Abstract
The complex interaction between dengue cases, entomological and meteorological variables has posed challenges for decades. Validated and updated evidences are in need for enhancing surveillance and vector control of dengue program. This study explores the relationship between the variables in the long run and short-term dynamic in Melaka, Malaysia. A multivariate time series with the application of Johansen Cointegration Test and Vector Error Correction Model are carried out to validate the interaction among dengue cases, temperature, ovitrap index (OI) and sticky ovitrap index (SOI) data from 2020-2022. Cointegration vector validates existence of long-term relationship of which an inverse interaction between temperature and SOI with cases and a direct relationship of OI with cases. Short-term equilibrium displays a robust causality among variables. Interaction of case with case demonstrates positive coefficients at lags -3, -7, and -8. Interaction of SOI with case shows negative coefficients on SOI variable at lags -3 and -4 and positive coefficient on the case variable at lag -1. OI equation with OI variable shows unique interaction of negative coefficients on OI variable at lags -1, -3, and -4. However, it produced positive coefficient on OI variable at lag -9. Case equation reveals negative coefficient of temperature variable at lag -6. This study implies that the variables are linked in a long-term and stable relationship. In the context of public health, VECM is still a new methodology to capture such dynamicity and causality between the variables. In long term interaction, the study expressed the temporal pattern of dengue transmission, which is persistent, stable, and cyclical in nature. Failure to control epidemics resulting in the progression of succession of dengue cases in short term. The model predicts the utility and efficacy of sticky ovitraps acting as dual role; surveillance and control tool. Hence, there is a much broader scope for future directions in dengue control. The long-term equilibrium indicates the ovitrap index as a reliable predictor of dengue cases. Temperature is an overall excellent estimator of the meteorological parameter that has a direct impact on the development of dengue cases.