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Data on Rift Valley fever virus (RVFV) prevalence in urban settings and pastoral areas of Tanzania are scarce. We performed a cross-sectional study of RVFV seroprevalence and determinants in humans and animals from Ilala, Rufiji, and Sengerema districts of Tanzania.
Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection.
The global distribution and morbidity effects for each specific hookworm species is unknown, which prevents implementation of the optimum intervention for local hookworm control.
Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic.
A potential response to the COVID-19 pandemic in sub-Saharan Africa (SSA) with long-term benefits is to provide electricity for medical equipment in rural health centers and communities. This study identifies a large gap in the electrification of healthcare facilities in SSA, and it shows that decentralized photovoltaic systems can offer a clean, reliable, quick, and cost-effective solution.
Disaggregation regression has become an important tool in spatial disease mapping for making fine-scale predictions of disease risk from aggregated response data.
This study uses H i image data from the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) pilot survey with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, covering the Hydra cluster out to 2.5r 200. We present the projected phase-space distribution of H i-detected galaxies in Hydra, and identify that nearly two-thirds of the galaxies within 1.25r200 may be in the early stages of ram pressure stripping.
Infectious diseases such as tuberculosis (TB), malaria and soil-transmitted helminthiasis continue to impose a significant global health burden and socio-economic impact. Globally, minority indigenous people are disproportionately affected by poverty and are shown to experience a disparate burden of disease and poorer health outcomes than the comparative majority population.
As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low-prevalence areas are increasingly needed. For low-burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons.
Insecticide-treated nets (ITNs) are one of the most widespread and impactful malaria interventions in Africa, yet a spatially-resolved time series of ITN coverage has never been published. Using data from multiple sources, we generate high-resolution maps of ITN access, use, and nets-per-capita annually from 2000 to 2020 across the 40 highest-burden African countries.