Using non-exceedance probabilities of policy-relevant malaria prevalence thresholds to identify areas of low transmission in Somalia.

BACKGROUND: Countries planning malaria elimination must adapt from sustaining universal control to targeted intervention and surveillance. Decisions to make this transition require interpretable information, including malaria parasite survey data. As transmission declines, observed parasite prevalence becomes highly heterogeneous with most communities reporting estimates close to zero. Absolute estimates of prevalence become hard to interpret as a measure of transmission intensity and suitable statistical methods are required to handle uncertainty of area-wide predictions that are programmatically relevant. METHODS: A spatio-temporal geostatistical binomial model for Plasmodium falciparum prevalence (PfPR) was developed using data from cross-sectional surveys conducted in Somalia in 2005, 2007-2011 and 2014. The fitted model was then used to generate maps of non-exceedance probabilities, i.e. the predictive probability that the region-wide population-weighted average PfPR for children between 2 and 10 years (PfPR2-10) lies below 1 and 5%. A comparison was carried out with the decision-making outcomes from those of standard approaches that ignore uncertainty in prevalence estimates. RESULTS: By 2010, most regions in Somalia were at least 70% likely to be below 5% PfPR2-10 and, by 2014, 17 regions were below 5% PfPR2-10 with a probability greater than 90%. Larger uncertainty is observed using a threshold of 1%. By 2011, only two regions were more than 90% likely of being < 1% PfPR2-10 and, by 2014, only three regions showed such low level of uncertainty. The use of non-exceedance probabilities indicated that there was weak evidence to classify 10 out of the 18 regions as < 1% in 2014, when a greater than 90% non-exceedance probability was required. CONCLUSION: Unlike standard approaches, non-exceedance probabilities of spatially modelled PfPR2-10 allow to quantify uncertainty of prevalence estimates in relation to policy relevant intervention thresholds, providing programmatically relevant metrics to make decisions on transitioning from sustained malaria control to strategies that encompass methods of malaria elimination.

Effectiveness of school-based intervention programs in reducing prevalence of overweight.

OBJECTIVES: To assess the effectiveness of school-based interventions program in reducing the prevalence of overweight or obesity among schoolchildren. DATA SOURCE: Ovid Medline (1950-December 2012), Embase (1980-2012), CINAHL (1982-2012), secondary references, review articles, and expert in the field. STUDY SELECTION: All published clinical trials were eligible for study if were randomized, methodologically strong-based on a validity assessment, aimed to evaluate a school-based intervention for childhood overweight or obesity, and measured outcome in term of prevalence/incidence difference in overweight and obesity among both groups. Studies involved in cost-effective analysis of school-based intervention have been excluded. Data from eligible studies abstracted and pooled for relative risk. RESULTS: Five trials with 3,904 schoolchildren were included. Mean age of the students (boys and girls) ranges 8.6-12.6 years. Meta-analysis showed a statistical significance beneficial effect of school-based intervention programs on obesity status of schoolchildren (risk ratio (RR) 0.58, 95% confidence interval (CI) 0.43-0.78) and suggested 42% reduction in prevalence of obesity among schoolchildren through school-based intervention programs. Individual studies also showed effectiveness of these school-based interventions. CONCLUSION: School-based intervention programs are effective in prevention of childhood overweight and obesity problem and our results quantitatively supported this argument.