Seasonal Climate Models May Help Warn for Malaria Outbreaks in Mozambique
Applying knowledge of climate variability may be a key to predicting public health trends in Mozambique, according to Ryan Harp, a postdoctoral research fellow with the Ubben Program for Carbon and Climate Science at the Institute for Sustainability and Energy at Northwestern (ISEN). Harp studied climate and health data in Mozambique to tie patterns of climate variability to increased malaria cases. He recently presented his research at the international Planetary Health Annual Meeting. Harp and his fellow researchers believe that this research could be applied to other countries and diseases to help lengthen lead times in warning systems and allow public health officials to better distribute resources in advance of an outbreak.
Malaria ranks fourth as the leading cause of death among infectious or parasitic diseases. The World Health Organization estimates that there were 229 million cases of malaria and 409,000 deaths worldwide in 2019. The disease is endemic to Mozambique, so it’s important for public health officials to be able to understand how climate affects case rates in the nation.
“Malaria depends on mosquitoes to carry it. So, generally speaking, the more precipitation you have, the more standing water and puddles there are for mosquitoes to breed, the more mosquitoes and cases of malaria there are,” Harp said.
Harp works with the Climate Change Research Group at Northwestern led by Daniel Horton, assistant professor and director of undergraduate studies with the Department of Earth and Planetary Sciences. The group uses models, observations, and statistical analyses to study the earth’s climate. Harp’s study, published in GeoHealth in January 2021, looks at the effect of climate and climate change on human health through the example of illness resulting from differences in year-to-year rainfall.
Harp and fellow researchers took malaria data from Mozambique’s 148 districts, similar to counties, and performed an empirical orthogonal function, which identifies areas of the data that vary together over time. Once these regions were identified, the researchers predicted that this trend in case variability would be tied to precipitation.
The research group found two main locations where the majority of variability in rainfall and malaria data were found. The first was in the southern half of Mozambique, which accounts for 64% of year-to-year variability in the disease, and the second in the northern third of the country, which accounts for 17% of variability.
From this main finding, Harp’s team used climate data, such as precipitation and sea surface temperature, to find that the two principle modes, or locations of variability, were linked to the El Niño-Southern Oscillation and the Subtropical Indian Ocean Dipole, two irregular climate events that impact precipitation patterns in southern Africa.
“This is kind of a novel discovery because other studies have looked to get more fine-scale, week-to-week, changes in malaria,” said Harp. “But we are really getting at this longer timescale and seeing if we could tie in the year-to-year changes in malaria at that timescale to these longer-term climate phenomena.”
Harp chose this area of study at the end of his PhD research at the University of Colorado Boulder, which he completed in 2020 before coming to Northwestern that same year. He liked the study because of its interdisciplinary nature and the ability to help prevent large outbreaks.
“I am devoting most of my time to studying climate and health,” Harp said. “I think it's just a really good fit for me personally because it's an interdisciplinary topic, it's combining two fairly different fields, and it's very applied so you are able to provide benefits to people.”