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.

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.