P-Adjinsala/cameroon-disease-burden-analysis

# 🦠 Disease Burden Analysis — Cameroon vs Sub-Saharan Africa ### Malaria, HIV/AIDS & Tuberculosis: trends, comparisons, and SDG 3 tracking --- ## Overview Sub-Saharan Africa carries a disproportionate share of the global burden of malaria, HIV/AIDS, and tuberculosis. This project uses **World Bank Open Data** to analyse Cameroon's disease burden trajectory from 2000 to 2022, benchmark it against the Sub-Saharan Africa regional average, and surface insights relevant to health governance, SDG 3 monitoring, and evidence-based advocacy. The analysis goes beyond charting: it constructs a **Normalised Disease Burden Index (NDBI)** across six burden dimensions, explores correlations between health spending and disease outcomes, and produces an SDG 3 target scorecard with current trajectory status. --- ## Indicators covered | Disease | Indicator | Code | |---------|-----------|------| | Malaria | Incidence per 1,000 at risk | SH.MLR.INCD.P3 | | Malaria | Deaths per 100,000 | SH.MLR.MORT.P3 | | Malaria | ITN usage, children (%) | SH.MLR.NETS.ZS | | HIV | Prevalence, adults 15-49 (%) | SH.DYN.AIDS.ZS | | HIV | ART coverage (%) | SH.HIV.ARTC.ZS | | HIV | New infections per 1,000 | SH.HIV.INCD.ZS | | TB | Incidence per 100,000 | SH.TBS.INCD | | TB | Treatment success rate (%) | SH.TBS.CURE.ZS | | TB | Mortality excl. HIV (per 100k) | SH.TBS.MORT | | System | Health expenditure per capita (USD) | SH.XPD.CHEX.PC.CD | | System | Physicians per 1,000 | SH.MED.PHYS.ZS | --- ## What this project demonstrates | Skill | Detail | |-------|--------| | **Live API integration** | 11 indicators fetched directly from World Bank API via `wbgapi` | | **Time-series analysis** | 22-year trend analysis with Cameroon vs SSA comparison | | **Index construction** | Normalised Disease Burden Index across 6 burden dimensions | | **Correlation analysis** | Pearson r heatmap — all 11 indicators, 2000–2022 | | **Policy framing** | SDG 3 target scorecard with on-track / below-target status | …