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

Effectiveness of the movement control measures during the third wave of COVID-19 in Malaysia

OBJECTIVES: Starting in March 2020, movement control measures were instituted across several phases in Malaysia to break the chain of transmission of coronavirus disease 2019 (COVID-19). In this study, we developed a susceptible-exposed-infected-recovered (SEIR) model to examine the effects of the various phases of movement control measures on disease transmissibility and the trend of cases during the third wave of the COVID-19 pandemic in Malaysia. METHODS: Three SEIR models were developed using the R programming software ODIN interface based on COVID-19 case data from September 1, 2020, to March 29, 2021. The models were validated and subsequently used to provide forecasts of daily cases from October 14, 2020, to March 29, 2021, based on 3 phases of movement control measures. RESULTS: We found that the reproduction rate (R-value) of COVID-19 decreased 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 numbers of cases were much lower than the forecasted cumulative and daily highest numbers of cases (by 64.4-98.9% and 68.8-99.8%, respectively). CONCLUSIONS: The movement control measures progressively reduced the R-value during the COVID-19 pandemic. In addition, more stringent movement control measures such as the MCO and CMCO were effective for further lowering the R-value and case numbers during the third wave of the COVID-19 pandemic in Malaysia due to their higher stringency than the nationwide RMCO

Gender Differences in Factors Associated with the Total Delay in Treatment of Pulmonary Tuberculosis Patients: A Cross-Sectional Study in Selangor, Malaysia

Background: Gender plays a significant role in health-care-seeking behavior for many diseases. Delays in seeking treatment, diagnosis, and treatment for pulmonary tuberculosis (pTB) may increase the risk of transmission in the community and lead to poorer treatment outcomes and mortality. This study explores the differences in factors associated with the total delay in treatment of male and female pTB patients in Selangor, Malaysia. Methods: A cross-sectional study was conducted from January 2017 to December 2017. Newly diagnosed pTB patients (≥18 years) were recruited from selected government health clinics and hospitals in Selangor during the specified study period. An interviewer-administered questionnaire was used to collect information on sociodemographic characteristics, lifestyle, knowledge about pTB, stigma, distance to the nearest health facility, and chronology of pTB symptom onset, diagnosis, and treatment. The total delay was measured as the length of time between the onset of pTB symptoms to treatment initiation. Factors significantly associated with a longer total delay among men and women were identified using binary logistic regression. Results: A total of 732 patients (61.5% men, 38.5% women) were enrolled in the study. The median total delay was 60 days. Men who have weight loss as a symptom (AOR: 1.63, 95%CI: 1.10–2.41) and are employed (1.89, 1.15–3.11) were more likely to have a longer total delay, while those who know others who have had pTB (0.64, 0.43–0.96) were less likely to have a longer total delay. On the other hand, among women, having a stigma towards TB (0.52, 0.32–0.84) and obtaining a pTB diagnosis at the first medical consultation (0.48, 0.29–0.79) were associated with a shorter total delay. Conclusion: Factors associated with the total delay in pTB treatment were different for male and female pTB patients. Increasing awareness of pTB symptoms and the importance of seeking early medical consultation and a prompt diagnosis among the general public may reduce total delay in pTB treatment

Forecasting COVID-19 Case Trends Using SARIMA Models during the Third Wave of COVID-19 in Malaysia

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

The effects of super spreading events and movement control measures on the COVID-19 pandemic in Malaysia

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 < 0.001 and r = 0.81, p < 0.001 during the validation period The Rt increased to reach the highest values at 3.40 (95% CI 1.47, 6.14) and 1.72 (95% CI 1.54, 1.90) due to the Sri Petaling and Sabah electoral process during the second and third waves of COVID-19 respectively. The MCOs was able to reduce the Rt values by 63.2 to 77.1% and 37.0 to 47.0% during the second and third waves of COVID-19, respectively. Mass gathering events were one of the important drivers of the COVID-19 outbreak in Malaysia. However, COVID-19 transmission can be fuelled by noncompliance to Standard Operating Procedure, population mobility, ventilation and environmental factors

Factors associated with occupational asthma among food industry workers: A systematic review.

IntroductionOccupational asthma (OA) is a type of Work-Related Asthma characterised by variable airflow limitation and/or inflammation due to causes and conditions attributable to a particular occupational environment, and not to stimuli encountered outside the workplace. There is an increasing need to extend the depth of knowledge of OA to better manage this condition, especially among food industry workers who are affected by it.ObjectiveThis systematic review aimed to determine the factors associated with occupational asthma among food industry workers by electronically collecting articles from two databases (Medline and Scopus).MethodsThis systematic review was prepared in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta Analyses) updated guideline. Two independent reviewers screened the titles and abstracts of the collected data, which were then stored in Endnote20 based on the inclusion and exclusion criteria. The included articles have been critically appraised to assess the quality of the studies using the Mixed Methods Appraisal Tool (MMAT).ResultThe search yielded 82 articles from Medline and 85 from SCOPUS, resulting in 167 unique hits. Only 22 articles have been included in the full-text assessment following a rigorous selection screening. Of the 22 articles identified, five were included in the final review. Several factors were found to have contributed to occupational asthma among food industry workers. They were classified into two categories: (1) work environment-related factors; and (2) individual factors.ConclusionSeveral work environment and individual-related factors were found to be associated with OA among food industry workers. A better understanding of the development of the disease and its potential risk factors is needed because it can affect worker's quality of life. Pre-employment and periodic medical surveillance should be conducted to assess and detect any possible risk of developing occupational asthma among workers

COVID-19 in Malaysia:Descriptive Epidemiologic Characteristics of the First Wave

This study aimed to describe the characteristics of COVID-19 cases and close contacts during the first wave of COVID-19 in Malaysia (23 January 2020 to 26 February 2020), and to analyse the reasons why the outbreak did not continue to spread and lessons that can be learnt from this experience. Characteristics of the cases and close contacts, spatial spread, epidemiological link, and timeline of the cases were examined. An extended SEIR model was developed using several parameters such as the average number of contacts per day per case, the proportion of close contact traced per day and the mean daily rate at which infectious cases are isolated to determine the basic reproduction number (R0) and trajectory of cases. During the first wave, a total of 22 cases with 368 close contacts were traced, identified, tested, quarantine and isolated. Due to the effective and robust outbreak control measures put in place such as early case detection, active screening, extensive contact tracing, testing and prompt isolation/quarantine, the outbreak was successfully contained and controlled. The SEIR model estimated the R0 at 0.9 which further supports the decreasing disease dynamics and early termination of the outbreak. As a result, there was a 11-day gap (free of cases) between the first and second wave which indicates that the first wave was not linked to the second wave

Seroprevalence of diphtheria toxoid IgG antibodies in the Malaysian population

Abstract Background Despite high childhood immunization coverage, sporadic cases of diphtheria have been reported in Malaysia in recent years. This study aims to evaluate the seroprevalence of diphtheria among the Malaysian population. Methods A total of 3317 respondents age 2 years old to 60 years old were recruited in this study from August to November 2017. Enzyme-linked immunosorbent assay (ELISA) was used to measure the level of IgG antibody against the toxoid of C. diphtheriae in the blood samples of respondents. We classified respondent antibody levels based on WHO definition, as protective (≥0.1 IU/mL) and susceptible (< 0.1 IU/mL) to C. diphtheriae infection. Results Among the 3317 respondents, 57% were susceptible (38.1% of children and 65.4% of adults) and 43% (61.9% of children and 34.6% of adults) had protective antibody levels against diphtheria. The mean antibody level peaked among individuals aged 1–2 years old (0.59 IU/mL) and 6–7 years old (0.64 IU/mL) but generally decreased with age, falling below 0.1 IU/mL at around 4–6 years old and after age 20 years old. There was a significant association between age [Children: χ2 = 43.22(df = 2),p < 0.001)], gender [Adults: χ2 = 5.58(df = 1),p = 0.018] and ethnicity [Adults: χ2 = 21.49(df = 5),p = 0.001] with diphtheria toxoid IgG antibody level. Conclusions About 57% of the Malaysian population have inadequate immunity against diphtheria infection. This is apparently due to waning immunity following childhood vaccination without repeated booster vaccination in adults. Children at age 5–6 years old are particularly vulnerable to diphtheria infection. The booster vaccination dose normally given at 7 years should be given earlier, and an additional booster dose is recommended for high-risk adults

Forecasting the effects of vaccination on the COVID-19 pandemic in Malaysia using SEIRV compartmental models

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