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Mathematical model to thwart mosquito borne diseases
July 30, 2017, 4:18 pm
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Researchers at Upstate Medical University in the US have created a mathematical model capable of serving as a guide to predict when people are at greatest risk for contracting mosquito-borne viruses, such as dengue, Zika and chikungunya, due to climate conditions. The new tool could lead to developing early warning systems that could help halt the spread of these potentially deadly viruses.

Zika, dengue and chikungunya are mosquito-borne viral illnesses that are leading causes of illness in tropical and subtropical regions. Because there are no vaccines or cures for these viruses there is an increased urgency for those in the public health sector to identify alternative strategies to manage the disease, including early warning systems.

Studies have consistently found that unusually high rainfall and minimum temperatures are associated with mosquito-transmitted viral diseases in epidemic prone areas like Ecuador. Other studies have shown that transmission of dengue, and other arboviruses by Aedes aegypti and Aedes albopictus mosquitoes, occur between 18-34°C with maximal transmission in the range of 26-29°C.

The research team used real-time seasonal rainfall, temperature and El Niño forecasts, issued at the start of 2016 for Ecuador, combined with data from active surveillance studies, in a probabilistic model of dengue epidemics to produce robust dengue risk estimates for the entire year. The researchers said that since the same mosquito species, Aedes aegypti, is responsible for diseases such as chikungunya and zika, their model could also be used to predict outbreaks of these diseases.

In Ecuador, the researchers correctly forecast the peak in dengue incidence would occur three months earlier than expected in March 2016, with the mean dengue incidence having a 90 percent chance of exceeding the average for previous five years. Also, using climate models, the team predicted the extreme flooding that occurred in some parts of Ecuador, several months in advance.

When combined, these mathematical models give public health and governmental officials vital climate information needed to create early warning systems — systems that can alert the public to the risk for disease and allow public health officials to mobilize resources and enact mosquito control programs and surveillance ahead of peak season.

The researchers said that their study demonstrated the potential value of incorporating climate information in the public health decision-making process not only in Ecuador but also in any epidemic-prone region, impacted by El Nino events.

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