App/Software

Mark Adams of Population Services International in the U.S. will develop a "Digital Gateway" that provides health campaign managers easy access to a range of datasets to improve the planning and performance, and lower the cost, of health campaigns. Health campaigns generate data, such as population estimates, locations of health clinics, and mobile phone data, that could make planning new campaigns much more efficient, but these data tend to be difficult to access.

Seth Cochran of Operation Fistula in the U.S. and Nick Bennett of Simprints in the United Kingdom will incorporate facial recognition technology from Simprints into their existing automated patient registry to better track and support women with obstetric fistula in low-resource settings. Obstetric fistula is caused during childbirth and leads to the uncontrolled release of bodily wastes. It is estimated that more than 2 million young women live with untreated obstetric fistula in Asia and sub-Saharan Africa.

Hamed Alemohammad of Open Imagery Network Inc. in the U.S. and Ernest Mwebaze of Google AI Research Center in Ghana will generate synthetic imaging data to train machine learning algorithms to better interpret satellite images in low-resource settings to monitor crops and increase food security. The increase in global satellite observations at different spatial and temporal scales has led to the development of sophisticated analytical methods such as machine learning for a variety of applications.

Outside the Lens in the U.S. will launch an app-based participatory media project in partnership with high school students, connecting communities to understand the historical barriers to economic mobility in redline communities, places where there exists a systemic denial of basic services. This phone application will enable data visualization, geo-tagging, interactive maps, and community engagement events to explore how historical economic barriers impact our cities in the past, present, and collective future.

SaverLife in the U.S. will connect financial data with the perspectives and experiences of low-income individuals from their online community to shift perceptions on who they are and why they are poor and help drive client-informed solutions. SaverLife's online community supports over 330,000 low-income members across the U.S. to help them save for their futures. As a result, SaverLife has gained rich insights into the causes and effects of poverty and the household impact of social policy.

The National Women's Law Center (NWLC) in the U.S. will partner with individuals doing their best to make ends meet to collate and present the receipts and paystubs they receive over the course of a year to dispel the myth that poverty is an individual problem. NWLC will provide a stipend and tools for storytellers to document how they navigate poverty and show how systemic failings, such as limited benefits for the disabled and unaffordable interest repayments, underlie poverty.

The Metropolitan Planning Council in the U.S. will build a website to push back against the myth of "good" and "bad" neighborhoods - dominant narratives that are value judgments, which help perpetuate inequity. Aided by a long history of racial and economic segregation, racialized policies and practices in many cities have systematically deprived communities of color of equitable investment.

Coite Manuel of Food Chain LLC. in the U.S. will develop a web-based tool that takes existing road network and population data for any country, divides it into regions, and identifies the closest health facility based on type and time of travel to improve health campaign planning and better monitor population health. Current approaches to map catchment areas for health facilities use administrative boundaries or population statistics, which often don't reflect where people actually go.

Pascal Geldsetzer of Stanford University in the U.S. will develop a computational tool to support health campaigns in low- and middle-income countries that can predict the number and location of the people that need targeting. They will use freely available databases, including the Demographic and Health Surveys (DHS), covering over 10 million households and high-resolution population estimates to estimate the percentage of children under 5-years-old who are un- or under-vaccinated within each 30m by 30m area.

Qingfeng Li of Johns Hopkins Bloomberg School of Public Health in the U.S. will develop a computational simulation tool to optimize the design of health campaigns in low-income settings. Health campaigns are complex events involving multiple, interconnected components, such as families and socioeconomic contexts, as well as being time restricted and targeting specific populations. Their tool uses geospatial measures and community maps, and it includes an automated algorithm to test different design strategies to identify the optimal design.