clinicaltrials.gov Identifier: NCT01374022.

Abstract. In this study, we aimed to estimate the effect that environmental, demographic, and socioeconomic factors have on dengue mortality in Latin America and the Caribbean. To that end, we conducted an observational ecological study, analyzing data collected between 1995 and 2009. Dengue mortality rates were highest in the Caribbean (Spanishspeaking and non-Spanish-speaking). Multivariate analysis through Poisson regression revealed that the following factors were independently associated with dengue mortality: time since identification of endemicity (adjusted rate ratio ; population density (aRR = 2.1 and 3.2 for 20-120 inhabitants/km 2 and > 120 inhabitants/km 2 , respectively); Human Development Index > 0.83 (aRR = 0.4); and circulation of the dengue 2 serotype (aRR = 1.7). These results highlight the important role that environmental, demographic, socioeconomic, and biological factors have played in increasing the severity of dengue in recent decades.

We evaluated biochemical alterations as predictors of dengue hemorrhagic fever (DHF). Patients with confirmed infection with dengue virus were prospectively evaluated for the first seven days of disease to determine their final clinical outcome. Serum samples taken 48-96 hours after onset of fever were used for biochemical tests. Of 199 patients, 30 developed DHF. Cases of DHF had higher levels of lactate dehydrogenase (LDH), creatine kinase (CK), and aspartate aminotransferase, and lower levels of albumin, total cholesterol, and triglycerides. Multivariate analysis showed that early alterations of CK (hazard ratio [HR] = 6.98, 95% confidence interval [CI] = 2.34-20.85, P = 0.001), LDH (HR = 3.19, 95% CI = 1.01-10.12, P < 0.05), and albumin (HR = 2.54, 95% CI = 1.09-5.92, P = 0.03) were associated with DHF. Triglyceride levels > 160 mg/dL were negatively associated with developing DHF (HR = 0.07, 95% CI = 0.01-0.59, P = 0.01). Early alterations of biochemical markers can predict DHF in patients with acute fever caused by dengue.

BackgroundOdds ratios (OR) significantly overestimate associations between risk factors and common outcomes. The estimation of relative risks (RR) or prevalence ratios (PR) has represented a statistical challenge in multivariate analysis and, furthermore, some researchers do not have access to the available methods. Objective: To propose and evaluate a new method for estimating RR and PR by logistic regression.MethodsA provisional database was designed in which events were duplicated but identified as non-events. After, a logistic regression was performed and effect measures were calculated, which were considered RR estimations. This method was compared with binomial regression, Cox regression with robust variance and ordinary logistic regression in analyses with three outcomes of different frequencies.ResultsORs estimated by ordinary logistic regression progressively overestimated RRs as the outcome frequency increased. RRs estimated by Cox regression and the method proposed in this article were similar to those estimated by binomial regression for every outcome. However, confidence intervals were wider with the proposed method.ConclusionThis simple tool could be useful for calculating the effect of risk factors and the impact of health interventions in developing countries when other statistical strategies are not available.

BackgroundCommunity integration in dengue control requires assessments of knowledge, attitudes and practices (KAPs), which can vary widely according to demographic and educational factors. We aimed to describe and compare the KAPs according to level of education in municipalities in the Caribbean region of Colombia.MethodsA survey was administered from October to December 2015, including families selected through probabilistic sampling in eleven municipalities. The analysis focused on the comparative description of the responses according to level of education. The KAP prevalence ratios (PR) according to education were estimated using Poisson regression (robust), including age and sex as adjustment variables.ResultsOut of 1057 participants, 1054 (99.7%) surveys were available for analysis, including 614 (58.3%) who had a high school level of education or higher and 440 (41.7%) who had a lower level of education (not high school graduates). The high school graduates showed a higher frequency of correct answers in relation to knowledge about dengue symptoms and transmission.On the other hand, graduates showed a higher probability of practices and attitudes that favor dengue control, including not storing water in containers (PR: 2.2; 95% Confidence Interval [CI]: 1.42–3.43), attend community meetings (PR: 1.33; 95% CI: 1.07–1.65), educate family members and neighbors in prevention measures (PR: 1.35; 95% CI: 1.15–1.59).ConclusionsLevel of education could be a key determinant of knowledge of the disease and its transmission, as well as attitudes and practices, especially those that involve the integration of community efforts for dengue control.

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The above findings suggest that doxycycline can provide a clinical benefit to dengue patients at high risk of complications. This effect could be mediated by decreasing pro-inflammatory cytokine levels.

Although many studies have identified social conditions associated with tuberculosis, contextual and individual factors have rarely been analysed simultaneously. Consequently, we aimed to identify contextual and individual factors associated with tuberculosis incidence in general population in Brazil in 2010. We also assessed whether household crowding mediates the association between socioeconomic determinants and tuberculosis incidence. Individual data of tuberculosis cases were obtained from 5,565 municipalities in Brazil in 2010 (last year of national census), and merged with contextual variables. The associations were evaluated in a multilevel analysis using negative binomial regression. After adjusting for individual factors (age, sex and race) and geographic region, the following contextual factors were associated with tuberculosis incidence rate: AIDS incidence rate [incidence rate ratio (IRR), 1.21; 95% confidence interval (CI), 1.18–1.24], unemployment rate (IRR, 1.16; 95% CI, 1.13–1.19), Gini coefficient (IRR, 1.05; 95% CI, 1.02–1.08), proportion of inmates (IRR, 1.11; 95% CI, 1.09–1.14), mean per capita household income (IRR, 0.94; 95% CI, 0.91–0.97) and primary care coverage (IRR, 0.94; 95% CI, 0.92–0.96). Inclusion of household crowding in the multivariate model led to a loss of the associations of both Gini coefficient and mean per capita household income. In conclusion, our findings suggest that income inequality and poverty, as determinants of tuberculosis incidence, can be mediated by household crowding. Moreover, prison population can represent a potential social reservoir of tuberculosis in Brazil and should be addressed as a priority for disease control. Finally, the negative association between primary health coverage and tuberculosis incidence highlights the importance of this level of care as a strategy to control this disease.