Spread pattern of the first dengue epidemic in the city of Salvador, Brazil

<p>Abstract</p> <p>Background</p> <p>The explosive epidemics of dengue that have been occurring in various countries have stimulated investigation into new approaches to improve understanding of the problem and to develop new strategies for controlling the disease. The objective of this study was to evaluate the characteristics of diffusion of the first dengue epidemic that occurred in the city of Salvador in 1995.</p> <p>Methods</p> <p>The epidemiological charts and records of notified cases of dengue in Salvador in 1995 constituted the source of data. The cases of the disease were georeferenced according to census areas (spatial units) and epidemiological weeks (temporal unit). Kernel density estimation was used to identify the pattern of spatial diffusion using the R-Project computer software program.</p> <p>Results</p> <p>Of the 2,006 census areas in the city, 1,400 (70%) registered cases of dengue in 1995 and the spatial distribution of these records revealed that by the end of 1995 practically the entire city had been affected by the virus, with the largest concentration of cases occurring in the western region, composed of census areas with a high population density and predominantly horizontal residences compared to the eastern region of the city, where there is a predominance of vertical residential buildings.</p> <p>Conclusion</p> <p>The pattern found in this study shows the characteristics of the classic process of spreading by contagion that is common to most infectious diseases. It was possible to identify the epicenter of the epidemic from which centrifugal waves of the disease emanated. Our results suggest that, if a more agile control instrument existed that would be capable of rapidly reducing the vector population within a few days or of raising the group immunity of the population by means of a vaccine, it would theoretically be possible to adopt control actions around the epicenter of the epidemic and consequently reduce the incidence of the disease in the city. This finding emphasizes the need for further research to improve the technology available for the prevention of this disease.</p

Factors associated with delayed diagnosis of tuberculosis in hospitalized patients in a high TB and HIV burden setting: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>The most essential components of TB control are early diagnosis and adequate treatment. Delay in the diagnosis and treatment of tuberculosis may result in more extensive disease and more complications, increase severity of the disease and is associated with higher risk of mortality. The purpose of this study was to identify factors associated with delayed diagnosis of TB in hospitalized patients.</p> <p>Methods</p> <p>We conducted a cross-sectional study in a general, tertiary care, university-affiliated hospital. Adult patients with TB that were hospitalized were identified retrospectively, and risk factors for delayed diagnosis were collected.</p> <p>Results</p> <p>The median delay until diagnosis was 6 days (IQR: 2-12 days). One hundred and sixty six (54.4%) patients were diagnosed ≤ 6 days, and 139 (45.6%) > 6 days after admission. The main factors associated with diagnostic delay (> 6 days) were extra-pulmonary TB and negative sputum smear.</p> <p>Conclusions</p> <p>Although hospitalization permits a rapid management of the patient and favors a faster diagnosis, we found an unacceptable time delay before the diagnosis of pulmonary TB was made. Future studies should focus on attempt to explain the reasons of diagnostic retard in the patients with the characteristics related to delay in this study.</p

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

BACKGROUND: Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. METHODS: The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. RESULTS: It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. CONCLUSION: The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources