Quantifying the human toll of malaria cases and deaths each year is critical for understanding progress towards a malaria-free world. Mapping the landscape of malaria risk allows resources to be better targeted. Tracking malaria control efforts, and their impact, allow strategies to be reviewed and refined. But measuring malaria is not easy. Data can be sparse, incomplete, or unrepresentative, and have the potential to mislead as well as to inform. At MAP, we aim to combine the world’s malaria data with cutting-edge analytics so that we can generate the best possible information to help guide the fight against the disease.
We house the world’s largest malaria ...
We house the world’s largest malaria database, assembling millions of data elements each year from field surveys, scientific studies, and routine surveillance systems, augmented by relevant environmental and demographic data from many sources.
MAP is a network of researchers from across the world ...
MAP is a network of researchers from across the world and from diverse disciplinary backgrounds. We are epidemiologists, public health specialists, geographers, statisticians, and modelling experts. MAP members have also bring expertise in working within National Malaria Control Programs and endemic country research institutions.
We develop innovative analytical ...
We develop innovative analytical approaches to making sense of complex malaria data. We are leaders in geospatial analysis, spatial and spatiotemporal statistical methods, machine learning, and computational disease models.
Everything MAP does is geared around ...
Everything MAP does is geared around achieving impact. This only happens by engagement with those making the decisions that matter, including malaria policy makers, funders, and control program personnel.
We generate high-resolution maps of the malaria risk landscape at both ...
We generate high-resolution maps of the malaria risk landscape at both global and national levels – estimating infection prevalence, incidence rates, and mortality by pixel.
We estimate annual malaria cases and deaths in endemic countries – ...
We estimate annual malaria cases and deaths in endemic countries – measuring the burden of the disease and the direction of trends towards international targets.
We use statistical models to infer the impact that current control measures ...
We use statistical models to infer the impact that current control measures are having on malaria transmission and burden – this can inform refinement of control strategies
We provide tools for calculating malaria commodity needs, enabling countries ...
We provide tools for calculating malaria commodity needs, enabling countries to quantify the resources they need to protect their populations.
We track the coverage of malaria drugs, diagnostics, and vector control to ...
We track the coverage of malaria drugs, diagnostics, and vector control to understand which populations may be less well protected
We provide training, supervision, and mentorship to build skills in malaria ...
We provide training, supervision, and mentorship to build skills in malaria analytics
The Malaria Atlas Project works extensively in partnership with a wide range of academic, policy and malaria control stakeholders. Some of our most enduring and important partnerships include the following organisations:
The World Health Organization Global Malaria Programme (WHO-GMP), based at the Geneva WHO headquarters, is responsible for coordinating WHO’s global efforts to control and eliminate malaria.
This includes setting and disseminating global guidance and policies on malaria control and elimination; supporting countries in formulation of national malaria strategic plans, strengthening of their surveillance systems, and responding to biological and operational emergencies. As part of its core mandate, GMP keeps independent score of global progress in the fight against malaria. MAP is a WHO Collaborating Centre in Geospatial Disease Modelling and under this remit we provide broad ranging analyses to WHO, including in burden estimation, intervention coverage tracking and risk stratification.
The Clinton Health Access Initiative (CHAI) is a global health organization committed to strengthening integrated health systems in the developing world and expanding access to care and treatment for HIV/AIDS, malaria and tuberculosis.
CHAI is supporting a number of countries in Southern Africa, South-East Asia, Hispaniola and Mesoamerica to sustainably accelerate efforts to eliminate indigenous cases of malaria by providing direct technical and management support to governments on elimination planning, surveillance, and targeted attached and response activities. MAP works with CHAI to support countries in their effort to map risk, evaluate intervention impact and access to care, and forecast malaria commodity needs.
The Institute for Health Metric and Evaluation (IHME), based at the University of Washington in Seattle has the stated mission of delivering to the world timely, relevant, and scientifically valid evidence to improve health policy and practice.
Their flagship project is the Global Burden of Disease study: a comprehensive global effort analysing 286 causes of death, 369 diseases and injuries, and 87 risk factors in 204 countries and territories. MAP works with IHME to generate the malaria component of the GBD study each year, providing detailed estimates of malaria prevalence, incidence, and mortality. In parallel with the GBD study, we also collaborate closely with Professor Dave Smith and his team at IHME with a focus on mathematical modelling of malaria to support intervention planning.
The Institute for Disease Modelling (IDM) is part of the Bill & Melinda Gates Foundation’s Global Health Division. IDM’s goal is to support global efforts to eradicate infectious diseases and achieve permanent improvements in health by developing, using, and sharing computational modelling tools and promoting quantitative decision-making. MAP works closely with IDM on work at the interface between malaria geospatial and mathematical modelling.
The Australian Centre of Research Excellence in Malaria Elimination (ACREME) is a network of leading malaria researchers dedicated to realising the goal of eliminating malaria in the region by 2030. ACREME is developing better tools to monitor, detect, prevent, and treat malaria, in order to improve health and economic outcomes for our regional neighbours, with research conducted within the three major themes of surveillance, diagnostics, and treatment and prevention. MAP joined ACREME following our relocation to Australia in 2019 and is a proud member of this vibrant Australian malaria research community.
The Intervention and Infectious Disease Modelling (IIDM) led by Melissa Penny is part of Telethon Kid’s Intervention & Vaccines Program. The group works to understand how pathogen, host and intervention dynamics combine to prevent disease progression and transmission and to address contemporary issues in infectious diseases and global health. IIDM are an interdisciplinary team of researchers that develops and uses models to understand parasitic and viral diseases and inform public health decision-making.
The group are key developers of the open-source disease models OpenMalaria and OpenCOVID. OpenMalaria is widely used by international research teams as the premier population-scale model for malaria disease, to help guide medical and non-medical malaria treatments for maximum health impact. MAP works closely with the IIDM Group at the interface between malaria geospatial and mechanistic mathematical modelling.
The Vector Atlas is a University of Oxford, International Centre of Insect Physiology and Ecology (icipe) and Malaria Atlas Project initiative, funded by the Bill and Melinda Gates Foundation. Building on the extensive vector (occurrence, bionomics and insecticide resistance) datasets collated as part of the Malaria Atlas Project, the Vector Atlas is a new sister initiative focused entirely on updating the vector data for the dominant and secondary vector species that maintain malaria transmission in Africa. The datasets will now include information on local ecology (e.g. flora and livestock), human activity relevant to malaria transmission and the genetic mechanisms that underlie the phenotypic insecticide resistance reported within vector populations.
These data will be used to develop new vector species, IR and abundance maps to provide a solid, evidence-based suite of surfaces for use in vector control decision making. The analyses-ready data and updated maps will be available on our Vector Atlas platform. The Vector Atlas is also working closely with our national partners in Nigeria, Democratic Republic of Congo, Burkina Faso, Cote d’Ivoire, Uganda and Senegal. Bespoke spatial models developed in collaboration with in-country experts will be specifically tailored for each national malaria control programme to target the unique challenges in vector control currently faced in each of these high burden countries.