Malaysia is currently facing an outbreak of COVID-19. We aim to present the first study in Malaysia to report the reproduction numbers and develop a mathematical model forecasting COVID-19 transmission by including isolation, quarantine, and movement control measures. We utilized a susceptible, exposed, infectious, and recovered (SEIR) model by incorporating isolation, quarantine, and movement control order (MCO) taken in Malaysia. The simulations were fitted into the Malaysian COVID-19 active case numbers, allowing approximation of parameters consisting of probability of transmission per contact (β), average number of contacts per day per case (ζ), and proportion of close-contact traced per day (q). The effective reproduction number (Rt) was also determined through this model. Our model calibration estimated that (β), (ζ), and (q) were 0.052, 25 persons, and 0.23, respectively. The (Rt) was estimated to be 1.68. MCO measures reduce the peak number of active COVID-19 cases by 99.1% and reduce (ζ) from 25 (pre-MCO) to 7 (during MCO). The flattening of the epidemic curve was also observed with the implementation of these control measures. We conclude that isolation, quarantine, and MCO measures are essential to break the transmission of COVID-19 in Malaysia.
The rising pressure on both cleaner production and sustainable development have been the main driving force that pushes mankind to seek for alternative greener and sustainable feedstocks for chemical and energy production. The biomass 'waste-to-wealth' concept which convert low value biomass into value-added products which contain high economic potential, have attracted the attentions from both academicians and industry players. With a tropical climate, Malaysia has a rich agricultural sector and dense tropical rainforest, giving rise to abundance of biomass which most of them are underutilized. Hence, the biomass 'waste-to-wealth' conversion through various thermochemical conversion technologies and the prospective challenges towards commercialization in Malaysia are reviewed in this paper. In this paper, a critical review about the maturity status of the four most promising thermochemical conversion routes in Malaysia (i.e. gasification, pyrolysis, liquefaction and hydroprocessing) is given. The current development of thermochemical conversion technologies for biomass conversion in Malaysia is also reviewed and benchmarked against global progress. Besides, the core technical challenges in commercializing these green technologies are highlighted as well. Lastly, the future outlook for successful commercialization of these technologies in Malaysia is included.
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%).