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August 6, 2018

Paul Block works to develop proactive disaster early warning system

There’s word a flood is approaching in the coming days and hours, so relief organizations and local volunteers quickly and frantically start sandbagging the area to provide some level of protection for the city’s residents.

The effort helps, but the majority of the work now has to be done reactively, which is something Paul Block wants to change.

Building off of a 2016 Global Health Institute (GHI) Seed Grant, Block, an assistant professor of civil and environmental engineering at the University of Wisconsin-Madison, is using a new UW2020 grant to develop an online flood and health risk management system in an attempt to give relief organizations months — not hours or days — to prepare for disasters. The advance information is centered on the ability to predict next season’s rainfall, by evaluating large-scale climate and land surface characteristics.

Developing the system can save lives and improve existing disaster management practices by providing advanced response strategies, says Block, a member of the Global Health Institute Advisory Committee. The early warning system is targeted at relief agencies and government organizations.

“We are aiming to establish frameworks for organizations so they may determine if and when they should take action and what course of action should that be,” Block says. “We are specifically addressing flood disasters, but such frameworks may be broadly applicable to disaster preparedness in general.”

Block, the principal investigator, is working with GHI Director Jonathan Patz; Stephen Vavrus, a senior scientist at the Nelson Institute Center for Climatic Research; Kristen Malecki, assistant professor in population health sciences; Justin Sydnor, associate professor of actuarial science, risk management and insurance; the International Federation of the Red Cross, and disaster management experts.

How vulnerable cities are — and the potential for disaster — varies depending on infrastructure and location.

Even though the model is global, the Red Cross will help Block’s team pick case studies to start researching and make the focus more place-specific. Four potential sites are in Ethiopia, Peru, Bangladesh and Mozambique.

These locations already have a framework for short-term actions they take when there is a flood, so the goal isn’t to build a new framework but figure out ways to extend it to include long-term warnings, Block says. A large piece of that will be developing sets of indicators that give an idea of the severity of impacts related to health due to these floods.

As the flood size increases, so do the negative health impacts that will vary from place to place. Communities face different risks in terms of their health priorities, the type of infrastructure they have and the possibility of medical services being interrupted.

“We are not foremost experts in local disaster prevention nor are we pretending to be,” Block says. “An important part of this project is connecting with those local experts in these different countries — there’s no way we can do this independently. We want to draw out what options and opportunities these different countries have and how they may benefit from advance information. Once that’s established, we can use our models and our systems to try to see if we can anticipate these conditions and what actions might be taken.”

Block’s current work with the UW2020 grant continues the work he started with a 2016 GHI Seed Grant that also looked at how flood prediction can support advanced disaster preparedness and identify public health risks.

The Seed Grant allowed Block to do preliminary research and explore if there was a sufficiently solid foundation to move onto the next level. The Seed Grant played a large role in helping him establish those early pieces, Block says.

“Seed Grants clearly serve an important role,” he says. “They provide a great opportunity to not only produce preliminary research and early results, but also show there’s a logical expression of ideas and research. They can also establish some early confidence that ‘OK, this is likely to work.’”