2017 ICT4D Conference

Data analytics enabled through technology at the individual-, community- and planetary-level is being used to improve individual and population health by integrating and synthesizing data across vast magnitudes of scale.

Today, our daily decisions about health often stem from data analytics using technology near and far (eg, from our wrists to outer space). If we consider the health effects associated with air pollution, such as particulate matter 2.5 ug/m3 or PM2.5 - usually generated by combustion, smog, diesel and gasoline sources, is thirty times smaller than the human hair and penetrates deep into the small airways of the respiratory tract - the technology that is being used to generate big data and fuel data analytics in this area varies immensely by scale and granularity. And it’s defining how we approach air pollution-associated disease prevention and control around the world.

At a larger scale, it enables us to highlight geographic hot spots, observe seasonal and secular trends and predict PM2.5 levels where local data don’t exist by using light-scattering satellite imagery. At a local level, it allows environmental advocates to inform policy makers on air pollution control measures using geo-visualization tools to target and protect vulnerable populations based on socio-economic determinants such as use of biomass fuel for cooking in rural areas or distance to high-traffic roads, bus stations and nearby power plants in urban areas. And at a more individual level, it allows health professionals to use epidemiological bio-marker cohorts to focus on medically susceptible populations such as young children, the elderly or those suffering from asthma or cardiovascular disease. What’s interesting is that the technology and data analytics inputs for these decisions can be equally important whether it comes from our wrists, the neighborhood monitoring station, a database listing brick kilns in the region, or a satellite in outer space; and extremely powerful when taken together and integrated as a whole.

So the decision to go out for a walk, take an auto or ride the metro for an individual on a high pollution day in New Delhi, can stem from his wearable device reading at that minute, a Harvard scientist’s prediction modelling in Boston, an engineer’s database in Goa, an epidemiologist’s cohort surveillance in Chennai and a big data analyst in Seattle.

For public health and environmental experts, this is the world of air pollution and disease control today. And this potential of technology and data analytics to drive the betterment of our health and planet, is spawning the next generation of change-makers for tomorrow.