Predicting Dengue Outbreak Risk Using Epidemiological Parameters Related to the Knowledge and Awareness of Community in Selangor on Dengue During Covid-19 Pandemic

Abstract

Introduction: Dengue is widely distributed mosquito-borne viral disease around the world. The objectives of this study are to assess the level of knowledge and awareness on dengue compared to Covid-19 during its pandemic season and to predict dengue outbreak risk at Selangor in 2022 using epidemiological parameters. Materials and methods: This was a cross-sectional study conducted on 388 respondents using validated questionnaire and accessible data in Selangor, Malaysia using epidemiological factors during Covid-19 pandemic season. The ARIMA modelling was designed to predict dengue cases in Selangor during 2022. Data analysis of demographic data, level of knowledge and awareness of respondents was analyzed by using descriptive tests. The Spearman Rank-Correlation test was used to determine the relationship between weather predictors and dengue cases. Results: The findings revealed that most of the community had moderate knowledge (53.35%) and good awareness (44.07%) on dengue during Covid-19 pandemic period. Monthly mean temperature (°C) showed a moderate positive correlation while a weak positive correlation observed for mean relative humidity (%). In addition, monthly mean rainfall (mm) illustrates a weak negative correlation with dengue. According to the best fit ARIMA (3,1,0) model chosen in this study, predicted dengue cases in Selangor in May, Jun, July, August, September and October 2022 showed a decreasing trend which were 354 followed by 281, 261, 200, 165 and 87 dengue cases respectively. Conclusion: The knowledge and awareness of community and meteorological data revealed to play an important role in dengue outbreak risk.