Evaluation of the sentinel surveillance system for influenza-like illnesses in the Greater Accra region, Ghana, 2018

Abstract

BackgroundInfluenza-like Illness (ILI) is a medical diagnosis of possible influenza or another respiratory illness with a common set of symptoms. The deaths of four schoolchildren, during a pandemic influenza outbreak in December 2017 in Ghana, raised doubts about the ILI surveillance system’s performance. We evaluated the ILI surveillance system in the Greater Accra region, Ghana, to assess the system’s attributes and its performance on set objectives.MethodsCDC guidelines were used to evaluate the data of the ILI surveillance system between 2013 and 2017. We interviewed the surveillance personnel on the system’s description and operation. Additionally, routinely entered ILI data from the National Influenza Center provided by the six sentinel sites in Accra was extracted. We sampled and reviewed 120 ILI case-investigation forms from these sites. Surveillance activities were examined on system’s performance indicators, each being scored on a scale of 1 to 3 (poorest to best performance).ResultsAll population and age groups were under ILI surveillance over the period evaluated. Overall, 2948 suspected case-patients, including 392 (13.3%) children under-five were reported, with 219 being positive for influenza virus (Predictive value positive = 7.4%). The predominant influenza subtype was H3N2, recorded in 90 (41.1%) of positive case-patients. The system only met two out of its four objectives. None of the six sentinel sites consistently met their annual 260 suspected case-detection quota. Samples reached the laboratory on average 48 hours after collection and results were disseminated within 7 days. Of 120 case-investigation forms sampled, 91 (76.3%) were completely filled in.ConclusionsThe ILI surveillance system in the Greater Accra region is only partially meeting its objectives. While it is found to be sensitive, representative and timely, the data quality was sub-optimal. We recommend the determination of thresholds for alert and outbreak detection and ensuring that sentinel sites meet their weekly case-detection targets.

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]. Each of the above mentioned attribute was evaluated using pre-defined quantitative or qualitative indicators.…”

“…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].…”