Evaluation of the Influenza Sentinel Surveillance System in the Democratic Republic of Congo, 2012-2015

• Published in: BMC Public Health
• Main Authors: Babakazo, Pelagie Diambalula, Kabamba-Tshilobo, Joelle, Wemakoy, Emile Okitolonda, Lubula, Léopold, Manya, Léonie Kitoko, Benoit Kebela Ilunga, Disasuani, Wally, Nkwembe, Edith, Hugo Kavunga-Membo, Changachanga, Jean-Claude, Saleh Muhemedi, Jean-Jacques Muyembe Tamfum, Tempia, Stefano
• Format: Web Resource
• Language: English
• Published: Durham Research Square 27.11.2019
• Subjects: Acceptability; Influenza; Medical personnel; Patients; Performance evaluation
• DOI: 10.21203/rs.2.12209/v3

Background The World Health Organization recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data about the performance of established influenza surveillance systems are limited in Africa, including in the Democratic Republic of Congo (DRC). Methods We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza sentinel surveillance system (ISSS) in DRC during 2012-2015. The performance of the system was evaluated using eight surveillance attributes: (i) data quality and completeness for key variables, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability and (viii) utility. For each attribute, specific indicators were developed and described using quantitative and qualitative methods. Scores for each indicator were as follows: <60% weak performance; 60-79% moderate performance; ≥80% good performance. Results During 2012-2015, we enrolled and tested 4,339 patients with influenza-like illness (ILI) and 2,869 patients with severe acute respiratory illness (SARI) from 11 sentinel sites situated in 5 of 11 provinces. Influenza viruses were detected in 446 (10.3%) samples from patients with ILI and in 151 (5.5%) samples from patients with SARI with higher detection during December-May. Data quality and completeness was >90% for all evaluated indicators. Other strengths of the system were timeliness, simplicity, stability and utility that scored >70% each. Representativeness, flexibility and acceptability had moderate performance. It was reported that the ISSS contributed to: (i) a better understanding of the epidemiology, circulating patterns and proportional contribution of influenza virus among patients with ILI or SARI; (ii) acquisition of new key competences related to influenza surveillance and diagnosis; and (iii) continuous education of surveillance staff and clinicians at sentinel sites about influenza. However, due to limited resources no actions were undertaken to mitigate the impact of seasonal influenza epidemics. Conclusions The system performed overall satisfactorily and provided reliable and timely data about influenza circulation in DRC. The simplicity of the system contributed to its stability. A better use of the available data could be made to inform and promote prevention interventions especially among the most vulnerable groups.