369/. DOI: 10.1093/cid/ciaa414
21. Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med [Internet]. 2020 Jul [citado 09 Jun 2020];180(7):[aprox. 10 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070509/.
doi: 10.1001/jamainternmed.2020.0994
22. Golpe R, Blanco N, Castro-Añón O, Corredoira J, García-Pais MJ, Pérez de-Llano LA, et al. Factores asociados al ingreso hospitalario en un protocolo asistencial en COVID-19. Arch Bronconeumol [Internet]. 2020 Oct [citado 09 Jun 2020];56(10):[aprox. 2 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298471/. doi: 10.1016/j.arbres.2020.05.038
23. Cheung KS, Hung IF, Chan PP, Lung, KC, Tso E, Liu R, et al. Gastrointestinal Manifestations of SARS-CoV-2 Infection and Virus Load in Fecal Samples From a Hong Kong Cohort: Systematic Review and Meta-analysis. Gastroenterology [Internet]. 2020 Jul [citado 09 Jun 2020];159(1):[aprox. 14 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194936/. doi: 10.1053/j.gastro.2020.03.065
24. Parasa S, Desai M, Chandrasekar VT, Patel HK, Kennedy KF, Roesch T, et al. Prevalence of Gastrointestinal Symptoms and Fecal Viral Shedding in Patients With Coronavirus Disease 2019. A Systematic Review and Meta-analysis. JAMA Netw Open [Internet]. 2020 Jun [citado 09 Jun 2020];3(6). Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290409/.
25. Zamora Matamoros L, Sagaró del Campo NM, Valdés García LE, Benítez Jiménez I. Entrada de viajeros y densidad poblacional en la propagación de la COVID-19 en Cuba. Rev Cubana Med [Internet]. 2020 [citado 09 Nov 2020]; 59(3). Disponible en: http://www.revmedicina.sld.cu/index.php/med/article/view/1375/1595
26. Jin L, Zhao Y, Zhou J, Tao M, Yang Y, Wang X, et al. Distribución temporal, geográfica y por población de la nueva enfermedad por coronavirus (COVID-19) desde el 20 de enero hasta el 10 de febrero del 2020, en China. Rev Clin Esp [Internet]. 2020 [citado 09 Jun 2020];220(8):[aprox. 5 p.]. Disponible en: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7151366/.
doi: 10.1016/j.rce.2020.04.001
27. Franch-Pardo I, Napoletano BM, Rosete-Verges F, Billa L. Spatial analysis and GIS in the study of COVID-19. A review. Sci Total Environ [Internet]. 2020 Oct [citado 09 Jun 2020];739. Disponible en: https://www.sciencedirect.com/science/article/pii/S0048969720335531
28. Kang D, Choi H, Kim JH, Choi J. Spatial epidemic dynamics of the COVID-19 outbreak in China. Int J Infect Dis [Internet]. 2020 May [citado 09 Jun 2020];94: [aprox. 6 p.]. Disponible en: https://pubmed.ncbi.nlm.nih.gov/32251789/.

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