Muffin-1234/Lassa-Fever-Epidemiological-Surveillance-Dashboard-2020-2025-
Domaine:
healthcareCréateur:
Muf
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This contains an advanced public health intelligence dashboard designed to track and analyze Lassa Fever surveillance metrics over a 5-year period in Nigeria.
# Lassa-Fever-Epidemiological-Surveillance-Dashboard-2020-2025-
This contains an advanced public health intelligence dashboard designed to track and analyze Lassa Fever surveillance metrics over a 5-year period in Nigeria.
It utilizes official data reporting from Nigeria Centre for Disease Control (NCDC), this project applies data analytics infrastructure to infectious disease surveillance, transforming raw metrics into split-second and actionable intelligence for stakeholders.
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## Tech Stack & Key Features
- Analytics & Visualization: Power BI & Advanced Excel
- Core Metrics Tracked (KPIs): Total Suspected Cases (48K), Total Confirmed Cases (6438), Total Deaths (1006), Case Fatality Rate (16%), and Confirmation Rate (11.34%).
- Temporal Trend Analysis: Dual-axis weekly and monthly tracking to isolate seasonal epidemiological surges against historical baselines.
- Operational Audit: A distributio breakdown analyzing data extraction methods (Automated vs Manual vs Mixed reporting lines) to evaluate surveillance system integrity.
## Core Insights
1. **Year-Round Endemic Reality:** The dashboard shows the dry season spike (December to March) driven rodent vector behavior, transmission never hits absolute zero durig the rainy season. Lassa Fever remains an active threat year-round.
2. **CFR and Under-Testing Red Flags:** A high **16% Case Fatality Rate** contrasted against a low **11.34% Confirmation Rate** statistically indicates delayed clinical presentation or localized under-testing. This suggests surveillance is primarily catching severe cases at tertiary facilities while mild, early-stage community infections go undetected.
3. **The 2024 Surveillance Divergence:** In 2024, suspected cases surged to an all-time high of 10.1K yet the confirmed cases remained flate. This points to either an aggressive widening of clinical case definitions or a concurrent outbreak of a lookalike febrile illnesses like severe malaria which triggers high pre-PCR false alarms.
4. …