Data and digital tools can be harnessed to address some of the fundamental public health challenges facing the developing world. The level of mortality and morbidity caused by infectious and parasitic disease in a country like Nigeria is six times higher than that of the leading cause of death in the United States (cardiovascular disease). Tens of millions of deaths and serious illnesses each year can be attributed to preventable causes such as malnutrition, lack of immunizations, inadequate maternal and early childhood care, unsafe sex, and inadequate water and sanitation systems that can spread infectious disease.
Cities can substantially reduce the risks of preventable and easily treatable illnesses by using big data and advanced analytics to shape public health interventions. Small subpopulations often account for a large share of certain conditions. Analytics can identify demographic groups with elevated risk profiles so that interventions can be targeted more precisely. Having identified the right target audiences, authorities can reach large numbers of people in a highly effective, low-cost way through text messaging, which does not require a smartphone or Internet access.
So-called mHealth interventions can disseminate lifesaving messages about vaccinations, sanitation, diabetes self-management, and safe sex as well as medication reminders for patients on antiretroviral therapy and other types of public health campaigns. This approach is valuable in any city, but it could have an outsized impact in the poorest developing cities. In particular, our analysis finds that data-based interventions focused on maternal and child health—such as sending at-risk mothers timely reminders about pre- and postnatal care—can reduce DALYs by more than 5 percent in a city with high childhood mortality rates. This type of approach is already producing results: a recent randomized control study found that timely SMS reminders increased childhood immunization rates in Kenya—and the effect was even larger when combined with small monetary incentives.
Big data is dramatically improving infectious disease surveillance, and we estimate that low income cities could reduce disability-adjusted life years (DALYs) by another 5% by implementing these systems. Health officials can stay a step ahead of fast-moving epidemics by tracking new cases in real time. This may involve monitoring social media, Internet searches, and even cellphone usage—and the tools are becoming more sophisticated.
During the 2016 Zika outbreak, experts in epidemiology, technology, and public health teamed up to capture location intelligence and analyze it with data visualizations and mapping tools as the disease spread throughout Rio and eventually made its way to Miami. Users of the mWater mobile app, an open-source tool being used in countries around the world, test for contamination in drinking water sources, and then upload the findings to a global water database for mapping.