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. 2019 Jan 31:2019:2950216.
doi: 10.1155/2019/2950216. eCollection 2019.

Evaluation of the Effects of Aedes Vector Indices and Climatic Factors on Dengue Incidence in Gampaha District, Sri Lanka

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Evaluation of the Effects of Aedes Vector Indices and Climatic Factors on Dengue Incidence in Gampaha District, Sri Lanka

N D A D Wijegunawardana et al. Biomed Res Int. .

Abstract

Constant monitoring of Aedes vector indices such as Aedes mosquito abundance and ovitrap data is important for the control of dengue epidemics. Therefore, the current study attempted to evaluate the effect of larval and climatic factors on the incidence of dengue outbreaks in the Gampaha district. Based on the distribution of previously reported dengue cases, 34 households in Narangodapaluwa PHI area, Ragama, Sri Lanka, were selected randomly, and entomological surveillance was done fortnightly using adult mosquito catches and larval surveillance techniques for a period of two years. Further, weekly ovitrap surveillance was conducted for one year, by maintaining four ovitraps in a single house, two indoors and two outdoors at ground and at a height of 1.5-2 m. Based on the findings, larval indices, namely, Breteau index (BI), House index (HI), and Container index (CI), were calculated, along with the Ovitrap index (OI). The study area was positive for Ae. albopictus with an adult capturing range of 1~15/34 households. BI initially remained < 3%, which subsequently decreased up to 0. No significant difference in OI was found between the ovitraps placed at ground level and at a height of 1.5-2m (p>0.05), 95% level of confidence. The OI varied from 56.9% to 94.7% during the study period of 12 months, indicating two peaks at the monsoons. Statistics of one-way ANOVA revealed a significant difference in the monthly OI during the study period (p≤0.001) with two peaks representing the monsoonal rainfall patterns. Pearson's correlation analysis revealed that the association between dengue cases and larval indices (BI, CI, HI, and OI) and meteorological parameters was not significant (p<0.05). Migration of mosquitoes and patients could be considered as possible factors affecting the absence of a significant relationship.

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Figures

Figure 1
Figure 1
Location of the Narangodapaluwa PHI area within the Gampaha district.
Figure 2
Figure 2
Relative abundance of adult mosquito species within study site and results of the mosquito indices (HI, CI, BI, PI) from September 2014 to August 2016.
Figure 3
Figure 3
Temporal variation of larval indices (HI, CI, BI, PI) with the reported number of dengue cases from June 2015 to May 2016.
Figure 4
Figure 4
Temporal variation of meteorological parameters with the reported number of dengue cases from June 2015 to May 2016.
Figure 5
Figure 5
Vector distribution map constructed based on OI followed by the number of positive cases reported in the study area.

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