Design New Solutions to Data Integration for Malaria Elimination (Round 18)

The Opportunity

The Bill & Melinda Gates Foundation sees surveillance as the backbone of effective malaria elimination efforts, but we believe that malaria surveillance needs a fundamental “rethink” to achieve the goal of a malaria-free world within a generation.

For malaria elimination, surveillance is defined as the information flow that people use to make decisions about how to find malaria parasites, how to eliminate them from human populations, and how to prevent parasites from coming back. Advances in digital and mobile technologies and the increased reach of mobile phone networks put the goal of timely, affordable, geo-located reporting within reach. There is a real opportunity to transform malaria surveillance in a way that can accelerate national and regional elimination efforts.

Malaria transmission events take place in a dynamic, interconnected, and complex system. But malaria elimination efforts can thrive if they have access to novel solutions that enable rapid data exchange via new, user-friendly platforms. The purpose of this call is to engage a broad spectrum of innovators to identify how new tools and strategies, including those that have been developed for other sectors, can be applied to the fight against malaria.

The Challenge

Despite the acknowledgement of the role of surveillance in malaria elimination, the full potential of available information communication technology (ICT), data systems, harmonization, analytics and visualization has not yet been effectively applied to the challenge of malaria elimination.

A wide range of different types of data are required to support effective elimination programs. These data are collected through a variety of mechanisms and are typically stored across different departments, organizations or levels of the health system. Malaria elimination programs need access to granular, timely information but the need to bring together data from multiple locations and in multiple formats results in long and inefficient processes to harmonize and compile information. Some analyses require data from multiple stakeholders where sharing between inter- and intra-national organizations, ministry departments, and across public and private sectors, is complex and sometimes prohibited. Because, in part, surveillance and analytical efforts have tended to be driven by civil society and developed by academic partners, there is no formal market or market leader for specialized malaria surveillance integration tools, nor have any existing systems reached global scale. The fact that solutions require national-level buy-in to be funded and implemented at scale further hampers innovation.

What we are looking for:

We are looking for proposals of innovative solutions for improving data availability and use in decision-making for malaria elimination that focus on innovation in interoperability: solutions that will reduce the time for data harmonization by automation or skill set simplification. This can include the use of machine learning or heuristics, and setting standards. Proposals should increase the availability of interoperable tools and/or facilitate the adoption of interoperable systems in country. Proposals which explore ICT as a means of incorporating novel data sources are also encouraged; however, we do not want respondents to develop new data collection tools.

Because many countries are currently undergoing the process of reorienting their programs and surveillance systems to a malaria elimination context, we do not yet have examples of places where data integration solutions exist at scale. The community is working on data collection standards and tools, and we expect these changes to happen in elimination settings over the next several years. We do not want applicants to develop new data collection tools. Instead, we are looking for solutions that integrate key data required to support malaria elimination including, for example:

Malaria case data, geolocated to the household level and including key information on travel history, treatment history, demographics and diagnosis
Population denominators (for example, from WorldPop)
Human movement patterns
Vector species identification abundance, and behavior (for example, from routine entomological surveillance systems or data repositories such as VectorBase or the Malaria Atlas Project)
Stock levels for malaria drugs and commodities
Coverage of key interventions at community level
Ecological and meteorological data

Although an advantage, access to country-level incidence data is not a requirement for applicants to propose a demonstration project. Solutions can be developed in a number of malaria elimination contexts, but any future implementation will need to focus on the priority geographies for the Bill & Melinda Gates Foundation. Specifically, the Greater Mekong Subregion, the “Elimination 8” of Southern Africa, and Mesoamerica.

We are especially interested in applicants and solutions that come from sectors beyond malaria, or even outside health. Solutions do not have to be brand new; they can be an existing method or tool used in another context repurposed and applied. However, in this case we will require proposals to include a demonstration project.

Winning proposals should::

Focus on simplicity of methods using routinely available data
Explain the rationale for targeting specific countries or regions
Describe approach for interoperability with country data systems including DHIS2
Provide evidence that the activity is aligned to relevant national strategies on eHealth
State the expected improvements over existing solutions, and how this will be evaluated
Address cost of the solution and a description of how it can be brought to scale and be sustainable in the malaria-endemic developing world context
Explain how the solution will strengthen existing health systems instead of building a parallel system
If the solution involves building on or integrating a reporting system for additional disease areas, explain how it will strengthen malaria elimination decision-making

A few examples of work that would be considered for funding:

Developing a novel algorithm or API that pulls together data on malaria cases and health facility stock. Or case data and vector control coverage. Or population and travel history. Or incorporating new types of data, such as population estimates through household maps
Integrating data derived from advanced identification and tagging methods (of people, habitats, structures, etc.) utilizing remote sensing platforms
Using ICT to incorporate new data sources (for example diagnostic data from point-of-care tests, or data and feedback elicited directly from users in the health system)
Heuristic or machine learning algorithms for data validation
Ontology, translation and other data integration services
A data integration method (i.e. ELT-related tooling) that is optimized and scalable for malaria elimination settings
Interoperable software modules for popular malaria elimination or other global health platforms

We will not consider funding for:

Proposals that do not focus on surveillance in countries with malaria elimination goals
Development of new primary data collection tools
Proposals that do not address the issue of interoperability
New modeling approaches for malaria early warning or risk mapping
Proposals that only focus on standalone research or survey contexts