Researchers have found that temperatures on the surface of the tropical South Atlantic Ocean in July can predict the severity of malaria outbreaks in northwestern India that begin to peak four months later.
- Researchers considered monthly ocean temperatures in all of the world’s oceans over the past twenty years, and compared that information to rainfall patterns and the size of yearly malaria outbreaks.
- In climate simulations, changing temperatures in a large area of the tropical South Atlantic led to changes in how the atmosphere over the ocean behaved and to increased rainfall in India.
- The ability to predict monsoons and the malaria epidemics they worsen gives public health workers more time to mobilize resources for prevention, control, and surveillance.
Temperatures on the surface of the tropical South Atlantic Ocean in July can predict the severity of malaria outbreaks in northwestern India that begin to peak four months later, Howard Hughes Medical Institute researchers have discovered.
The correlation they have found between ocean temperatures and distant monsoons that worsen malaria epidemics not only provides new information on the interaction of weather systems around the globe, but offers a new way to anticipate the need for anti-malaria resources in any given year. The finding was published March 3, 2013, in the journal Nature Climate Change.]
This gives us a longer lead time between environmental drivers and malaria epidemics than we’ve ever had before.
“This gives us a longer lead time between environmental drivers and malaria epidemics than we’ve ever had before,” says Mercedes Pascual, an HHMI investigator at the University of Michigan, who spearheaded the work. “And this lead time gives the region a better chance to mobilize measures of prevention, control, and even surveillance.”
Malaria is a mosquito-borne parasitic disease that is widespread in much of India, Africa, and Asia. While the disease is a year-round threat in some areas, in others—including northwestern India—outbreaks occur seasonally, since the mosquitos that carry the malaria parasite only thrive during part of the year. Pascual had previously studied how variations in seasonal rainfall patterns—or monsoons—throughout India affected the severity and location of these seasonal malaria epidemics. In general, more rainfall in any area worsened that year’s malaria, she found. The observation gave researchers a way to use mathematical models to predict malaria outbreaks in that section of India a month or two ahead of time—monsoon season ends in September and malaria peaks in November.
“We began to be interested in whether we could use other climate measures to predict monsoon patterns and get an even earlier warning system,” says Pascual. Past work by her lab group had discovered that changes to the ocean temperatures in the equatorial Pacific region—dubbed El Niño— could affect cholera outbreaks in Bangladesh. They suspected that El Niño could also play a role in malaria outbreaks in Northwest India through its effect on the monsoons.
The researchers cast a wide net looking for possible influences. They considered monthly ocean temperatures in all of the world’s oceans over the past twenty years and compared the information to both rainfall patterns and the size of malaria outbreaks in India each year. They found that while El Niño had no effect, the temperatures in a large area of the tropical South Atlantic did. The area had never been found as the key spot in affecting distant weather in India, so Pascual and her colleagues ran computerized climate simulations to test the effects of different ocean temperatures there. Sure enough, decreasing the sea surface temperatures led to changes in how the atmosphere over the ocean behaved and, over time, led to increased rainfall in India.
“This is important not just for disease but for agriculture and everything in arid Northwest India that is affected by monsoon season,” says Pascual. “This adds to our knowledge on understanding monsoons, which is a huge field within climate science.”
Pascual hopes that the discovery will help those working to eradicate malaria deploy resources to the right places. The planning and preparation for spraying insecticides inside dwellings, for example, can be time-consuming, and getting a head start can mean more houses get protected. Pascual also plans to add additional factors into her prediction models to make them even more useful. For example, she’d like to be able to better factor in varying disease control efforts each year.
“We always do predictions based on the past,” says Pascual. “But that doesn’t take into consideration what is happening differently with control, which is not a constant from year to year and is increasing over time.”
This can be a problem, she says, because if rainfall is low one year and the following malaria epidemic is small, it can give officials a false impression that their approach is working and might lead them to lessen their efforts the following year.
“What I would like to see in the future is how we can put together environmental observations with trends on control to have a more adaptive prediction model,” Pascual says. Additionally, she is looking at the effects of climate change and climate variability on other areas affected by seasonal malaria such as highlands in Africa and South America.