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.

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, $$\beta_{t}$$ β t 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.

Introduction There are few sources of published data on intra-cluster correlation coefficients (ICCs) amongst patients with type 2 diabetes (T2D) and/or hypertension in primary care, particularly in low- and middle-income countries. ICC values are necessary for determining the sample sizes of cluster randomized trials. Hence, we aim to report the ICC values for a range of measures from a cluster-based interventional study conducted in Malaysia. Method Baseline data from a large study entitled Evaluation of Enhanced Primary Health Care interventions in public health clinics (EnPHC-EVA: Facility) were used in this analysis. Data from 40 public primary care clinics were collected through retrospective chart reviews and a patient exit survey. We calculated the ICCs for processes of care, clinical outcomes and patient experiences in patients with T2D and/or hypertension using the analysis of variance approach. Results Patient experience had the highest ICC values compared to processes of care and clinical outcomes. The ICC values ranged from 0.01 to 0.48 for processes of care. Generally, the ICC values for processes of care for patients with hypertension only are higher than those for T2D patients, with or without hypertension. However, both groups of patients have similar ICCs for antihypertensive medications use. In addition, similar ICC values were observed for clinical outcomes, ranging from 0.01 to 0.09. For patient experience, the ICCs were between 0.03 (proportion of patients who are willing to recommend the clinic to their friends and family) and 0.25 (for Patient Assessment of Chronic Illness Care item 9, Given a copy of my treatment plan). Conclusion The reported ICCs and their respective 95% confidence intervals for T2D and hypertension will be useful for estimating sample sizes and improving efficiency of cluster trials conducted in the primary care setting, particularly for low- and middle-income countries.

BackgroundCatquest questionnaire was originally developed in Swedish to measure patients’ self-assessed visual function to evaluate the benefit of cataract surgery. The result of the Rasch analysis leading to the creation of the nine-item short form of Catquest, (Catquest-9SF), and it had been translated and validated in English. The aim is therefore to evaluate the translated Catquest-9SF questionnaire in Malay and Chinese (Mandarin) language version for measuring patient-reported visual function among cataract population in Malaysia.MethodsThe English version of Catquest-9SF questionnaire was translated and back translated into Malay and Chinese languages. The Malay and Chinese translated versions were self-administered by 236 and 202 pre-operative patients drawn from a cataract surgery waiting list, respectively. The translated Catquest-9SF data and its four response options were assessed for fit to the Rasch model.ResultsThe Catquest-9SF performed well in the Malay and Chinese translated versions fulfilling all criteria for valid measurement, as demonstrated by Rasch analysis. Both versions of questionnaire had ordered response thresholds, with a good person separation (Malay 2.84; and Chinese 2.59) and patient separation reliability (Malay 0.89; Chinese 0.87). Targeting was 0.30 and −0.11 logits in Malay and Chinese versions respectively, indicating that the item difficulty was well suited to the visual abilities of the patients. All items fit a single overall construct (Malay infit range 0.85–1.26, outfit range 0.73–1.13; Chinese infit range 0.80–1.51, outfit range 0.71–1.36), unidimensional by principal components analysis, and was free of Differential Item Functioning (DIF).ConclusionsThese results support the good overall functioning of the Catquest-9SF in patients with cataract. The translated questionnaire to Malay and Chinese-language versions are reliable and valid in measuring visual disability outcomes in the Malaysian cataract population.