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In malaria epidemiology, interpolation frameworks based on available observations are critical for policy decisions and interpreting disease burden. Updating our understanding of the empirical evidence across different populations, settings, and timeframes is crucial to improving inference for supporting public health.
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.
In 2023 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared endemic, yet hospital admissions have persisted and risen within populations at high and moderate risk of developing severe disease, which include those of older age, and those with co-morbidities. Antiviral treatments, currently only available for high-risk individuals, play an important role in preventing severe disease and hospitalisation within this subpopulation.
Seasonal malaria chemoprevention (SMC) with sulfadoxine-pyrimethamine plus amodiaquine prevents millions of clinical malaria cases in children younger than 5 years in Africa's Sahel region. However, Plasmodium falciparum parasites partially resistant to sulfadoxine-pyrimethamine (with quintuple mutations) potentially threaten the protective effectiveness of SMC. We evaluated the spread of quintuple-mutant parasites and the clinical consequences.
Individual-based models of infectious disease dynamics commonly use network structures to represent human interactions. Network structures can vary in complexity, from single-layered with homogeneous mixing to multi-layered with clustering and layer-specific contact weights. Here we assessed policy-relevant consequences of network choice by simulating different network structures within an established individual-based model of SARS-CoV-2 dynamics.
The Global Disease Modelling group informs development and implementation of drugs, medical treatments and non-medical interventions to effectively tackle disease. They build mathematical models of diseases, designed to take into account the complex constellation of interactions between pathogens, humans, diseases, the environment and entire healthcare systems.
Julian is the Program Manager for the Global Disease Modelling team at The Kids Research Institute Australia.
Epke is a veterinarian that specializes in infectious disease control, and holds a PhD in human neglected tropical disease (NTD) control and elimination.
Malaria is a leading cause of death in school-aged children in sub-Saharan Africa, and non-fatal chronic malaria infections are associated with anaemia, school absence and decreased learning, preventing children from reaching their full potential. Malaria chemoprevention has led to substantial reductions in malaria in younger children in sub-Saharan Africa.
Malaria remains a leading cause of illness and death globally, with countries in sub-Saharan Africa bearing a disproportionate burden. Global high-resolution maps of malaria prevalence, incidence, and mortality are crucial for tracking spatially heterogeneous progress against the disease and to inform strategic malaria control efforts. We present the latest such maps, the first since 2019, which cover the years 2000–22. The maps are accompanied by administrative-level summaries and include estimated COVID-19 pandemic-related impacts on malaria burden.