Real-time data are needed to monitor health after disasters

Weather-related disasters like the millions of Floridians left without power by Hurricane Ian or the record monsoon rains that have claimed 1,500 lives in Pakistan have increased five-fold in the past 50 years due to climate change. Researchers need to be ready to respond quickly to climate-related and human-made disasters.

When investigating the health effects of a disaster like a hurricane or an oil spill on community members and cleanup workers, the most valuable information for researchers is timely health and exposure data from them. Those kinds of data, however are rarely gathered in real time, which poses a challenge to research teams and for the communities themselves, as they seek to learn how their health could be affected.

I and my colleagues working on the Gulf Long-Term Follow-up Study encountered this challenge while studying workers involved in the response and cleanup of the Deepwater Horizon oil spill in the Gulf of Mexico in 2010, where nearly 5 million barrels of oil were spewed into the surrounding water. The resulting oil slicks covered thousands of miles. Workers involved in the response and cleanup soon began reporting symptoms such as coughing, wheezing, shortness of breath, and more. My colleagues and I wanted to know if those symptoms were possibly related to exposure to chemicals used to disperse oil in the Gulf during the cleanup.

Without real-time data from the cleanup workers, we had to estimate their exposures to dispersants that were applied by planes and boats. By sifting through thousands of pages of reports, papers, and reference materials, we were able to adapt a model used in pesticide management to estimate levels to which cleanup workers may have been potentially exposed.

It is now possible to collect data in real time using sensors and cloud-based data management systems during the aftermath of unplanned events like the Deepwater Horizon spill. Using technology for this purpose would make it much easier to assess exposures associated with response and cleanup activities and could facilitate the assessment of job-task-based exposures and community exposures. It would also enable epidemiologists to evaluate associations between exposures and health outcomes with greater precision.

The increasing frequency and magnitude of weather and climate-related disasters over the past decade, along with a number of significant human-made disasters, is a trend that is likely to continue and will affect the public and industry, both directly and indirectly.

There is an urgent need to develop real-time data collection and management systems that put minimal burden on the community members recovering from the crisis or teams that are busy responding to it. Collecting health and exposure data in real time could facilitate more agile risk management decision-making and will contribute to more accurate studies of how disaster-related exposures affect health.

This will require investing in low-cost sensor technologies to measure specific agents, such as chemical agents following a chemical spill, with geo-location capacity and cloud-based software that is compatible with a wide range of sensor types. The benefits of gathering real-time data from an array of low-cost, real-time sensor technologies compared to the cost of using conventional instrument technologies go beyond gaining an understanding of health effects. Rapid identification of high-risk situations that could lead to human health risks as well as to loss of property or harm to the environment allows crisis managers to respond quickly, focusing resources where they are most needed, resulting in more efficient use of resources.

To make sense of this information, a workforce must be trained in advance on these technologies and systems and be ready to deploy.

Though building this infrastructure may sound daunting, it is imperative to begin collecting health and exposure data in real time after disasters to learn how to better protect community members and workers in their aftermath.

Susan Arnold is an associate professor of occupational and environmental health in the Division of Environmental Health Sciences at the University of Minnesota and director of its Exposure Science and Sustainability Institute.