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Community knowledge, attitude and practices regarding zoonotic viral haemorrhagic fevers in five geo-ecological zones in TanzaniaViral haemorrhagic fevers (VHF) cause significant economic and public health impact in Sub-Saharan Africa. Community knowledge, awareness and practices regarding such outbreaks play a pivotal role in their management and prevention. This study was carried out to assess community knowledge, attitude and practices regarding VHF in five geo-ecological zones in Tanzania.
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Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humansBuruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months.
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Geospatial modelling for malaria risk stratification and intervention targeting for low-endemic countriesEwan Punam Susan Tasmin Cameron Amratia Rumisha Symons BSc PhD PhD PhD (Biostatistics) Director of Malaria Risk Stratification Honorary Research
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A Maximum Entropy Model of the Distribution of Dengue Serotype in MexicoPathogen strain diversity is an important driver of the trajectory of epidemics. The role of bioclimatic factors on the spatial distribution of dengue virus serotypes has, however, not been previously studied. Hence, we developed municipality-scale environmental suitability maps for the four dengue virus serotypes using maximum entropy modeling.
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Patterns and trends of in-hospital mortality due to non-communicable diseases and injuries in Tanzania, 2006–2015Globally, non-communicable diseases (NCD) kill about 40 million people annually, with about three-quarters of the deaths occurring in low- and middle-income countries. This study was carried out to determine the patterns, trends, and causes of in-hospital non-communicable disease (NCD) and injury deaths in Tanzania from 2006-2015.
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Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventionsSince 2004, malaria transmission on Bioko Island has declined significantly as a result of the scaling-up of control interventions. The aim of eliminating malaria from the Island remains elusive, however, underscoring the need to adapt control to the local context. Understanding the factors driving the risk of malaria infection is critical to inform optimal suits of interventions in this adaptive approach.
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Spatial distribution of rotavirus immunization coverage in Ethiopia: a geospatial analysis using the Bayesian approachRotavirus causes substantial morbidity and mortality every year, particularly among under-five children. Despite Rotavirus immunization preventing severe diarrheal disease in children, the vaccination coverage remains inadequate in many African countries including Ethiopia.
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The Centres for Disease Control light trap and the human decoy trap compared to the human landing catch for measuring Anopheles biting in rural TanzaniaVector mosquito biting intensity is an important measure to understand malaria transmission. Human landing catch (HLC) is an effective but labour-intensive, expensive, and potentially hazardous entomological surveillance tool. The Centres for Disease Control light trap (CDC-LT) and the human decoy trap (HDT) are exposure-free alternatives.
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Viral haemorrhagic fevers and malaria co-infections among febrile patients seeking health care in TanzaniaIn recent years there have been reports of viral haemorrhagic fever (VHF) epidemics in sub-Saharan Africa where malaria is endemic. VHF and malaria have overlapping clinical presentations making differential diagnosis a challenge.
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Modelling temperature-driven changes in species associations across freshwater communitiesDue to global climate change–induced shifts in species distributions, estimating changes in community composition through the use of Species Distribution Models has become a key management tool. Being able to determine how species associations change along environmental gradients is likely to be pivotal in exploring the magnitude of future changes in species’ distributions.