Malaria

Jonathan Jackson of Dimagi in the U.S., together with James Faghmous from the Arnhold Institute for Global Health, Icahn School of Medicine at Mount Sinai, will develop an open platform that combines real-time data on health, climate, and the environment at high resolution, and near real-time satellite data to inform on population density, in order to detect areas containing limited information (cold-spots) on malaria so that control programs can better allocate resources.

Emmanuel Roux of the French National Research Institute for Sustainable Development in France will develop a method to standardize malaria datasets from different countries so that they can be used to monitor the disease across borders, which is crucial for elimination. They will co-design domain ontologies with relevant experts to bridge heterogeneities and standardize metadata across existing national surveillance databases, and use generic tools to extract data on individual disease incidence in cross-border areas to build a cross-border database.

Matt Berg of Ona Systems Inc. in the U.S. will develop a map widget that enables data collected by different platforms on different aspects of malaria, such as disease incidence and intervention efforts, to be accurately mapped and therefore more effectively integrated to help eliminate malaria. It is currently difficult to map specific events particularly in rural areas of developing countries, which lack formal addresses. Different groups use different naming schemes when recording disease-relevant data, making them difficult to cross-reference.

Mark Westra and their team at the Akvo Foundation in the Netherlands will build a central data integration platform for malaria that assembles existing data from a variety of sources and enables it to be easily visualized, analyzed, and shared by all types of users. They will build an initial system and test it with a first set of users composed of key groups of stakeholders and users in multiple countries. This will help them gain a detailed understanding of what different users need from such a platform to ensure it becomes a valuable resource for the community.

Isabel Cruz of the University of Illinois at Chicago in the U.S. will build an ontology-based data integration framework that can predict where malaria incidence is likely to increase or decrease in Zimbabwe, to better target elimination efforts. Eliminating malaria requires being able to monitor the changing patterns of infection risk across an entire region, which is affected by multiple factors including the location of health centers, temperature, rainfall, type of landscape, and population distribution.

Nick Ruktanonchai of the University of Southampton in the United Kingdom will develop a web-based application to integrate currently disparate data on malaria disease risk, seasonal population dynamics, and past interventions, to identify prioritized areas for elimination efforts. Control programs are currently provided these data independently, making it difficult to know at a given time where elimination efforts would have the highest impact. They will develop the application together with a national malaria elimination program in one country in southern Africa.

Helder Nakaya of the University of Sao Paulo in Brazil will identify hotspots of malaria transmission using the GPS data from mobile phones of infected individuals in order to find asymptomatic cases and help elimination efforts. Malaria is a major public health concern in many countries including Brazil. Eliminating the disease is difficult due in part to the existence of asymptomatic individuals who can still spread the disease but are difficult to detect. Relying on a patient remembering where they have been to identify asymptomatic individuals has not been adequate.

Kirsten Hanson from the Instituto de Medicina Molecular in Portugal has developed a screening strategy to identify compounds that specifically block the final maturation stage of the malaria-causing Plasmodium parasite that occurs in human liver. These compounds could prevent the symptoms and establishment of malaria in humans (i.e. act as prophylactics), and block transmission back to the mosquitoes.

Gregory Goldgof, Elizabeth Winzeler and colleagues from the University of California, San Diego in the U.S. have developed a drug-sensitive yeast strain by deleting the main multi-drug export pumps to help identify the mechanisms of action of the 400 next-generation anti-malarial drug candidates in the Malaria Box. This will help optimize drug safety and efficacy for clinical trials. In Phase I, they successfully screened the Malaria Box compounds and identified 30 that were active in their assay.

Dyann Wirth of the Harvard School of Public Health in the U.S. is building a platform to identify combinations of anti-malarial compounds that inhibit the development of drug resistance, which is a major barrier to combatting the disease. Their approach involves predicting how the Plasmodium falciparum malaria parasite will evolve to become resistant to a specific anti-malarial compound, and then designing a second compound that will target these resistant parasites.