Evaluating Senegal's COVID-19 surveillance system for early detection and response: lessons from the Keur Massar district, March 03, 2020 to May 31, 2022.

Background: The COVID-19 pandemic highlights the importance of strong surveillance systems in detecting and responding to public health threats. We sought to evaluate attributes of Keur Massar district's existing COVID-19 surveillance system.

Method: A descriptive, cross-sectional study was conducted in June 2022; desk review covered data collected from March 03, 2020 to May 31, 2022 in 18 health posts. Data were collected using a standardized questionnaire completed during a face-to-face interview and a desk review of surveillance data gathered from different notification platforms (Excel, ODK, DHIS2 aggregated, and tracker). Study was conducted in Keur Massar department, in the Dakar region. We conducted face-to-face interviews with 18 nurses in June 2022. We utilized a standardized, semi-structured questionnaire adapted from CDC guidelines for surveillance evaluation.

Results: All 18 head nurses targeted, responded to the questionnaire, with an average age of 41.5 years and 63% aged between 30 and 44. The sex ratio (M/F) was 0.6, and respondents had an average of 15.1 years of experience. All nurses were involved in COVID-19 surveillance and had notified at least one suspected case. While 39% conducted COVID-19 data analysis, 55.6% received feedback from the national level. The usefulness score for the surveillance system was 77.7, with the lowest score (72.9) related to describing the pandemic's magnitude. Simplicity scored 63.3, with low scores for the availability of guidelines (0) but high scores for training and equipment (94.4). Acceptability scored 76.6, with strong support for COVID-19 surveillance but weak community involvement (48.6). While no cases were reported through the DHIS2 aggregated platform, 1327 PCR-positive SARS-CoV-2 cases were reported through the national Excel sheet and 278 PCR-positive cases were reported through the COVID-19 DHIS2 tracker during the same period. Timeliness varied, averaging 3 days using ODK and 7 days with the national Excel sheet, with a combined average of 5 days across both systems.

Conclusion: The study highlights challenges in COVID-19 surveillance due to limited human resources, multiple data systems, and delays in notification. While most nurses were trained and equipped, gaps in data quality, timeliness, and community support emphasize the need for streamlined processes and increased workforce capacity.