Distributed Lag Nonlinear Modelling Approach to Identify Relationship between Climatic Factors and Dengue Incidence in Colombo District, Sri Lanka
DOI:
https://doi.org/10.2427/11522Keywords:
Dengue, Distributed Lag Non Linear Modelling, Quasi - Poisson, Climate, Time SeriesAbstract
Dengue fever and its more severe deadly complication dengue hemorrhagic fever is an infectious mosquito borne disease. The rise in dengue fever has made a heavy economic burden to the country. Climate variability is considered as the major determinant of dengue transmission. Sri Lanka has a favorable climatic condition for development and transmission of dengue. Hence the aim of this study is to estimate the effect of diverse climatic variables on the transmission of dengue while taking the lag effect and nonlinear effect into account. Weekly data on dengue cases were obtained from January, 2009 to September, 2014. Temperature, precipitation, visibility, humidity, and wind speed were also recorded as weekly averages. Poisson regression combined with distributed lag nonlinear model was used to quantify the impact of climatic factors. Results of DLNM revealed; Mean Temperature 250C – 270C at lag 1 – 8 weeks, Precipitation higher than 70mm at lag 1- 5 weeks and 20- 50mm at lag 10 – 20 weeks, humidity ranged from 65% to 80% at lag 10 – 18 weeks, visibility greater than 14 km have a positive impact on the occurrence of dengue incidence while, mean temperature higher than 280C at lag 6 – 25 weeks, maximum temperature at lag 4 – 6 weeks, precipitation higher than 65mm at lag 15 – 20 weeks, humidity less than 70% at lag 4 – 9 weeks, visibility less than 14km, high wind speed have a negative impact on the occurrence of dengue incidence. These findings can aid the targeting of vector control interventions and the planning for dengue vaccine implementation.
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Copyright (c) 2022 T. Talagala
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