The highest relative risk was observed with the premise index and Breteau index at a maximum temperature of 34☌ after a 2 month lag ( figure 3B), which subsequently subsided 1 month later ( appendix pp 11–13). The relative risk of vector indices seemed to increase with increasing maximum temperatures above 31♵☌. Monthly means of daily maximum temperature had the lowest quasi-AIC value suggesting a better fit to the data when compared with mean and minimum temperature ( appendix p 7). However, Ae aegypti was much more prevalent in Panadura and Horana ( appendix p 6). By the end of 2018, this vector was detected in rural areas of Bulathsinhala and Agalawatta. Initially, Ae aegypti was found only in urban MOH divisions, namely Panadura, Horana, and Mathugame. The average container index for Ae aegypti was 3% during the study period. Ae albopictus was found to be the most prevalent species with an average container index around 97%.
Covering items, tires, and roof gutters were the most productive breeding sites with higher prevalence of pupae ( figure 2B). Refrigerator trays and water storage tanks, which are typically considered as indoor breeding sites, accounted for 14 904 (14%) sites. The main vector breeding sites were discarded receptacles (eg, plastic containers, tins, clay pots, coconut shells, damaged ceramic items) which accounted for 41 904 (39%) of 108 000 breeding sites, temporary removed items (eg, barrels, cisterns, and cans, which are kept outside until they can be used again) which accounted for 15 984 (15%) sites, covering items (eg, tarpaulins and plastic coverings) which accounted for 11448 (11%) of sites, and tyres which accounted for 6696 (6%) breeding sites ( figure 2A). A descriptive analysis of the distribution of rainfall and temperature across all MOH divisions is given in the appendix (pp 3–5). Of the three temperature monitoring stations, the highest mean temperature (31♸☌) was recorded at the monitoring station in Rathmalana, which is located close to the coast. Panadura, which is close to the coast, received the lowest amount of rainfall (208♹ mm per month). Across the whole study period, the highest average rainfall was reported in Palindanuwara.
The other two El Niño events in 20 were also associated with relatively high rainfall and temperature (754♲ mm and 33♴☌ in 2010 759♹ mm and 33♲☌ in 2018). The highest temperature (34♳☌) was recorded at the monitoring station in Agalawatta. The highest monthly rainfalls during the 2014–16 El Niño were reported at the monitoring stations in Palindanuwara (1203♰ mm), Bulathsinhala (1138♹ mm), and Agalawatta (1089♰ mm) MOH divisions. Knowledge of types and distribution of vector breeding sites in different geographical locations can help public health authorities to design and implement context-specific behavioural interventions for successful community mobilisation.Ĭoncomitantly, the highest average monthly rainfall (884♶ mm) and average maximum temperature (33♶☌) events were recorded following the major-so-called Godzilla-El Niño from October, 2014, to March, 2016. This information is useful for spatial risk categorisation to prioritise areas for more intense vector control interventions. ONI has the added advantage of predicting the seasonal prevalence of Aedes vectors with a lead time of 6 months. Temperature and ONI have the potential to serve as predictors of vector activity with a lead time of 1–6 months. The amount of rainfall seems to indicate the magnitude of vector indices in the same month.
The lags identified between climate and larval indices were shorter compared with those for climate and dengue incidence, which suggests that vector control needs to be implemented earlier than indicated by the previous studies to be effective. Our findings have several important implications for vector control policies.
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