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Revista Cubana de Medicina Tropical ; 74(1), 2022.
Article in Spanish | Scopus | ID: covidwho-2012463


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. Objective: To identify the main modes of direct transmission among contacts of imported and autochthonous cases. Methods: A cross-sectional descriptive study was conducted in two populations: the confirmed cases of COVID-19 in Santiago de Cuba in the last quarter of 2020, and their declared direct contacts. In the search of the best representativeness, a two-stage stratified sampling method was used. The interview was used to collect the primary data;numbers and percentage, to summarize the information;the one-sample proportion hypothesis test and the compare proportions test using Minitab v.19, to identify possible differences across groups;and Microsoft Excel 2016, to produce the graphics. Results: The average number of contacts was higher among the autochthonous cases, prevailing the co-workers, neighbors and children. The contact-case relationship in imported cases was friend, driver, and mother or father-in-law;while in the autochthonous cases, it was son or daughter. Preventive actions were less used, and extra-domiciliary contacts of imported cases predominated. Contacts of imported cases were hospitalized more often, and had a higher proportion of asymptomatic than the autochthonous cases, but there was no significant differences. Conclusions: A differentiated pattern of transmission was not obtained;except that, transmission among autochthonous cases was between parent and child;while in imported cases, it was between friends. © 2022, Editorial Ciencias Medicas. All rights reserved.

Revista Mexicana De Fisica ; 67(1):123-136, 2021.
Article in English | Web of Science | ID: covidwho-1059946


In the province of Santiago de Cuba, Cuba, the COVID-19 epidemic has a limited progression that shows an early small-number peak of infections. Most published mathematical models fit data with high numbers of confirmed cases. In contrast, small numbers of cases make it difficult to predict the course of the epidemic. We present two known models adapted to capture the noisy dynamics of COVID-19 in the Santiago de Cuba province. Parameters of both models were estimated using the approximate-Bayesian-computation framework with dedicated error laws. One parameter of each model was updated on key dates of travel restrictions. Both models approximately predicted the infection peak and the end of the COVID-19 epidemic in Santiago de Cuba. The first model predicted 57 reported cases and 16 unreported cases. Additionally, it estimated six initially exposed persons. The second model forecasted 51 confirmed cases at the end of the epidemic. In conclusion, an opportune epidemiological investigation, along with the low number of initially exposed individuals, might partly explain the favorable evolution of the COVID-19 epidemic in Santiago de Cuba. With the available data, the simplest model predicted the epidemic evolution with greater precision, and the more complex model helped to explain the epidemic phenomenology.