Global Malaria Epidemiology

Members:

Core Research

The Global Malaria Epidemiology team, led by Director of Global Malaria Epidemiology Dr Daniel Weiss, is responsible for generating malaria burden estimates for the Global Burden of Disease project and the World Malaria Report, produced in collaboration with the Institute for Health Metrics and Evaluation of the University of Washington and the World Health Organization, respectively. This team uses epidemiological data and geostatistical modelling approaches to produce global maps of malaria parasite rate, clinical incidence, and mortality at 5km spatial resolution for years 1980 to the present. Key publications relating to this work include Hay et al. (2007), Gething et al. 2010, and Bhatt et al. 2015.

Ancillary Research

Additional research agendas that intersect with the production of global burden estimates include modelling aspects key malaria interventions, modelling treatment seeking behaviour, modelling malaria seasonality, and creating geospatial covariates that support many modelling efforts both within and outside of MAP.

Examples of improved covariates include the newly created global map of travel time to cities, temperature suitability for Plasmodium falciparum in Africa, and correcting remotely-sensed imagery to create gap-free data.

Projects

Indirect effects of the COVID-19 pandemic on malaria intervention coverage

Current Project

Project Date: November 12, 2020

Substantial progress has been made in reducing the burden of malaria in Africa since 2000, but those gains could be jeopardised if the COVID-19 pandemic affects the availability of key malaria control interventions. The aim of this study was to evaluate plausible effects on malaria incidence and mortality under different levels of disruption to malaria control.

Current Project

Project Date: July 31, 2020

Access to healthcare is a measure of human well-being that is constrained by numerous geographically-varying factors, the most immediate of which is the time it takes individuals to travel to a properly equipped and adequately staffed healthcare facility. Under the leadership of Dr Daniel Weiss, Director of Global Malaria Epidemiology at MAP, we characterize travel time to healthcare facilities in unprecedented detail. We produce global travel time maps with and without access to motorized transport, thus characterizing travel time to healthcare for populations distributed across the wealth spectrum.

Current Project

Project Date: February 28, 2018

The Global Malaria Epidemiology team generates detailed models of interventions to improve burden estimation models and attribute declines in malaria to specific measures.

Current Project

Project Date: February 28, 2018

In low burden areas of the world, surveillance data is often a more informative measurement of malaria burden than parasite rate surveys, but these data are challenging to use in pixel-level modelling. We are developing disaggregation models that use these data alongside pixel-level environmental and human covariates in order to produce high-resolution burden estimates.

Current Project

Project Date: January 10, 2018

The ease with which people are able to connect with the services, institutions, and individuals supportive of socioeconomic success, good health, and overall wellbeing can ultimately separate communities that thrive from those left behind. Regardless of recent advances in electronic and online communications, inequalities persist in physical access to resources and opportunities that are primarily concentrated in urban centres. Understanding where the largest gaps in accessibility remain is of critical importance to a broad range of policymakers, investors, and development partners. Under the leadership Dr Daniel Weiss, Director of Global Malaria Epidemiology at MAP, we offer a first, crucial step toward tracking exactly where gaps in accessibility remain in 2015 and where the world can collectively address the most fundamental inequalities still experienced today. Read More

Predicting the effect of seasonality on malaria transmission

Current Project

Project Date: December 5, 2017

Most malaria endemic countries experience seasonal variation in transmission. The aim of this work is to be able to accurately predict seasonal malaria transmission patterns where malaria survey data are sparse.

Past Project

Project Date: August 1, 2017

A 2015 study by MAP, published in Nature, has quantified the attributable effect of malaria disease control efforts in Africa showing that Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015. Read More

TEAM