O-03 CARPHA’s Aberration Reporting System: A DHIS2- Based web application for syndromic surveillance and timely detection of elevated signals
Author(s):
B Bhagwandeen, B Armour, G Garcia, L Indar
Year of Presentation:
2026
Objective: To describe the design, implementation, and
performance of CARPHA’s Aberration Reporting System
(CARS v2.0), focusing on its unique dual-gate aberration
detection engine, automated email alerting, and alignment
with CARPHA’s Regional Integrated Early Warning Surveillance System (RIEWSS).
Methods: CARS v2.0 processes weekly syndromic reports for six priority conditions. Data undergo automated validation before being analysed by a dual-gate detection system that integrates CDC’s Early Aberration Reporting System (EARS) C1-C3 algorithms with a seasonally adjusted Locally Estimated Scatterplot Smoothing (LOESS) regression baseline. Alerts are generated only when both shortterm (EARS) and long-term (LOESS) thresholds are breached. Outputs include rule computations, highlighted aberrations, and instantaneous email notifications.
Results: Application testing using historical CMS datasets demonstrated that CARS v2.0 identifies elevated signals in under five seconds. It displays full computational transparency for EARS thresholds, LOESS expectations, and dualgate determinations. Dual-gate logic reduced false positives while maintaining sensitivity. The integrated automated email alert system enables instant dissemination to national and regional stakeholders.
Conclusion: CARS v2.0 operationalizes a robust, automated surveillance analytics platform within DHIS2, advancing CARPHA’s RIEWSS and strengthening early warning systems in the Caribbean. Its dual-gate design, user-friendly interface, and real-time alerting represent a significant innovation and a scalable model for digital public health surveillance. The system is particularly valuable for the Caribbean, where the geographic dispersion, small population sizes, tourism-driven mobility, and resource constraints of Small Island Developing States (SIDS) demand a highly sensitive, automated, and regionally harmonised early warning mechanism.