Estimation of public compliance with COVID-19 prevention standard operating procedures through a mathematical model

Despite the enforcement of control plan and preventive measures, the transmission of COVID-19 is still ongoing and yet to be contained successfully. Hence, this study aimed to determine the level of compliance of the public with the standard operating procedures for COVID-19 prevention in Malaysia. A compartmental model with new formulations of timely dependent epidemiological parameter for COVID-19 outbreaks was developed. The model, consisting of ordinary differential equations, was solved by the 4th order Runge–Kutta method. The model representation is in the form of graphical user interface (GUI) built in MATLAB. The estimation of the level of compliance of the population with the control measures was done by fitting the model curve to the actual data in the GUI. The result shows that the current compliance level of the public to the control measures is at an unsatisfactory level that leads to repeated lockdown. The compliance level estimation is important to policymakers and health officials as they can infer the effectiveness of intervention strategies. Additionally, this study revealed how individual responsibility to adherence the control measures will affects the number of cases. Further action to increase public compliance to a satisfactory level is required to halt the pandemic successfully

Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I) and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βt and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4.7% each day with a decreased capacity of 40%. For 7-day and 14-day projections, the modified SIR model accurately predicted I total, I and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19

Development and user testing study of MozzHub : a bipartite network-based dengue hotspot detector

Traditionally, dengue is controlled by fogging, and the prime location for the control measure is at the patient’s residence. However, when Malaysia was hit by the first wave of the Coronavirus disease (COVID-19), and the government-imposed movement control order, dengue cases have decreased by more than 30% from the previous year. This implies that residential areas may not be the prime locations for dengue-infected mosquitoes. The existing early warning system was focused on temporal prediction wherein the lack of consideration for spatial component at the microlevel and human mobility were not considered. Thus, we developed MozzHub, which is a web-based application system based on the bipartite network-based dengue model that is focused on identifying the source of dengue infection at a small spatial level (400 m) by integrating human mobility and environmental predictors. The model was earlier developed and validated; therefore, this study presents the design and implementation of the MozzHub system and the results of a preliminary pilot test and user acceptance of MozzHub in six district health offices in Malaysia. It was found that the MozzHub system is well received by the sample of end-users as it was demonstrated as a useful (77.4%), easy-to-operate system (80.6%), and has achieved adequate client satisfaction for its use (74.2%)

The effects of the COVID-19 pandemic on dengue cases in Malaysia

BackgroundGlobally, the COVID-19 pandemic has affected the transmission dynamics and distribution of dengue. Therefore, this study aims to describe the impact of the COVID-19 pandemic on the geographic and demographic distribution of dengue incidence in Malaysia.MethodsThis study analyzed dengue cases from January 2014 to December 2021 and COVID-19 confirmed cases from January 2020 to December 2021 which was divided into the pre (2014 to 2019) and during COVID-19 pandemic (2020 to 2021) phases. The average annual dengue case incidence for geographical and demographic subgroups were calculated and compared between the pre and during the COVID-19 pandemic phases. In addition, Spearman rank correlation was performed to determine the correlation between weekly dengue and COVID-19 cases during the COVID-19 pandemic phase.ResultsDengue trends in Malaysia showed a 4-year cyclical trend with dengue case incidence peaking in 2015 and 2019 and subsequently decreasing in the following years. Reductions of 44.0% in average dengue cases during the COVID-19 pandemic compared to the pre-pandemic phase was observed at the national level. Higher dengue cases were reported among males, individuals aged 20–34 years, and Malaysians across both phases. Weekly dengue cases were significantly correlated (ρ = −0.901) with COVID-19 cases during the COVID-19 pandemic.ConclusionThere was a reduction in dengue incidence during the COVID-19 pandemic compared to the pre-pandemic phase. Significant reductions were observed across all demographic groups except for the older population (>75 years) across the two phases

Spatial distribution and long-term persistence of Wolbachia-infected Aedes aegypti in the Mentari Court, Malaysia

Dengue is endemic in Malaysia, and vector control strategies are vital to reduce dengue transmission. The Wolbachia strain wAlbB carried by both sexes of Ae. aegypti was released in Mentari Court, a high-rise residential site, in October 2017 and stopped after 20 weeks. Wolbachia frequencies are still being monitored at multiple traps across this site, providing an opportunity to examine the spatiotemporal distribution of Wolbachia and mosquito density with respect to year, residential block, and floor, using spatial interpolation in ArcGIS, GLMs, and contingency analyses. In just 12 weeks, Wolbachia-infected mosquitoes were established right across the Mentari Court site with an overall infection frequency of >90%. To date, the Wolbachia frequency of Ae. aegypti has remained high in all areas across the site despite releases finishing four years ago. Nevertheless, the Wolbachia invaded more rapidly in some residential blocks than others, and also showed a relatively higher frequency on the eighth floor. The Ae. aegypti index tended to differ somewhat between residential blocks, whilst the Ae. albopictus index was relatively higher at the top and bottom floors of buildings. In Mentari Court, only a short release period was required to infiltrate Wolbachia completely and stably into the natural population. The results inform future releases in comparable sites in a dengue control programme