Health Intelligence

15 countries · DHIS2 + WHO GHO + Africare telemetry

Live · Verified

AI-assisted analysis — Forecasts are generated by an XGBoost + LSTM ensemble (MLflow experiment #africare-v2). All critical alerts require human clinical validation before action. Data last verified: WHO standards · 27 May 2026

Facilities Online

47.3K

+2,410 this quarter

DHIS2

Countries

15

Pan-African

WHO GHO

Patients Reached

8.2M

+18% YoY

Africare DB

Active Alerts

4

3 escalating

WHO GOARN

Avg Vaccination

67.2%

+4.1% vs last year

WHO GHO

Response Time

4.2h

↓ from 11.2h

Africare DB

Disease Burden Trends

12-month case counts · pan-African aggregate

Outbreak Alerts

4 active

AI-flagged · human validation required on CRITICAL

NigeriaHIGH

Cholera — Delta State

Model confidence91%

Key risk drivers

  • ·↑ case velocity +340%
  • ·↓ water sanitation index
  • ·Dense delta population
DHIS2 sentinel + WHO GOARN Validated
EthiopiaHIGH

Malaria surge — Oromia

Model confidence84%

Key risk drivers

  • ·↑ malaria vector density
  • ·↓ insecticide coverage 38%
  • ·Seasonal rainfall peak
WHO GHO + national HMIS Validated
UgandaCRITICAL Human review

Mpox — Northern Uganda

Model confidence78%

Key risk drivers

  • ·Cross-border movement index
  • ·↑ zoonotic spillover risk
  • ·Low seroprevalence data
WHO GOARN + Africare DB Pending review
DR CongoCRITICAL Human review

Ebola watch — Equateur

Model confidence88%

Key risk drivers

  • ·Historical Ebola corridor
  • ·↓ healthcare worker density
  • ·Active conflict zone
WHO AFRO + GOARN Pending review

WHO GOARN coordination active · 2 alerts escalated to regional level

Resource Forecast

XGBoost · 60-day

Predictive depletion · CI shown as 30 / 60-day range

Ensemble model: XGBoost + LSTM · trained on 36-month supply chain data · holdout MAE ±4.1%

Artemisinin
Mod conf.45%
30d: 28% ±4%60d: 12% ±6%
ARV
Mod conf.72%
30d: 61% ±4%60d: 48% ±6%
TB Drugs
High conf.58%
30d: 42% ±4%60d: 31% ±6%
Oral Rehydration Salts
Mod conf.34%
30d: 18% ±4%60d: 8% ±6%
Rapid Test Kits
High conf.81%
30d: 67% ±4%60d: 54% ±6%
Healthcare Workers
Low conf.68%
30d: 65% ±4%60d: 61% ±6%

For procurement planning only. Forecasts reflect statistical trends and must be verified with national supply chain officers before procurement decisions.

Country Index

15 nations · click headers to sort

CountryDigitalizedVacc %HIV %HW /10kRisk
Cameroon
1,100
60%
3.4%0.8high
Côte d'Ivoire
720
65%
2%1high
DR Congo
1,200
45%
0.7%0.3critical
Ethiopia
4,200
59%
0.9%0.8high
Ghana
2,700
79%
1.7%1.7medium
Kenya
6,100
73%
4.2%1.4medium
Mozambique
890
57%
12.6%0.5critical
Nigeria
8,240
42%
1.4%1.6high
Rwanda
540
91%
2.5%0.8low
Senegal
820
74%
0.4%0.9medium
South Africa
2,890
68%
18.3%9.1medium
Tanzania
2,900
68%
4.7%0.9high
Uganda
2,400
62%
5.4%0.5critical
Zambia
980
70%
11.1%1.1high
Zimbabwe
690
72%
11.9%1.6high

Model Transparency

Responsible AI

Forecast model

XGBoost + LSTM ensemble

MLflow experiment #africare-v2

AI language model

Llama 3.1 8B (Workers AI)

Cloudflare edge · <50ms latency

Training data

WHO GHO · DHIS2 · World Bank

2015–2025 · 54 African nations

Holdout accuracy

87.3% MAE on 90-day forecasts

Validated Jan 2025 · CI: ±4.1%

⚠ Clinical disclaimer: Africare provides decision-support intelligence, not clinical advice. All alerts and forecasts must be reviewed by qualified health professionals before any clinical or policy action is taken. Model outputs reflect statistical patterns in aggregated population data and do not substitute for epidemiological investigation or medical judgment.