AnophelesModel: An R package to interface mosquito bionomics, human exposure and intervention effects with models of malaria intervention impact.

In recent decades, field and semi-field studies of malaria transmission have gathered geographic-specific information about mosquito ecology, behaviour and their sensitivity to interventions. Mathematical models of malaria transmission can incorporate such data to infer the likely impact of vector control interventions and hence guide malaria control strategies in various geographies. To facilitate this process and make model predictions of intervention impact available for different geographical regions, we developed AnophelesModel. AnophelesModel is an online, open-access R package that quantifies the impact of vector control interventions depending on mosquito species and location-specific characteristics. In addition, it includes a previously published, comprehensive, curated database of field entomological data from over 50 Anopheles species, field data on mosquito and human behaviour, and estimates of vector control effectiveness. Using the input data, the package parameterizes a discrete-time, state transition model of the mosquito oviposition cycle and infers species-specific impacts of various interventions on vectorial capacity. In addition, it offers formatted outputs ready to use in downstream analyses and by other models of malaria transmission for accurate representation of the vector-specific components. Using AnophelesModel, we show how the key implications for intervention impact change for various vectors and locations. The package facilitates quantitative comparisons of likely intervention impacts in different geographical settings varying in vector compositions, and can thus guide towards more robust and efficient malaria control recommendations. The AnophelesModel R package is available under a GPL-3.0 license at https://github.com/SwissTPH/AnophelesModel.

Putative Biomarkers of Environmental Enteric Disease Fail to Correlate in a Cross-Sectional Study in Two Study Sites in Sub-Saharan Africa.

Environmental enteric dysfunction (EED) is an elusive, inflammatory syndrome of the small intestine thought to be associated with enterocyte loss and gut leakiness and lead to stunted child growth. To date, the gold standard for diagnosis is small intestine biopsy followed by histology. Several putative biomarkers for EED have been proposed and are widely used in the field. Here, we assessed in a cross-sectional study of children aged 2-5 years for a large set of biomarkers including markers of protein exudation (duodenal and fecal alpha-1-antitrypsin (AAT)), inflammation (duodenal and fecal calprotectin, duodenal, fecal and blood immunoglobulins, blood cytokines, C-reactive protein (CRP)), gut permeability (endocab, lactulose-mannitol ratio), enterocyte mass (citrulline) and general nutritional status (branched-chain amino acids (BCAA), insulin-like growth factor) in a group of 804 children in two Sub-Saharan countries. We correlated these markers with each other and with anemia in stunted and non-stunted children. AAT and calprotectin, CRP and citrulline and citrulline and BCAA correlated with each other. Furthermore, BCAA, citrulline, ferritin, fecal calprotectin and CRP levels were correlated with hemoglobin levels. Our results show that while several of the biomarkers are associated with anemia, there is little correlation between the different biomarkers. Better biomarkers and a better definition of EED are thus urgently needed.

Cardiovascular mortality associated with 5 leading risk factors: national and state preventable fractions estimated from survey data.

BACKGROUND: Impressive decreases in cardiovascular mortality have been achieved through risk factor reduction and clinical intervention, yet cardiovascular disease remains a leading cause of death nationally. OBJECTIVE: To estimate up-to-date preventable fractions of cardiovascular mortality associated with elimination and reduction of 5 leading risk factors nationally and by state in the United States. DESIGN: Cross-sectional and cohort studies. SETTING: Nationally representative and state-representative samples of the U.S. population. PARTICIPANTS: Adults aged 45 to 79 years. MEASUREMENTS: Self-reported risk factor status in the BRFSS (Behavioral Risk Factor Surveillance System) 2009-2010 was corrected to approximate clinical definitions. The relative hazards of cardiovascular death (International Classification of Diseases, 10th Revision, codes I00 to I99) associated with risk factors were estimated using data from NHANES (National Health and Nutrition Examination Survey) (1988-1994 and 1999-2004, followed through 2006). RESULTS: The preventable fraction of cardiovascular mortality associated with complete elimination of elevated cholesterol levels, diabetes, hypertension, obesity, and smoking was 54.0% for men and 49.6% for women in 2009 to 2010. When the more feasible target of reducing risk factors to the best achieved levels in the states was considered, diabetes (1.7% and 4.1%), hypertension (3.8% and 7.3%), and smoking (5.1% and 4.4%) were independently associated with the largest preventable fractions among men and women, respectively. With both targets, southern states had the largest preventable fractions, and western states had the smallest. LIMITATION: Self-reported state data; mortality hazards relied on baseline risk factor status. CONCLUSION: Major modifiable cardiovascular risk factors collectively accounted for half of cardiovascular deaths in U.S. adults aged 45 to 79 years in 2009 to 2010. Fewer than 10% of cardiovascular deaths nationally could be prevented if all states were to achieve risk factor levels observed in the best-performing states. PRIMARY FUNDING SOURCE: Robert Wood Johnson Foundation.