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

Abstract

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, representativeness, simplicity, stability and utility that scored >70% each. Flexibility and acceptability had moderate to week 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.

An Evaluation of the Zambia Influenza Sentinel Surveillance System, 2011-2017

“…For consistency and comparability of findings we used the evaluation method and scoring system utilized for influenza surveillance evaluations conducted in other African countries [17,18,19,20,21]. Data for calculation of the indicators for data quality and completeness, timeliness, stability and utility were obtained from various sources including the main influenza sentinel surveillance database, the laboratory database, annual reports and other documents and records.…”

“…For each quantitative indicator we first obtained the proportion (expressed as percentage) of the outcome of interest over the total [18,19,20,21]. For instance, for the indicator on completeness of laboratory testing (one of the indicators used to evaluate the data quality and completeness attribute) we divided the number of samples with available influenza results by the total number of samples collected and received by the laboratory.…”

“…For instance, for the indicator on completeness of laboratory testing (one of the indicators used to evaluate the data quality and completeness attribute) we divided the number of samples with available influenza results by the total number of samples collected and received by the laboratory. Subsequently, similar to other influenza surveillance evaluations conducted in Africa, we used a scale from 1 to 3 to provide a score for each quantitative indicator as follows: <60% (as obtained in the example above) scored 1 (weak performance); 60-79% scored 2 (moderate performance); ≥80% scored 3 (good performance) [18,19,20,21]. For indicators for which a proportion over a total could not be obtained (qualitative indicators) a score was assigned based on the same scale using expert consensus.…”

“…Thereafter, the scores assigned to each indicator were averaged for all indicators evaluated within each attribute to provide an overall score for each surveillance attribute assessed in this study. An overall score for the surveillance system was obtained by averaging the scores of all evaluated indicators as previously described [18,19,20,21]. All data generated by the surveillance system during the review period were included in the evaluation.…”

“…Such evaluations are useful to identify shortfalls, improve performance and provide evidence of data reliability for policy making and public health interventions. However, despite recent progress in describing the epidemiology and burden of influenza in sub-Saharan Africa [8,9,10,11,12,13,14,15,16], only a few countries have implemented a comprehensive evaluation of their surveillance systems [17,18,19,20,21].…”