Trends in respiratory virus positivity across urban and rural hospitals in Ontario over three seasons

Highlights

• •Over 170,000 respiratory virus tests were analyzed across eight hospitals over multiple seasons.
• •Consistent positivity rates but variable peak timing were observed.
• •Seasonal shifts in peak positivity were observed for influenza and non-influenza respiratory viruses.

Abstract

Objectives

Respiratory viruses are a global health burden. While influenza has been a large focus of surveillance, non-influenza viruses remain understudied in Canada, leaving gaps in understanding their seasonal patterns and epidemiology. The coronavirus disease 2019 pandemic further disrupted typical virus seasonality, highlighting the urgent need for expanded surveillance to track evolving trends.

Methods

A multicenter retrospective analysis of molecular testing data for 15 respiratory viruses was conducted on tests performed over three consecutive respiratory virus seasons. Hospital-level variability was assessed by calculating deviations of each hospital’s peak week from the seasonal median peak week, summarized across years for each virus. We analyzed the timing of the weekly peak in test positivity for each virus.

Results

Each respiratory virus showed distinct yearly peak weeks, with influenza A virus, respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reaching the highest positivity rates (11.6%, 13%, and 11.7%, respectively). Significant shifts in peak timing were observed for adenovirus, SARS-CoV-2, influenza A virus, parainfluenza virus, and RSV across the 2022-2025 seasons, with adenovirus and SARS-CoV-2 peaking much earlier in 2024-2025 than in previous years. Influenza A virus peaked later, and RSV also peaked later only in the 2024-2025 season compared to 2023-2024.

Conclusions

Overall, our results highlight shifts in respiratory virus transmission dynamics across Ontario hospitals. Ongoing surveillance will support targeted public health interventions and strategies for respiratory virus surges.

Introduction

Respiratory viruses are a major health burden as they contribute to significant hospitalizations, morbidity, and mortality worldwide [1]. Historically, surveillance efforts have primarily focused on influenza viruses because of their well-established epidemic and pandemic potential [2,3]. However, non-influenza respiratory viruses (NIRVs) account for an estimated 28-62% of respiratory infections requiring hospital admissions and disproportionately affect vulnerable populations such as children, older adults, and patients who are immunocompromised [4,5]. Despite their clinical impact, surveillance of NIRVs is limited, particularly at the regional and hospital levels in Canada, and therefore, there is little knowledge of the epidemiology and seasonal patterns. Furthermore, the coronavirus disease 2019 (COVID-19) pandemic has disrupted traditional respiratory virus seasonality [6], and recent studies have shown altered viral circulation patterns, including off-season activity, changes in viral subtype dominance, and delayed peaks [7,8]. These shifts have been linked to changes in population behavior, viral interference, and immunity gaps, underscoring the need for more comprehensive, high-quality surveillance to better understand these dynamics [9]. This study aims to examine the epidemiology and spatiotemporal trends of circulating respiratory viruses from eight Ontario hospitals over multiple seasons and identify shifts in seasonality over multiple years.

Methods

Study design

We conducted a multicenter retrospective analysis of molecular respiratory virus testing data collected between September 25, 2022, and May 10, 2025. All testing was performed at the Shared Hospital Laboratory in Toronto, Canada. Eight hospitals were included (community and academic), and all patients with a nasopharyngeal swab collected for respiratory virus testing as part of routine care during the study period were included. Samples were tested using a multiplex polymerase chain reaction panel for the following respiratory viruses: severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus, respiratory syncytial virus (RSV), adenovirus, parainfluenza viruses 1-4, rhinovirus/enterovirus, human metapneumovirus, and seasonal human coronaviruses (HCoV-OC43, HCoV-229E, HCoV-NL63, and HCoV-HKU1) [10]. In the case where there were multiple positive results for the same virus within a 30-day interval from the same patient, only the earliest positive test was included. Tests more than 30 days apart or involving a different detected virus from the same patient were retained.

Peak week analysis

Weeks are reported as calendar weeks (1-52/53), and respiratory virus seasons were defined as calendar week 35 through week 34 of the following calendar year. Temporal trends were evaluated by plotting weekly positivity averaged across hospitals for each virus and season. Hospital-level variability was assessed by calculating deviations of each hospital’s peak week from the seasonal median peak week, summarized across years for each virus. We analyzed the timing of the weekly peak in test positivity for each virus (i.e., “peak week”). For each virus and season year, we then calculated the median peak week averaged across hospitals. Differences in timing of weekly peak positivity across seasons were assessed using Kruskal-Wallis tests, followed by pairwise comparisons conducted using Wilcoxon rank-sum tests with Bonferroni adjustment for multiple comparisons. Differences in peak timing (earlier vs later week) were determined relative to the yearly median peak week. Visualization of temporal and spatial patterns was conducted using R version 3.6 (R Core Team, Vienna, Austria), Excel 2019 (v1808), and quantum geographic information system.

Results

During the period of this study, a total of 170,970 samples were tested for respiratory viruses. Among these tests, 35,880 (21.0%) were positive for at least one respiratory virus. The eight hospitals included were a mix of large academic centers and community hospitals in both urban and rural settings across the province and, as shown in Figure 1, were separated by significant geographical distances in some cases. These eight hospitals include a catchment area of over 2 million people. Across all viruses, peak week positivity showed minimal variation between hospitals. Year to year, there were differences in median peak week for each respiratory virus, with no viruses having the same peak week (Figure 2). The highest positivity rates consistently over the 3-year period were seen for influenza A virus (11.6%), RSV (13%), and SARS-CoV-2 (11.7%). Notably, for several viruses, peak timing differed across seasons. Specifically, peak seasonal weeks for adenovirus, SARS-CoV-2, influenza A virus, parainfluenza virus (pooled for types 1-4), and RSV showed significant differences (P < 0.05). Pairwise Wilcoxon rank-sum tests with Bonferroni adjustment indicated that the 2024-2025 adenovirus median peak week occurred 24 weeks earlier than in 2022-2023 (P = 0.0071). No significant difference was observed between other seasons. For SARS-CoV-2, the 2024-2025 season peaked significantly earlier than both 2022-2023 (median season week was 15.5 weeks earlier; P = 0.048) and 2023-2024 (12.5 weeks earlier; P = 0.029). For influenza A virus, the only difference was observed in the 2024-2025 season, when it peaked 5 weeks later than in the previous season (P = 0.019). Examination of peak positivity for parainfluenza virus indicated that the 2023-2024 season peaked significantly earlier than 2022-2023 (median 8 weeks earlier, P = 0.0234), and the 2024-2025 season peaked significantly earlier than 2022-2023 (19.5 weeks earlier, P = 0.0071). There was no significant difference in peak timing between the 2023-2024 and 2024-2025 seasons. For RSV, the 2024-2025 season peaked significantly later than 2023-2024 (median 4.5 weeks later, P = 0.045). There was no significant difference in peak timing between the 2022-2023 and 2023-2024 seasons or between 2024-2025 and 2022-2023.

Figure 1.

Eight hospitals were included in the study. The distance from the testing laboratory (in kilometers) is shown on the green lines to highlight geographical distances.

Figure 2.

(a) Average median week of peak positivity for each virus, shown by year and averaged across hospitals. (b) Hospital deviations from seasonal median peak week. Deviation (in weeks) of each hospital's overall median peak week from the median peak in each season.

COVID-19, coronavirus disease 2019.

Discussion

Our study describes the epidemiology of respiratory virus circulation patterns in multiple rural and urban hospitals in Ontario over multiple seasons since COVID-19. Here, we demonstrate that peak positivity weeks for multiple, but not all, viruses shifted over different seasons. Interestingly, these deviations may reflect pandemic-driven behavioral changes, such as nonpharmaceutical interventions (e.g., ongoing masking, social distancing when symptomatic), which temporarily reduced exposure during the COVID-19 pandemic, followed by a rebound once schools and workplaces reopened, altering normal seasonal dynamics of these viruses [11,12]. Patterns in population immunity, vaccine uptake, and changing demographics likely also contribute. Interestingly, examination of historical influenza A virus data from the Public Health Agency of Canada FluWatch program has noted that the timing of the national peak levels can vary between seasons. For example, peak positivity was at week 10 in 2015-2016, week 7 in 2017-2018, and week 52 in 2018-2019 [13]. However, lack of data on other respiratory viruses from the same time period makes it difficult to determine if this shift was unique to influenza A virus.

Similar disruptions in respiratory virus seasonality have been reported following the COVID-19 pandemic. Surveillance studies describe reduced circulation of influenza, RSV, and other respiratory viruses during periods of nonpharmaceutical interventions, followed by delayed, off-season, or shifted peak timing after their relaxation [5,7]. Delayed RSV epidemics and atypical peak timing have also been observed across multiple regions [8]. Additionally, viral interference, a phenomenon whereby the presence of one virus affects the presence of another virus, may be playing a role, as this has been reported for RSV and rhinoviruses [14]. Interestingly, we observed shifting in peak positivity for RSV, but not for rhinoviruses. Notably, this occurred in respiratory virus seasons following the introduction of the RSV vaccine in Canada, as well as monoclonal antibodies (e.g., nirsevimab). As Canada lacks a central vaccine registry, it is difficult to determine exact vaccine uptake, but this may be contributing to the shifting peaks. As rollout continues to wider segments of the population (e.g., maternal vaccination), future studies should examine how this affects RSV activity.

Some limitations must be considered when interpreting our findings. Our data do not allow us to determine if patients visited multiple hospitals during a respiratory virus season. The retrospective nature of this study also limits our ability to confirm causal relationships or account for unmeasured confounders such as variations in testing protocols, healthcare-seeking behaviors, and demographic shifts over the study period. Analyses of differences in peak timing across seasons included all available weeks for each season. Notably, data from 2025 only extended through May, so the full seasonal peak may not be represented for that year. Additionally, we did not have data for influenza B virus, although provincial-level public health data indicated very low positivity rates in the first two seasons of our study [15]. Future studies examining changing patterns of influenza B virus should be undertaken. Despite this limitation, inspection of the complete-season data from other years suggested that peaks were generally captured, minimizing potential bias.

Overall, our results highlight shifts in respiratory virus transmission dynamics across multiple Ontario hospitals. Future research should aim to integrate genomic sequencing data that could further reveal viral transmission pathways and variant-specific impacts on public health [16]. Furthermore, exploration of environmental determinants, including analysis of various air quality parameters’ roles in viral transmission, could provide more insight into the multifactorial nature of respiratory virus epidemiology [17]. Ongoing surveillance will support targeted public health interventions and preparedness strategies for respiratory virus surges and outbreaks in hospitals.

Funding

This work was funded by the Canadian Institutes of Health Research.

Ethical approval

The study did not require ethics board approval or informed consent because the study used deidentified laboratory data collected as part of routine work.

CRediT authorship contribution statement

Rosalyn Deng: Writing – review & editing, Writing – original draft, Investigation, Formal analysis, Data curation. Andrew Mendlowitz: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation. Kevin Katz: Writing – review & editing, Resources, Methodology, Investigation. Christie Vermeiren: Writing – review & editing, Resources, Investigation. Mia Biondi: Writing – review & editing, Investigation, Formal analysis. Xena Li: Writing – review & editing, Supervision, Methodology, Investigation, Formal analysis. Robert Kozak: Writing – review & editing, Writing – original draft, Supervision, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Declaration of competing interests

The authors have no competing interests to declare.