Impact of COVID-19 on Influenza Virus Trends and Subtypes in Saudi Arabia: A Cross-Sectional Analysis

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The COVID-19 pandemic led to major shifts in respiratory viruses’ transmission. This study investigates the effect of the COVID-19 pandemic on influenza virus trends in Saudi Arabia, focusing on changes in influenza activity, subtype distribution, and seasonal patterns across pre- and post-pandemic periods. Methods Influenza data from the World Health Organization (WHO) FluNet database were analyzed, comparing influenza cases, subtype distributions, and seasonal trends before (2017–2020) and after (2021–2024) the COVID-19 pandemic in Saudi Arabia. Statistical tests, including the Chi-Square Test, two-proportion z-tests, and the Kolmogorov-Smirnov test, were utilized to evaluate the changes in influenza patterns. Results The findings of this study showed a substantial increase in the number of influenza virus testing and positive cases post-COVID-19 compared to the pre-COVID-19 period. In addition, the results revealed an altered distribution of influenza subtypes circulating in the Saudi Arabia post-pandemic, with a notable reduction in the prevalence of H1N1 pdm09 (39.23% vs.19.99%, p < 0.0001), and a dramatic increase in H3N2 (0.02% vs.17.59%, p < 0.0001), which was nearly absent in the pre-pandemic period. Conclusions This report underscores significant changes in influenza patterns in Saudi Arabia following the COVID-19 pandemic. These changes are likely influenced by reduced community immunity and the return of international travel after COVID-19 restrictions were lifted. This study highlights the importance of continuous surveillance to inform public health strategies and effectively manage future outbreaks in the post-pandemic landscape. Influenza COVID-19 pandemic H1N1 pdm09 H3N2 Figures Figure 1 1. Background Influenza, commonly referred to as the flu, is a highly contagious viral infection that affect the respiratory system. It poses a significant public health challenge due to its ability to cause seasonal epidemics and, at times, global pandemics, resulting in widespread morbidity and mortality. Transmission occurs via respiratory droplets, especially in crowded or enclosed settings. While symptoms vary in severity, the virus poses significant risks to vulnerable groups such as the elderly, children, and those with underlying health conditions [ 1 , 2 ]. The influenza virus belongs to the Orthomyxoviridae family and is classified into four types based on the antigenic properties of two key surface proteins, hemagglutinin (HA) and neuraminidase (NA). The four types of influenza viruses are Influenza A, B, C, and D. Influenza A, the most common and severe, is further subtyped (e.g., H1N1, H3N2), while Influenza B is divided into two lineages: B/Yamagata and B/Victoria [ 3 – 5 ]. Annual surveillance by the World Health Organization (WHO) monitors circulating strains primarily types A and B to inform vaccine composition. However, continual viral evolution through antigenic drift and shift presents ongo-ing challenges in influenza prevention and control [ 6 ]. In Saudi Arabia, the flu season generally peaks between November and March, following pat-terns seen in other temperate countries. However, the country’s role as a hub for religious pil-grimages, particularly Hajj and Umrah, adds a unique dimension to its flu burden. These mass gatherings involve prolonged close contact among individuals from diverse regions, creating opportunities for the introduction and spread of novel strains [ 7 , 8 ]. Saudi Arabia has implement-ed seasonal vaccination campaigns targeting high-risk groups and encouraging uptake among pilgrims. However, disparities in flu vaccination rates among international visitors complicate these efforts [ 8 ]. The global response to COVID-19 significantly disrupted the transmission of respiratory viruses, including influenza. In Saudi Arabia, flu activity declined sharply following the introduction of widespread public health interventions. Typically, the country experiences seasonal peaks during cooler months, but the emergence of COVID-19 in early 2020 altered both global and local pat-terns. Measures such as lockdowns, mask mandates, travel restrictions, and social distancing drastically reduced influenza transmission [ 9 ]. The WHO estimates that influenza causes 3 to 5 million cases of severe illness and up to 650,000 respiratory related deaths, with variable sea-sonality depending on geographic region [ 10 ]. Between 2015 and 2019, Saudi Arabia experi-enced predictable flu seasons, with strains such as H1N1, H3N2, and influenza B circulating consistently. Public health measures focused on annual vaccinations and routine prevention strategies [ 7 , 11 ]. However, the emergence of COVID-19 in early 2020 brought a major shift in public health priorities and actions. The global response to the novel coronavirus was swift and severe, leading to extraordinary interventions to limit its spread [ 12 ]. Saudi Arabia implemented strong public health measures to control COVID-19, evolving them as the situation progressed. Initial steps included health screenings and travel bans for high-risk countries. On February 27, 2020, Umrah was suspended, and by March, following the first con-firmed case, all international and domestic travel was halted [ 8 , 13 ]. A national lockdown followed, with closures of schools, mosques, and public venues. As cases stabilised, restrictions were eased; businesses reopened under health protocols, and mask man-dates and social distancing remained in effect. In late 2020, gradual reopening resumed. Travel restrictions were loosened, Umrah restarted under strict guidelines, and a national vaccination campaign began in December. By early 2021, vaccinated individuals received expanded free-doms, and a limited Hajj was conducted for vaccinated or recovered residents. Most restrictions were lifted by late 2021, though some precautions persisted [ 14 , 15 ]. In March 2022, remaining restrictions including quarantine for travelers were removed, and full religious and social activi-ties resumed. The government continued monitoring variants and encouraging vaccination [ 14 , 16 ]. In addition to limiting COVID-19 transmission, the implemented measures had a clear impact on other respiratory infections, particularly influenza. In Saudi Arabia, influenza activity dropped sharply during the pandemic. As restrictions eased in 2021 and beyond, flu activity gradually returned, both locally and globally. However, the post-pandemic pattern did not fully resemble previous seasons. Some regions showed delayed or prolonged influenza circulation, likely due to reduced immunity and changes in circulating subtypes [ 9 , 16 ]. Continuous surveil-lance and research are crucial in understanding whether flu seasons will eventually return to their pre-pandemic norms or if permanent changes in transmission patterns will persist. This retro-spective cross-sectional study explores the variation in flu activity before and after the COVID-19 pandemic in Saudi Arabia, using data publicly available from the WHO. 2. Materials and Methods 2.1. Data Collection We used the FluNet database, an online surveillance tool maintained by the WHO. Pre-COVID-19 displays influenza subtype activity from 2017-03 to 2020-12 year-week (ISO 8601 calendar), while post-COVID-19 reflects influenza activity from 2021-03 to 2024-12 year-week (ISO 8601 calendar). All data were obtained from sentinel surveillance as indicated by the reporting country. 2.2. Data Analysis To evaluate the difference in the proportion of positive influenza cases between the pre- and post-COVID-19 lockdown periods, a two-proportion z-test was conducted. Chi-Square Test was used to compare the observed frequencies of each subtype (A H1, A H1N1pdm09, A H3, A not subtyped, and B lineage not determined) in pre-COVID-19 positive cases. For seasonal decom-position, STL (Seasonal-Trend Decomposition using LOESS) method was performed to extract seasonal patterns from the weekly time series data for each influenza subtype. Subtypes were analyzed separately for the pre- and post-COVID-19 periods to capture the differences in flu activity. A Kolmogorov-Smirnov (KS) test was performed to compare the seasonal distributions of each subtype in the pre- and post-pandemic periods. Figures were created using Python with the Matplotlib library. GraphPad Prism 10 was used for statistical tests. 3. Results 3.1. Total Influenza Testing Numbers Pre- and Post-COVID-19 Lockdown As shown in table.1, a total of 28,767 influenza tests were conducted during the pre-COVID-19 period (early 2017 to late 2020), of which 4,828 (16.78%) tested positive and 23,939 (83.22%) tested negative. In contrast, during the post-COVID-19 lockdown period (early 2021to late 2024), testing increased substantially to 38,360, with 7,497 (19.54%) positives and 30,863 (80.46%) negatives. This represents a 33.2% increase in testing capacity after the pandemic period. Importantly, the proportion of positive influenza cases also increased by 2.76% during this time. The two-proportion z-test confirmed that this increase was statistically significant (p < 0.0001). Although this rise in positivity may reflect increased influenza circulation, it could also be influenced by extended surveillance capacity and greater public health attention post-pandemic. Table 1 Summary of Influenza Testing and Results (Pre and Post COVID-19 Lockdown) Pre-COVID-19 Post-COVID-19 N % N % Total Tests Conducted 28767 100.00 38360 100.00 Positive Cases 4828 16.78 7497 19.54 Negative Cases 23939 83.22 30863 80.46 3.2. Prevalence of Influenza Subtypes Among Positive Cases Table 2 shows the distribution of influenza subtypes among all positive cases in the pre and post COVID-19 periods. Before the pandemic, A(H1N1) pdm09 was the most frequently detected sub-type, accounting for 39.23% of positive cases. However, this dropped significantly to 19.99% in the post-COVID period (p < 0.0001). In contrast, A(H3), which was almost absent prior to the pandemic (0.02%), showed a significant increase to 17.59% of positive cases post-COVID (p < 0.0001), suggesting a shift in dominant circulating strains post-pandemic, potentially due to im-munity gaps from reduced exposure during COVID-19. The proportion of A not subtyped cases remained relatively stable before and after the pandemic (34.09% versus 33.64%). Influenza B (lineage not determined) showed a slight but statistically significant increase from 26.62–28.74% (p = 0.017). The A(H1) subtype continued to be rare in both periods, with no meaningful difference observed (0.04% pre-pandemic versus 0.03% post-pandemic, p = 0.657). These findings indicate a clear shift in subtype circulation following the pandemic, particularly the reduction in A(H1N1)pdm09 and the increased detection of A(H3). Table 2 Distribution of Influenza Subtypes Among Positive Cases (Pre and Post COVID-19 Lockdown) Pre-COVID-19 Post-COVID-19 p- value N % N % A (H1) 2 0.04 2 0.03 0.657 A (H1N1) pdm09 1894 39.23 1499 19.99 < 0.0001 A (H3) 1 0.02 1319 17.59 < 0.0001 A not subtyped 1646 34.09 2522 33.64 0.657 B (lineage not determined) 1285 26.62 2155 28.74 0.017 Total 4828 100.00 7497 100.00 3.3. The Impact of COVID-19 Lockdown on the Seasonal Trends of Influenza Subtypes The seasonal trends of influenza subtypes before and after the COVID-19 pandemic, based on smoothed data (Fig. 1 ), reveal important shifts in subtype circulation patterns. Prior to the pandemic, A(H1N1)pdm09 was the most frequently detected subtype, with a gradual increase in activity over time. A(not subtyped) and B (lineage not determined) also showed sustained circu-lation throughout the pre-pandemic years, while A(H3) and A(H1) remained at low levels. In the post-COVID-19 period, subtype activity changed considerably. A(H1N1)pdm09 declined steadily, while A(H3) emerged with increasing presence starting in 2023. A(not subtyped) showed a moderate increase in activity during the post-pandemic period, while B (lineage not determined) peaked in 2022 and declined thereafter. A(H1) remained consistently low through-out. The post-pandemic pattern also differed in terms of timing and consistency. Compared to the clearer seasonal patterns observed before 2020, the recovery in influenza circulation after the pandemic appeared delayed and more gradual. These shifts may reflect reduced population im-munity due to suppressed circulation during the pandemic, as well as changes in dominant strains. To statistically assess changes in subtype distribution over time, a Kolmogorov-Smirnov (KS) test was performed (Table 3 ). Significant differences were observed for A(H1N1)pdm09, A(H3), and B (lineage not determined), with the most pronounced shift found in A(H3) (KS statistic = 0.5488, p = 4.53 × 10⁻²²). A(H1) did not show meaningful change. For all combined subtypes, the KS statistic was 0.2503 (p = 0.00017), indicating a moderate but significant distributional dif-ference between the two periods. Table 3 Kolmogorov-Smirnov (KS) Test Results for Influenza Subtypes Among Positive Cases (Pre and Post COVID-19 Lockdown) KS test p-value A (H1) 0.0077 1 A (H1N1) pdm09 0.252 0.00015 A (H3) 0.5488 4.53 × 10⁻²² A not subtyped 0.1694 0.0198 B (lineage not determined) 0.2229 0.0007 Combined 0.2503 0.00017 4. Discussion The study evaluates the effect of the COVID-19 pandemic on influenza virus patterns in Saudi Arabia, by influenza activity across pre- and post-pandemic periods. The findings reveal im-portant changes in influenza epidemiology within the country, which also reflect broader global trends observed during and after the pandemic. A marked increase in influenza testing was ob-served in Saudi Arabia following the pandemic. This may reflect heightened awareness of res-piratory infections, as well as improvements in the healthcare system’s capacity to detect viral outbreaks[ 14 , 17 ] As in many other countries, the pandemic prompted a shift in public health strategy, with a stronger focus on early detection of respiratory viruses to prevent community spread[ 18 ]. The scale-up of COVID-19 testing infrastructure also contributed indirectly to better influenza surveillance and reporting capacity in Saudi Arabia [ 14 , 19 ]. The COVID-19 pandemic caused large disruptions to daily life on an unprecedented scale. Sev-eral reports suggest that changes in social interactions and mobility patterns due to COVID-19 restriction measures have influenced the typical seasonal trends of various infectious diseases, including influenza [ 20 – 22 ]. In this study, we observed a significant increase in confirmed in-fluenza cases in Saudi Arabia following the pandemic, compared to the pre-pandemic period. This observation is consistent with findings from other countries, where a resurgence in influen-za activity was reported after COVID-19 restrictions were lifted [ 23 – 25 ]. Recent national esti-mates have also confirmed this trend in Saudi Arabia, showing high hospitalization rates for in-fluenza-associated illness during the 2022–2023 season, particularly among children under five and adults aged 65 years and older. (PMID: 40111565). It has been proposed that the resurgence of influenza after the COVID-19 pandemic may be linked to the "immune gap." Public health measures such as lockdowns, social distancing, and mask-wearing drastically reduced the popu-lation's exposure to influenza and other common respiratory pathogens during the pandemic. As a result, community immunity levels to those pathogens dropped significantly. When COVID-19 restrictions were lifted, this reduced immunity left individuals more susceptible to severe flu outbreaks. The delayed exposure to these pathogens likely contributed to the sharp rebound in influenza cases post-pandemic, particularly in 2023 [ 26 ]. Another potential factor contributing to the observed increase in influenza cases post-COVID-19 in Saudi Arabia is the decreased admin-istering of flu vaccines among the population [ 12 , 27 ]. During the pandemic, the global focus shifted predominantly toward COVID-19 vaccinations, and in Saudi Arabia, a substantial portion of the population prioritized receiving the COVID-19 vaccine. This shift in focus inadvertently led to a decreased emphasis on other routine immunizations, including the seasonal flu vaccine, which may have contributed to the significant rise rebound of influenza cases in the country [ 12 , 27 – 29 ]. The H1N1 pdm09 first emerged in 2009/2010, causing a flu pandemic. Since then, the H1N1 pdm09 strain has become the predominant cause of seasonal influenza in several countries, in-cluding Saudi Arabia [ 30 – 32 ]. There were conflicting reports regarding the dominant influenza strain in Saudi Arabia before the COVID-19 pandemic [ 33 , 34 ]. However, our results suggest that H1N1 was the predominant strain in the country until the implementation of national lockdown measures. One of the interesting findings in the presented study is the dramatic increase in A (H3) cases post-COVID-19, compared to its near absence before the pandemic. A (H3) likely re-fers to the H3N2 subtype, as only the hemagglutinin protein was tested, with no specification for neuraminidase (N). This aligns with global trends, as several studies have confirmed the resur-gence of H3N2 following the relaxation of COVID-19 restrictions [ 35 , 36 ]. The increase in H3N2 infections following the relaxation of COVID-19 measures can be attributed to several factors. A primary factor is the comparatively high mutation rate of H3N2 in relative to other influenza strains, including H1N1. H3N2 tends to exhibit antigenic drift more frequently, with new vari-ants emerging approximately every 2–5 years, whereas H1N1 typically undergoes such changes less often, around every 3–8 years [ 37 , 38 ]. This rapid antigenic evolution gives H3N2 a competi-tive advantage, particularly in a population with limited exposure to the influenza virus during the COVID-19 restriction measures period, leading to decreased immunity against it. Another factor could have resulted from the resumption of international travel, which likely facilitated the re-introduction of the H3N2 strain into the Saudi population. Saudi Arabia heavily relies on migrant workers from countries where H3N2 is actively circulating, such as India, Pakistan, and Egypt. The influx of travelers from these regions likely facilitated the re-introduction and sub-sequent spread of H3N2 in Saudi Arabia [ 39 – 41 ]. Our study has few limitations that should be considered in interpreting the findings. Pri-marily, it relies solely on data from the FluNet database, which, though comprehensive, may not account for all influenza cases, especially those unreported or undiagnosed. Addi-tionally, the generalizability of the findings may be limited outside Saudi Arabia due to variations in pandemic response measures and healthcare infrastructure. Future studies could enhance these findings by incorporating broader data sources and patient-level in-formation to further clarify post-pandemic influenza trends. 5. Conclusions In conclusion, our study highlights significant shifts in influenza activity in Saudi Arabia post-COVID-19, with an increase in influenza testing and a notable change in the prevalence of influenza subtypes. The decline in A(H1N1) pdm09 and the rise in A(H3) reflect global patterns observed in other regions, underscoring the broader impact of the COVID-19 pandemic on res-piratory virus epidemiology. Continuous surveillance and research are essential to understanding how these trends will evolve and to guide future public health strategies for managing influenza outbreaks in the post-pandemic world. Abbreviations COVID-19 Coronavirus Disease 2019 WHO World Health Organization HA Hemagglutinin NA Neuraminidase H1N1 Influenza A subtype H1N1 H3N2 Influenza A subtype H3N2 STL Seasonal-Trend Decomposition using LOESS KS test Kolmogorov-Smirnov test B/Victoria Influenza B virus, Victoria lineage B/Yamagata Influenza B virus, Yamagata lineage Declarations Ethics approval and consent to participate: Not applicable. The study used aggregated, de-identified data on patient testing from the publicly accessible WHO FluNet database. As no individual-level or personally identifiable information was used, informed consent was not required. Clinical Trial: Not applicable. Consent for publication: Not applicable. This manuscript does not contain any individual person’s data in any form (including individual details, images, or videos). Availability of data and materials: The data supporting the findings of this study are publicly available from the WHO FluNet platform at https://www.who.int/tools/flunet. Competing interests: The authors declare that they have no competing interests. Funding: This research was funded by the Ongoing Research Funding program, (ORF-2025-1353), King Saud University, Riyadh, Saudi Arabia. Author Contributions: Conceptualization, L.A.; methodology, L.A, and A.Alr..; software L.A, and A.Alr., formal analysis, L.A.; writing—original draft preparation, S.A., E.A., L.F., A.Alm., A.Alr. and L.A.; writing—review and editing, S.A., E.A., L.F., A.Alm., A.Alr. and L.A.; visualization, A.Alr.; funding acquisition, L.A. All authors have read and agreed to the published version of the manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6949129","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":487474800,"identity":"7dd7954e-3ae2-465f-983a-93235325a3da","order_by":0,"name":"Lama Alzamil","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIie3OMQuCQBTA8RNBl5NbX5B9BkMQwaGv4hHk4tDYEHEhOBl+lSZ3EXK5aG3MxS2wsaHodGtIa2u4PxzHg/vxDiGZ7A+zkMrEBWOCu1n9higdwaPkR4Kwxb8meh4199DFNi9rQCuPMlJc+gmmbLrLADvHxAHEA8pgYQ18jDLfaMkJa6DEhSBogJCK5Q9B7FSvQXkKQsqmnwDdRu0Wy2AOKEwQFA5sgSpSTUGAc9v1D4EdQ7jsJbN0Xtyu2WZCkqA6N2vPTEm57yXv+eJoP7yXyWQy2YdeFFpAjI+kkUcAAAAASUVORK5CYII=","orcid":"","institution":"King Saud University","correspondingAuthor":true,"prefix":"","firstName":"Lama","middleName":"","lastName":"Alzamil","suffix":""},{"id":487474801,"identity":"116aa6f4-c734-4dd4-bb94-704ae64007ee","order_by":1,"name":"Abdulrahman Alrezaihi","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Abdulrahman","middleName":"","lastName":"Alrezaihi","suffix":""},{"id":487474802,"identity":"723e9c9c-0960-45b8-840e-411dfc1d8ca8","order_by":2,"name":"Abdulaziz Almuqrin","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Abdulaziz","middleName":"","lastName":"Almuqrin","suffix":""},{"id":487474803,"identity":"e303712c-8645-460c-9009-944d8cddbd28","order_by":3,"name":"Esraa Aldawood","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Esraa","middleName":"","lastName":"Aldawood","suffix":""},{"id":487474804,"identity":"992dc186-2909-40fc-9172-54c8bf90161d","order_by":4,"name":"Layla Faqih","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Layla","middleName":"","lastName":"Faqih","suffix":""},{"id":487474805,"identity":"4c072c5f-8d02-420c-a61a-7a0265ba5c11","order_by":5,"name":"Sarah Alharbi","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Alharbi","suffix":""}],"badges":[],"createdAt":"2025-06-22 11:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6949129/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6949129/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87382905,"identity":"c0ffcfc9-2f38-48c4-b819-9c7341685862","added_by":"auto","created_at":"2025-07-23 08:39:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":626393,"visible":true,"origin":"","legend":"\u003cp\u003eSmoothed seasonal trends of laboratory-confirmed influenza subtypes in Saudi Arabia before (March 2017–December 2020) and after (March 2021–May 2024) the COVID-19 pandemic. Data were obtained from the WHO FluNet surveillance platform. Each curve represents a different influenza subtype, plot-ted using weekly case counts and smoothed to highlight overall trends. The top panel shows pre-pandemic patterns with clear winter peaks, while the bottom panel reflects altered post-pandemic circulation, including reduced A(H1N1)pdm09 activity and a rise in A(H3) starting in 2023.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6949129/v1/a21be9f91d663d58a8b022cf.png"},{"id":109166084,"identity":"0e802a7c-72e3-4392-8669-aea44ce8b925","added_by":"auto","created_at":"2026-05-13 08:16:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":729067,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6949129/v1/72c9258e-3294-4a1c-8d2e-9c2d9fffebdb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of COVID-19 on Influenza Virus Trends and Subtypes in Saudi Arabia: A Cross-Sectional Analysis","fulltext":[{"header":"1. Background","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eInfluenza, commonly referred to as the flu, is a highly contagious viral infection that affect the respiratory system. It poses a significant public health challenge due to its ability to cause seasonal epidemics and, at times, global pandemics, resulting in widespread morbidity and mortality. Transmission occurs via respiratory droplets, especially in crowded or enclosed settings. While symptoms vary in severity, the virus poses significant risks to vulnerable groups such as the elderly, children, and those with underlying health conditions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe influenza virus belongs to the Orthomyxoviridae family and is classified into four types based on the antigenic properties of two key surface proteins, hemagglutinin (HA) and neuraminidase (NA). The four types of influenza viruses are Influenza A, B, C, and D. Influenza A, the most common and severe, is further subtyped (e.g., H1N1, H3N2), while Influenza B is divided into two lineages: B/Yamagata and B/Victoria [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Annual surveillance by the World Health Organization (WHO) monitors circulating strains primarily types A and B to inform vaccine composition. However, continual viral evolution through antigenic drift and shift presents ongo-ing challenges in influenza prevention and control [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn Saudi Arabia, the flu season generally peaks between November and March, following pat-terns seen in other temperate countries. However, the country\u0026rsquo;s role as a hub for religious pil-grimages, particularly Hajj and Umrah, adds a unique dimension to its flu burden. These mass gatherings involve prolonged close contact among individuals from diverse regions, creating opportunities for the introduction and spread of novel strains [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Saudi Arabia has implement-ed seasonal vaccination campaigns targeting high-risk groups and encouraging uptake among pilgrims. However, disparities in flu vaccination rates among international visitors complicate these efforts [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe global response to COVID-19 significantly disrupted the transmission of respiratory viruses, including influenza. In Saudi Arabia, flu activity declined sharply following the introduction of widespread public health interventions. Typically, the country experiences seasonal peaks during cooler months, but the emergence of COVID-19 in early 2020 altered both global and local pat-terns. Measures such as lockdowns, mask mandates, travel restrictions, and social distancing drastically reduced influenza transmission [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The WHO estimates that influenza causes 3 to 5\u0026nbsp;million cases of severe illness and up to 650,000 respiratory related deaths, with variable sea-sonality depending on geographic region [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Between 2015 and 2019, Saudi Arabia experi-enced predictable flu seasons, with strains such as H1N1, H3N2, and influenza B circulating consistently. Public health measures focused on annual vaccinations and routine prevention strategies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, the emergence of COVID-19 in early 2020 brought a major shift in public health priorities and actions. The global response to the novel coronavirus was swift and severe, leading to extraordinary interventions to limit its spread [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSaudi Arabia implemented strong public health measures to control COVID-19, evolving them as the situation progressed. Initial steps included health screenings and travel bans for high-risk countries. On February 27, 2020, Umrah was suspended, and by March, following the first con-firmed case, all international and domestic travel was halted [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA national lockdown followed, with closures of schools, mosques, and public venues. As cases stabilised, restrictions were eased; businesses reopened under health protocols, and mask man-dates and social distancing remained in effect. In late 2020, gradual reopening resumed. Travel restrictions were loosened, Umrah restarted under strict guidelines, and a national vaccination campaign began in December. By early 2021, vaccinated individuals received expanded free-doms, and a limited Hajj was conducted for vaccinated or recovered residents. Most restrictions were lifted by late 2021, though some precautions persisted [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In March 2022, remaining restrictions including quarantine for travelers were removed, and full religious and social activi-ties resumed. The government continued monitoring variants and encouraging vaccination [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In addition to limiting COVID-19 transmission, the implemented measures had a clear impact on other respiratory infections, particularly influenza. In Saudi Arabia, influenza activity dropped sharply during the pandemic. As restrictions eased in 2021 and beyond, flu activity gradually returned, both locally and globally. However, the post-pandemic pattern did not fully resemble previous seasons. Some regions showed delayed or prolonged influenza circulation, likely due to reduced immunity and changes in circulating subtypes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Continuous surveil-lance and research are crucial in understanding whether flu seasons will eventually return to their pre-pandemic norms or if permanent changes in transmission patterns will persist. This retro-spective cross-sectional study explores the variation in flu activity before and after the COVID-19 pandemic in Saudi Arabia, using data publicly available from the WHO.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Data Collection\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWe used the FluNet database, an online surveillance tool maintained by the WHO. Pre-COVID-19 displays influenza subtype activity from 2017-03 to 2020-12 year-week (ISO 8601 calendar), while post-COVID-19 reflects influenza activity from 2021-03 to 2024-12 year-week (ISO 8601 calendar). All data were obtained from sentinel surveillance as indicated by the reporting country.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Data Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo evaluate the difference in the proportion of positive influenza cases between the pre- and post-COVID-19 lockdown periods, a two-proportion z-test was conducted. Chi-Square Test was used to compare the observed frequencies of each subtype (A H1, A H1N1pdm09, A H3, A not subtyped, and B lineage not determined) in pre-COVID-19 positive cases. For seasonal decom-position, STL (Seasonal-Trend Decomposition using LOESS) method was performed to extract seasonal patterns from the weekly time series data for each influenza subtype. Subtypes were analyzed separately for the pre- and post-COVID-19 periods to capture the differences in flu activity. A Kolmogorov-Smirnov (KS) test was performed to compare the seasonal distributions of each subtype in the pre- and post-pandemic periods. Figures were created using Python with the Matplotlib library. GraphPad Prism 10 was used for statistical tests.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Total Influenza Testing Numbers Pre- and Post-COVID-19 Lockdown\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs shown in table.1, a total of 28,767 influenza tests were conducted during the pre-COVID-19 period (early 2017 to late 2020), of which 4,828 (16.78%) tested positive and 23,939 (83.22%) tested negative. In contrast, during the post-COVID-19 lockdown period (early 2021to late 2024), testing increased substantially to 38,360, with 7,497 (19.54%) positives and 30,863 (80.46%) negatives. This represents a 33.2% increase in testing capacity after the pandemic period. Importantly, the proportion of positive influenza cases also increased by 2.76% during this time. The two-proportion z-test confirmed that this increase was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Although this rise in positivity may reflect increased influenza circulation, it could also be influenced by extended surveillance capacity and greater public health attention post-pandemic.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of Influenza Testing and Results (Pre and Post COVID-19 Lockdown)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003ePre-COVID-19\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003ePost-COVID-19\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Tests Conducted\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38360\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePositive Cases\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e19.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNegative Cases\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23939\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30863\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e80.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Prevalence of Influenza Subtypes Among Positive Cases\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the distribution of influenza subtypes among all positive cases in the pre and post COVID-19 periods. Before the pandemic, A(H1N1) pdm09 was the most frequently detected sub-type, accounting for 39.23% of positive cases. However, this dropped significantly to 19.99% in the post-COVID period (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In contrast, A(H3), which was almost absent prior to the pandemic (0.02%), showed a significant increase to 17.59% of positive cases post-COVID (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), suggesting a shift in dominant circulating strains post-pandemic, potentially due to im-munity gaps from reduced exposure during COVID-19. The proportion of A not subtyped cases remained relatively stable before and after the pandemic (34.09% versus 33.64%). Influenza B (lineage not determined) showed a slight but statistically significant increase from 26.62\u0026ndash;28.74% (p\u0026thinsp;=\u0026thinsp;0.017). The A(H1) subtype continued to be rare in both periods, with no meaningful difference observed (0.04% pre-pandemic versus 0.03% post-pandemic, p\u0026thinsp;=\u0026thinsp;0.657). These findings indicate a clear shift in subtype circulation following the pandemic, particularly the reduction in A(H1N1)pdm09 and the increased detection of A(H3).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of Influenza Subtypes Among Positive Cases (Pre and Post COVID-19 Lockdown)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePre-COVID-19\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003ePost-COVID-19\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003ep- value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.657\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H1N1) pdm09\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H3)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA not subtyped\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1646\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.657\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB (lineage not determined)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1285\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4828\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.3. The Impact of COVID-19 Lockdown on the Seasonal Trends of Influenza Subtypes\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe seasonal trends of influenza subtypes before and after the COVID-19 pandemic, based on smoothed data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), reveal important shifts in subtype circulation patterns. Prior to the pandemic, A(H1N1)pdm09 was the most frequently detected subtype, with a gradual increase in activity over time. A(not subtyped) and B (lineage not determined) also showed sustained circu-lation throughout the pre-pandemic years, while A(H3) and A(H1) remained at low levels.\u003c/p\u003e\u003cp\u003eIn the post-COVID-19 period, subtype activity changed considerably. A(H1N1)pdm09 declined steadily, while A(H3) emerged with increasing presence starting in 2023. A(not subtyped) showed a moderate increase in activity during the post-pandemic period, while B (lineage not determined) peaked in 2022 and declined thereafter. A(H1) remained consistently low through-out.\u003c/p\u003e\u003cp\u003eThe post-pandemic pattern also differed in terms of timing and consistency. Compared to the clearer seasonal patterns observed before 2020, the recovery in influenza circulation after the pandemic appeared delayed and more gradual. These shifts may reflect reduced population im-munity due to suppressed circulation during the pandemic, as well as changes in dominant strains.\u003c/p\u003e\u003cp\u003eTo statistically assess changes in subtype distribution over time, a Kolmogorov-Smirnov (KS) test was performed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Significant differences were observed for A(H1N1)pdm09, A(H3), and B (lineage not determined), with the most pronounced shift found in A(H3) (KS statistic\u0026thinsp;=\u0026thinsp;0.5488, p\u0026thinsp;=\u0026thinsp;4.53 \u0026times; 10⁻\u0026sup2;\u0026sup2;). A(H1) did not show meaningful change. For all combined subtypes, the KS statistic was 0.2503 (p\u0026thinsp;=\u0026thinsp;0.00017), indicating a moderate but significant distributional dif-ference between the two periods.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKolmogorov-Smirnov (KS) Test Results for Influenza Subtypes Among Positive Cases (Pre and Post COVID-19 Lockdown)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKS test\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H1N1) pdm09\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA (H3)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.53 \u0026times; 10⁻\u0026sup2;\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eA not subtyped\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0198\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eB (lineage not determined)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCombined\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.2503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe study evaluates the effect of the COVID-19 pandemic on influenza virus patterns in Saudi Arabia, by influenza activity across pre- and post-pandemic periods. The findings reveal im-portant changes in influenza epidemiology within the country, which also reflect broader global trends observed during and after the pandemic. A marked increase in influenza testing was ob-served in Saudi Arabia following the pandemic. This may reflect heightened awareness of res-piratory infections, as well as improvements in the healthcare system\u0026rsquo;s capacity to detect viral outbreaks[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] As in many other countries, the pandemic prompted a shift in public health strategy, with a stronger focus on early detection of respiratory viruses to prevent community spread[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The scale-up of COVID-19 testing infrastructure also contributed indirectly to better influenza surveillance and reporting capacity in Saudi Arabia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe COVID-19 pandemic caused large disruptions to daily life on an unprecedented scale. Sev-eral reports suggest that changes in social interactions and mobility patterns due to COVID-19 restriction measures have influenced the typical seasonal trends of various infectious diseases, including influenza [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In this study, we observed a significant increase in confirmed in-fluenza cases in Saudi Arabia following the pandemic, compared to the pre-pandemic period. This observation is consistent with findings from other countries, where a resurgence in influen-za activity was reported after COVID-19 restrictions were lifted [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Recent national esti-mates have also confirmed this trend in Saudi Arabia, showing high hospitalization rates for in-fluenza-associated illness during the 2022\u0026ndash;2023 season, particularly among children under five and adults aged 65 years and older. (PMID: 40111565). It has been proposed that the resurgence of influenza after the COVID-19 pandemic may be linked to the \"immune gap.\" Public health measures such as lockdowns, social distancing, and mask-wearing drastically reduced the popu-lation's exposure to influenza and other common respiratory pathogens during the pandemic. As a result, community immunity levels to those pathogens dropped significantly. When COVID-19 restrictions were lifted, this reduced immunity left individuals more susceptible to severe flu outbreaks. The delayed exposure to these pathogens likely contributed to the sharp rebound in influenza cases post-pandemic, particularly in 2023 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Another potential factor contributing to the observed increase in influenza cases post-COVID-19 in Saudi Arabia is the decreased admin-istering of flu vaccines among the population [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. During the pandemic, the global focus shifted predominantly toward COVID-19 vaccinations, and in Saudi Arabia, a substantial portion of the population prioritized receiving the COVID-19 vaccine. This shift in focus inadvertently led to a decreased emphasis on other routine immunizations, including the seasonal flu vaccine, which may have contributed to the significant rise rebound of influenza cases in the country [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe H1N1 pdm09 first emerged in 2009/2010, causing a flu pandemic. Since then, the H1N1 pdm09 strain has become the predominant cause of seasonal influenza in several countries, in-cluding Saudi Arabia [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. There were conflicting reports regarding the dominant influenza strain in Saudi Arabia before the COVID-19 pandemic [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, our results suggest that H1N1 was the predominant strain in the country until the implementation of national lockdown measures. One of the interesting findings in the presented study is the dramatic increase in A (H3) cases post-COVID-19, compared to its near absence before the pandemic. A (H3) likely re-fers to the H3N2 subtype, as only the hemagglutinin protein was tested, with no specification for neuraminidase (N). This aligns with global trends, as several studies have confirmed the resur-gence of H3N2 following the relaxation of COVID-19 restrictions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The increase in H3N2 infections following the relaxation of COVID-19 measures can be attributed to several factors. A primary factor is the comparatively high mutation rate of H3N2 in relative to other influenza strains, including H1N1. H3N2 tends to exhibit antigenic drift more frequently, with new vari-ants emerging approximately every 2\u0026ndash;5 years, whereas H1N1 typically undergoes such changes less often, around every 3\u0026ndash;8 years [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This rapid antigenic evolution gives H3N2 a competi-tive advantage, particularly in a population with limited exposure to the influenza virus during the COVID-19 restriction measures period, leading to decreased immunity against it. Another factor could have resulted from the resumption of international travel, which likely facilitated the re-introduction of the H3N2 strain into the Saudi population. Saudi Arabia heavily relies on migrant workers from countries where H3N2 is actively circulating, such as India, Pakistan, and Egypt. The influx of travelers from these regions likely facilitated the re-introduction and sub-sequent spread of H3N2 in Saudi Arabia [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur study has few limitations that should be considered in interpreting the findings. Pri-marily, it relies solely on data from the FluNet database, which, though comprehensive, may not account for all influenza cases, especially those unreported or undiagnosed. Addi-tionally, the generalizability of the findings may be limited outside Saudi Arabia due to variations in pandemic response measures and healthcare infrastructure. Future studies could enhance these findings by incorporating broader data sources and patient-level in-formation to further clarify post-pandemic influenza trends.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn conclusion, our study highlights significant shifts in influenza activity in Saudi Arabia post-COVID-19, with an increase in influenza testing and a notable change in the prevalence of influenza subtypes. The decline in A(H1N1) pdm09 and the rise in A(H3) reflect global patterns observed in other regions, underscoring the broader impact of the COVID-19 pandemic on res-piratory virus epidemiology. Continuous surveillance and research are essential to understanding how these trends will evolve and to guide future public health strategies for managing influenza outbreaks in the post-pandemic world.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eCOVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eCoronavirus Disease 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eWorld Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eHA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eHemagglutinin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eNeuraminidase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eH1N1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eInfluenza A subtype H1N1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eH3N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eInfluenza A subtype H3N2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSTL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eSeasonal-Trend Decomposition using LOESS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eKS test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eKolmogorov-Smirnov test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eB/Victoria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eInfluenza B virus, Victoria lineage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eB/Yamagata\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003eInfluenza B virus, Yamagata lineage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable. The study used aggregated, de-identified data on patient testing from the publicly accessible WHO FluNet database. As no individual-level or personally identifiable information was used, informed consent was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Trial:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable. This manuscript does not contain any individual person\u0026rsquo;s data in any form (including individual details, images, or videos).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data supporting the findings of this study are publicly available from the WHO FluNet platform at https://www.who.int/tools/flunet.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by the Ongoing Research Funding program, (ORF-2025-1353), King Saud University, Riyadh, Saudi Arabia. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, L.A.; methodology, L.A, and A.Alr..; software L.A, and A.Alr., formal analysis, L.A.; writing\u0026mdash;original draft preparation, S.A., E.A., L.F., A.Alm., A.Alr. and L.A.; writing\u0026mdash;review and editing, S.A., E.A., L.F., A.Alm., A.Alr. and L.A.; visualization, A.Alr.; funding acquisition, L.A. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors thank the Ongoing Research Funding program, (ORF-2025-1353), King Saud University, Riyadh, Saudi Arabia. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\u003cp dir=\"LTR\"\u003e\u003cstrong\u003eDisclaimer/Publisher\u0026rsquo;s Note:\u003c/strong\u003e The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLiang Y. Pathogenicity and virulence of influenza. Virulence. 2023 Jun 20;14(1):2223057. \u003c/li\u003e\n\u003cli\u003eNypaver C, Dehlinger C, Carter C. 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Emerg Infect Dis. 2018 Oct;24(10):1961. \u003c/li\u003e\n\u003cli\u003eAlshahrani SM, Zahrani Y. Prevalence and Predictors of Seasonal Influenza Vaccine Uptake in Saudi Arabia Post COVID-19: A Web-Based Online Cross-Sectional Study. Vaccines. 2023 Feb 3;11(2):353. \u003c/li\u003e\n\u003cli\u003eSayed AA. The Progressive Public Measures of Saudi Arabia to Tackle Covid-19 and Limit Its Spread. Int J Environ Res Public Health. 2021 Jan 18;18(2):783. \u003c/li\u003e\n\u003cli\u003eSheerah HA, Almuzaini Y, Khan A. Public Health Challenges in Saudi Arabia during the COVID-19 Pandemic: A Litera-ture Review. Healthc Basel Switz. 2023 Jun 15;11(12):1757. \u003c/li\u003e\n\u003cli\u003eKhan A, Alsofayan Y, Alahmari A, Alowais J, Algwizani A, Alserehi H, et al. COVID-19 in Saudi Arabia: the national health response. East Mediterr Health J Rev Sante Mediterr Orient Al-Majallah Al-Sihhiyah Li-Sharq Al-Mutawassit. 2021 Dec 1;27(11):1114\u0026ndash;24. \u003c/li\u003e\n\u003cli\u003eSalam AA, Al-Khraif RM, Elsegaey I. COVID-19 in Saudi Arabia: An Overview. Front Public Health. 2021;9:736942. \u003c/li\u003e\n\u003cli\u003eChow EJ, Uyeki TM, Chu HY. The effects of the COVID-19 pandemic on community respiratory virus activity. Nat Rev Microbiol. 2023 Mar;21(3):195\u0026ndash;210. \u003c/li\u003e\n\u003cli\u003eOlsen SJ, Winn AK, Budd AP, Prill MM, Steel J, Midgley CM, et al. Changes in Influenza and Other Respiratory Virus Activity During the COVID-19 Pandemic - United States, 2020-2021. MMWR Morb Mortal Wkly Rep. 2021 Jul 23;70(29):1013\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eAlBahrani S, AlZahrani SJ, Al-Maqati TN, Almehbash A, Alshammari A, Bujlai R, et al. Dynamic Patterns and Predomi-nance of Respiratory Pathogens Post-COVID-19: Insights from a Two-Year Analysis. J Epidemiol Glob Health. 2024 Jun;14(2):311\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003ePeng JL, Xu K, Tong Y, Wang SZ, Huang HD, Bao CJ, et al. Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province, China, 2020\u0026ndash;2023 post-COVID-19 pandemic. BMC Infect Dis. 2024 Oct 22;24:1189. \u003c/li\u003e\n\u003cli\u003eYang M, Chen C, Zhang X, Cao K, Du Y, Jiang D, et al. Social contact patterns with acquaintances and strangers related to influenza in the post-pandemic era. J Public Health [Internet]. 2024 Feb 16 [cited 2024 Nov 1]; Available from: https://doi.org/10.1007/s10389-024-02213-2\u003c/li\u003e\n\u003cli\u003eLessani MN, Li Z, Jing F, Qiao S, Zhang J, Olatosi B, et al. Human mobility and the infectious disease transmission: a sys-tematic review. Geo-Spat Inf Sci. 0(0):1\u0026ndash;28. \u003c/li\u003e\n\u003cli\u003eLiu P, Cheng F, Su L, Ye Z, Xu M, Lu L, et al. An outbreak of influenza A in Shanghai after ending the zero-COVID policy in February-March 2023. J Infect. 2023 Aug;87(2):e33\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003ePendrey CG, Strachan J, Peck H, Aziz A, Moselen J, Moss R, et al. The re-emergence of influenza following the COVID-19 pandemic in Victoria, Australia, 2021 to 2022. Euro Surveill Bull Eur Sur Mal Transm Eur Commun Dis Bull. 2023 Sep;28(37):2300118. \u003c/li\u003e\n\u003cli\u003eWrorld Health Organization. Influenza Update N\u0026deg; 421 [Internet]. [cited 2024 Nov 1]. Available from: https://www.who.int/publications/m/item/influenza-update-n-421\u003c/li\u003e\n\u003cli\u003eYang R, Xu H, Zhang Z, Liu Q, Zhao R, Zheng G, et al. The Epidemiology of Pathogens in Community-Acquired Pneumo-nia Among Children in Southwest China Before, During and After COVID-19 Non-pharmaceutical Interventions: A Cross-Sectional Study. Influenza Other Respir Viruses. 2024 Aug;18(8):e13361. \u003c/li\u003e\n\u003cli\u003eMinshawi F, Samannodi M, Alwafi H, Assaggaf HM, Almatrafi MA, Salawati E, et al. The Influence of COVID-19 Pan-demic on Influenza Immunization in Saudi Arabia: Cross-Sectional Study. J Multidiscip Healthc. 2022;15:1841\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eSales IA, Syed W, Almutairi MF, Al Ruthia Y. Public Knowledge, Attitudes, and Practices toward Seasonal Influenza Vac-cine in Saudi Arabia: A Cross-Sectional Study. Int J Environ Res Public Health. 2021 Jan 8;18(2):479. \u003c/li\u003e\n\u003cli\u003eMa L, Han X, Ma Y, Yang Y, Xu Y, Liu D, et al. Decreased influenza vaccination coverage among Chinese healthcare workers during the COVID-19 pandemic. Infect Dis Poverty. 2022 Oct 8;11(1):105. \u003c/li\u003e\n\u003cli\u003eFarrag MA, Hamed ME, Amer HM, Almajhdi FN. Epidemiology of respiratory viruses in Saudi Arabia: toward a complete picture. Arch Virol. 2019 Aug;164(8):1981\u0026ndash;96. \u003c/li\u003e\n\u003cli\u003eFineberg HV. Pandemic preparedness and response--lessons from the H1N1 influenza of 2009. N Engl J Med. 2014 Apr 3;370(14):1335\u0026ndash;42. \u003c/li\u003e\n\u003cli\u003eAbdalla O, Mohammed M, Hakawi AM, Aljifri A, Abdalla M, Eltigani S, et al. Hospital-based surveillance of influenza A(H1N1)pdm09 virus in Saudi Arabia, 2010-2016. Ann Saudi Med. 2020 Feb 6;40(1):1. \u003c/li\u003e\n\u003cli\u003eAlthaqafi A, Farahat F, Alsaedi A, Alshamrani M, Alsaeed MS, AlhajHussein B, et al. Molecular Detection of Influenza A and B Viruses in Four Consecutive Influenza Seasons 2015\u0026ndash;16 to 2018\u0026ndash;19 in a Tertiary Center in Western Saudi Arabia. J Epidemiol Glob Health. 2021 Jun;11(2):208. \u003c/li\u003e\n\u003cli\u003eAl Khatib HA, Al Thani AA, Gallouzi I, Yassine HM. Epidemiological and genetic characterization of pH1N1 and H3N2 influenza viruses circulated in MENA region during 2009\u0026ndash;2017. BMC Infect Dis. 2019 Apr 11;19(1):314. \u003c/li\u003e\n\u003cli\u003eWang X, Walker G, Kim KW, Stelzer-Braid S, Scotch M, Rawlinson WD. The resurgence of influenza A/H3N2 virus in Australia after the relaxation of COVID-19 restrictions during the 2022 season. J Med Virol. 2024;96(9):e29922. \u003c/li\u003e\n\u003cli\u003eLee SS, Viboud C, Petersen E. Understanding the rebound of influenza in the post COVID-19 pandemic period holds im-portant clues for epidemiology and control. Int J Infect Dis. 2022 Aug 4;122:1002. \u003c/li\u003e\n\u003cli\u003ePetrova VN, Russell CA. The evolution of seasonal influenza viruses. Nat Rev Microbiol. 2018 Jan;16(1):47\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eBedford T, Riley S, Barr IG, Broor S, Chadha M, Cox NJ, et al. Global circulation patterns of seasonal influenza viruses vary with antigenic drift. Nature. 2015 Jul 9;523(7559):217\u0026ndash;20. \u003c/li\u003e\n\u003cli\u003eKandeel A, Fahim M, Deghedy O, Roshdy WH, Khalifa MK, Shesheny RE, et al. Resurgence of influenza and respiratory syncytial virus in Egypt following two years of decline during the COVID-19 pandemic: outpatient clinic survey of infants and children, October 2022. BMC Public Health. 2023 Jun 5;23(1):1067. \u003c/li\u003e\n\u003cli\u003eBadar N, Ikram A, Salman M, Saeed S, Mirza HA, Ahad A, et al. Evolutionary analysis of seasonal influenza A viruses in Pakistan 2020\u0026ndash;2023. Influenza Other Respir Viruses. 2024;18(2):e13262. \u003c/li\u003e\n\u003cli\u003ePriyanka, Khandia R, Chopra H, Choudhary OP, Bonilla-Aldana DK, Rodriguez-Morales AJ. The re-emergence of H3N2 influenza: An update on the risk and containment. New Microbes New Infect. 2023 May 4;53:101147. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Influenza, COVID-19 pandemic, H1N1 pdm09, H3N2","lastPublishedDoi":"10.21203/rs.3.rs-6949129/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6949129/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eInfluenza is a highly infectious respiratory illness that imposes a substantial health burden globally. The COVID-19 pandemic led to major shifts in respiratory viruses\u0026rsquo; transmission. This study investigates the effect of the COVID-19 pandemic on influenza virus trends in Saudi Arabia, focusing on changes in influenza activity, subtype distribution, and seasonal patterns across pre- and post-pandemic periods.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eInfluenza data from the World Health Organization (WHO) FluNet database were analyzed, comparing influenza cases, subtype distributions, and seasonal trends before (2017\u0026ndash;2020) and after (2021\u0026ndash;2024) the COVID-19 pandemic in Saudi Arabia. Statistical tests, including the Chi-Square Test, two-proportion z-tests, and the Kolmogorov-Smirnov test, were utilized to evaluate the changes in influenza patterns.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe findings of this study showed a substantial increase in the number of influenza virus testing and positive cases post-COVID-19 compared to the pre-COVID-19 period. In addition, the results revealed an altered distribution of influenza subtypes circulating in the Saudi Arabia post-pandemic, with a notable reduction in the prevalence of H1N1 pdm09 (39.23% vs.19.99%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and a dramatic increase in H3N2 (0.02% vs.17.59%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), which was nearly absent in the pre-pandemic period.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis report underscores significant changes in influenza patterns in Saudi Arabia following the COVID-19 pandemic. These changes are likely influenced by reduced community immunity and the return of international travel after COVID-19 restrictions were lifted. This study highlights the importance of continuous surveillance to inform public health strategies and effectively manage future outbreaks in the post-pandemic landscape.\u003c/p\u003e","manuscriptTitle":"Impact of COVID-19 on Influenza Virus Trends and Subtypes in Saudi Arabia: A Cross-Sectional Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 08:39:45","doi":"10.21203/rs.3.rs-6949129/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7c5f9a1f-a0db-4be7-b51d-b59c90788f38","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Withdrawn","date":"2026-05-13T07:52:44+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T08:15:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-23 08:39:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6949129","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6949129","identity":"rs-6949129","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}