Description of the COVID-19 epidemiology in Malaysia.

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.

Burden of pertussis among young infants in Malaysia: A hospital-based surveillance study.

BACKGROUND: The case fatality rate and the risk of complications due to pertussis is very high in infants. Asia has the second highest childhood pertussis burden. The study aimed to assess the prevalence, clinical complications, and mortality rates of pertussis disease requiring hospitalization among young infants in Malaysia. METHODS: The study was a one-year, hospital-based, multi-site surveillance of infants less than six months of age with symptoms consistent with pertussis and a cross-sectional analysis of their mothers for recent pertussis infection. Information was obtained from medical records and interviews with the parents. Pertussis diagnosis was confirmed for all infants through serum anti-PT titration test or PCR test. RESULTS: 441 possible cases of pertussis were included in this study. Of these, 12.7 % had laboratory confirmation of pertussis. Infants with confirmed pertussis had significantly higher rates of cyanosis (37.5 % vs 8.6 %; p < 0.0001) and apnea (12.5 % vs 3.9 %; p = 0.027) than test-negative infants. Most infants from both groups were in recovery/recovered at discharge. Those with confirmed pertussis had higher case fatality rate than test-negative cases (5.4 % vs 1.0 %; p = 0.094), but the difference did not reach significance. The majority of confirmed pertussis cases (89.3 %) occurred in infants too young to be fully vaccinated or under-vaccinated for their age. Both test-negative and confirmed pertussis resulted in work-day losses and incurred costs for both parents. CONCLUSIONS: A high pertussis disease burden persists in infants less than six months of age, especially among those un- and under-vaccinated. Maternal and complete, on-time infant vaccination is important to reduce disease burden.

Differential Regulation of NK Cell Receptors in Acute Lymphoblastic Leukemia.

Cancer immunotherapies are preferred over conventional treatments which are highly cytotoxic to normal cells. Focus has been on T cells but natural killer (NK) cells have equal potential. Concepts in cancer control and influence of sex require further investigation to improve successful mobilization of immune cells in cancer patients. Acute lymphoblastic leukemia (ALL) is a hematological malignancy mainly of B cell (B-ALL) and T cell (T-ALL) subtypes. Influence of ALL on NK cell is still unclear. Targeted next-generation sequencing was conducted on 62 activating/inhibitory receptors, ligands, effector, and exhaustion molecules on T-ALL (6 males) and normal controls (NC) (4 males and 4 females). Quantitative PCR (q-PCR) further investigated copy number variation (CNV), methylation index (MI), and mRNA expression of significant genes in T-ALL (14 males), NC (12 males and 12 females), and B-ALL samples (N = 12 males and 12 females). Bioinformatics revealed unique variants particularly rs2253849 (T>C) in KLRC1 and rs1141715 (A>G) in KLRC2 only among T-ALL (allele frequency 0.8-1.0). Gene amplification was highest in female B-ALL compared to male B-ALL (KLRC2, KLRC4, and NCR3, p < 0.05) and lowest in male T-ALL cumulating in deletion of KLRD1 and CD69. MI was higher in male ALL of both subtypes compared to normal (KIR2DL1-2 and 4 and KIR2DS2 and 4, p < 0.05) as well as to female B-ALL (KIR3DL2 and KIR2DS2, p < 0.05). mRNA expressions were low. Thus, ALL subtypes potentially regulated NK cell suppression by different mechanisms which should be considered in future immunotherapies for ALL.

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.

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.

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.

Efficiency and management factors: finding the balance in Thalassaemia care centres.

BACKGROUND: Optimizing efficiency has become increasingly critical with the growing demand for finite healthcare resources driven by population growth and an ageing society. Hence, policymakers are urgently finding more efficient ways to deliver health services. Thalassemia is a complex inherited blood disorder with significant prevalence in Malaysia. The high number of patients put substantial strain on the healthcare system. This study aims to evaluate the technical efficiency of thalassaemia care centres throughout Malaysia and the determinants that affect the efficiency. METHOD: Data from 30 public hospitals with thalassaemia care centres were collected. A double bootstrap data envelopment analysis (DEA) approach is used with the assumption of input-oriented and variable-to-scale DEA models to generate technical efficiency scores. Bootstrap truncated regression was later conducted to identify the factors affecting the efficiency scores. RESULTS: The mean bias-corrected technical efficiency score has improved to 0.75 in 2017 from 0.71 in 2016. In both years, more than 50% of thalassaemia care centres showed good efficiency scores (0.8-1.0). Management factors that affect the efficiency scores include separation of patient management (ß = 0.0653) and budget (ß = 0.0843), where they are found to positively affect the efficiency scores. In contrast, having longer operating hours is found to inversely influence the performance levels (ß = - 0.4023). CONCLUSIONS: The study provides a pioneering framework to evaluate the technical efficiency of thalassaemia treatment centres in public healthcare settings and could provide a useful guide for policymaker and thalassaemia care centre managers to improve efficiency in service delivery to thalassaemia patients and their caregivers without compromising quality of care.

PICK-ing Malaysia's Epidemic Apart: Effectiveness of a Diverse COVID-19 Vaccine Portfolio.

Malaysia rolled out a diverse portfolio of predominantly three COVID-19 vaccines (AZD1222, BNT162b2, and CoronaVac) beginning 24 February 2021. We evaluated vaccine effectiveness with two methods, covering 1 April to 15 September 2021: (1) the screening method for COVID-19 (SARS-CoV-2) infection and symptomatic COVID-19; and (2) a retrospective cohort of confirmed COVID-19 cases for COVID-19 related ICU admission and death using logistic regression. The screening method estimated partial vaccination to be 48.8% effective (95% CI: 46.8, 50.7) against COVID-19 infection and 33.5% effective (95% CI: 31.6, 35.5) against symptomatic COVID-19. Full vaccination is estimated at 87.8% effective (95% CI: 85.8, 89.7) against COVID-19 infection and 85.4% effective (95% CI: 83.4, 87.3) against symptomatic COVID-19. Among the cohort of confirmed COVID-19 cases, partial vaccination with any of the three vaccines is estimated at 31.3% effective (95% CI: 28.5, 34.1) in preventing ICU admission, and 45.1% effective (95% CI: 42.6, 47.5) in preventing death. Full vaccination with any of the three vaccines is estimated at 79.1% effective (95% CI: 77.7, 80.4) in preventing ICU admission and 86.7% effective (95% CI: 85.7, 87.6) in preventing deaths. Our findings suggest that full vaccination with any of the three predominant vaccines (AZD1222, BNT162b2, and CoronaVac) in Malaysia has been highly effective in preventing COVID-19 infection, symptomatic COVID-19, COVID-19-related ICU admission, and death.

Modelling infectious diseases with herd immunity in a randomly mixed population.

The conventional susceptible-infectious-recovered (SIR) model tends to magnify the transmission dynamics of infectious diseases, and thus the estimated total infections and immunized population may be higher than the threshold required for infection control and eradication. The study developed a new SIR framework that allows the transmission rate of infectious diseases to decline along with the reduced risk of contact infection to overcome the limitations of the conventional SIR model. Two new SIR models were formulated to mimic the declining transmission rate of infectious diseases at different stages of transmission. Model A utilized the declining transmission rate along with the reduced risk of contact infection following infection, while Model B incorporated the declining transmission rate following recovery. Both new models and the conventional SIR model were then used to simulate an infectious disease with a basic reproduction number (r0) of 3.0 and a herd immunity threshold (HIT) of 0.667 with and without vaccination. Outcomes of simulations were assessed at the time when the total immunized population reached the level predicted by the HIT, and at the end of simulations. Further, all three models were used to simulate the transmission dynamics of seasonal influenza in the United States and disease burdens were projected and compared with estimates from the Centers for Disease Control and Prevention. For the simulated infectious disease, in the initial phase of the outbreak, all three models performed expectedly when the sizes of infectious and recovered populations were relatively small. As the infectious population increased, the conventional SIR model appeared to overestimate the infections even when the HIT was achieved in all scenarios with and without vaccination. For the same scenario, Model A appeared to attain the level predicted by the HIT and in comparison, Model B projected the infectious disease to be controlled at the level predicted by the HIT only at high vaccination rates. For infectious diseases with high r0, and at low vaccination rates, the level at which the infectious disease was controlled cannot be accurately predicted by the current theorem. Transmission dynamics of infectious diseases with herd immunity can be accurately modelled by allowing the transmission rate of infectious diseases to decline along with the reduction of contact infection risk after recovery or vaccination. Model B provides a credible framework for modelling infectious diseases with herd immunity in a randomly mixed population.

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.

Evidence of new intragenic HBB haplotypes model for the prediction of beta-thalassemia in the Malaysian population.

This study sought to determine the potential role of HBB haplotypes to predict beta-thalassemia in the Malaysian population. A total of 543 archived samples were selected for this study. Five tagging SNPs in the beta-globin gene (HBB; NG_000007.3) were analyzed for SNP-based and haplotype association using SHEsis online software. Single-SNP-based association analysis showed three SNPs have a statistically significant association with beta-thalassemia. When Bonferroni correction was applied, four SNPs were found statistically significant with beta-thalassemia; IVS2-74T>G (padj = 0.047), IVS2-16G>C (padj = 0.017), IVS2-666C>T (padj = 0.017) and 3'UTR + 314G>A (padj = 0.002). However, 3'UTR + 233G>C did not yield a significant association with padj value = 0.076. Further investigation using combined five SNPs for haplotype association analysis revealed three susceptible haplotypes with significant p values of which, haplotypes 1-2-2-1-1 (p = 6.49 × 10-7, OR = 10.371 [3.345-32.148]), 1-2-1-1-1 (p = 0.009, OR = 1.423 [1.095-1.850] and 1-1-1-1-1 (p = 1.39 × 10-4, OR = 10.221 [2.345-44.555]). Three haplotypes showed protective effect with significant p value of which, 2-2-1-1-1 (p = 0.006, OR = 0.668 [0.500-0.893]), 1-1-2-2-1 (p = 0.013, OR = 0.357 [0.153-0.830]) and 1-1-2-1-1 (p = 0.033, OR = 0.745 [0.567-0.977]). This study has identified the potential use of intragenic polymorphic markers in the HBB gene, which were significantly associated with beta-thalassemia. Combining these five SNPs defined a new haplotype model for beta-thalassemia and further evaluation for predicting severity in beta-thalassemia.

Economic burden in the management of transfusion-dependent thalassaemia patients in Malaysia from a societal perspective.

BACKGROUND: Transfusion-dependent thalassaemia (TDT) is a hereditary blood disorder in which blood transfusion is the mainstay treatment to prolong survival and improve quality of life. Patients with this disease require blood transfusion at more than 100 ml/kg annually and iron-chelating therapy (ICT) to prevent iron overload (IOL) complications. There are substantial numbers of TDT patients in Malaysia, but limited data are available regarding the economic burden associated with this disease. The purpose of this study was to determine the lifetime cost of TDT from a societal perspective and identify potential factors increasing patient and family expenditures among thalassaemia populations. METHODS: The total lifetime cost per TDT patient (TC1) is the sum of lifetime healthcare cost (TC2) and lifetime patient and family healthcare expenditure (TC3). TC2 was simulated using the Markov model, taking into account all costs subsidized by the government, and TC3 was estimated through a cross-sectional health survey approach. A survey was performed using a two-stage sampling method in 13 thalassaemia centres covering all regions in Malaysia. RESULTS: A TDT patient is expected to incur TC2 of USD 561,208. ICT was the main driver of cost and accounted for 56.9% of the total cost followed by blood transfusion cost at 13.1%. TC3 was estimated to be USD 45,458. Therefore, the estimated TC1 of a TDT patient was USD 606,665. Sensitivity analyses showed that if all patients were prescribed oral ICT deferasirox for their lifetime, the total healthcare cost would increase by approximately 65%. Frequency of visits to health facilities for blood transfusion/routine monitoring and patients who were prescribed desferrioxamine were observed to be factors affecting patient and family monthly expenses. CONCLUSION: The lifetime cost per TDT patient was USD 606,665, and this result may be useful for national health allocation planning. An estimation of the economic burden will provide additional information to decision makers on implementing prevention interventions to reduce the number of new births and medical service reimbursement.

Validity of the Malay EQ-5D-3L in the Malaysian Transfusion-Dependent Thalassemia Population.

OBJECTIVE: The objective of this study was to examine the cross-sectional convergent and known-group validity of the Malay-language EQ-5D-3L instrument in children and adults with transfusion-dependent thalassemia (TDT). METHODS: A cross-sectional health-related quality of life survey involving TDT patients from 12 different treatment centers across Malaysia was conducted using the Malay PedsQL 4.0 Generic Core Scales and the Malay EQ-5D-3L questionnaire. Patients with non-TDT and other hemoglobinopathies were excluded. Convergent, discriminant, and known-group validity of the EQ-5D-3L was assessed against the PedsQL 4.0 Generic Core Scales in children. In the adult population, known-group validity of the EQ-5D-3L was assessed using an a priori hypothesis between patients' demographic characteristics and health outcomes obtained from literature. RESULTS: A total of 370 children and 225 adults were sampled. The mean (standard deviation) EQ-5D-3L scores of the children were 0.892 (0.082) and the adults were 0.887 (0.085). Convergent and discriminant validity was identified when correlated with the PedsQL domain in children. In both groups, known-group validity was evident when comparing groups of patients with reported problems to the group of patients with no reported problems on the EQ-5D-3L domains based on the a priori hypothesis derived from literature. CONCLUSION: This study found convergent, discriminant, and known-group validity of the Malay EQ-5D-3L in a population-based sample of patients with TDT. Hence, the instrument is valid for the assessment of health-related quality of life in children and adults with TDT in Malaysia.

Rurioctocog alfa pegol PK-guided prophylaxis in hemophilia A: results from the phase 3 PROPEL study.

Rurioctocog alfa pegol prophylaxis targeting factor VIII (FVIII) troughs ≥1% has shown to be efficacious with an acceptable safety profile in people with hemophilia A (PwHA). The PROPEL trial compared safety and efficacy of 2 target FVIII troughs in PwHA aged 12 to 65 years, with severe disease, annualized bleeding rate ≥2, and previous FVIII treatment. PwHA were randomized to 12 months' pharmacokinetic (PK)-guided rurioctocog alfa pegol prophylaxis targeting FVIII troughs of 1% to 3% (reference arm) or 8% to 12% (elevated arm); first 6 months was treatment-adjustment period. The primary endpoint was absence of bleeds during the second 6 months, analyzed using multiple imputations (full analysis set [FAS]). In the 1% to 3% and 8% to 12% arms, respectively, point estimates (95% confidence interval) of proportions of PwHA with zero total bleeds were 42% (29% to 55%) and 62% (49% to 75%) in FAS (N = 115; P = .055) and 40% (27% to 55%) and 67% (52% to 81%) in per-protocol analysis set (N = 95; P = .015). Dosing frequency and consumption varied in each arm. Adverse events (AEs) occurred in 70/115 (60.9%) PwHA; serious AEs in 7/115 (6%) PwHA, including 1 treatment-related in 8% to 12% arm (transient anti-FVIII inhibitor). There were no deaths, serious thrombotic events, or AE-related discontinuations. PK-guided prophylaxis was achievable and efficacious in both arms. No new safety signals were observed in the 8% to 12% arm. These results demonstrate elevated FVIII troughs can increase the proportion of PwHA with zero bleeds and emphasize the importance of personalized treatment. This trial was registered at www.clinicaltrials.gov as #NCT02585960.

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, [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.

Forecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models.

INTRODUCTION: The novel coronavirus infection has become a global threat affecting almost every country in the world. As a result, it has become important to understand the disease trends in order to mitigate its effects. The aim of this study is firstly to develop a prediction model for daily confirmed COVID-19 cases based on several covariates, and secondly, to select the best prediction model based on a subset of these covariates. METHODOLOGY: This study was conducted using daily confirmed cases of COVID-19 collected from the official Ministry of Health, Malaysia (MOH) and John Hopkins University websites. An Autoregressive Integrated Moving Average (ARIMA) model was fitted to the training data of observed cases from 22 January to 31 March 2020, and subsequently validated using data on cases from 1 April to 17 April 2020. The ARIMA model satisfactorily forecasted the daily confirmed COVID-19 cases from 18 April 2020 to 1 May 2020 (the testing phase). RESULTS: The ARIMA (0,1,0) model produced the best fit to the observed data with a Mean Absolute Percentage Error (MAPE) value of 16.01 and a Bayes Information Criteria (BIC) value of 4.170. The forecasted values showed a downward trend of COVID-19 cases until 1 May 2020. Observed cases during the forecast period were accurately predicted and were placed within the prediction intervals generated by the fitted model. CONCLUSIONS: This study finds that ARIMA models with optimally selected covariates are useful tools for monitoring and predicting trends of COVID-19 cases in Malaysia.

Modelling the Effectiveness of Epidemic Control Measures in Preventing the Transmission of COVID-19 in Malaysia.

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 (ß), 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 (ß), (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.

Observational study on the current status of thalassaemia in Malaysia: a report from the Malaysian Thalassaemia Registry.

OBJECTIVE: Thalassaemia is the most common inherited blood disorder in Malaysia. This study aims to report the current status of thalassaemia in Malaysia and provide a comprehensive understanding of the disease through data obtained from the Malaysian Thalassaemia Registry. DESIGN: Data were extracted from the Malaysian Thalassaemia Registry, a web-based system accessible to enrolled users through www.mytalasemia.net.my. SETTING: The Malaysian Thalassaemia Registry data was recorded from reports obtained from 110 participating government and university hospitals in Malaysia. PARTICIPANTS: The patients were those attending the 110 participating hospitals for thalassaemia treatment. INTERVENTION: Data were collected from the Malaysian Thalassaemia Registry from 2007 until the fourth quarter of 2018. PRIMARY OUTCOME MEASURE: 7984 out of 8681 patients with thalassaemia registered in the Malaysian Thalassaemia Registry were reported alive. RESULTS: Majority of the patients were reported in the state of Sabah (22.72%); the largest age group affected was 5.0-24.9 years old (64.45%); the largest ethnic group involved was Malay (63.95%); and the major diagnosis was haemoglobin E/ß-thalassaemia (34.37%). From the 7984 patients, 56.73% were on regular blood transfusions and 61.72% were on chelation therapy. A small fraction (14.23%) has undergone splenectomy, while the percentage of patients with severe iron overload (serum ferritin ≥5000 µg/L) reduced over time. However, cardiac complications are still the main cause of death in patients with thalassaemia. CONCLUSION: Data gathered into the registry can be used to understand the progression of the disorder, to monitor iron overload management and to improve the outcomes of treatment, to enhance preventive strategies, reduce healthcare burden and improve the quality of life. Sustainability of the Malaysian Thalassaemia Registry is important for surveillance of thalassaemia management in the country and help the national health authorities to develop more effective policies.

Genotype-Phenotype Correlation of ß-Thalassemia in Malaysian Population: Toward Effective Genetic Counseling.

Effective prevention of ß-thalassemia (ß-thal) requires strategies to detect at-risk couples. This is the first study attempting to assess the prevalence of silent ß-thal carriers in the Malaysian population. Hematological and clinical parameters were evaluated in healthy blood donors and patients with ß-thal trait, Hb E (HBB: c.79G>A)/ß-thal and ß-thal major (ß-TM). ß-Globin gene sequencing was carried out for 52 healthy blood donors, 48 patients with Hb E/ß-thal, 34 patients with ß-TM and 38 patients with ß-thal trait. The prevalence of silent ß-thal carrier phenotypes found in 25.0% of healthy Malaysian blood donors indicates the need for clinician's awareness of this type in evaluating ß-thal in Malaysia. Patients with ß-TM present at a significantly younger age at initial diagnosis and require more blood transfusions compared to those with Hb E/ß-thal. The time at which genomic DNA was extracted after blood collection, particularly from patients with ß-TM and Hb E/ß-thal, was found to be an important determinant of the quality of the results of the ß-globin sequencing. Public education and communication campaigns are recommended as apparently healthy individuals have few or no symptoms and normal or borderline hematological parameters. ß-Globin gene mutation characterization and screening for silent ß-thal carriers in regions prevalent with ß-thal are recommended to develop more effective genetic counseling and management of ß-thal.

Health-related quality of life among children with transfusion-dependent thalassemia: A cross-sectional study in Malaysia.

BACKGROUND: The treatment of children with transfusion-dependent thalassemia (TDT) in Malaysia has progressed since 2005. This study provides an updated health-related quality of life (HRQoL) assessment for children with the disorder and the factors affecting the HRQoL. METHODS: A cross-sectional HRQoL survey of Malaysian children with TDT was conducted using the PedsQL™ 4.0 Generic Core Scales. Patients with non-transfusion dependent thalassemia and other haemoglobinopathies were excluded. Parent-proxy and self-reported HRQoL scores were obtained using a multi-stage convenient sampling. The relationship between HRQoL scores and demographic factors were tested using association, correlation and regression analysis. RESULTS: A total of 368 patients were recruited. The mean (SD) Total Summary Score (TSS) was 80.12(13.87). Predictors for a lower TSS was an increasing age group and the use of dual chelating agents (R2 = 0.057, F (4, 359) = 5.40, p = < 0.001). The mean (SD) Physical Health Summary Score (PHSS) was 82.21 (16.82). Predictors of a higher PHSS score was being male, while predictors of a lower score was an increasing age group and parent-proxy reports(R2 = 0.075, F (5,358) = 5.80, p = < 0.001). The mean (SD) Psychosocial Health Summary Score (PCHS) was 79.39 (14.81). Predictors for a lower PCHS was the use of dual chelating agents(R2 = 0.041, F (1, 362) = 15.60, p = < 0.001). The school functioning score had the lowest mean (SD) score of 69.52(20.92) in the psychosocial dimension. CONCLUSION: The HRQoL of TDT children in Malaysia has improved over the last decade owing to the better access in treatment. However, further effort is needed to improve the school functioning dimension.