Inferring the temporal dissemination patterns of Aedes indices and weather variables in Penang: a five-year study / Nazri Che Dom ... [et al.]

The aim of this study was to assess the temporal characteristics of Aedes indices (AI) using weather variables over a period of five years, specifically from 2011 to 2016. This study utilized an integrated epidemiological approach to investigate the temporal distribution of AI with the pattern of we...

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Main Authors: Che Dom, Nazri (Author), Ab Rahman, Mohd Hafiz (Author), Camalxaman, Siti Nazrina (Author)
Format: Book
Published: Faculty of Health Sciences, Universiti Teknologi MARA, 2019-06.
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042 |a dc 
100 1 0 |a Che Dom, Nazri  |e author 
700 1 0 |a Ab Rahman, Mohd Hafiz  |e author 
700 1 0 |a Camalxaman, Siti Nazrina  |e author 
245 0 0 |a Inferring the temporal dissemination patterns of Aedes indices and weather variables in Penang: a five-year study / Nazri Che Dom ... [et al.] 
260 |b Faculty of Health Sciences, Universiti Teknologi MARA,   |c 2019-06. 
500 |a https://ir.uitm.edu.my/id/eprint/54679/1/54679.pdf 
520 |a The aim of this study was to assess the temporal characteristics of Aedes indices (AI) using weather variables over a period of five years, specifically from 2011 to 2016. This study utilized an integrated epidemiological approach to investigate the temporal distribution of AI with the pattern of weather variables. A retrospective cross-sectional study was conducted to analyze information obtained from the meteorological department and the Ministry of Health, Malaysia. A Pearson correlation analysis was conducted by using five lag-terms of temperature, relative humidity and cumulative rainfall as an attempt to evaluate the relationship between AI and climatic variables as well as its exposure-response effects. In general, the trends of the AI in the study area vary from year to year and demonstrate an increase in all spot areas. Open and construction areas recorded the highest AI values. Results indicate that the overall distribution of AI was analogous to the distribution patterns of monthly temperature. In addition, the highest AI was observed at temperature exceeding 27○C. This study revealed no correlation between AI with weather variables. Nevertheless, the characteristics and pattern of both parameters have potential to be used as a baseline data for dengue vector control programme and can be used to evaluate its efficacy. 
546 |a en 
690 |a Diptera (Flies) 
690 |a Communicable diseases and public health 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/54679/ 
787 0 |n http://healthscopefsk.com/ 
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