KeerthikaSunchu/dhis2-sierra-leone-healthcare-project

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. --- ## 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. --- ## 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`: …