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Updating estimates of Plasmodium knowlesi malaria risk in response to changing land use patterns across Southeast AsiaPlasmodium knowlesi is a zoonotic parasite that causes malaria in humans. The pathogen has a natural host reservoir in certain macaque species and is transmitted to humans via mosquitoes of the Anopheles Leucosphyrus Group. The risk of human P. knowlesi infection varies across Southeast Asia and is dependent upon environmental factors.
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Mapping the incidence rate of typhoid fever in sub-Saharan AfricaWith more than 1.2 million illnesses and 29,000 deaths in sub-Saharan Africa in 2017, typhoid fever continues to be a major public health problem. Effective control of the disease would benefit from an understanding of the subnational geospatial distribution of the disease incidence.
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Global distribution of human hookworm species and differences in their morbidity effects: a systematic reviewThe global distribution and morbidity effects for each specific hookworm species is unknown, which prevents implementation of the optimum intervention for local hookworm control.
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Improving Influenza Vaccination in Children With Comorbidities: A Systematic ReviewChildren with medical comorbidities are at greater risk for severe influenza and poorer clinical outcomes. Despite recommendations and funding, influenza vaccine coverage remains inadequate in these children. We aimed to systematically review literature assessing interventions targeting influenza vaccine coverage in children with comorbidities and assess the impact on influenza vaccine coverage.
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Mapping malaria by sharing spatial information between incidence and prevalence data setsAs 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.
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A simulation study of disaggregation regression for spatial disease mappingDisaggregation regression has become an important tool in spatial disease mapping for making fine-scale predictions of disease risk from aggregated response data.
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Global maps of travel time to healthcare facilitiesAccess to healthcare is a requirement for human well-being that is constrained, in part, by the allocation of healthcare resources relative to the geographically dispersed human population. Quantifying access to care globally is challenging due to the absence of a comprehensive database of healthcare facilities. We harness major data collection efforts underway by OpenStreetMap, Google Maps and academic researchers to compile the most complete collection of facility locations to date.
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Multidrug-resistant tuberculosis during pregnancy and adverse birth outcomes: a systematic review and meta-analysisMultidrug-resistant tuberculosis (MDR-TB) is a major global public health concern. However, there is a dearth of literature on whether MDR-TB and its medications impact maternal and perinatal outcomes, and when such evidence exists the findings are conflicting. This systematic review and meta-analysis aimed to examine the impact of MDR-TB and its medications during pregnancy on maternal and perinatal outcomes.
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Risk factors for COVID-19 infection, disease severity and related deaths in Africa: A systematic reviewThe aim of this study was to provide a comprehensive evidence on risk factors for transmission, disease severity and COVID-19 related deaths in Africa. A systematic review has been conducted to synthesise existing evidence on risk factors affecting COVID-19 outcomes across Africa.
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Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for ImprovementMonitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.