A diagnostic tool for assessing the wellbeing of billions of people around the world in real-time at a reasonable cost would constitute a breakthrough in global health management. But is such a tool feasible, what fraction of the world population could practicably be captured by such a tool and could it be economically viable? In an ongoing experiment at Arizona State University, the Human Health Observatory (HHO) was created and is being expanded to measure the health and sustainability of human populations around the world. The HHO project relies on wastewater-based epidemiology and urban metabolism metrology (UMM) to inform on the human condition around the globe. Samples collected and archived in the HHO currently cover a timespan of the past two decades and account for about 10% of the U.S. population and over 250 million people, residing in some 400 cities, communities and neighborhoods worldwide. Health determinants investigated include the daily consumption of 120+ pharmaceuticals and personal care products (PPCPs), presence of and human exposure to over 350 contaminants of emerging concern (CECs), and additional chemical agents including illicit drugs, stress hormones, dietary markers as well as biological agents such as viruses, antibiotic resistance genes and bacteria of human health concern. The limits of the HHO approach were analytically examined by estimating the fraction of the world population currently and projected in the future to be connected to centralized wastewater treatment plants that serve as the principal monitoring stations and public health observatories for localized populations. A summary of case studies using HHO data was compiled to illustrate how past and ongoing measurements of fresh and archived samples can serve to inform on population health status, policy decisions, safer chemical design, waste-to-energy conversion, as well as tracking progress toward achieving sustainable development goals and environmental justice in the U.S. and globally.

Assessing the human condition globally in near real-time using the human health observatory

2019 Fall National Meeting

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