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Malaria Atlas Project (MAP)

The Malaria Atlas Project (MAP) aims to disseminate free, accurate and up-to-date geographical information on malaria and associated topics. Our mission is to generate new and innovative methods to map malaria, to produce a comprehensive range of maps and estimates that will support effective planning of malaria

Child Health Analytics

Our Child Health Analytics Team uses cutting-edge technologies to better understand how and why the health and wellbeing of children varies from place to place. We develop innovative geospatial methods that can harness large, complex datasets to pinpoint hotspots of elevated risk, evaluate change through time, and explore underlying drivers.

New study identifies African ‘hotspot’ for highly infectious diseases

A regional corner of Africa is a hotspot for cases of HIV, tuberculosis and malaria, prompting researchers to call for targeted health support rather than a national response.

Fine-scale maps of malaria incidence to inform risk stratification in Laos

Malaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017-2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data. 

Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for Improvement

Monitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.

WALLABY Pre-pilot Survey: The Effects of Tidal Interaction on Radial Distribution of Color in Galaxies of the Eridanus Supergroup

We study the tidal interaction of galaxies in the Eridanus supergroup, using H i data from the pre-pilot survey of the Widefield ASKAP L-band Legacy All-sky Blind surveY.

Viral haemorrhagic fevers and malaria co-infections among febrile patients seeking health care in Tanzania

In recent years there have been reports of viral haemorrhagic fever (VHF) epidemics in sub-Saharan Africa where malaria is endemic. VHF and malaria have overlapping clinical presentations making differential diagnosis a challenge.

A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations

Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species).

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.

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.