Can Temperature Fluctuations in the Indian Ocean Predict Dengue Epidemics?
According to experts, monitoring temperature fluctuations in the Indian Ocean could help predict dengue epidemics in advance, leading to a more effective public health response. Dengue is a virus transmitted by mosquitoes and poses a threat to nearly half of the global population, with up to 400 million cases reported annually.
A recent study published in Science suggests that variations in the sea surface temperature of the Indian Ocean may have the ability to predict the severity of dengue outbreaks in Asian and South American countries up to nine months in advance. The study examined 30 global climate indices and found that the Indian Ocean basin-wide index (IOBW), which measures average sea-surface temperatures in the basin, had the most significant impact on dengue outbreaks in both hemispheres.
The researchers believe that increased sea surface temperatures in the Indian Ocean can alter global weather patterns, creating favorable conditions for mosquito reproduction and dengue transmission. While local climate indicators like temperature influence seasonal dengue upticks, global climate trends also play a role in yearly incidences.
Yiting Xu, a professor at Beijing Normal University, explains that the IOBW index offers a more reliable early warning system compared to local temperature measurements. Current dengue early warning systems already use climate parameters like temperature and rainfall to predict illness patterns. For example, El Niño events affect mosquito reproductive conditions, which subsequently impact the global transmission patterns of dengue.
To identify long-distance climate drivers of dengue epidemics, researchers simulated connections between global climate patterns and reported case counts from 32 countries in the Americas and 14 in Asia, including India, between 1990 and 2019. The IOBW index accurately forecasted epidemics in countries like Venezuela, Brazil, Peru, Thailand, Singapore, and the Philippines.
In simulations of dengue transmission scenarios with and without the IOBW index, the study accurately replicated the dengue outbreak in 2015-2016 and the significantly reduced epidemics worldwide in 2017-2018. These outcomes align with the warm IOBW event in 2015-2016 and the cold IOBW event in 2017-2018.
However, the researchers emphasize the need for improved validations and comprehensive dengue indicators. They plan to integrate additional variables like socioeconomic circumstances, local herd immunity, and vector control into their models. Environmental epidemiologist Ramesh Dhiman suggests that factors like rainfall, water availability, housing conditions, and personal protective equipment also influence disease transmission and the timing of outbreaks.
Dhiman notes that it may not be possible to predict outbreaks more than four to five months in advance due to the potential variability in rainfall patterns. However, he points out that Aedes mosquito vectors can persist for an extended period due to increased humidity caused by precipitation.
Dhiman’s research indicates that dengue epidemics in certain Indian states are closely linked to El Niño events, monsoons, and post-monsoon rainfall. However, in other regions, dengue infections decrease during summer El Niño events. He also warns that as temperatures rise, previously colder regions may become susceptible to local dengue transmission.
In conclusion, monitoring temperature fluctuations in the Indian Ocean using the IOBW index shows promise for predicting dengue epidemics in advance. While local climate indicators are already utilized in early warning systems, global climate trends play a significant role in yearly dengue incidences. However, further research and integration of additional variables are necessary to improve the accuracy of predictions and enhance public health responses.