Notes on the occurrence and habitats of Sabethes purpureus in Salta Province, Argentina.

The finding of Sabethes purpureus larvae and pupae in tree holes both in urban and forest environments in San Ramón de la Nueva Orán, Salta Province, Argentina, is reported, together with information on the larval habitat. Tree holes were sampled monthly from January to March or April of 2011, 2012, and 2013 along sidewalks, in public access areas, and in 3 sites within forested areas outside the city, selected along an urban gradient in Orán. Sabathes purpureus was most frequently found in low numbers and with other mosquito species. A higher proportion of tree holes was positive in the urban compared to the forest environment, although there were no significant differences in abundances or densities per hole. To our best knowledge, this paper reports the species for the first time breeding in an urban environment, and extends its geographical distribution from the Atlantic and Paranaense forests to the Southern Andean Yungas in northwestern Argentina.

Clinical diagnosis of COVID-19. A multivariate logistic regression analysis of symptoms of COVID-19 at presentation.

INTRODUCTION: The objective of this cross-sectional study was to describe the main symptoms associated with COVID-19, and their diagnostic characteristics, to aid in the clinical diagnosis. METHODS: An analysis of all patients diagnosed by RT-PCR for SARS-CoV-2 between April and May 2020 in Argentina was conducted. The data includes clinical and demographic information from all subjects at the time of presentation (n=67318, where 12% were positive for SARS-CoV-2). The study population was divided into four age groups: pediatric (0-17 years), young adults (18-44 years), adults (45-64 years), and elderly (65-103 years). Multivariate logistic regression was used to measure the association of all symptoms and to create a diagnostic model based on symptoms. RESULTS: Symptoms associated with COVID-19 were anosmia, dysgeusia, headache, low-grade fever, odynophagia, and malaise. However, the presentation of these symptoms was different between the different age groups. In turn, at the time of presentation, the symptoms associated with respiratory problems (chest pain, abdominal pain, and dyspnea) had a negative association with COVID-19 or did not present statistical relevance. On the other hand, the model based on 16 symptoms, age and sex, presented a sensitivity of 80% and a specificity of 46%. CONCLUSIONS: There were significant differences between the different age groups. Additionally, there were interactions between different symptoms that were highly associated with COVID-19. Finally, our findings showed that a regression model based on multiple factors (age, sex, interaction between symptoms) can be used as an accessory diagnostic method or a rapid screening of suspected COVID-19 cases.

Spatial spread of dengue in a non-endemic tropical city in northern Argentina.

After more than eighty years dengue reemerged in Argentina in 1997. Since then, the largest epidemic in terms of geographical extent, magnitude and mortality, was recorded in 2009. In this report we analyzed the DEN-1 epidemic spread in Orán, a mid-size city in a non-endemic tropical area in Northern Argentina, and its correlation with demographic and socioeconomic factors. Cases were diagnosed by ELISA between January and June 2009. We applied a space-time and spatial scan statistic under a Poisson model. Possible association between dengue incidence and socio-economic variables was studied with the Spearman correlation test. The epidemic started from an imported case from Bolivia and space-time analysis detected two clusters: one on February and other in April (in the south and the northeast of the city respectively) with risk ratios of 25.24 and 4.07 (p<0.01). Subsequent cases spread widely around the city without significant space-temporal clustering. Maximum values of the entomological indices were observed in January, at the beginning of the epidemic (B=21.96; LH=8.39). No statistically significant association between socioeconomic variables and dengue incidence was found but positive correlation between population size and the number of cases (p<0.05) was detected. Two mechanisms may explain the observed pattern of epidemic spread in this non-endemic tropical city: a) Short range dispersal of mosquitoes and people generates clusters of cases and b) long-distance (within the city) human movement contributes to a quasi-random distribution of cases.

Identification of geographic factors associated with early spread of foot-and-mouth disease.

OBJECTIVE: To explore whether early analysis of spatial data may result in identification of variables associated with epidemic spread of foot and mouth disease. SAMPLE POPULATION: 37 farms with infected cattle (ie, case farms) reported within the first 6 days of the 2001 Uruguayan foot-and-mouth disease epidemic. PROCEDURE: A georeferenced database was created and retrospective analysis was performed on case farm location in relation to farm density, cattle density, farm type (ie, beef vs dairy cattle production), road density, case farm distance to the nearest road, farm size, farm ownership, and day of infection. Mean or median results of 1 to 3 day versus 4 to 6 day spatial data were compared. Spatial-temporal associations were investigated by correlation analysis. RESULTS: Comparison of mean or median values between the first 3 days and days 4 to 6 of the epidemic and results of correlation analysis indicated a significant increase in road density, cattle density, and dairy cattle production and a significant decrease in farm size and case farm distance to the nearest road that developed over time. A route that linked most case farms by the shortest possible distance and also considered significantly associated variables was created. It included 86.1% of all case farms reported by 60 days into the epidemic. CONCLUSIONS AND CLINICAL RELEVANCE: Epidemic direction can be assessed on the basis of road density and other spatial variables as early as 6 days into an epidemic. Epidemic control areas may be more effectively identified if local and regional georeferenced data are considered.

Markers of disease evolution: the case of tuberculosis.

Abrupt changes in environmental conditions--broadly understood to include demographic and social dynamics--can seriously impact the local or global disease dynamics of a population. These changes in the evolutionary landscape, which may occur over relatively short time-scales, are very likely to play a critical role in disease evolution. The potential impact of demographic, social and epidemiological shifts on the evolution of tuberculosis epidemics in the United States over the past century and a half is the main subject of this article. Evidence is provided to support the hypothesis that the observed substantial decreases in the incidence of active tuberculosis are the result of abrupt reductions in the rates of disease progression.