Emerging Microbes & Infections · 2017 · 257 citations · 45 references
Dengue incidence in India has risen over the past decade, driven by host‑vector‑virus interactions that are modulated by climatic factors. The study aims to examine how the extrinsic incubation period varies across India’s climatic zones. EIP was estimated using daily and monthly mean temperatures for Punjab, Haryana, Gujarat, Rajasthan, and Kerala. Simulations showed Kerala’s EIP was short (8–15 days at 30.8 °C) and lowest during monsoon, whereas Punjab’s EIP was long (5.6–96.5 days at 35–0 °C); dengue cases correlated significantly with precipitation, highlighting temperature’s importance in virus development and spatial‑temporal risk. The study was published in Emerging Microbes & Infections (2017) and urges climate‑based dengue forecasting models to be tailored to each Indian climatic zone.
For the past ten years, the number of dengue cases has gradually increased in India. Dengue is driven by complex interactions among host, vector and virus that are influenced by climatic factors. In the present study, we focused on the extrinsic incubation period (EIP) and its variability in different climatic zones of India. The EIP was calculated by using daily and monthly mean temperatures for the states of Punjab, Haryana, Gujarat, Rajasthan and Kerala. Among the studied states, a faster/low EIP in Kerala (8–15 days at 30.8 and 23.4 °C) and a generally slower/high EIP in Punjab (5.6–96.5 days at 35 and 0 °C) were simulated with daily temperatures. EIPs were calculated for different seasons, and Kerala showed the lowest EIP during the monsoon period. In addition, a significant association between dengue cases and precipitation was also observed. The results suggest that temperature is important in virus development in different climatic regions and may be useful in understanding spatio-temporal variations in dengue risk. Climate-based disease forecasting models in India should be refined and tailored for different climatic zones, instead of use of a standard model.Emerging Microbes & Infections (2017) 6, e70 doi:10.1038/emi.2017.57; published online 9 August 2017
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