Spatial and temporal distribution of soil-transmitted helminth infection in sub-Saharan Africa: a systematic review and geostatistical meta-analysis.

BACKGROUND: Interest is growing in predictive risk mapping for neglected tropical diseases (NTDs), particularly to scale up preventive chemotherapy, surveillance, and elimination efforts. Soil-transmitted helminths (hookworm, Ascaris lumbricoides, and Trichuris trichiura) are the most widespread NTDs, but broad geographical analyses are scarce. We aimed to predict the spatial and temporal distribution of soil-transmitted helminth infections, including the number of infected people and treatment needs, across sub-Saharan Africa. METHODS: We systematically searched PubMed, Web of Knowledge, and African Journal Online from inception to Dec 31, 2013, without language restrictions, to identify georeferenced surveys. We extracted data from household surveys on sources of drinking water, sanitation, and women's level of education. Bayesian geostatistical models were used to align the data in space and estimate risk of with hookworm, A lumbricoides, and T trichiura over a grid of roughly 1 million pixels at a spatial resolution of 5 × 5 km. We calculated anthelmintic treatment needs on the basis of WHO guidelines (treatment of all school-aged children once per year where prevalence in this population is 20-50% or twice per year if prevalence is greater than 50%). FINDINGS: We identified 459 relevant survey reports that referenced 6040 unique locations. We estimate that the prevalence of hookworm, A lumbricoides, and T trichiura among school-aged children from 2000 onwards was 16·5%, 6·6%, and 4·4%. These estimates are between 52% and 74% lower than those in surveys done before 2000, and have become similar to values for the entire communities. We estimated that 126 million doses of anthelmintic treatments are required per year. INTERPRETATION: Patterns of soil-transmitted helminth infection in sub-Saharan Africa have changed and the prevalence of infection has declined substantially in this millennium, probably due to socioeconomic development and large-scale deworming programmes. The global control strategy should be reassessed, with emphasis given also to adults to progress towards local elimination. FUNDING: Swiss National Science Foundation and European Research Council.

Comparative Logic Modeling for policy analysis: the case of HIV testing policy change at the Department of Veterans Affairs.

OBJECTIVE: Logic models have been used to evaluate policy programs, plan projects, and allocate resources. Logic Modeling for policy analysis has been used rarely in health services research but can be helpful in evaluating the content and rationale of health policies. Comparative Logic Modeling is used here on human immunodeficiency virus (HIV) policy statements from the Department of Veterans Affairs (VA) and Centers for Disease Control and Prevention (CDC). We created visual representations of proposed HIV screening policy components in order to evaluate their structural logic and research-based justifications. DATA SOURCES AND STUDY DESIGN: We performed content analysis of VA and CDC HIV testing policy documents in a retrospective case study. DATA COLLECTION: Using comparative Logic Modeling, we examined the content and primary sources of policy statements by the VA and CDC. We then quantified evidence-based causal inferences within each statement. PRINCIPAL FINDINGS: VA HIV testing policy structure largely replicated that of the CDC guidelines. Despite similar design choices, chosen research citations did not overlap. The agencies used evidence to emphasize different components of the policies. CONCLUSION: Comparative Logic Modeling can be used by health services researchers and policy analysts more generally to evaluate structural differences in health policies and to analyze research-based rationales used by policy makers.

Similarities and differences between smoking-related gene expression in nasal and bronchial epithelium.

Previous studies have shown that physiological responses to cigarette smoke can be detected via bronchial airway epithelium gene expression profiling and that heterogeneity in this gene expression response to smoking is associated with lung cancer. In this study, we sought to determine the similarity of the effects of tobacco smoke throughout the respiratory tract by determining patterns of smoking-related gene expression in paired nasal and bronchial epithelial brushings collected from 14 healthy nonsmokers and 13 healthy current smokers. Using whole genome expression arrays, we identified 119 genes whose expression was affected by smoking similarly in both bronchial and nasal epithelium, including genes related to detoxification, oxidative stress, and wound healing. While the vast majority of smoking-related gene expression changes occur in both bronchial and nasal epithelium, we also identified 27 genes whose expression was affected by smoking more dramatically in bronchial epithelium than nasal epithelium. Both common and site-specific smoking-related gene expression profiles were validated using independent microarray datasets. Differential expression of select genes was also confirmed by RT-PCR. That smoking induces largely similar gene expression changes in both nasal and bronchial epithelium suggests that the consequences of cigarette smoke exposure can be measured in tissues throughout the respiratory tract. Our findings suggest that nasal epithelial gene expression may serve as a relatively noninvasive surrogate to measure physiological responses to cigarette smoke and/or other inhaled exposures in large-scale epidemiological studies.