Adapting health information systems in crisis settings: The implementation of DHIS2 during the COVID-19 pandemic in Guinea

Introduction: Guinea adopted the University of Oslo’s DHIS2 COVID-19 Surveillance Package in March 2020 to capture all COVID-19 data, marking the first large-scale deployment of DHIS2 in Guinea for a public health emergency response. This paper describes the implementation of the COVID-19 package, including the role of DHIS2 in public health decision-making, in Guinea from March 2020 to December 2022. Methods: Implementation was organized around four interconnected components: data collection during the response, training and equipment, data quality and innovations, and data use and public health decision-making. A multidisciplinary committee guided package configuration and customization to fit the Guinean epidemiological context. Results: In total, 648 data agents were trained across 43 week-long sessions, and 500 devices were provided to support data collection at testing sites, laboratories, treatment centres, and vaccination sites. Two country-specific innovations were developed: automated SMS notification of negative test results to patients and automated COVID-19 travel certificates for authorized travelers. From March 2020 to December 2022, data on 557,886 persons tested for COVID-19 were entered in DHIS2; 406,088 records were classified, of which 40,961 were confirmed cases, representing 10% of classified records. Data completeness was 56% for confirmed case outcomes and 60% for symptom severity variables, highlighting ongoing data quality challenges during large, rapidly scaled operations. A total of 4,045 situation reports were produced, and 155 national-level meetings were held, with dashboards and situation reports supporting real-time decision-making at district, regional, and national levels. DHIS2 data directly informed a targeted vaccination campaign that reached over 500,000 high-risk individuals between July and September 2022. Conclusion: Guinea’s experience demonstrates that DHIS2 can be adapted and deployed for large-scale epidemic response when supported by early preparedness, strong multi-partner collaboration, continuous data quality monitoring, and sustained institutional investment.