Forecasting Cardiovascular Disease Mortality in Sindh, Pakistan
Author Information
Author(s): Moiz Qureshi, Khushboo Ishaq, Muhammad Daniyal, Iftikhar Hasnain, Ziaur Rehman Mohd, S. A. Atif Salar
Hypothesis
This study aims to investigate the modeling and forecasting of cardiovascular disease mortality in Sindh, Pakistan.
Conclusion
The ANNAR model is the most effective method for predicting cardiovascular disease mortality in Sindh, providing valuable insights for health policy and resource allocation.
Supporting Evidence
- The ANNAR model outperformed classical time series models in predicting CVD mortality.
- The study utilized a comprehensive dataset covering over two decades of CVD mortality data.
- Findings can assist policymakers in making informed decisions regarding public health interventions.
Takeaway
This study used a smart computer model to predict how many people might die from heart disease in a part of Pakistan, helping doctors and leaders make better health decisions.
Methodology
The study analyzed a time series dataset of CVD mortality cases from 1999 to 2021 using classical time series models and compared them with the ANNAR model.
Limitations
The study is limited to data from a single region and may not be generalizable to other areas.
Participant Demographics
The dataset includes CVD mortality cases from the Sindh province of Pakistan.
Statistical Information
Confidence Interval
95% confidence interval provided for long-term forecasts.
Digital Object Identifier (DOI)
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