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How can modeling responsibly inform decision-making in malaria?

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.

Automated reporting of primaquine dose efficacy, tolerability and safety for Plasmodium vivax malaria using a systematic review and individual patient data meta-analysis

The antirelapse efficacy of primaquine is related to the total dose administered, whereas the risks of haemolysis and gastrointestinal intolerance are associated with the daily dose administered. National Malaria Control Programmes require local information on efficacy, tolerability and safety to optimize antimalarial treatment policies for Plasmodium vivax malaria control and elimination efforts.

Subnational tailoring of malaria interventions to prioritize the malaria response in Guinea

In the context of high malaria burden yet limited resources, Guinea's national malaria programme adopted an innovative subnational tailoring approach, including engagement of stakeholders, data review, and data analytics, to update their malaria operational plan for 2024-2026 and identify the most appropriate interventions for each district considering the resources available.

Evaluating COVID-19-Related Disruptions to Effective Malaria Case Management in 2020–2021 and Its Potential Effects on Malaria Burden in Sub-Saharan Africa

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.

Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions

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.

Geospatial joint modeling of vector and parasite serology to microstratify malaria transmission

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.

Short-course, high-dose primaquine regimens for the treatment of liver-stage vivax malaria in children

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.

Mapping tuberculosis prevalence in Ethiopia using geospatial meta-analysis\

Reliable and detailed data on the prevalence of tuberculosis (TB) with sub-national estimates are scarce in Ethiopia. We address this knowledge gap by spatially predicting the national, sub-national and local prevalence of TB, and identifying drivers of TB prevalence across the country.

Community knowledge, attitude, practices and beliefs associated with persistence of malaria transmission in North-western and Southern regions of Tanzania

Despite significant decline in the past two decades, malaria is still a major public health concern in Tanzania; with over 93% of the population still at risk. Community knowledge, attitudes and practices, and beliefs are key in enhancing uptake and utilization of malaria control interventions, but there is a lack of information on their contribution to effective control of the disease.

Comparison of new computational methods for spatial modelling of malaria

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.