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In recent decades, field and semi-field studies of malaria transmission have gathered geographic-specific information about mosquito ecology, behaviour and their sensitivity to interventions. Mathematical models of malaria transmission can incorporate such data to infer the likely impact of vector control interventions and hence guide malaria control strategies in various geographies.
Knowing when and where infected mosquitoes bite is required for estimating accurate measures of malaria risk, assessing outdoor exposure, and designing intervention strategies. This study combines secondary analyses of a human behaviour survey and an entomological survey carried out in the same area to estimate human exposure to malaria-infected Anopheles mosquitoes throughout the night in rural villages in south-eastern Tanzania.
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.
The rising burden of mosquito-borne diseases in Europe extends beyond urban areas, encompassing rural and semi-urban regions near managed and natural wetlands evidenced by recent outbreaks of Usutu and West Nile viruses. While wetland management policies focus on biodiversity and ecosystem services, few studies explore the impact on mosquito vectors.
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.
Children recovering from severe malarial anaemia (SMA) remain at high risk of readmission and death after discharge from hospital. However, a recent trial found that post-discharge malaria chemoprevention (PDMC) with dihydroartemisinin-piperaquine reduces this risk. We developed a mathematical model describing the daily incidence of uncomplicated and severe malaria requiring readmission among 0-5-year old children after hospitalised SMA.
The study aimed to explore sociocultural factors influencing the risk of malaria and practices and beliefs towards malaria prevention, transmission and treatment in a remote village in Khatyad Rural Municipality (KRM) of Nepal. A sequential exploratory mixed methods approach was used.
As both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.
The spatial and temporal variability inherent in malaria transmission within countries implies that targeted interventions for malaria control in high-burden settings and subnational elimination are a practical necessity. Identifying the spatio-temporal incidence, risk, and trends at different administrative geographies within malaria-endemic countries and monitoring them in near real-time as change occurs is crucial for developing and introducing cost-effective, subnational control and elimination intervention strategies.
Malaria in Lao People's Democratic Republic (Lao PDR) has declined rapidly over the last two decades, from 279,903 to 3926 (99%) cases between 2001 and 2021. Elimination of human malaria is an achievable goal and limited resources need to be targeted at remaining hotspots of transmission.