This community innovation has been accepted at the 2025 DHIS2 Annual Conference
DHIS2 for Community Surveillance: Lebanon Insights
Implementing DHIS2 for Community-Based Surveillance: Insights from Lebanon Background: Early warning and response system is critical for detecting and responding to public health threats. The Epidemiological Surveillance Unit at the Ministry of Public Health has integrated DHIS2 for community-based surveillance. This abstract presents results of using DHIS2 for signal detection, and reporting by the community facilities. Methods: The Community-Based Surveillance was implemented in Lebanon focusing on two main groups: 1) the Non-Governmental Organizations (NGOs) dealing with vulnerable population in particular the displaced and refugees’ population, and 2) the municipalities and thus in coordination with the Lebanese Red Cross. The NGOs and the municipalities were trained on CBS and use of DHIS2. The target conditions were polio, measles, cholera, food poisoning and hepatitis A. As a reporting tool, a weekly reporting dataset was implemented to ensure continuous reporting, even in the absence of signals. Additionally, a tracker program was created for signal-based reporting in the event of disease occurrence. Dashboards were generated to follow on daily and weekly basis. Dashboards were accessible by the sources and the MOPH teams. . Results: For CBS, 378 municipalities were trained and allowed to report via DHIS2. During 2024, 7136 reports were received. The completeness was 37%. For CBS case-base reporting, 248 signals were reported, out of which 19% (n=48) were selected, 40% (n=50) were verified from those needed verification, 20% (n=50) were investigated out of which 30% (n=15) cases were confirmed. Conclusion The use of DHIS2 for community-based surveillance has led to receive signals detected from the community and thus detecting alerts leading to verification, investigation and public health response.
Primary Author: Hawraa Sweidan
Keywords:
DHIS2, Community-Based Surveillance, Lebanon, Completeness, Dashboards, Signal,