Assessing the Utility of Over-The-Counter Medication to Track Influenza Season Timing in a South African Population.

BACKGROUND: Laboratory-based influenza surveillance in low- and middle-income countries may have limited timeliness and geographic coverage. We evaluated whether over-the-counter (OTC) respiratory medication sales track seasonal influenza activity and provide early warning of influenza onset in South Africa. METHODS: Daily OTC medication sales were obtained from a national pharmaceutical chain and analysed nationally and in Gauteng, KwaZulu-Natal and Western Cape. Weekly laboratory-confirmed influenza cases were obtained from sentinel surveillance programmes for 2012-2019 and 2022-2023. Seasonal characteristics were compared using the Moving Epidemic Method. Lead-lag relationships were assessed using Pearson cross-correlation, with 3-week smoothing and first differencing as sensitivity analyses. Forecasts at 1- to 5-week horizons were evaluated using influenza-only, OTC-only, combined influenza-plus-OTC generalized linear model (GLM), Random Forest and naïve persistence models. Performance was assessed using root mean square error and area under the receiver operating characteristic curve (AUC). RESULTS: OTC sales preceded increases in influenza detections nationally and provincially. Sales-defined seasons began and peaked earlier in 70% of national seasons and 67%-89% across provinces. Primary analyses indicated that OTC sales preceded influenza detections by 2-3 weeks (mean peak correlations, 0.77-0.81). After first differencing, OTC changes preceded influenza changes in 5-8 of 10 seasons across locations (correlations, 0.42-0.50). Influenza-only models produced the lowest forecast errors. OTC-informed models achieved AUC ≥ 0.90 at 1- to 2-week horizons. All significant squared-error comparisons favoured naïve persistence. CONCLUSIONS: OTC respiratory medication sales may complement virological surveillance by supporting earlier identification of seasonal influenza activity but should not replace laboratory surveillance.