Challenge: Help Apply Advances in Information Communication Technology to Malaria Elimination
Malaria is a disease caused by a parasite that occurs in over 90 countries worldwide, with 77 percent of deaths occurring in children under age 5, mostly in Sub-Saharan Africa. However, huge gains have been made in recent years in reducing the number of cases and deaths, and many countries have declared elimination goals.
Malaria is preventable and treatable, and history shows that it can be eliminated. The disease used to be prevalent in Europe and North America, and was only eliminated in these regions in the first half of the 20th century.
As Melinda Gates said in 2007, "Any goal short of eradicating malaria is accepting malaria; it's making peace with malaria; it's rich countries saying: ‘We don't need to eradicate malaria around the world as long as we've eliminated malaria in our own countries.' That's just unacceptable."
The Bill & Melinda Gates Foundation sees surveillance as the backbone of effective malaria elimination efforts. By surveillance, we mean the information flow that helps health care workers in countries trying to eliminate malaria make decisions about what to do, when and where, in order to find malaria parasites, how to eliminate them from human populations, and how to prevent parasites from coming back.
The focus on malaria elimination goals requires a shift to action-oriented surveillance, which places an increased demand on the surveillance systems and people that use the data. For example, cases need to be reported in near real-time, and be geolocated at a fine scale resolution. This shift to action-oriented surveillance means a fundamental "rethink" of how data are collected and used and how surveillance systems are best structured to achieve the goal of a malaria-free world within a generation.
Despite acknowledging the role of surveillance in malaria elimination, the full potential of recent advances in information communication technology, data systems, and data harmonization has not yet been effectively applied to the challenge of malaria elimination.
There are multiple breakdowns in the data life cycle for malaria elimination. District and National Data is often collected and stored across organizations and different levels of the health system in multiple locations and in multiple formats, resulting in long and inefficient processes to harmonize and compile data. Some analyses that are specific for the needs of malaria elimination programs require sharing between inter- and intra-national organizations, ministry departments, and public and private sectors; this is complex and sometimes legally prohibited.
It is important to note that malaria elimination programs do not operate in isolation – the interventions themselves as well as the reporting of cases in health facilities are a part of a country's broader health system. This makes introducing changes to what kind of information is collected and how it flows within the system challenging.
We are most interested in improving data informed decision-making for key decision-makers for malaria elimination at various levels in national health systems. Innovations in this area will need to recognize that the data needs of key decision-makers vary across programs. For example at district level, managers are typically responsible for monitoring local trends in in health facility attendance, fevers, and positive malaria tests, ordering appropriate stock, deploying case investigation teams and carrying out supportive supervision. At national level, managers are responsible for interpreting malaria risk estimates, developing national plans and budgets, deciding on the best malaria control interventions to use, informing central medical store purchases, and prioritizing geographic areas to target these interventions.
With this call, we are looking for proposals of innovative solutions for improving data availability and use in decision-making for malaria elimination. Specifically, we are looking for innovations in interoperability that reduce the time for data harmonization, or innovation in analytics for how to analyze and present the most pertinent, actionable information. Solutions should streamline reporting burden, communications, and data analysis for District- and National-level Malaria Control Program staff. Solutions should also focus on simplicity of methods using routinely available data, demonstrate interoperability with existing country data systems including DHIS2, and be sustainable in the malaria endemic developing world context by scaling nationally.
We are especially interested in applicants and solutions that come from sectors outside of malaria, or even outside health.
We hope that you will surprise us with exciting ideas we can't even yet imagine. Submit your great ideas here! Grand Challenges Explorations
Originally published on Impatient Optimists