Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England
Abstract Background During the COVID-19 pandemic in England, increases and falls in COVID-19 cases were monitored using many surveillance systems (SS). However, surveillance sensitivity may have changed as different variants were introduced to the population, due to greater disease-resistance after...
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BMC
2025-05-01
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| Online Access: | https://doi.org/10.1186/s12879-025-11120-0 |
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| author | Julii Brainard Iain R. Lake Roger A. Morbey Alex J. Elliot Paul R. Hunter |
| author_facet | Julii Brainard Iain R. Lake Roger A. Morbey Alex J. Elliot Paul R. Hunter |
| author_sort | Julii Brainard |
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| description | Abstract Background During the COVID-19 pandemic in England, increases and falls in COVID-19 cases were monitored using many surveillance systems (SS). However, surveillance sensitivity may have changed as different variants were introduced to the population, due to greater disease-resistance after comprehensive vaccination programmes and widespread natural infection or for other reasons. Methods Time series data from ten epidemic trackers in England that were available Sept 2021-June 2022 were compared to each other using Spearman correlation statistics. Least biased and most timely SS in England were identified as ‘best’ standard epidemic trackers, while other COVID-19 tracking datasets we denote as complementary trackers. We compared the best standard trackers with each other and with the complementary trackers. Correlation calculations with 95% confidence intervals were made between complementary and best standard epidemic trackers. We tested the hypothesis that correlation with the best trackers was especially poor during transition periods when Delta, Omicron BA.1 and Omicron BA.2 sublineages were each dominant. Daily ascertainment percentages of incident cases that each SS detected during each variant’s dominance were calculated. We tested for statistically significant (at p < 0.05) differences in the distribution of the ascertainment values during each COVID-19 variant’s dominance, using Welch’s oneway ANOVA. Results Spearman rho correlation was significantly positive between most complementary and the best trackers over the whole period. There was no apparent visual indication that correlations were especially poor during transition period from Delta to BA.1. There were falls in correlation in the transition period from BA.1 to BA.2 but these falls were relatively small compared to correlation fluctuations over the full period. Ascertainment was highest in the Delta period for complementary systems against the least biased tracker of incidence. Ascertainment was statistically different between the three variant-dominant periods. Conclusions From September 2021 to June 2022, complementary SS generally reflected case rises and falls. Ascertainment was highest in the Delta-dominant period but no complementary tracker was highly stable. Factors other than which variant was dominant seem likely to have affected how well each tracker reflected true case rises and falls. |
| format | Article |
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| institution | DOAJ |
| issn | 1471-2334 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
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| series | BMC Infectious Diseases |
| spelling | doaj-art-3bf6537c99b14b30bf78bce57337163d2025-08-20T03:16:40ZengBMCBMC Infectious Diseases1471-23342025-05-0125111310.1186/s12879-025-11120-0Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in EnglandJulii Brainard0Iain R. Lake1Roger A. Morbey2Alex J. Elliot3Paul R. Hunter4Norwich Medical School, University of East AngliaNational Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, King’s College LondonNational Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, King’s College LondonNational Institute for Health and Care Research Health Protection Research Unit in Emergency Preparedness and Response, King’s College LondonNorwich Medical School, University of East AngliaAbstract Background During the COVID-19 pandemic in England, increases and falls in COVID-19 cases were monitored using many surveillance systems (SS). However, surveillance sensitivity may have changed as different variants were introduced to the population, due to greater disease-resistance after comprehensive vaccination programmes and widespread natural infection or for other reasons. Methods Time series data from ten epidemic trackers in England that were available Sept 2021-June 2022 were compared to each other using Spearman correlation statistics. Least biased and most timely SS in England were identified as ‘best’ standard epidemic trackers, while other COVID-19 tracking datasets we denote as complementary trackers. We compared the best standard trackers with each other and with the complementary trackers. Correlation calculations with 95% confidence intervals were made between complementary and best standard epidemic trackers. We tested the hypothesis that correlation with the best trackers was especially poor during transition periods when Delta, Omicron BA.1 and Omicron BA.2 sublineages were each dominant. Daily ascertainment percentages of incident cases that each SS detected during each variant’s dominance were calculated. We tested for statistically significant (at p < 0.05) differences in the distribution of the ascertainment values during each COVID-19 variant’s dominance, using Welch’s oneway ANOVA. Results Spearman rho correlation was significantly positive between most complementary and the best trackers over the whole period. There was no apparent visual indication that correlations were especially poor during transition period from Delta to BA.1. There were falls in correlation in the transition period from BA.1 to BA.2 but these falls were relatively small compared to correlation fluctuations over the full period. Ascertainment was highest in the Delta period for complementary systems against the least biased tracker of incidence. Ascertainment was statistically different between the three variant-dominant periods. Conclusions From September 2021 to June 2022, complementary SS generally reflected case rises and falls. Ascertainment was highest in the Delta-dominant period but no complementary tracker was highly stable. Factors other than which variant was dominant seem likely to have affected how well each tracker reflected true case rises and falls.https://doi.org/10.1186/s12879-025-11120-0SurveillanceEpidemicCOVID-19OmicronHealth care seeking |
| spellingShingle | Julii Brainard Iain R. Lake Roger A. Morbey Alex J. Elliot Paul R. Hunter Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England BMC Infectious Diseases Surveillance Epidemic COVID-19 Omicron Health care seeking |
| title | Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England |
| title_full | Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England |
| title_fullStr | Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England |
| title_full_unstemmed | Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England |
| title_short | Did COVID-19 surveillance system sensitivity change after Omicron? a retrospective observational study in England |
| title_sort | did covid 19 surveillance system sensitivity change after omicron a retrospective observational study in england |
| topic | Surveillance Epidemic COVID-19 Omicron Health care seeking |
| url | https://doi.org/10.1186/s12879-025-11120-0 |
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