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When models are used to inform decision-making, both their strengths and limitations must be considered. Using malaria as an example, we explain how and why models are limited and offer guidance for ensuring a model is well-suited for its intended purpose.
Providing protection from malaria vector bites, both indoors and outdoors, is crucial to curbing malaria parasite transmission. Screening of house entry points, especially with incorporated insecticides, confers significant protection but remains a costly and labour-intensive application. Use of spatial repellents has shown promise in creating areas of protection in peri-domestic areas.
Seasonal malaria chemoprevention (SMC) is recommended for disease control in settings with moderate to high Plasmodium falciparum transmission and currently depends on the administration of sulfadoxine-pyrimethamine plus amodiaquine.
The 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.
Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions.
The COVID-19 pandemic has led to far-reaching disruptions to health systems, including preventative and curative services for malaria. The aim of this study was to estimate the magnitude of disruptions in malaria case management in sub-Saharan Africa and their impact on malaria burden during the COVID-19 pandemic. We used survey data collected by the World Health Organization, in which individual country stakeholders reported on the extent of disruptions to malaria diagnosis and treatment.
Since 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.
Low socioeconomic status (SES), high temperature, and increasing rainfall patterns are associated with increased dengue case counts. However, the effect of climatic variables on individual dengue virus (DENV) serotypes and the extent to which serotype count affects the rate of severe dengue in Mexico have not been studied before.
To assess the pharmacokinetics, safety, and tolerability of two high-dose, short-course primaquine (PQ) regimens compared with standard care in children with Plasmodium vivax infections.
Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes.