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Introduction: SARS-CoV-2 spreads, mainly, through close contact among people, hence the importance of detecting contacts of confirmed cases and identifying the mode of transmission between them.
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Background: International travelers from regions with high incidence rates of COVID-19 have a high probability of being infected and spreading the disease when in contact with other people, so it is necessary to investigate the influence of the entry of these travelers on the transmission of COVID-19 during the second wave of the epidemic. Objective: To determine the influence of the entry of international travelers and other indicators on the transmission of COVID-19 in Santiago de Cuba province. Methods: an ecological study of correlation of the incidence of COVID-19 with certain variables was developed considering as units of analysis the municipalities of Santiago de Cuba province. Spearman's correlation coefficient was used to determine the correlation. To determine the variables that most influenced the number of confirmed cases, multiple linear regression and partial least squares were applied. Cluster analysis was used to determine the most similar municipalities. Results: six models and the formation of several clusters were obtained. The municipality of Santiago de Cuba was atypical. The most influential variables were: travelers, travelers with COVID, number of outbreaks, number of asymptomatic, population density and collaborator. The regions and countries that determined the model were America, Europe, Spain, Mexico and Venezuela. Conclusions: the number of travelers with and without COVID-19 has been a trigger for the number of infected cases in the epidemic in Santiago de Cuba.
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Introduction: Since March 2020, Cuba has been affected by SARS-CoV-2, a highly infectious coronavirus that causes COVID-19. In COVID-19 a set of associated symptoms is presented and its evolution can be influenced by the presence of certain personal pathological antecedents in the host. Objective: To identify through principal components the grouping of clinical variables in cases with COVID-19 in Santiago de Cuba province, Cuba. Methods: We conducted an observational, descriptive and transversal study. The study population consisted of the 49 confirmed cases with COVID-19 in the province of Santiago de Cuba. Ten clinical variables were selected: nine related to symptoms and personal pathological history, and one to the state “deceased”. Principal component analysis was applied as a statistical technique. Results: Variables were represented at the level of the first two principal components. The first component was associated to symptoms and the second component to personal pathological antecedents not associated to the respiratory system. This representation revealed that variables leading to an unfavorable evolution of cases were located in the first and fourth quadrants of the plane, being remarkable for those located in the fourth quadrant. The second and third quadrants were indicators of the favorable evolution, being marked in the second quadrant. Conclusions: The principal component analysis groups the clinical variables and corroborates that personal pathological antecedents have an essential role in the unfavorable evolution of patients with COVID-19. © 2021, Editorial Ciencias Medicas. All rights reserved.
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Introduction: From the onset of COVID-19 epidemic, a multidisciplinary team is formed in Santiago de Cuba with the participation of several institutions and activated by the Provincial Defense Council. Integrated epidemiological analysis, government management and social response would be decisive in controlling the disease. Objectives: To identify possible groups of COVID-19 cases in the Santiago de Cuba province and to describe the transmission according to epidemiological variables.
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Objective: To describe the behaviour of COVID-19 confirmed cases from Santiago de Cuba province between March and April, 2020. Methods: It was carried out a cross-sectional, observational descriptive study taking as studied population 49 COVID-19 positive cases in Santiago de Cuba province between March and April, 2020. There were selected clinic and epidemiologic variables. As statistical technique it was applied the implicative statistical analysis with its three forms: similarity, cohesive, and implicative. Results: It was obtained a set of all the relations among the studied variables in a graphic way, being highlighted the differences among both sexes since the females were related to the asymptomatic category and the males to symptomatic, seriously ill and deceased categories;while older adults were related with the higher amount of personal pathological background and the deceased ones, and young adults were related to the backgrounds and respiratory system’s symptoms. Conclusions: This study allows to visualize, as a distinctive feature of COVID-19 cases´ behaviour in Santiago de Cuba province, that the highest risk sub-group is the one of male 2 older adults with underlying diseases, mainly arterial hypertension, which is similar to what is happening in other regions of the world. © 2020, Editorial Ciencias Medicas. All rights reserved.
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Introduction: The non-homogeneous behavior of the number of COVID-19 confirmed cases in different regions of Cuba has not yet been clarified, which would be useful for decision-making in future epidemics in the country.
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Objective: To describe the behaviour of COVID-19 confirmed cases from Santiago de Cuba province between March and April, 2020.
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Some researchers have used demographic indicators to estimate the number of people infected by COVID-19. The first goal of this study is to determine to what extent the incidence of cases of COVID-19 in the municipalities of the province of Santiago de Cuba can be explained by certain demographic indicators. The second goal is to construct a hierarchy of groups of municipalities according to the differentiated behavior of the selected demographic indicators. An ecological, exploratory, multi-group study was developed, comparing the nine municipalities of Santiago de Cuba province according to global level variables, supposedly related to the number of cases with COVID-19 confirmed from October 15, 2020 to January 16, 2021. Multiple linear regression analysis was applied to select the model that best described the behavior of the data and cluster analysis to visualize the grouping of the municipalities. A significant correlation was found between the number of cases with COVID-19, population density and urbanization level. On the other hand, in the regression model, only population density was significant when the nine municipalities were considered and the masculinity index, when the atypical municipality, Santiago de Cuba, was excluded. The masculinity index turned out to be a spurious variable conditioned by population density as a confounding variable. The cluster analysis revealed the formation of three groups of municipalities, with Santiago de Cuba being isolated from the rest of the municipalities. © 2021, Associacao Brasileira de Estudos Populacionais. All rights reserved.