Inter-District Health Dashboard

One national picture, built from district reporting

Sierra Leone's outbreak response depends on knowing what is happening in every district at the same time. Before this platform, that picture was assembled from separate returns arriving on different schedules, which meant national coordination was always working from partial information.

We built a single surveillance platform where district health teams submit data and the Ministry sees the consolidated national view — trend analysis, district comparison and exception alerts — as the data arrives rather than weeks later.

The challenge

Surveillance data was fragmented across facilities, districts and programme units. Reporting timeliness varied, formats differed, and there was no shared view that district and national teams could both work from.

• No single national view across all 16 districts.
• Outbreak signals surfacing late, after the window for a cheap response.
• Inconsistent reporting formats between districts and programme units.
• Analysis done manually in spreadsheets, and rarely repeated the same way twice.

Platform capabilities

Outbreak signal detection

Anomaly detection flags unusual disease clusters soon after data arrives, and routes them to district and national focal persons for verification.

Epidemiological analytics

Incidence and mortality curves, district comparison views and trend summaries disaggregated by age and sex, grounded in Sierra Leone's own programme and surveillance definitions.

National health security reporting

IHR-aligned reporting workflows supporting timely event notification from districts to the Ministry and partner technical agencies.

Inter-district coordination

Verified signals are shared across district boundaries when cases move, so neighbouring teams are not working blind.

Routine programme dashboards

Beyond outbreaks, the platform carries routine programme reporting — immunisation coverage, reporting timeliness and facility completeness.

What changed

• One shared national view. District teams and the Ministry work from the same numbers, so coordination conversations start from agreement rather than reconciliation.
• Signals surface earlier. Anomalies are flagged as data arrives instead of being found during a periodic review.
• Reporting is consistent. One structure across all 16 districts makes comparison meaningful.

How it is built

Django and PostgreSQL, deployed for reliability on local connectivity, with role-based access separating district, programme and national views.