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Malaria imposes a significant global health burden and remains a major cause of child mortality in sub-Saharan Africa. In many countries, malaria transmission varies seasonally. The use of seasonally-deployed interventions is expanding, and the effectiveness of these control measures hinges on quantitative and geographically-specific characterisations of malaria seasonality.
Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control.
To effectively inform infectious disease control strategies, accurate knowledge of the pathogen's transmission dynamics is required. Since the timings of infections are rarely known, estimates of the infection incidence, which is crucial for understanding the transmission dynamics, often rely on measurements of other quantities amenable to surveillance.
Consistent with the principles of differential privacy protection, the Australian Bureau of Statistics artificially perturbs all count data from the Australian Census prior to its release to researchers through the TableBuilder platform. This perturbation involves the addition of random noise to every non-zero cell count followed by the suppression of small values to zero.
Current malaria elimination targets must withstand a colossal challenge-resistance to the current gold standard antimalarial drug, namely artemisinin derivatives. If artemisinin resistance significantly expands to Africa or India, cases and malaria-related deaths are set to increase substantially.
With 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.
Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017-2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data.
Nipah virus is a zoonotic paramyxovirus responsible for disease outbreaks with high fatality rates in south and southeast Asia. However, knowledge of the potential geographical extent and risk patterns of the virus is poor. We aimed to establish an integrated spatiotemporal and phylogenetic database of Nipah virus infections in humans and animals across south and southeast Asia.
Urbanization combined with climate change are exacerbating water scarcity for an increasing number of the world’s emerging cities. Water and sanitation infrastructure, which in the first place was largely built to cater only to a small subsector of developing city populations, is increasingly coming under excessive strain.
Viral 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.