tetano
Editor, Senior Moderator
Influenza Other Respir Viruses
. 2026 Sep;20(9):e70313.
doi: 10.1111/irv.70313.
Malebo Sephule Makunyane 1 2 , Neville Sweijd 3 4 , Jhandre Bredenkamp 5 , Sibongile Walaza 6 7 , Cheryl Cohen 6 7 , Jonny Peter 1 2
Affiliations
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.
Keywords: South Africa; influenza; over‐the‐counter medication sales; proxy data; surveillance.
. 2026 Sep;20(9):e70313.
doi: 10.1111/irv.70313.
Assessing the Utility of Over-The-Counter Medication to Track Influenza Season Timing in a South African Population
Malebo Sephule Makunyane 1 2 , Neville Sweijd 3 4 , Jhandre Bredenkamp 5 , Sibongile Walaza 6 7 , Cheryl Cohen 6 7 , Jonny Peter 1 2
Affiliations
- PMID: 42707052
- DOI: 10.1111/irv.70313
Abstract
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.
Keywords: South Africa; influenza; over‐the‐counter medication sales; proxy data; surveillance.