Abstract
Background At 145 days from Jan. 25, the Covid-19 recovery rate was 92.5% of the total cumulative cases of 8,515 with 1.4% fatalities were recorded in Malaysia. On top of the provided medical services and facilities, the recoveries could be mainly resulted from the Movement Control Order (MCO) enforcements in six phases for mitigating the pandemic nationwide. To understand the Covid-19 pandemic trend and dynamic mathematically to the MCO phases, the applicability of the proposed models ( tri-logistic growth model) on covid-19 related responses was studied by using the ‘matured’ 145-day data duration. The study also aimed at, (1) identifying information/parameters obtained through modeling technique that could be used in explaining the pattern of dynamic subjected to MCO enforcements, and (2) forecasting the quantitative information for postdate days beyond the used data duration. Methods Each serial layered-logistic growth of cumulative cases, recoveries, fatalities, and active cases were linked among them via the asymptotic cumulative cases and the nature of the recovery-fatality complementarity. The used data of Jan. 25 – Jun. 17, 2020 were quite ‘matured’ trend as observed in the ‘plateauing’ of cumulative cases. The appropriate R2 was used for model fitness analysis. The innovative SAS program writing of SAS9.4 version was used for the analysis. Conclusion Predicted cumulative cases, recoveries, fatalities, and active cases vs. days were significantly fitted to the observed values (R2 > 99 %), indicating the validity of the tri-logistic growth proposed model. Via the derivative of cumulative cases function, the daily cases or dynamic model was significant (R2=70%) with the fluctuating daily cases moved around the predicted curve. The authority has been classified the pandemic as of two waves (Jan. 25 – Feb. 26, 2020, and Feb. 27, 2020 onwards), and these were regrouped as wave 1 (primary wave) in this study. Within this one wave, the study shows that covid-19 in Malaysia has three cycles: cycle 1(1o cycle) [Jan. 25 – Apr.27], cycle 2 [Apr. 28 – May 14] and cycle 3 [May 15 and onwards] with the aggressiveness order of wave 1 > wave 3 > wave 2 (wave 3 had mainly caused by local foreigners). The observed cumulative cases were slightly higher than the predicted (by 0.07% -0.49%) during Jun 13 – 17 suggesting small room of resources still available for covid-19 infection, thus, maintaining the current MCO is crucial. Beyond Jun.17, the forecasts of cumulative cases, recoveries, fatalities, and active cases at June 30 would be 8500, 8168, 128, and 202 cases, respectively, with daily cases of 1 case day-1 . If no any further odd-extraordinary wave occurrence, the country would probably be enjoying a non-significant covid or ‘covid-free’ pandemic by the July end or mid-August, 2020. The model had validated the correctness and appropriateness of the MCO phases’ enforcements. The active cases model was the resultant of linkages of all models via asymptotic cumulative cases. Based on above resultant and the logistic growth function applicability in various fields, the modeling approach involving serial tri-logistic functions could probably be used in analyzing covid or covid-related epidemic elsewhere and in the future.
Evaluation of the Effectiveness of Movement Control Order to Limit the Spread of COVID-19
