Sea surface temperatures of Indian Ocean could help predict dengue outbreaks globally: Study

Abnormal trends in sea surface temperatures of the Indian Ocean could help predict trends in global dengue epidemics, including case numbers and how they might change with time, according to new research.

Scientists said that these observed abnormal temperatures, which are a ‘climate indicator’, could help enhance the forecasting and planning for outbreak responses.

Currently, precipitation and temperature are some of the climate indicators that are being used as early warning systems to forecast disease trends such as dengue, they said.

The team, including researchers from Beijing Normal University, China, explained that, for example, events associated with warmer sea surface temperatures, driven by El Nino, are known to influence how dengue is transmitted around the world by affecting mosquito breeding.

Being able to predict the risk of outbreaks and prepare for them can be crucial for many regions, especially those where the mosquito-borne disease is endemic, or constantly present.

However, the authors said there were gaps in our understanding of long-distance climate drivers of dengue outbreaks. Their findings are published in the journal Science.

In this study, the researchers used data on yearly dengue cases reported from across each of the 46 Southeast Asian and American countries from 1990-2019. Data of monthly cases from 24 of these countries reported from 2014-19 was also used for analysis.

Through modelling, the team drew associations between changes in climate patterns around the world and those in seasonal and yearly case numbers during dengue epidemics.

They found that dengue epidemics around the world were “closely” linked with abnormalities in sea surface temperatures of the tropical Indian Ocean.

“We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres,” the authors wrote.

In the three months before a dengue outbreak, the IOBW index was found to be a crucial factor in predicting the disease magnitude and timing of outbreaks per year in each hemisphere. The ability of IOBW to predict dengue incidence likely arises due to its effect on regional temperatures, the researchers said.

“These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses,” the authors wrote.

They, however, cautioned that more assessments are needed to evaluate the performance of their model in predicting dengue epidemics.

“Although our model demonstrates its capability to capture observed patterns, making premature claims about its predictive ability without rigorous validation of future data would be unjustified,” the authors wrote.