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Background: HIV transmitted drug resistance (TDR) remains at moderate level in Latin America and the Caribbean (LAC). However, different epidemiologic scenarios could influence national and sub-regional TDR levels and trends. Methods and Findings: We performed a systematic review of currently available publications on TDR in antiretroviral treatment-naïve adults in LAC. Ninety-eight studies published between January 2000 and June 2015 were included according to critical appraisal criteria and classified by sub-region: Brazil (50), Mesoamerica (17), Southern Cone (16), Andean (8) and Caribbean (7). From these, 81 studies encompassing 11,441 individuals with data on DR mutation frequency were included in a meta-analysis. Overall TDR prevalence in LAC was 7.7% (95% CI: 7.2%-8.2%). An increasing trend was observed for overall TDR when comparing 2000–2005 (6.0%) and 2006–2015 (8.2%) (p<0.0001), which was associated with significant NNRTI TDR increase (p<0.0001). NRTI TDR decreased (4.5% vs. 2.3%, p<0.0001). NNRTI TDR increase was associated mainly with K101E, K103N and G190A. NRTI TDR decrease was associated mainly with M184V, K70R and T215Y. All sub-regions reached moderate overall TDR levels. The rapid increase in TDR to all antiretroviral classes in the Caribbean is notable, as well as the significant increase in NNRTI TDR reaching moderate levels in the Southern Cone. NRTI TDR was dominant in 2000–2005, mainly in the Caribbean, Mesoamerica and Brazil. This dominance was lost in 2006–2015 in all sub-regions, with the Southern Cone and the Caribbean switching to NNRTI dominance. PI TDR remained mostly constant with a significant increase only observed in the Caribbean. Conclusions: Given the high conceptual and methodological heterogeneity of HIV TDR studies, implementation of surveys with standardized methodology and national representativeness is warranted to generate reliable to inform public health policies. The observed increasing trend in NNRTI TDR supports the need to strengthen TDR surveillance and programme monitoring and evaluation in LAC. [ABSTRACT FROM AUTHOR]

Objective: To carry out a systematic review with meta-analysis of prevalence of caries in Latin America and Caribbean children considering studies performed in this new century. Methods: Two reviewers searched PubMed, Embase, LILACS and governmental databases through May 2016 to identify papers published in English, Portuguese or Spanish. Studies in those countries performed with 5–6 or 11–13 year-old children and that presented separate prevalence figures from primary and permanent teeth were selected. We performed a descriptive analysis of studies and meta-analysis to calculate the overall prevalence and 95% confidence intervals (95% CI) in both primary and permanent teeth. We also analyzed the trends of prevalence of caries through the years and influence of other variables on caries prevalence using multilevel analysis. Results: Seventy-five studies were included from the 1,306 articles initially retrieved. The meta-analysis of caries prevalence grouped for Latin American and the Caribbean countries were highly different from Brazil and other investigated countries for primary teeth (5–6 years-old—Brazil: 0.52, other countries:0.70) and permanent teeth (11–12 years-old—Brazil: 0.56, other countries: 0.63). For studies conducted only in Brazil the prevalence was significant lower for primary but not for permanent teeth. In Brazil, a downward trend of caries prevalence was observed in 11-13-year-old children. Conclusion: Despite the decline of caries prevalence in permanent teeth, mainly in Brazil, the disease still affects more than half of the children population in Latin American and Caribbean countries in the 21st Century. [ABSTRACT FROM AUTHOR]

The adoption of the shared prosperity goal by the World Bank in 2013 and Sustainable Development Goal 10, on inequality, by the United Nations in 2015 should strengthen the focus of development interventions and cooperation on the income growth of the bottom 40 percent of the income distribution. This paper contributes to the incipient literature on within-country allocations of development institutions and assesses the geographic targeting of World Bank projects to the bottom 40 percent. Bivariate correlations between the allocation of project funding approved over 2005–14 and the geographical distribution of the bottom 40 as measured by survey income or consumption data are complemented by regressions with population and other potential factors affecting the within-country allocations as controls. The correlation analysis shows that, of the 58 countries in the sample, 41 exhibit a positive correlation between the shares of the bottom 40 and World Bank funding, and, in almost half of these, the correlation is above 0.5. Slightly more than a quarter of the countries, mostly in Sub-Saharan Africa, exhibit a negative correlation. The regression analysis shows that, once one controls for population, the correlation between the bottom 40 and World Bank funding switches sign and becomes significant and negative on average. This is entirely driven by Sub-Saharan Africa and not observed in the other regions. Hence, the significant and positive correlation in the estimations without controlling for population suggests that World Bank project funding is concentrated in administrative areas in which more people live (including the bottom 40) rather than in poorer administrative areas. Furthermore, capital cities receive disproportionally high shares of World Bank funding on average. [ABSTRACT FROM AUTHOR]

Measuring quality of care in family planning services is essential for policymakers and stakeholders. However, there is limited agreement on which mathematical approaches are best able to summarize quality of care. Our study used data from recent Service Provision Assessment surveys in Haiti, Malawi, and Tanzania to compare three methods commonly used to create summary indices of quality of care—a simple additive, a weighted additive that applies equal weights among domains, and principal components analysis (PCA) based methods. The PCA results indicated that the first component cannot sufficiently summarize quality of care. For each scoring method, we categorized family planning facilities into low, medium, and high quality and assessed the agreement with Cohen’s kappa coefficient between pairs of scores. We found that the agreement was generally highest between the simple additive and PCA rankings. Given the limitations of simple additive measures, and the findings of the PCA, we suggest using a weighted additive method. [ABSTRACT FROM AUTHOR]

Background: Over 18 million adults have initiated life-saving antiretroviral therapy (ART) in resource-poor settings; however, mortality and lost-to-follow-up rates continue to be high among patients in their first year after treatment start. Clinical decision tools are needed to identify patients at high risk for poor outcomes in order to provide individualized risk assessment and intervention. This study aimed to develop and externally validate risk prediction tools that estimate the probability of dying or of being lost to follow-up (LTF) during the year after starting ART. Methods: We used a derivation cohort of 7,031 adults age 15–70 years initiating ART from 2007 to 2013 at 6 clinics in Haiti; 242 (3.5%) had documented death and 1,521 (21.6%) were LTF at 1 year after starting ART. The following routinely collected data were used as predictors in two logistic regression models (one to predict death and another to predict LTF): age, gender, weight, CD4 count, WHO Stage, and diagnosis of tuberculosis (TB). The validation cohort consisted of 1,835 adults initiating ART at a different HIV clinic in Haiti during 2012. We assessed model discrimination by measuring the C-statistic, and measured model calibration by how closely the predicted probabilities approximated actual probabilities of the two outcomes. We derived a nomogram and a point-based risk score from the predictive models. Findings: The model predicting death within the year after starting ART had a C-statistic of 0.75 (95% CI 0.74 to 0.81). There was no evidence for significant overfitting and the predictions were well calibrated. The strongest predictors of 1-year mortality were male gender, low weight, low CD4 count, advanced WHO stage, and the absence of TB. In the validation cohort, the C-statistic was 0.69 (95% CI 0.59 to 0.77). A point-based risk score for death had a C-statistic 0.73 (95% CI 0.69 to 0.76) and categorizes patients as low risk (<2% risk of death), average risk (3–4%), and high-risk (8–10%) and very high-risk (14–19%) with likelihood ratios to be used in settings where the baseline risk is different from our study population. The model predicting LTF did not discriminate well (C-statistic 0.59). Conclusions: A simple risk-score using routinely collected data can predict 1-year mortality after ART initiation for HIV-positive adults in Haiti. However, predicting lost to follow-up using routinely collected data was not as successful. The next step is to assess whether use of this risk score can identify patients who need tailored services to reduce mortality in resource-poor settings such as Haiti. [ABSTRACT FROM AUTHOR]

Various natural and manmade disasters during last decades have highlighted the need of further improving on governmental preparedness to emergency events, and a relief supplies distribution problem named Inventory Slack Routing Problem (ISRP) has received increasing attentions. In an ISRP, inventory slack is defined as the duration between reliefs arriving time and estimated inventory stock-out time. Hence, a larger inventory slack could grant more responsive time in facing of various factors (e.g., traffic congestion) that may lead to delivery lateness. In this study, the relief distribution problem is formulated as an optimization model that maximize the minimum slack among all dispensing sites. To efficiently solve this problem, we propose a two-stage approach to tackle the vehicle routing and relief allocation sub-problems. By analyzing the inter-relations between these two sub-problems, a new objective function considering both delivery durations and dispensing rates of demand sites is applied in the first stage to design the vehicle routes. A hierarchical routing approach and a sweep approach are also proposed in this stage. Given the vehicle routing plan, the relief allocation could be easily solved in the second stage. Numerical experiment with a comparison of multi-vehicle Traveling Salesman Problem (TSP) has demonstrated the need of ISRP and the capability of the proposed solution approaches. [ABSTRACT FROM AUTHOR]

Model-based epidemiological assessment is useful to support decision-making at the beginning of an emerging Aedes-transmitted outbreak. However, early forecasts are generally unreliable as little information is available in the first few incidence data points. Here, we show how past Aedes-transmitted epidemics help improve these predictions. The approach was applied to the 2015–2017 Zika virus epidemics in three islands of the French West Indies, with historical data including other Aedes-transmitted diseases (Chikungunya and Zika) in the same and other locations. Hierarchical models were used to build informative a priori distributions on the reproduction ratio and the reporting rates. The accuracy and sharpness of forecasts improved substantially when these a priori distributions were used in models for prediction. For example, early forecasts of final epidemic size obtained without historical information were 3.3 times too high on average (range: 0.2 to 5.8) with respect to the eventual size, but were far closer (1.1 times the real value on average, range: 0.4 to 1.5) using information on past CHIKV epidemics in the same places. Likewise, the 97.5% upper bound for maximal incidence was 15.3 times (range: 2.0 to 63.1) the actual peak incidence, and became much sharper at 2.4 times (range: 1.3 to 3.9) the actual peak incidence with informative a priori distributions. Improvements were more limited for the date of peak incidence and the total duration of the epidemic. The framework can adapt to all forecasting models at the early stages of emerging Aedes-transmitted outbreaks. [ABSTRACT FROM AUTHOR]