Badwap 14 Age Exclusive May 2026

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| Step | Action | Tools / Data | |------|--------|--------------| | | Confirm the exact boundaries of Badwap (e.g., village, ward, block). Use GIS layers from the national statistical office or OpenStreetMap. | QGIS/ArcGIS, shapefiles, satellite imagery | | 2. Identify the target population | All residents who turned 14 during the reference year (e.g., 2024). Decide whether to use “age‑as‑of‑31 Dec” or “age‑on‑survey‑date”. | Household registers, school enrolment lists | | 3. Choose indicators | Typical adolescent‑focus indicators: – School enrolment / attendance – Completion of primary education – Vaccination status (e.g., HPV, Tetanus) – Nutritional status (BMI‑for‑age) – Access to digital devices – Incidence of child labour / early marriage | DHS/MICS questionnaires, national monitoring frameworks | | 4. Data collection | • Survey : design a short module (10‑15 min) to be added to an existing household survey. • Administrative data extraction : pull school‑attendance registers, health‑clinic records. • Qualitative : focus‑group discussions with 14‑year‑olds, parents, teachers. | SurveyCTO, KoboToolbox, Excel, NVivo for qualitative coding | | 5. Data cleaning & analysis | Apply age‑validation checks; weight data if using a sample survey; compute prevalence rates, disaggregated by gender, socioeconomic status, and location within Badwap. | Stata, R, SPSS, Python (pandas) | | 6. Validation & triangulation | Cross‑check survey estimates with administrative records; conduct spot‑checks in a subset of households. | Field verification, data‑quality dashboards | | 7. Reporting | Produce an executive summary, detailed tables/figures, and policy briefs. Include limitations and recommendations for next data‑collection cycle. | LaTeX/Word for report, Tableau/PowerBI for visualisation | Badwap 14 Age