Blum Center chief seeks solutions for tiny African nation bedeviled by climate change
Richard Matthew’s answer to the ageless grammar school question “What did you do this summer?” would include a visit to Chisi Island. But the UC Irvine professor of urban planning & public policy and political science was not vacationing on the island in the middle of Lake Chilwa, the second largest lake in the landlocked Southeastern Africa country of Malawi.
For years, the director of the Blum Center for Poverty Alleviation has traveled to carry out field research in some of the world’s least-developed countries. This summer, he was part of an international team that set up a weather station to “help monitor the growing impacts of climate change on local health.”
Collecting data that can be parlayed into solutions for vulnerable populations is what drives Matthew and the Blum Center. While each challenge is unique, the process of identifying and investigating the situation—in person—is quite similar.
“We have to travel to these sites to experience them firsthand, collaborate with local stakeholders and experts, integrate local knowledge and try to fill critical data gaps,” Matthew explains. “After reviewing existing research, remote sensing data and other available sources, we go there to acquire and assess additional local data that they have. In the case of health challenges, a lot of the data is in small clinics, scattered across these rural areas where they’re gathering data by hand. While their goal is to centralize and digitalize it, the resources are not always available to do so.”
Drought is common in Southeastern Africa, but they have been longer and more frequent of late in Malawi, which is also being hit by more cyclones than ever before. “As those things happen, we are trying to model how climate change might affect health outcomes through nutrition and increased exposure to disease. Once we have reviewed the literature, consulted experts in the community and visited the area to collect data, we go from the conceptual diagrams to developing what we call agent-based and system-dynamics models,” Matthew says.
Effective modeling requires good, solid data. With that secured, “we can work with our counterparts in Malawi to predict how more frequent droughts and floods could lead to agricultural and fishing losses that could then lead to malnutrition that will cause higher levels of food insecurity and problems like stunting,” Matthew says.
If historical health data shows stunting and other health challenges are not affected by climate change in certain areas, it may be that people living there have come up with solutions of their own. But the modeling could also identify where the relationship is strong, so experts can zero in on where to focus on potential solutions or, as Matthew puts it, “viable intervention points.”
“What makes sense?” he rhetorically asks. “Is it more wells and infrastructure for sanitation and water? Is it new types of crops? Is it better vaccine programs? Is it more education? Where are the places that you could apply resources to try and improve health outcomes? That’s what we have to do.”
Developing models for Malawi has taken longer than the Blum Center originally anticipated, as this summer’s trip was delayed a couple years due to the COVID-19 pandemic. Fortunately, Matthew reports, the funders of the research understood the bang for their donated bucks had to be postponed.
As he spoke, his team was at the stage of integrating three complex models to get a big picture view of Malawi’s climate change challenges. The Blum Center can then work with local communities on short-term and long-term strategies to improve health and nutrition.
That cannot come soon enough in Malawi, which is densely populated for a relatively small country. Matthew says records he has been provided indicate Malawi used to suffer severe droughts every 20 to 25 years. Locals could adjust to the resulting depletion of fish stocks by temporarily finding alternative sources of food. But now, the professor says, droughts are happening every two to three years, fish stocks are not having enough time to recover and alternatives are more and more scarce.
“We are seeing serious declines in nutrition,” Matthew says. “About 70 percent of the population is anemic, and about 40 percent of children are stunted. Malawi is one of the poorest countries in the world, and it doesn’t have a lot of resources. It has a severe challenge as a landlocked country with no ocean access. The opportunities for economic development are much more constrained than they are in other countries where you do have port access.”
One fear is Malawi will eventually become so uninhabitable that some people will be forced to leave . . . but to where? Many surrounding countries are not much better off, and their leaders and inhabitants might not be keen on millions of new mouths to feed crossing their borders.
However, Matthew has not lost hope.
“I think it’s really important for people to think about the sort of enormous opportunity we have using some of the technological innovations, especially of the past 10 or 15 years, where we have this unprecedented ability to process data,” he says. “We have an incredible ability to see trends and patterns, to recognize anomalies, and to efficiently begin to allocate resources to generate desirable outcomes. We have technologies that are very powerful. These technologies work very well, and are working very well, in health and education and security.”
Making this happen requires more investment in data collection, he adds.
“Computer modeling allows us to use resources so much more efficiently. Otherwise, you’re dealing with too much uncertainty. If you’re a policymaker, and I tell you there’s a 50 percent chance of this happening, you’re sitting there thinking, ‘So what if I punted for a year?’ But with the data, if I say there is a 96 percent chance of this happening over here, and there’s a 4 percent chance over here, a policymaker can say, ‘Okay, now it’s a much smaller investment in a much more targeted area.’ We can do that. There’s a body of data that is very good and very reliable.”
— Matt Coker