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  1. Shafie AA, Yeo HY, Coudeville L, Steinberg L, Gill BS, Jahis R, et al.
    Pharmacoeconomics, 2017 May;35(5):575-589.
    PMID: 28205150 DOI: 10.1007/s40273-017-0487-3
    BACKGROUND: Dengue disease poses a great economic burden in Malaysia.

    METHODS: This study evaluated the cost effectiveness and impact of dengue vaccination in Malaysia from both provider and societal perspectives using a dynamic transmission mathematical model. The model incorporated sensitivity analyses, Malaysia-specific data, evidence from recent phase III studies and pooled efficacy and long-term safety data to refine the estimates from previous published studies. Unit costs were valued in $US, year 2013 values.

    RESULTS: Six vaccination programmes employing a three-dose schedule were identified as the most likely programmes to be implemented. In all programmes, vaccination produced positive benefits expressed as reductions in dengue cases, dengue-related deaths, life-years lost, disability-adjusted life-years and dengue treatment costs. Instead of incremental cost-effectiveness ratios (ICERs), we evaluated the cost effectiveness of the programmes by calculating the threshold prices for a highly cost-effective strategy [ICER <1 × gross domestic product (GDP) per capita] and a cost-effective strategy (ICER between 1 and 3 × GDP per capita). We found that vaccination may be cost effective up to a price of $US32.39 for programme 6 (highly cost effective up to $US14.15) and up to a price of $US100.59 for programme 1 (highly cost effective up to $US47.96) from the provider perspective. The cost-effectiveness analysis is sensitive to under-reporting, vaccine protection duration and model time horizon.

    CONCLUSION: Routine vaccination for a population aged 13 years with a catch-up cohort aged 14-30 years in targeted hotspot areas appears to be the best-value strategy among those investigated. Dengue vaccination is a potentially good investment if the purchaser can negotiate a price at or below the cost-effective threshold price.

  2. Dass SC, Kwok WM, Gibson GJ, Gill BS, Sundram BM, Singh S
    PLoS One, 2021;16(5):e0252136.
    PMID: 34043676 DOI: 10.1371/journal.pone.0252136
    The second wave of COVID-19 in Malaysia is largely attributed to a four-day mass gathering held in Sri Petaling from February 27, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting from March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model disease dynamics before and after intervention which is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implementation within a short time period. The models and methodology used provided important insights into the nature of local transmissions to decision makers in the Ministry of Health, Malaysia.
  3. Thiruchelvam L, Dass SC, Asirvadam VS, Daud H, Gill BS
    Sci Rep, 2021 Mar 12;11(1):5873.
    PMID: 33712664 DOI: 10.1038/s41598-021-84176-y
    The state of Selangor, in Malaysia consist of urban and peri-urban centres with good transportation system, and suitable temperature levels with high precipitations and humidity which make the state ideal for high number of dengue cases, annually. This study investigates if districts within the Selangor state do influence each other in determining pattern of dengue cases. Study compares two different models; the Autoregressive Integrated Moving Average (ARIMA) and Ensemble ARIMA models, using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) measurement to gauge their performance tools. ARIMA model is developed using the epidemiological data of dengue cases, whereas ensemble ARIMA incorporates the neighbouring regions' dengue models as the exogenous variable (X), into traditional ARIMA model. Ensemble ARIMA models have better model fit compared to the basic ARIMA models by incorporating neighbuoring effects of seven districts which made of state of Selangor. The AIC and BIC values of ensemble ARIMA models to be smaller compared to traditional ARIMA counterpart models. Thus, study concludes that pattern of dengue cases for a district is subject to spatial effects of its neighbouring districts and number of dengue cases in the surrounding areas.
  4. Md Zamri ASS, Singh S, Ghazali SM, Herng LC, Dass SC, Aris T, et al.
    Epidemiol Health, 2021 Sep 23.
    PMID: 34607399 DOI: 10.4178/epih.e2021073
    Objectives: Since March 2020, several phases of the movement control measures were instituted in Malaysia to break the COVID-19 chain of transmission. In this study, we developed Susceptible-Exposed-Infected-Recovered (SEIR) models to examine the effects of the various movement control phases on the disease transmissibility and case trends during the third COVID-19 wave in Malaysia.

    Methods: Three SEIR models were developed using the R programming software ODIN interface based on COVID-19 case data from 1 September 2020 to 29 March 2021. The models were validated and subsequently used to provide forecasts of daily cases from 14 October 2020 to 29 March 2021 based on three movement control phases.

    Results: We found that the R values had reduced by 59.1% from an initial high of 2.2 during the Nationwide Recovery Movement Control Order (RMCO) to 0.9 during the Movement Control Order (MCO) and Conditional MCO (CMCO) phases. In addition, the observed cumulative and daily highest cases were much lower compared to the forecast cumulative and daily highest cases at 64.4% to 98.9% and 68.8% to 99.8%, respectively.

    Conclusion: We conclude that the movement control measures were able to progressively reduce the R values during the COVID-19 pandemic. In addition, more stringent movement control measures such as the MCO and CMCO were effective in reducing the R values and case numbers further during the third wave of COVID-19 outbreak in Malaysia due to their higher stringency levels compared to the Nationwide RMCO.

  5. Tan CV, Singh S, Lai CH, Zamri ASSM, Dass SC, Aris TB, et al.
    PMID: 35162523 DOI: 10.3390/ijerph19031504
    With many countries experiencing a resurgence in COVID-19 cases, it is important to forecast disease trends to enable effective planning and implementation of control measures. This study aims to develop Seasonal Autoregressive Integrated Moving Average (SARIMA) models using 593 data points and smoothened case and covariate time-series data to generate a 28-day forecast of COVID-19 case trends during the third wave in Malaysia. SARIMA models were developed using COVID-19 case data sourced from the Ministry of Health Malaysia's official website. Model training and validation was conducted from 22 January 2020 to 5 September 2021 using daily COVID-19 case data. The SARIMA model with the lowest root mean square error (RMSE), mean absolute percentage error (MAE) and Bayesian information criterion (BIC) was selected to generate forecasts from 6 September to 3 October 2021. The best SARIMA model with a RMSE = 73.374, MAE = 39.716 and BIC = 8.656 showed a downward trend of COVID-19 cases during the forecast period, wherein the observed daily cases were within the forecast range. The majority (89%) of the difference between the forecasted and observed values was well within a deviation range of 25%. Based on this work, we conclude that SARIMA models developed in this paper using 593 data points and smoothened data and sensitive covariates can generate accurate forecast of COVID-19 case trends.
  6. Lim KH, Lim HL, Ghazali SM, Kee CC, Teh CH, Gill BS, et al.
    Tob Induc Dis, 2020;18:53.
    PMID: 32565765 DOI: 10.18332/tid/122586
    INTRODUCTION: We investigated the prevalence of children's exposure to secondhand smoke (SHS) in the car of their parents/guardians and the associated factors.

    METHODS: A self-administered validated questionnaire was used to obtain data from the nationally representative samples of school-going adolescents aged 11-19 years in Malaysia. Prevalence rates were computed and chi-squared tests and multiple logistic regression were conducted.

    RESULTS: Of the participants, 23.3% reported exposure to SHS at least once in the car of their parents/guardians during the last 7 days before the survey. The prevalence and likelihood of SHS exposure were significantly higher in Malays, descendants of natives of Sabah and Sarawak, schools in rural areas, females, and current smokers. However, age group and knowledge on the harmful effects of SHS were not significant after adjusting for confounding effects.

    CONCLUSIONS: A substantial proportion of school-going adolescents were exposed to secondhand smoke in the car of their parents/guardians. This highlights the need for effective tobacco control measures to include health promotion and smoke-free car regulations to be introduced to prevent severe health hazards and to reduce smoking initiation among non-smoking adolescents.

  7. Williams CR, Gill BS, Mincham G, Mohd Zaki AH, Abdullah N, Mahiyuddin WR, et al.
    Epidemiol Infect, 2015 Oct;143(13):2856-64.
    PMID: 25591942 DOI: 10.1017/S095026881400380X
    We aimed to reparameterize and validate an existing dengue model, comprising an entomological component (CIMSiM) and a disease component (DENSiM) for application in Malaysia. With the model we aimed to measure the effect of importation rate on dengue incidence, and to determine the potential impact of moderate climate change (a 1 °C temperature increase) on dengue activity. Dengue models (comprising CIMSiM and DENSiM) were reparameterized for a simulated Malaysian village of 10 000 people, and validated against monthly dengue case data from the district of Petaling Jaya in the state of Selangor. Simulations were also performed for 2008-2012 for variable virus importation rates (ranging from 1 to 25 per week) and dengue incidence determined. Dengue incidence in the period 2010-2012 was modelled, twice, with observed daily weather and with a 1 °C increase, the latter to simulate moderate climate change. Strong concordance between simulated and observed monthly dengue cases was observed (up to r = 0·72). There was a linear relationship between importation and incidence. However, a doubling of dengue importation did not equate to a doubling of dengue activity. The largest individual dengue outbreak was observed with the lowest dengue importation rate. Moderate climate change resulted in an overall decrease in dengue activity over a 3-year period, linked to high human seroprevalence early on in the simulation. Our results suggest that moderate reductions in importation with control programmes may not reduce the frequency of large outbreaks. Moderate increases in temperature do not necessarily lead to greater dengue incidence.
  8. Law KB, Peariasamy KM, Gill BS, Singh S, Sundram BM, Rajendran K, et al.
    Sci Rep, 2020 12 10;10(1):21721.
    PMID: 33303925 DOI: 10.1038/s41598-020-78739-8
    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, [Formula: see text] 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.
  9. Dass S, Ngui R, Gill BS, Chan YF, Wan Sulaiman WY, Lim YAL, et al.
    Trans R Soc Trop Med Hyg, 2021 08 02;115(8):922-931.
    PMID: 33783526 DOI: 10.1093/trstmh/trab053
    BACKGROUND: We studied the spatiotemporal spread of a chikungunya virus (CHIKV) outbreak in Sarawak state, Malaysia, during 2009-2010.

    METHODS: The residential addresses of 3054 notified CHIKV cases in 2009-2010 were georeferenced onto a base map of Sarawak with spatial data of rivers and roads using R software. The spatiotemporal spread was determined and clusters were detected using the space-time scan statistic with SaTScan.

    RESULTS: Overall CHIKV incidence was 127 per 100 000 population (range, 0-1125 within districts). The average speed of spread was 70.1 km/wk, with a peak of 228 cases/wk and the basic reproduction number (R0) was 3.1. The highest age-specific incidence rate was 228 per 100 000 in adults aged 50-54 y. Significantly more cases (79.4%) lived in rural areas compared with the general population (46.2%, p<0.0001). Five CHIKV clusters were detected. Likely spread was mostly by road, but a fifth of rural cases were spread by river travel.

    CONCLUSIONS: CHIKV initially spread quickly in rural areas mainly via roads, with lesser involvement of urban areas. Delayed spread occurred via river networks to more isolated areas in the rural interior. Understanding the patterns and timings of arboviral outbreak spread may allow targeted vector control measures at key transport hubs or in large transport vehicles.

  10. Ariff MI, Yahya A, Zaki R, Sarimin R, Mohamed Ghazali IM, Gill BS, et al.
    PLoS One, 2017;12(5):e0178137.
    PMID: 28562626 DOI: 10.1371/journal.pone.0178137
    Clinical Practice Guideline (CPG) provides evidence-based guidance for the management of Dengue Infection in adult patients. A cross sectional study was conducted to evaluate awareness and utilization of CPG among doctors in public or private hospitals and clinics in Malaysia. Doctors practicing only at hospital Medical and Emergency Departments were included, while private specialist clinics were excluded in this study. A multistage proportionate random sampling according to region (Central, Northern, Southern, Eastern, Sabah and Sarawak) was performed to select study participants. The overall response rate was 74% (84% for public hospitals, 82% for private hospitals, 70% for public clinics, and 64% for private clinics). The CPG Awareness and Utilization Feedback Form were used to determine the percentage in the study. The total numbers of respondent were 634 with response rate of 74%. The mean lengths of service of the respondent were 13.98 (11.55).A higher percentages of doctors from public facilities (99%) were aware of the CPG compared to those in private facilities (84%). The percentage of doctors utilising the CPG were also higher (98%) in public facilities compared to private facilities (86%). The percentage of Medical Officer in private facilities that utilizing the CPG were 84% compares to Medical Officer in public facilities 98%. The high percentage of doctors using the CPG in both public (97%) and private (94%) hospitals were also observed. However, only 69% of doctors in private clinics utilised the CPG compared to doctors in public clinics (98%). Doctors in both public and private facilities were aware of the dengue CPG. However, most doctors in private clinic were less likely to utilise the CPG. Therefore, there is a need to increase the level of CPG utilisation especially in private clinics.
    Study site: primary care and hospital from Medical and Emergency Department, public and private health facilities in Malaysia
  11. Herng LC, Singh S, Sundram BM, Zamri ASSM, Vei TC, Aris T, et al.
    Sci Rep, 2022 02 09;12(1):2197.
    PMID: 35140319 DOI: 10.1038/s41598-022-06341-1
    This paper aims to develop an automated web application to generate validated daily effective reproduction numbers (Rt) which can be used to examine the effects of super-spreading events due to mass gatherings and the effectiveness of the various Movement Control Order (MCO) stringency levels on the outbreak progression of COVID-19 in Malaysia. The effective reproduction number, Rt, was estimated by adopting and modifying an Rt estimation algorithm using a validated distribution mean of 3.96 and standard deviation of 4.75 with a seven-day sliding window. The Rt values generated were validated using thea moving window SEIR model with a negative binomial likelihood fitted using methods from the Bayesian inferential framework. A Pearson's correlation between the Rt values estimated by the algorithm and the SEIR model was r = 0.70, p 
  12. Gill BS, Jayaraj VJ, Singh S, Mohd Ghazali S, Cheong YL, Md Iderus NH, et al.
    Int J Environ Res Public Health, 2020 Jul 30;17(15).
    PMID: 32751669 DOI: 10.3390/ijerph17155509
    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.
  13. Bowman LR, Tejeda GS, Coelho GE, Sulaiman LH, Gill BS, McCall PJ, et al.
    PLoS One, 2016;11(6):e0157971.
    PMID: 27348752 DOI: 10.1371/journal.pone.0157971
    BACKGROUND: Worldwide, dengue is an unrelenting economic and health burden. Dengue outbreaks have become increasingly common, which place great strain on health infrastructure and services. Early warning models could allow health systems and vector control programmes to respond more cost-effectively and efficiently.

    METHODOLOGY/PRINCIPAL FINDINGS: The Shewhart method and Endemic Channel were used to identify alarm variables that may predict dengue outbreaks. Five country datasets were compiled by epidemiological week over the years 2007-2013. These data were split between the years 2007-2011 (historic period) and 2012-2013 (evaluation period). Associations between alarm/ outbreak variables were analysed using logistic regression during the historic period while alarm and outbreak signals were captured during the evaluation period. These signals were combined to form alarm/ outbreak periods, where 2 signals were equal to 1 period. Alarm periods were quantified and used to predict subsequent outbreak periods. Across Mexico and Dominican Republic, an increase in probable cases predicted outbreaks of hospitalised cases with sensitivities and positive predictive values (PPV) of 93%/ 83% and 97%/ 86% respectively, at a lag of 1-12 weeks. An increase in mean temperature ably predicted outbreaks of hospitalised cases in Mexico and Brazil, with sensitivities and PPVs of 79%/ 73% and 81%/ 46% respectively, also at a lag of 1-12 weeks. Mean age was predictive of hospitalised cases at sensitivities and PPVs of 72%/ 74% and 96%/ 45% in Mexico and Malaysia respectively, at a lag of 4-16 weeks.

    CONCLUSIONS/SIGNIFICANCE: An increase in probable cases was predictive of outbreaks, while meteorological variables, particularly mean temperature, demonstrated predictive potential in some countries, but not all. While it is difficult to define uniform variables applicable in every country context, the use of probable cases and meteorological variables in tailored early warning systems could be used to highlight the occurrence of dengue outbreaks or indicate increased risk of dengue transmission.

  14. Labadin J, Hong BH, Tiong WK, Gill BS, Perera D, Rigit ARH, et al.
    Multimed Tools Appl, 2023;82(11):17415-17436.
    PMID: 36404933 DOI: 10.1007/s11042-022-14120-3
    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%).
  15. Lim MC, Singh S, Lai CH, Gill BS, Kamarudin MK, Md Zamri ASS, et al.
    Epidemiol Health, 2023;45:e2023093.
    PMID: 37905314 DOI: 10.4178/epih.e2023093
    OBJECTIVES: This study aimed to develop susceptible-exposed-infectious-recovered-vaccinated (SEIRV) models to examine the effects of vaccination on coronavirus disease 2019 (COVID-19) case trends in Malaysia during Phase 3 of the National COVID-19 Immunization Program amidst the Delta outbreak.

    METHODS: SEIRV models were developed and validated using COVID-19 case and vaccination data from the Ministry of Health, Malaysia, from June 21, 2021 to July 21, 2021 to generate forecasts of COVID-19 cases from July 22, 2021 to December 31, 2021. Three scenarios were examined to measure the effects of vaccination on COVID-19 case trends. Scenarios 1 and 2 represented the trends taking into account the earliest and latest possible times of achieving full vaccination for 80% of the adult population by October 31, 2021 and December 31, 2021, respectively. Scenario 3 described a scenario without vaccination for comparison.

    RESULTS: In scenario 1, forecasted cases peaked on August 28, 2021, which was close to the peak of observed cases on August 26, 2021. The observed peak was 20.27% higher than in scenario 1 and 10.37% lower than in scenario 2. The cumulative observed cases from July 22, 2021 to December 31, 2021 were 13.29% higher than in scenario 1 and 55.19% lower than in scenario 2. The daily COVID-19 case trends closely mirrored the forecast of COVID-19 cases in scenario 1 (best-case scenario).

    CONCLUSIONS: Our study demonstrated that COVID-19 vaccination reduced COVID-19 case trends during the Delta outbreak. The compartmental models developed assisted in the management and control of the COVID-19 pandemic in Malaysia.

  16. Md Iderus NH, Singh SSL, Ghazali SM, Zulkifli AA, Ghazali NAM, Lim MC, et al.
    Front Public Health, 2023;11:1213514.
    PMID: 37693699 DOI: 10.3389/fpubh.2023.1213514
    BACKGROUND: Globally, 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.

    METHODS: This 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.

    RESULTS: Dengue 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.

    CONCLUSION: There 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.

  17. Md Nadzri MN, Md Zamri ASS, Singh S, Sumarni MG, Lai CH, Tan CV, et al.
    Front Public Health, 2024;12:1289622.
    PMID: 38544725 DOI: 10.3389/fpubh.2024.1289622
    INTRODUCTION: Since the COVID-19 pandemic began, it has spread rapidly across the world and has resulted in recurrent outbreaks. This study aims to describe the COVID-19 epidemiology in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate for each outbreak from the beginning of the pandemic in 2020 till endemicity of COVID-19 in 2022 in Malaysia.

    METHODS: Data was sourced from the GitHub repository and the Ministry of Health's official COVID-19 website. The study period was from the beginning of the outbreak in Malaysia, which began during Epidemiological Week (Ep Wk) 4 in 2020, to the last Ep Wk 18 in 2022. Data were aggregated by Ep Wk and analyzed in terms of COVID-19 cases, deaths, ICU admissions, ventilator requirements, testing, incidence rate, death rate, case fatality rate (CFR) and test positivity rate by years (2020 and 2022) and for each outbreak of COVID-19.

    RESULTS: A total of 4,456,736 cases, 35,579 deaths and 58,906,954 COVID-19 tests were reported for the period from 2020 to 2022. The COVID-19 incidence rate, death rate, CFR and test positivity rate were reported at 1.085 and 0.009 per 1,000 populations, 0.80 and 7.57%, respectively, for the period from 2020 to 2022. Higher cases, deaths, testing, incidence/death rate, CFR and test positivity rates were reported in 2021 and during the Delta outbreak. This is evident by the highest number of COVID-19 cases, ICU admissions, ventilatory requirements and deaths observed during the Delta outbreak.

    CONCLUSION: The Delta outbreak was the most severe compared to other outbreaks in Malaysia's study period. In addition, this study provides evidence that outbreaks of COVID-19, which are caused by highly virulent and transmissible variants, tend to be more severe and devastating if these outbreaks are not controlled early on. Therefore, close monitoring of key epidemiological indicators, as reported in this study, is essential in the control and management of future COVID-19 outbreaks in Malaysia.

  18. Nazni WA, Hoffmann AA, NoorAfizah A, Cheong YL, Mancini MV, Golding N, et al.
    Curr Biol, 2019 Dec 16;29(24):4241-4248.e5.
    PMID: 31761702 DOI: 10.1016/j.cub.2019.11.007
    Dengue has enormous health impacts globally. A novel approach to decrease dengue incidence involves the introduction of Wolbachia endosymbionts that block dengue virus transmission into populations of the primary vector mosquito, Aedes aegypti. The wMel Wolbachia strain has previously been trialed in open releases of Ae. aegypti; however, the wAlbB strain has been shown to maintain higher density than wMel at high larval rearing temperatures. Releases of Ae. aegypti mosquitoes carrying wAlbB were carried out in 6 diverse sites in greater Kuala Lumpur, Malaysia, with high endemic dengue transmission. The strain was successfully established and maintained at very high population frequency at some sites or persisted with additional releases following fluctuations at other sites. Based on passive case monitoring, reduced human dengue incidence was observed in the release sites when compared to control sites. The wAlbB strain of Wolbachia provides a promising option as a tool for dengue control, particularly in very hot climates.
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