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SayPro Raw Data and Data Sources Log: Metadata, references, and structured data tables used in analysis.
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SayPro Raw Data and Data Sources Log
Compiled by: SayPro Research & Analytics Division
Document Purpose: To outline the origin, structure, and characteristics of the raw data used in SayPro’s demographic and disease pattern analyses.
SayPro Section 1: Data Inventory Overview
This log captures all datasets and information sources consulted during recent demographic-disease intersection analysis, including health outcomes, geographic indicators, population demographics, and service delivery metrics across SayPro’s operational territories.
SayPro Section 2: Metadata Table
| Dataset Name | Description | Source | Format | Date Range | Update Frequency | Access Level |
|---|---|---|---|---|---|---|
| SayPro Disease Case Registry | Raw disease case entries by region, age, and diagnosis | SayPro Health Programs | CSV / SQL | Jan 2020 – Apr 2025 | Monthly | Internal |
| SayPro Demographic Survey Panel | Longitudinal panel survey capturing household data, income, education, etc. | SayPro Field Research Unit | XLSX / JSON | 2019 – 2025 | Bi-annual | Internal |
| SayPro GIS Mapping Dataset | Location-tagged disease prevalence and resource mapping | SayPro GIS Team | GeoJSON | 2021 – 2025 | Quarterly | Internal |
| National Census Extract (SayPro regions) | Official demographic data by ward, gender, age distribution | National Statistics Agency | CSV / XML | 2011, 2021 | Decadal | Public |
| WHO Regional Health Reports | Public health indicators, mortality, NCD rates by region | World Health Organization | PDF / XLSX | 2020 – 2024 | Annual | Public |
| Education & Literacy Baseline (SayPro) | Literacy rates and school attendance by district | SayPro Education Partnerships | XLSX | 2022 – 2025 | Annual | Internal / Shared |
| Mobile Health Feedback Logs | Anonymized patient feedback from SayPro mHealth tools | SayPro Digital Health Systems | JSON / CSV | 2023 – 2025 | Ongoing | Internal |
| Immunization Coverage Reports | District-level vaccine uptake and dropout rates | SayPro Vaccine Access Initiative | XLSX / Tableau | 2020 – 2024 | Monthly | Internal |
| Health Worker Staffing Tracker | Deployment log of medical and outreach staff by region | SayPro HR Analytics | Google Sheets | 2021 – 2025 | Weekly | Internal |
SayPro Section 3: Reference Sources and Validation
All datasets were triangulated and validated through the following methods:
- Peer Review: Reviewed by SayPro’s Epidemiology and Data Quality teams.
- Cross-Source Verification: Matched against WHO regional estimates and national statistics.
- Metadata Consistency Checks: Field definitions, timestamps, and geocodes verified across merged data sources.
SayPro Key external references:
- World Health Organization (www.who.int)
- National Department of Health (Country-specific)
- UNICEF Open Health Data
- African Regional Health Observatories
- Peer-reviewed journals in PubMed and JSTOR
- SayPro internal publications (Q1–Q4 2024 Impact Reports)
SayPro Section 4: Structured Data Tables Used in Analysis
SayPro Age vs Disease Prevalence Matrix (Extract)
| Age Group | TB Cases | Diabetes Cases | COVID-19 Cases | Hypertension Cases |
|---|---|---|---|---|
| 0–14 years | 182 | 45 | 310 | 28 |
| 15–24 years | 491 | 103 | 892 | 122 |
| 25–49 years | 1,203 | 540 | 1,487 | 698 |
| 50–64 years | 899 | 683 | 641 | 1,231 |
| 65+ years | 332 | 499 | 212 | 1,491 |
SayPro Region vs Immunization Coverage Table
| Region Name | DPT Coverage (%) | Measles Coverage (%) | Dropout Rate (%) |
|---|---|---|---|
| West Metro | 94 | 91 | 3.2 |
| South Highlands | 81 | 76 | 6.5 |
| Eastern Basin | 88 | 85 | 4.1 |
| Central Valley | 79 | 73 | 7.9 |
SayPro Gender-Based Health Access Metrics
| Gender Identity | Avg Clinic Visits per Year | Health Literacy Score | Chronic Illness % |
|---|---|---|---|
| Male | 2.4 | 58% | 41% |
| Female | 3.7 | 71% | 38% |
| Non-binary | 1.9 | 52% | 43% |
SayPro Section 5: Data Usage Policy
All SayPro datasets are used under strict ethical guidelines, following:
- Informed Consent Protocols for all survey-based data
- Anonymization Procedures for patient records
- Data Security Standards, compliant with national data protection laws and SayPro’s internal privacy policy
Third-party access must be approved by the SayPro Data Governance Committee and must include justification, use case, and data protection measures.
SayPro Conclusion
This Raw Data and Data Sources Log provides transparency and traceability for SayPro’s analytical work. It ensures that all insights derived for strategic planning, health programming, and stakeholder reporting are grounded in validated, well-documented data systems.
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