Distributed Lag Nonlinear Modelling Approach to Identify Relationship between Climatic Factors and Dengue Incidence in Colombo District, Sri Lanka
Categorie(s):
Health
Author(s):
Thiyanga Talagala
Keyword(s):
Dengue, Distributed Lag Non Linear Modelling, Quasi - Poisson, Climate, Time Series
DOI:
10.2427/11522
Abstract :
Dengue fever and its 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. Quasi Poisson regression combined with distributed lag nonlinear
model was used to identify the association between dengue incidence and climate variables.
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 help to strengthen dengue prevention and control campaigns.