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Julian HengJulian is the Program Manager for the Global Disease Modelling team at The Kids Research Institute Australia.
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Epke Annelie Le RutteEpke is a veterinarian that specializes in infectious disease control, and holds a PhD in human neglected tropical disease (NTD) control and elimination.
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.
Research
Intervention effect of targeted workplace closures may be approximated by single-layered networks in an individual-based model of COVID-19 controlIndividual-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.
Research
Severe outcomes of malaria in children under time-varying exposureIn 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.
Research
Effect of maternal prebiotic supplementation on human milk immunological composition: Insights from the SYMBA studyImmunomodulatory proteins in human milk (HM) can shape infant immune development. However, strategies to modulate their levels are currently unknown. This study investigated whether maternal prebiotic supplementation alters the levels of immunomodulatory proteins in HM.
Research
Barriers to uptake and implementation of malaria chemoprevention in school-aged children: a stakeholder engagement meeting reportMalaria 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.
Research
Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum and Plasmodium vivax malaria, 2000-22: a spatial and temporal modelling studyMalaria 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.
Research
Public health impact of current and proposed age-expanded perennial malaria chemoprevention: a modelling studyIn 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).
Research
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.