Developing time-based model for the prediction of breeding activities of dengue vectors using early life cycle variables and epidemiological information in Northern Malaysia
- Author:
Nur Aida, H.
- Publication Type:Original Article
- From:Tropical Biomedicine
2017;34(3):691-707
- CountryMalaysia
- Language:English
-
Abstract:
Autoregressive integrated moving average (ARIMA) was applied to make realtime
predictions on the Aedes egg populations in three selected dengue hotspots of
Penang, Malaysia. The weekly ovitrap collection was carried out to determine the
abundance of Aedes eggs in field population in some selected areas. The ARIMA models
were able to estimate actual egg abundance using two criteria. The first criteria is
determine the reliability of statistics and the second is to measure the accuracy of
forecasting ability of the model equation. The parsimonious model with a lowest order
of AR or MA and RMSE value of the forecast for each data set was considered the best.
ARIMA (1,0,0), ARIMA (2,0,0) and ARIMA (0,1,1) models were judged to be the best fit
for the suburban, urban squatter and urban area data sets respectively. The models were
able to forecast the number of eggs within a range of one to eleven weeks. The developed
models were able to estimate the egg abundance adequately to permit their use in Aedes
control programme in Penang Island. Thus, it can be a useful tool for health officials to
improve the management of mosquito control and alert the public to reduce the possibility
of dengue outbreaks.
