Weather-Based Prediction Models for the Prevalence of Dengue Vectors and .

Dengue is an important vector-borne disease transmitted by the mosquitoes and . In the absence of an effective vaccine, vector control has become the key intervention tool in controlling the disease. Vector densities are significantly affected by the changing weather patterns of a region. The present study was conducted in three selected localities, i.e., urban Bandaranayakapura, semiurban Galgamuwa, and rural Buluwala in the Kurunegala district of Sri Lanka to assess spatial and temporal distribution of dengue vector mosquitoes and to predict vector prevalence with respect to changing weather parameters. Monthly ovitrap surveys and larval surveys were conducted from January to December 2019 and continued further in the urban area up to December 2021. was found moderately in the urban area and to a lesser extent in semiurban but not in the rural area. had the preference for rural over urban areas. preferred indoor breeding, while preferred both indoor and outdoor. For , ovitrap index (OVI), premise index (PI), container index (CI), and Breteau index (BI) correlated with both the rainfall (RF) and relative humidity (RH) of the urban site. Correlations were stronger between OVI and RH and also between BI and RF. Linear regression analysis was fitted, and a prediction model was developed using BI and RF with no lag period ( (sq) = 86.3%;  = 53.12; (pred) = 63.12%; model: Log10 (BI) = 0.153 + 0.286 Log10 (RF); RMSE = 1.49). Another prediction model was developed using OVI and RH with one month lag period ( (sq) = 70.21%;  = 57.23; model: OVI predicted = 15.1 + 0.528 Lag 1 month RH; RMSE = 2.01). These two models can be used to monitor the population dynamics of in urban settings to predict possible dengue outbreaks.