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Spatial codistribution of HIV, tuberculosis and malaria in EthiopiaHIV, tuberculosis (TB) and malaria are the three most important infectious diseases in Ethiopia, and sub-Saharan Africa. Understanding the spatial codistribution of these diseases is critical for designing geographically targeted and integrated disease control programmes. This study investigated the spatial overlap and drivers of HIV, TB and malaria prevalence in Ethiopia.
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Data utilisation and factors influencing the performance of the health management information system in TanzaniaHealth Management Information System (HMIS) is a set of data regularly collected at health care facilities to meet the needs of statistics on health services. This study aimed to determine the utilisation of HMIS data and factors influencing the health system's performance at the district and primary health care facility levels in Tanzania.
Our Child Health Analytics Team uses cutting-edge technologies to better understand how and why the health and wellbeing of children varies from place to place. We develop innovative geospatial methods that can harness large, complex datasets to pinpoint hotspots of elevated risk, evaluate change through time, and explore underlying drivers.
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Modelling the COVID pandemic with the Geographical COVID-19 Model (GEO-COV)Researchers have developed a new model for simulating covid-19 outbreaks in Western Australia.
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Geospatial joint modeling of vector and parasite serology to microstratify malaria transmissionThe World Health Organization identifies a strong surveillance system for malaria and its mosquito vector as an essential pillar of the malaria elimination agenda. Anopheles salivary antibodies are emerging biomarkers of exposure to mosquito bites that potentially overcome sensitivity and logistical constraints of traditional entomological surveys.
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A fractional land use change model for ecological applicationsBy mapping land use under projections of socio-economic change, ecological changes can be predicted to inform conservation decision-making. We present a land use model that enables the fine-scale mapping of land use change under future scenarios. Its predictions can be used as input to virtually all existing spatially-explicit ecological models.
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Inequalities in excess premature mortality in England during the COVID-19 pandemic: A cross-sectional analysis of cumulative excess mortality by area deprivation and ethnicityTo examine magnitude of the impact of the COVID-19 pandemic on inequalities in premature mortality in England by deprivation and ethnicity.
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Risk factors associated with unsuccessful tuberculosis treatment outcomes in Hunan Province, ChinaGlobally, China has the third highest number of tuberculosis (TB) cases despite high rates (85.6%) of effective treatment coverage. Identifying risk factors associated with unsuccessful treatment outcomes is an important component of maximising the efficacy of TB control programmes.
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A novel statistical framework for exploring the population dynamics and seasonality of mosquito populationsUnderstanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species).