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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.

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.

Public health impact of current and proposed age-expanded perennial malaria chemoprevention: a modelling study

In 2022, the World Health Organization extended their guidelines for perennial malaria chemoprevention (PMC) from infants to children up to 24 months old. However, evidence for PMC's public health impact is primarily limited to children under 15 months. Further research is needed to assess the public health impact and cost-effectiveness of PMC, and the added benefit of further age-expansion. We integrated an individual-based model of malaria with pharmacological models of drug action to address these questions for PMC and a proposed age-expanded schedule (referred as PMC+, for children 03-36 months).

Estimating the impact of imported malaria on local transmission in a near elimination setting: a case study from Bhutan

Bhutan has achieved a substantial reduction in both malaria morbidity and mortality over the last two decades and is aiming for malaria elimination certification in 2025. However, a significant percentage of malaria cases in Bhutan are imported (acquired in another country). The aim of the study was to understand how importation drives local malaria transmission in Bhutan.

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.

Malaria treatment for prevention: a modelling study of the impact of routine case management on malaria prevalence and burden

Testing and treating symptomatic malaria cases is crucial for case management, but it may also prevent future illness by reducing mean infection duration. Measuring the impact of effective treatment on burden and transmission via field studies or routine surveillance systems is difficult and potentially unethical. This project uses mathematical modeling to explore how increasing treatment of symptomatic cases impacts malaria prevalence and incidence. 

Artemisinin combination therapy at delivery to prevent postpartum malaria: A randomised open-label controlled trial

Although the incidence of malaria is increased in women in endemic areas after delivery compared to non-pregnant women, no studies have assessed the benefit of presumptive antimalarial treatment given postpartum.

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.

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.

The Centres for Disease Control light trap and the human decoy trap compared to the human landing catch for measuring Anopheles biting in rural Tanzania

Vector mosquito biting intensity is an important measure to understand malaria transmission. Human landing catch (HLC) is an effective but labour-intensive, expensive, and potentially hazardous entomological surveillance tool. The Centres for Disease Control light trap (CDC-LT) and the human decoy trap (HDT) are exposure-free alternatives.