Congratulate Dr Mohd Ariff Ab Rashid on the successful completion of his DrPH Viva Voce

The Department would like to congratulate Dr Mohd Ariff Ab Rashid on the successful completion of his DrPH Viva Voce for his thesis titled “Determinants of Tuberculosis in Malaysia: A Temporal Analysis Approach”. He was supervised by Assoc Prof Dr Rafdzah Ahmad Zaki, Dr Abqariyah Yahya and Dr. Wan Rozita Wan Mahiyuddin from the Climate Medical Unit, Environmental Health Research Center, National Institute of Health.

The thesis was examined by Professor Dr. Kamarul Imran Musa, Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, and Dr. Lim Yin Cheng, Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya.

The Viva Voce examination, held on July 2, 2024, from 2:30 pm to 4:30 pm and was chaired by Professor Dr. Rafidah Atan, Faculty of Medicine, Universiti Malaya, and attended by Professor Dr. Shahrul Bahyah Kamaruzzaman, Deputy Dean, Postgraduate, Faculty of Medicine, Universiti Malaya, Professor Dr. Victor Hoe, Head of Department, Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya, and his supervisors.

He has published Forecasting New Tuberculosis Cases in Malaysia: A Time-Series Study Using the Autoregressive. Integrated Moving Average (ARIMA) Model in Cureus 2023 Sep 4;15(9): e44676.

Summary of the Thesis:

The thesis titled “Determinants of Tuberculosis in Malaysia: A Temporal Analysis Approach” by Mohd Ariff Bin Ab Rashid focuses on understanding the epidemiological trends of tuberculosis (TB) in Malaysia, analyzing the impact of various factors on TB incidence, and developing predictive models for future TB cases using time series analysis. Below is a comprehensive summary of the thesis:

Epidemiological Trends

The study analyzed 150,606 new TB cases reported in Malaysia from 2013 to 2018. Key findings include:

• The overall trend of new TB cases and the TB incidence rate showed an upward trend during the study period.
• Men had a higher incidence of new TB cases compared to women, with an average age of 43 years for new TB cases.
• The majority of new TB cases were detected in densely populated and urban regions such as Selangor, Sabah, Sarawak, Johor, and Kuala Lumpur.

Impact of Comorbidities and Sociodemographic Factors

The study examined the relationship between new TB cases and comorbidities (HIV and diabetes) and sociodemographic factors (foreign workers). Key findings include:

• There were more new TB cases in individuals with TB/diabetes coinfection than those with TB/HIV coinfection.
• A positive correlation was observed between new TB cases and new diabetes cases, particularly within the same months and with a lag of 5 months.
• A positive correlation was also observed between new TB cases and new foreign workers, with contemporaneous and lagged effects.

Predictive Modeling

The study developed predictive models using the ARIMA/SARIMA approach to forecast new TB cases. Key findings include:

• The ARIMA (2,1,1)(0,1,0)12(2,1,1)(0,1,0)12​ model was identified as the best-fit model, exhibiting the lowest Mean Absolute Percentage Error (MAPE) of 6.762.
• The model showed clear seasonality with two peaks occurring in March and December.
• The inclusion of new diabetes cases and new foreign workers as external regressors improved the forecasting accuracy by 3%.

Recommendations

The study provides several recommendations for enhancing TB surveillance, prevention, and control in Malaysia:

• Implementing robust monitoring systems to track TB incidence and the impact of comorbidities and sociodemographic factors.
• Utilizing predictive models as early warning tools for public health authorities to manage potential TB outbreaks.
• Conducting further research to explore additional factors influencing TB incidence and to refine predictive models.

Conclusion

The thesis demonstrates the feasibility and benefits of using time series analysis to forecast new TB cases in Malaysia. The ARIMA and ARIMAX models with sociodemographic and comorbidity data are valuable tools for disease control and prevention programs. The study expands the understanding of TB epidemiology in Malaysia and identifies new avenues for research and public health interventions.