CPO/IRAP supported study shows potential for climate forecasts to predict infectious disease outbreaks

  • 25 August 2020

The mosquito species Aedes albopictus is native to Southeast Asia but can be found across the tropics and subtropics. Photo credit: James Gathany (Centers for Disease Control and Prevention)

Despite increased disease control efforts, the French island of Réunion in the Indian Ocean experienced an unprecedented dengue outbreak in early 2018, with a 6000% increase in cases from 2017. New research supported by CPO’s International Research and Applications Project (IRAP) revisits this outbreak and shows that it could have been predicted based on climate forecasts—with enough advanced notice for health authorities to initiate an early response strategy and minimize the impact. The research was recently published in the journal of GeoHealth.

The authors integrated forecasts of rainfall and temperature data up to four weeks ahead of the outbreak into a mosquito model to better understand if the increased mosquito population could have been calculated. Their success has implications for the use of climate data in future public health efforts.

Dengue fever is a viral tropical disease spread by mosquitoes. It's a significant public health concern globally, estimated to cause nearly 100 million symptomatic cases per year. In Réunion, the disease is carried by the local species Aedes albopictus. Mosquito populations are influenced by a complicated web of environmental factors that are difficult to monitor on a local scale. However, the study by researchers at Columbia University’s International Research Institute for Climate and Society, Umeä University, New York University and the European Center for Disease Control and Prevention shows that there is great potential for using climate information to predict how suitable an environment will be for vector-borne diseases.

Mosquito species such as A. albopictus thrive only within a unique temperature range. Rainfall events also have distinctive effects on their survival. These factors and others can be identified among climate data, and the researchers recognized that an ideal confluence of these environmental factors could bring on an increase in the abundance of mosquitoes, which could lead to an outbreak.

“Tropical-cyclone-related rainfall events and higher-than-average temperatures played a role in the 2018 dengue outbreak,” said Laurel DiSera, a senior research staff associate at the International Research Institute for Climate and Society and the study’s lead author. “Since we can forecast such conditions up to four weeks in advance, we thought it would be possible that the outbreak itself could be predicted weeks ahead.” (See map below)

To test the idea, DiSera and her colleagues incorporated subseasonal climate forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) model, available via the Subseasonal-to-seasonal Prediction Project Database, into a vector model that generated predictions of mosquito populations; they found that the methodology was reasonably predictive of the outbreak event in 2018. According to their results, both the onset and size of the outbreak could have been accurately predicted two weeks in advance, with some accuracy three to four weeks in advance — enough time for enhanced preparedness measures.

“Our results strongly suggest that we can use subseasonal data to better understand suitability for mosquito populations and the potential for resulting outbreak events,” DiSera said.

The top map (a) shows the observed rainfall anomalies in Réunion and nearby islands for January 8, 2018. The maps below it are rainfall-anomaly forecasts for January 8, 2018 made one (b), two (c), three (d) and four (e) weeks before.

“The routine way to prevent and manage dengue outbreaks is through mosquito control,” said coauthor Joacim Rocklöv for Sweden’s Umeå University. “Having more time to act makes a difference, not in the least operationally.”

DiSera added that in a time when many public-health systems are already under strain, new methodologies like the one proposed may help public health agencies save resources and time and allow them to be more flexible in dealing with urgent and unexpected threats.

This research was supported by the NOAA Climate Program Office's International Research and Application's Project (grant NA18OAR4310339), the ARBOPREVENT project (Swedish Research Council Formas grant 2018-01754), and Adapting Agriculture to Climate Today, for Tomorrow (ACToday), a Columbia World Project.

This was adapted from a web story written by Columbia University’s International Research Institute for Climate and Society. Read their web story here.

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