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Rift Valley fever virus (RVFV) is responsible for a substantive disease burden in pastoralist communities and the agricultural sector in the African continent and Arabian Peninsula. Enzootic, epizootic and zoonotic RVFV transmission dynamics remain ill‐defined, particularly due to a poor understanding of the role of mammalian hosts in the epidemiology and infection ecology of this arbovirus. Using a piecewise structural equation model, this study sought to identify associations between biological and ecological characteristics of mammalian species and documented RVFV infection to highlight species‐level traits that may influence wildlife host status. Interspecific network centrality, size of species home range and reproductive life‐history traits were all associated with being an RVFV host. The identification of these species‐level characteristics may help to provide ecological context for the role of wildlife amplification hosts in the epidemiology of spillover to livestock and humans and may also help to identify specific points of vulnerability at the wildlife–livestock interface. [ABSTRACT FROM AUTHOR]

Highly pathogenic avian influenza subtype H5N1 (H5N1) has contributed to substantial economic loss for backyard and large-scale poultry farmers each year since 1997. While the distribution of domestic H5N1 outbreaks across Africa, Europe and Asia is extensive, those features of the landscape conferring greatest risk remain uncertain. Furthermore, the extent to which influential landscape features may vary by season has been inadequately described. The current investigation used World Organization for Animal Health surveillance data to (i) delineate areas at greatest risk of H5N1 epizootics among domestic poultry, (ii) identify those abiotic and biotic features of the landscape associated with outbreak risk and (iii) examine patterns of epizootic clustering by season. Inhomogeneous point process models were used to predict the intensity of H5N1 outbreaks and describe the spatial dependencies between them. During October through March, decreasing precipitation, increasing isothermality and the presence of H5N1 in wild birds were significantly associated with the increased risk of domestic H5N1 epizootics. Conversely, increasing precipitation and decreasing isothermality were associated with the increased risk during April through September. Increasing temperature during the coldest quarter, domestic poultry density and proximity to surface water were associated with the increased risk of domestic outbreaks throughout the year. Spatial dependencies between outbreaks appeared to vary seasonally, with substantial clustering at small and large scales identified during October through March even after accounting for inhomogeneity due to landscape factors. In contrast, during April to September, H5N1 outbreaks exhibited no clustering at small scale once accounting for landscape factors. This investigation has identified seasonal differences in risk and clustering patterns of H5N1 outbreaks in domestic poultry and may suggest strategies in high-risk areas with features amenable to intervention such as controlling domestic bird movement in areas of high poultry density or preventing contact between poultry and wild birds and/or surface water features. [ABSTRACT FROM AUTHOR]

Dietary zinc (Zn) deficiency is widespread globally, and in particular among people in sub-Saharan Africa (SSA). In Malawi, dietary sources of Zn are dominated by maize and spatially dependent variation in grain Zn concentration, which will affect dietary Zn intake, has been reported at distances of up to ~ 100 km. The aim of this study was to identify potential soil properties and environmental covariates which might explain this longer-range spatial variation in maize grain Zn concentration. Data for maize grain Zn concentrations, soil properties, and environmental covariates were obtained from a spatially representative survey in Malawi (n = 1600 locations). Labile and non-labile soil Zn forms were determined using isotopic dilution methods, alongside conventional agronomic soil analyses. Soil properties and environmental covariates as potential predictors of the concentration of Zn in maize grain were tested using a priori expert rankings and false discovery rate (FDR) controls within the linear mixed model (LMM) framework that informed the original survey design. Mean and median grain Zn concentrations were 21.8 and 21.5 mg kg−1, respectively (standard deviation 4.5; range 10.0–48.1). A LMM for grain Zn concentration was constructed for which the independent variables: soil pH(water), isotopically exchangeable Zn (ZnE), and diethylenetriaminepentaacetic acid (DTPA) extractable Zn (ZnDTPA) had predictive value (p < 0.01 in all cases, with FDR controlled at < 0.05). Downscaled mean annual temperature also explained a proportion of the spatial variation in grain Zn concentration. Evidence for spatially dependent variation in maize grain Zn concentrations in Malawi is robust within the LMM framework used in this study, at distances of up to ~ 100 km. Spatial predictions from this LMM provide a basis for further investigation of variations in the contribution of staple foods to Zn nutrition, and where interventions to increase dietary Zn intake (e.g. biofortification) might be most effective. Other soil and landscape factors influencing spatially dependent variation in maize grain Zn concentration, along with factors operating over shorter distances such as choice of crop variety and agronomic practices, require further exploration beyond the scope of the design of this survey. [ABSTRACT FROM AUTHOR]