KeerthikaSunchu/dhis2-sierra-leone-healthcare-project
Domaine:
healthcareType de record:
project
Créateur:
Kee
Hôte:
Comprehensive healthcare analysis for Sierra Leone, including predictive modeling, sentiment analysis, and DHIS2 dashboards to inform healthcare policies and trends.
# Sierra Leone Healthcare Project
This repository showcases a comprehensive healthcare analysis for Sierra Leone. The project focuses on evaluating healthcare trends, performing predictive analytics, conducting sentiment and topic analysis, and providing actionable insights through visualizations and dashboards.
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## Objectives
1. **Referrals and Predictions**:
- Analyze referral trends for Ngelehun CHC and Jembe CHC.
- Build predictive models to forecast monthly referrals for 2025.
2. **Reporting Trends**:
- Evaluate reporting rates for Reproductive Health across districts in Sierra Leone for 2023.
- Analyze inter-dataset reporting trends for Reproductive Health, Child Health, and PMTCT datasets.
3. **Childhood Illnesses**:
- Examine diarrhea incidence rates and forecast Oral Rehydration Solution (ORS) stock requirements.
4. **Vaccination and Maternal Health**:
- Investigate OPV1 vaccination coverage across chiefdoms and facilities.
- Compare ANC-3 coverage and PHU delivery rates on Sherbro Island.
5. **Text Analysis**:
- Perform sentiment and topic analysis on team discussions related to Reporting Rates and Vaccination Coverage.
6. **Dashboard Creation**:
- Consolidate insights into a DHIS2 dashboard for policy recommendations.
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## Deliverables
1. **Presentation**:
- `sierra_leone_healthcare_analysis_presentation.pdf`: Overview of findings, methods, and insights.
2. **Dashboard**:
- `sierra_leone_healthcare_dashboard.pdf`: DHIS2 dashboard consolidating visualizations and findings.
3. **Code Notebooks**:
- `q2_reporting_rates_analysis.ipynb`: Analyzing Reporting Rates and time series trends.
- `q4b_diarrhea_ors_forecasting.ipynb`: Forecasting ORS stock requirements using predictive models.
- `q1b_referral_forecasting.ipynb`: Predicting referral trends for health facilities.
- `sentiment_and_topic_analysis.ipynb`: Sentiment analysis and topic modeling for discussions.
4. **Support Files**:
- `q2_interpretations.xlsx` & `q8_interpretations.xlsx`: …