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Good practice Imported

Tanzania e-IDSR — AI alert triage for national disease surveillance

Tanzania · Dar es Salaam · See the Tanzania profile · See the Dar es Salaam profile

Evidence: Observational / pre–post Top 35% 67/100 · Ask Evidence Copilot about this practice

Tanzania's Ministry of Health deployed an AI triage layer in its DHIS2 disease-surveillance platform, clearing 85% of a 15,000-alert backlog and reducing processing time from 36–48 hours to near-instant, routing 23% of alerts for human epidemiological investigation.

26
Regions covered by e-IDSR
>15,000
Unreviewed alert backlog (2021-2023)
~23%
Alerts routed to human epidemiologists
36-48 hours
Processing time per alert batch, before
85%
Backlog cleared following deployment
5
Initial rollout regions
21
Remaining regions targeted for expansion
95%
Target auto-triage rate
>70
Countries using DHIS2

Details

Maturity
Scaling
Promoter
Tanzania Ministry of Health
Period
2021–present
Keywords
health, disease surveillance, public health

Context

Tanzania's Electronic Integrated Disease Surveillance and Response (e-IDSR) system collects disease-alert reports from health facilities across all 26 regions via the DHIS2 platform; as facility reporting improved over 2021-2023, a backlog of over 15,000 unreviewed alerts accumulated, hampering timely outbreak detection.

Objectives

Clear the alert backlog and speed up triage to prevent recurrence, at a time when outbreak-detection speed is critical.

Activities

The Tanzania Ministry of Health, the UDSM DHIS2 Lab, and the U.S. CDC developed a rule-based AI alert-triage tool embedded in DHIS2 that automatically classifies incoming alerts, routing approximately 23% to human epidemiologists and filtering the remainder, with machine-learning enhancements planned; initial rollout covered five high-priority regions, with expansion underway to the remaining 21.

Results

Processing that previously took 36-48 hours per alert batch now occurs in near-real time, and the system successfully cleared 85% of the 15,000-alert backlog following deployment.

Conclusions

The Ministry of Health is expanding the tool nationwide with a target of 95% auto-triage; DHIS2's use in over 70 countries suggests the approach could be adaptable to other low- and middle-income country health systems.

Implementation

Implementation detail (cost, timeline, staffing, conditions for success) is not yet available for this practice.

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Data sources

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