- Baseline and Midterm Data Analysis: A baseline study will be conducted to assess the current state of disease surveillance. A midterm evaluation will assess the project’s effectiveness in improving data accuracy and outbreak response times.
- Performance Metrics: Key indicators will include the number of healthcare workers trained, the accuracy of AI predictions, the speed of outbreak detection, and the number of lives saved due to early interventions.
- Quarterly Progress Reports: Regular reporting will track the integration of AI tools into healthcare systems, ensuring that timelines and objectives are met.
- Final Impact Assessment: A final evaluation will assess the overall impact of the project on public health outcomes and its potential for scalability.
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