Lesson Learned from the Management of the COVID-19 Pandemic: The Influenza Morbidity and Mortality during the Pre-COVID-19 Era could Be Reduced
Bibliographic record
Abstract
Dear Editor, We have read with interest the paper by Sabeena et al.[1] which concluded in a systematic review and meta-analysis that globally there was a decline in influenza surveillance during the COVID-19 pandemic except in Canada. As a tremendous decline in influenza cases was observed even though influenza surveillance was maintained overall in Canada, we made the following hypothesis: we were not doing enough against influenza in the pre-COVID-19 era. Indeed, from March 28 to mid-September 2020, influenza surveillance in Quebec suffered from a significant decrease in the number of tests carried out by Sentinel Laboratories due to the massive efforts deployed to fight COVID-19. Fortunately, these changed quickly the following year. Despite the increasing number of samples tested in 2021–2022 for seasonal influenza from week 44 to week 13 in Sentinel laboratories, <1% were positives, whereas we reached 36% in the pre-COVID-19 years 2019–2020. A similar trend was found from the Canadian national surveillance data: FLuWatch surveillance (Flu [influenza]: FluWatch surveillance-Canada.ca). The epidemiological situation in Quebec, Canada, the United States, and Europe showed that influenza was almost absent in all areas in 2020–2021. These were attributed to both artifactual changes related to declines in routine health-seeking for respiratory illness as well as real changes in influenza virus circulation due to the widespread implementation of measures to mitigate the transmission of SARS-CoV-2.[2] The sustained use of infection prevention and control (IPAC) measures at all levels may explain the virtual disappearance of influenza during the COVID-19 pandemic. Unfortunately, maintaining preventive measures over time, and doing so consistently, is not feasible in the long-term perspectives. Thus, it is uncertain, unlikely, and unacceptable to apply these preventive measures with the same intensity after the pandemic. Besides flu vaccine and antiviral drugs, there is surely a threshold for raising and applying preventive actions that would significantly reduce the morbidity and mortality of both influenza and COVID-19 without necessarily harming the physical and mental health of anyone affected as it had been with more restrictive measures during the pandemic era.[3,4]Figure 1 shows the reduction in influenza mortality-morbidity as more restrictives measures are applied, but with a raised in mortality-morbidity due social isolation. Theoretically, from A to B (Arrow in the figure), mortality and morbidity could be reduced by rigorous and consistent application of preventive measures without increasing adverse effects due to a lack of social interactions.Figure 1: Preventive measures, influenza morbidity-mortality, and health harm trend.While writing this paper, we have to consider the following. First, new variants spread more quickly. Second, vaccines and infection are transforming SARS-COV-2 into a manageable “endemic” respiratory virus. Thus, it is about preventing severe disease, protecting vulnerable people, and protecting the health system. Thereby, we hope that the acquired living way, processes, and protocols put in place when fighting COVID-19 will have a downward impact on the burden of influenza on the health-care system. Rational plans are needed to lower both influenza and COVID-19 burdens using IPAC measures without necessarily confining and restricting people’s mobility. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.008 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".