Entrada de viajeros y densidad poblacional en la propagación de la COVID-19 en Cuba / Arrival of travelers and population density in the spread of COVID-19 in Cuba

Introducción: El comportamiento no homogéneo de la cantidad de casos confirmados con COVID-19 en diferentes regiones de Cuba aún no se ha esclarecido, lo cual resultaría de utilidad para la toma de decisiones en futuras epidemias en el país. Objetivo: Determinar la influencia de la entrada de viajeros y la densidad poblacional sobre la distribución no homogénea de la cantidad de casos con COVID-19 por provincias en Cuba. Métodos: Se desarrolló un estudio ecológico, exploratorio, de grupos múltiples, comparando las provincias cubanas según variables del nivel global y agregado, relacionadas con la cantidad de casos con COVID-19, confirmados durante la epidemia en Cuba. Se aplicó el análisis de regresión lineal múltiple para seleccionar el modelo que mejor describe el comportamiento de los datos y el análisis de clúster para visualizar la agrupación de las provincias. Resultados: Se evidenció una correlación significativa entre la cantidad de casos con COVID-19 y la cantidad de viajeros con COVID-19, la cantidad total de viajeros que arribaron al país en marzo y los eventos de trasmisión. En el modelo de regresión resultaron significativas la densidad poblacional y las cantidades de viajeros total y con COVID-19. El análisis de clúster reveló la formación de cuatro grupos de provincias. Conclusiones: La cantidad de casos con COVID-19 por provincia se relaciona con la cantidad de viajeros que entraron al país, con y sin COVID-19, y la densidad poblacional. Se forman cuatro grupos de provincias por su similitud en los aspectos identificados en la regresión(AU)

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. Objective: To determine the influence of the arrival of travelers and the population density on the non-homogeneous distribution of the number of COVID-19 cases by provinces in Cuba. Methods: An ecological, exploratory, multiple group study was carried out, comparing Cuban provinces according to variables of the global and aggregate levels, related to the number of COVID-19 cases, confirmed during the epidemic in Cuba. Multiple linear regression analysis was applied to select the model that best describes the behavior of the data and cluster analysis to visualize the grouping of the provinces. Results: A significant correlation was proved between the number of COVID-19 cases and the number of travelers with COVID-19, the total number of travelers who arrived in Cuba in March, and transmission events. In the regression model, the population density and the total number of travelers and those with COVID-19 were significant. The cluster analysis revealed the formation of four groups of provinces. Conclusions: The number of cases with COVID-19 by province is related to the number of travelers who arrived in the country, with and with no COVID-19, and the population density. Four groups of provinces are formed by their similarity in the aspects identified at regression(AU)

Influenza and other respiratory viruses in three Central American countries.

BACKGROUND: Despite the disease burden imposed by respiratory diseases on children in Central America, there is a paucity of data describing the etiologic agents of the disease. AIMS: To analyze viral etiologic agents associated with influenza-like illness (ILI) in participants reporting to one outpatient health center, one pediatric hospital, and three general hospitals in El Salvador, Honduras, and Nicaragua Material & METHODS: Between August 2006 and April 2009, pharyngeal swabs were collected from outpatients and inpatients. Patient specimens were inoculated onto cultured cell monolayers, and viral antigens were detected by indirect and direct immunofluorescence staining. RESULTS: A total of 1,756 patients were enrolled, of whom 1,195 (68.3%) were under the age of 5; and 183 (10.4%) required hospitalization. One or more viral agents were identified in 434 (24.7%) cases, of which 17 (3.9%) were dual infections. The most common viruses isolated were influenza A virus (130; 7.4% of cases), respiratory syncytial virus (122; 6.9%), adenoviruses (63; 3.6%), parainfluenza viruses (57; 3.2%), influenza B virus (47; 2.7% of cases), and herpes simplex virus 1 (22; 1.3%). In addition, human metapneumovirus and enteroviruses (coxsackie and echovirus) were isolated from patient specimens. DISCUSSION: When compared to the rest of the population, viruses were isolated from a significantly higher percentage of patients age 5 or younger. The prevalence of influenza A virus or influenza B virus infections was similar between the younger and older age groups. RSV was the most commonly detected pathogen in infants age 5 and younger and was significantly associated with pneumonia (p < 0.0001) and hospitalization (p < 0.0001). CONCLUSION: Genetic analysis of influenza isolates identified A (H3N2), A (H1N1), and B viruses. It also showed that the mutation H274Y conferring resistance to oseltamivir was first detected in Honduran influenza A/H1N1 strains at the beginning of 2008. These data demonstrate that a diverse range of respiratory pathogens are associated with ILI in Honduras, El Salvador, and Nicaragua. RSV infection in particular appears to be associated with severe disease in infants in the region.