Factors determining dengue outbreak in Malaysia

• Published in: PloS one Vol. 13; no. 2; p. e0193326
• Main Authors: Ahmad, Rohani, Suzilah, Ismail, Wan Najdah, Wan Mohamad Ali, Topek, Omar, Mustafakamal, Ibrahim, Lee, Han Lim
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 23.02.2018; Public Library of Science (PLoS)
• Subjects: Aedes aegypti; Air pollution; Air temperature; Analysis; Aquatic insects; Autoregressive models; Biology and Life Sciences; Data collection; Dengue; Dengue fever; Disease; Disease transmission; Distribution; Early warning systems; Earth Sciences; Environmental factors; Environmental indicators; Epidemiology; Intervention; Larvae; Maximum temperatures; Medical research; Medicine and Health Sciences; Model accuracy; Mosquitoes; Outbreaks; Outdoor air quality; People and Places; Pest outbreaks; Pollution; Pollution abatement; Pollution index; Polymerase chain reaction; Population; Population number; Predictions; Prevalence studies (Epidemiology); Rain; Rainfall; Relative humidity; Studies; Temperature; Vector-borne diseases; Viral diseases; Viruses; Malaysia; Kuala Lumpur Malaysia; Puerto Rico; Southeast Asia; Selangor Malaysia; United States > US
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0193326

A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.