Temperature is a primary driver of Aedes aegypti biology, shaping survival, development, fecundity, and vectorial capacity across its geographic range. As climate change alters thermal conditions in dengue-endemic regions, understanding how mosquito populations from different climatic backgrounds respond to temperature becomes increasingly relevant. We evaluated the impact of temperature on the development and lifespan of Aedes aegypti from two climatically diverse regions: New Delhi, India (subtropical, seasonally variable climate) and Salvador, Brazil (tropical, consistently warm climate). Laboratory-reared mosquito colonies from both regions were exposed to a range of constant temperatures (20 °C, 28 °C, 32 °C) and a diurnally cycling temperature range. We measured key life-table parameters, including egg hatching rates, larval development time, pupation success, adult emergence, and adult lifespan and post-blood-meal faecal output as a proxy for digestive efficiency. Results demonstrated significant temperature-dependent effects, with optimal development and survival at 25–30 °C for both mosquito strains. However, the New Delhi strain exhibited greater tolerance to lower temperatures (20 °C), with higher survival rates and longer lifespans, while the Salvador strain showed enhanced performance at higher temperatures (32 °C), including faster development and higher reproductive output. These findings indicate strain-specific thermal performance patterns consistent with the climatic conditions of their source regions. The study demonstrates that Ae. aegypti populations from different climatic regions exhibit distinct thermal performance profiles across survival, reproduction, digestion, and development. While both strains performed optimally near 28 °C, the New Delhi strain showed enhanced tolerance to cooler conditions, whereas the Salvador strain was more resilient at elevated temperatures. These strain-specific differences have important implications for mechanistic models of arboviral transmission and climate-driven risk prediction. Incorporating population-level thermal variation into vector surveillance and control strategies may improve preparedness for emerging vector-borne disease threats under climate change.
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Sunil et al. (2026) studied this question.
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