Abdallah Abusam

A simple dynamic model is proposed for modeling the COVID-19 pandemic based on the number of daily new cases rather than their cumulative sum. The developed model was tested using data from the pandemic in the GCC countries. The model was found to fit well both single and multiple waves when both smoothed and unsmoothed profiles of the pandemic were used.

Kuwait’s wastewater treatment plants experience severe sludge bulking and foaming problems during the winter months. In an effort to identify the possible causes of these problems, sample of wastewater and sludge was collected from Um-Al-Haiman and Riqqa activated sludge systems each week for 32 weeks. The quality of wastewater was determined following standard methods of water analysis, while the dominant filamentous bacteria were identified and quantified using a molecular method called Vermicon Identification Technology (VIT). Multivariate statistical analysis (namely, Pearson’s correlation analysis and principal component analysis) was then carried out on the obtained datasets of results. Pearson’s correlation analysis revealed several significant associations between filamentous bacteria growth and influent quality and operational modes for the systems. The principal component analysis revealed six components that accounted for more than 70% of the total datasets’ information. The techniques used in this study can also be used to assess the relationship between filamentous bacteria growth and the operating conditions of other activated sludge systems.

Treated municipal wastewater produced in Kuwait is used mainly in agricultural and landscape irrigations. However, there are strong doubts that severe sludge bulking and foaming problems, particularly during winter seasons, may render this water unsuitable for irrigation purposes. To assess the impact of these problems on the quality of irrigation water in Kuwait, samples of secondary and tertiary effluents and sludge-mixed liquor were collected weekly from two wastewater treatment plants for nine months. Routine wastewater quality parameters were then determined for the collected influent and effluent samples. Further, dominant filamentous bacteria in the sludge-mixed liquor samples collected from the aeration tanks were also identified and quantified using a molecular method called Vermicon Identification Technology (VIT). Obtained results of the effluents’ qualities were then statistically analyzed and compared to Kuwait’s irrigation water standards. Statistical results indicated that secondary effluents were greatly impacted by sludge bulking and foaming problems, while tertiary effluents were slightly affected. This finding highlights the importance of having tertiary treatment units in plants to encounter sludge bulking and foaming problems.

Logistic models have been widely used for modelling the ongoing COVID-19 pandemic. This study used the data for Kuwait to assess the adequacy of the two most commonly used logistic models (Verhulst and Richards models) for describing the dynamics COVID-19. Specifically, the study assessed the predictive performance of these two models and the practical identifiability of their parameters. Two model calibration approaches were adopted. In the first approach, all the data was used to fit the models as per the heuristic model fitting method. In the second approach, only the first half of the data was used for calibrating the models, while the other half was left for validating the models. Analysis of the obtained calibration and validation results have indicated that parameters of the two models cannot be identified with high certainty from COVID-19 data. Further, the models shown to have structural problems as they could not predict reasonably the validation data. Therefore, they should not be used for long-term predictions of COVID-19. Suggestion have been made for improving the performances of the models.