Monitoring COVID-19 Parameters in Qatar Using Statistical Techniques
Author Information
Author(s): Abdel-Salam Abdel-Salam G., Boone Edward L., Ghanam Ryad
Primary Institution: Qatar University
Hypothesis
Can multivariate control charts effectively monitor COVID-19 model parameters in Qatar?
Conclusion
The study demonstrates that MEWMA and MCUSUM charts are effective tools for monitoring COVID-19 model parameters and can aid decision-making during pandemics.
Supporting Evidence
- MEWMA and MCUSUM charts effectively monitor changes in COVID-19 dynamics.
- The SEIRDV model incorporates vaccination status for better pandemic tracking.
- Real-time monitoring can help decision-makers respond to emerging variants.
- The study highlights the importance of statistical process control in public health.
- Findings indicate that monitoring tools can improve pandemic response strategies.
Takeaway
This study shows how special charts can help keep track of COVID-19 numbers in Qatar, helping people make better decisions about health.
Methodology
The study used MEWMA and MCUSUM control charts to monitor SEIRDV model parameters based on COVID-19 data from Qatar.
Potential Biases
Potential biases may arise from the assumption of equal susceptibility across different demographic groups.
Limitations
The model assumes a homogeneous population and constant movement rates between compartments, which may not reflect real-world variations.
Participant Demographics
The study focuses on the population of Qatar, but specific demographic details are not provided.
Digital Object Identifier (DOI)
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