Increased population susceptibility to seasonal influenza during the COVID-19 pandemic in China and the United States

Seasonal Shifts in Influenza, Respiratory Syncytial Virus, and Other Respiratory Viruses After the COVID-19 Pandemic: An Eight-Year Retrospective Study in Jalisco, Mexico

The coronavirus disease 2019 (COVID-19) pandemic profoundly disrupted the epidemiology of respiratory viruses, driven primarily by widespread non-pharmaceutical interventions (NPIs) such as social distancing and masking. This eight-year retrospective study examines the seasonal patterns and incidence of influenza virus, respiratory syncytial virus (RSV), and other respiratory viruses across pre-pandemic, pandemic, and post-pandemic phases in Jalisco, Mexico. Weekly case counts were analyzed using an interrupted time series (ITS) model, segmenting the timeline into these three distinct phases. Significant reductions in respiratory virus circulation were observed during the pandemic, followed by atypical resurgences as NPIs were relaxed. Influenza displayed alternating subtype dominance, with influenza A H3 prevailing in 2022, influenza B surging in 2023, and influenza A H1N1 increasing thereafter, reflecting potential immunity gaps. RSV activity was marked by earlier onset and higher intensity post-pandemic. Other viruses, including human rhinovirus/enterovirus (HRV/HEV) and parainfluenza virus (HPIV), showed altered dynamics, with some failing to return to pre-pandemic seasonality. These findings underscore the need for adaptive surveillance systems and vaccination strategies to address evolving viral patterns. Future research should investigate the long-term public health implications, focusing on vaccination, clinical outcomes, and healthcare preparedness.

Temperature variability and influenza incidence in China: Effect modification by ambient fine particulate matter

This study aims to examine the association between temperature variabilit (TV) exposure and influenza incidence in China, and the modification effect of PM2.5 levels. Data on daily influenza cases, weather conditions, and PM2.5 concentrations were collected from 339 cities across mainland China from 2014 to 2019. TV was computed as the standard deviation of daily maximum and minimum temperatures for the current day and the previous several days (i.e., TV0-1 to TV0-7). A space-time-stratified case-crossover design with conditional Poisson regression was employed. Overall, each 1 °C increase in TV0-6 was linked to 3.3 % (95 % CI: 3.1 %, 3.5 %) rise in influenza incidence, potentially attributing 14.73 % (95 % CI: 14.08 %, 15.37 %) of cases to this exposure. PM2.5 concentration showed substantial modification effect on the association, such that the relative risk (RR) of influenza incidence grew from 1.027 (95 % CI: 1.025, 1.029) to 1.040 (95 % CI: 1.038, 1.042) as PM2.5 levels increased from 15 to 75 μg/m³ . Females and individuals over 65 years old were more susceptible to TV exposure and the PM2.5 modification. Stronger effects were observed during cold season and in North region. The findings highlight the integrating considerations of TV and PM2.5 exposures into public health measures for influenza prevention and control.

The circulating characteristics of common respiratory pathogens in Ningbo, China, both before and following the cessation of COVID-19 containment measures

To assess the circulating characteristics of common respiratory pathogens following the complete relaxation of non-pharmaceutical interventions (NPIs) and the cessation of the dynamic zero-COVID policy. The retrospective analysis was conducted from 14,412 patients with acute respiratory infections (ARIs) from January 24, 2020, to December 31, 2023, including Influenza A virus (IFV-A), Influenza B virus (IFV-B), Respiratory Syncytial Virus (RSV), Human Rhinovirus (HRV), Human Parainfluenza Virus (HPIV), Human Metapneumovirus (HMPV), Human Coronavirus (HCoV), Human Bocavirus (HBoV), Human Adenovirus (HAdV), and Mycoplasma pneumoniae (MP). Compared with 2020-2022, Joinpoint analysis indicated a monthly increase in overall pathogen activity in 2023, rising from an average of 43.05% to an average of 68.46%. The positive rates of IFV-A, IFV-B, HMPV, HPIV, HCoV, and MP increased, while those of HRV and RSV decreased, and no differences in HAdV and HBoV. The outbreak of IFV-A and MP was observed, the positive rate of MP has surpassed pre-COVID-19 pandemic levels and the spread of RSV was interrupted by IFV-A. Infants and toddlers were primarily infected by HRV and RSV, Children and adolescents exhibited a higher prevalence of infections with MP, IFV-A, and HRV, whereas Adults and the elderly were primarily infected by IFV-A. The incidence of co-infections rose from 4.25 to 13.73%. Restricted cubic spline models showed that the susceptible age ranges for multiple pathogens expanded. These changes serve as a reminder to stay alert in the future and offer clinicians a useful guide for diagnosing and treating.

Changes in the Epidemiological Features of Influenza After the COVID-19 Pandemic in China, the United States, and Australia: Updated Surveillance Data for Influenza Activity

BACKGROUND

There has been a global decrease in seasonal influenza activity since the onset of the COVID-19 pandemic.

OBJECTIVE

We aimed to describe influenza activity during the 2021/2022 season and compare it to the trends from 2012 to 2023. We also explored the influence of social and public health prevention measures during the COVID-19 pandemic on influenza activity.

METHODS

We obtained influenza data from January 1, 2012, to February 5, 2023, from publicly available platforms for China, the United States, and Australia. Mitigation measures were evaluated per the stringency index, a composite index with 9 measures. A general additive model was used to assess the stringency index and the influenza positivity rate correlation, and the deviance explained was calculated.

RESULTS

We used over 200,000 influenza surveillance data. Influenza activity remained low in the United States and Australia during the 2021/2022 season. However, it increased in the United States with a positive rate of 26.2% in the 49th week of 2022. During the 2021/2022 season, influenza activity significantly increased compared with the previous year in southern and northern China, with peak positivity rates of 28.1% and 35.1% in the second week of 2022, respectively. After the COVID-19 pandemic, the dominant influenza virus genotype in China was type B/Victoria, during the 2021/2022 season, and accounted for >98% (24,541/24,908 in the South and 20,543/20,634 in the North) of all cases. Influenza virus type B/Yamagata was not detected in all these areas after the COVID-19 pandemic. Several measures individually significantly influence local influenza activity, except for influenza type B in Australia. When combined with all the measures, the deviance explained values for influenza A and B were 87.4% (P<.05 for measures of close public transport and restrictions on international travel) and 77.6% in southern China and 83.4% (P<.05 for measures of school closing and close public transport) and 81.4% in northern China, respectively. In the United States, the association was relatively stronger, with deviance-explained values of 98.6% for influenza A and 99.1% (P<.05 for measures of restrictions on international travel and public information campaign) for influenza B. There were no discernible effects on influenza B activity in Australia between 2020 and 2022 due to the incredibly low positive rate of influenza B. Additionally, the deviance explained values were 95.8% (P<.05 for measures of restrictions on gathering size and restrictions on international travel) for influenza A and 72.7% for influenza B.

CONCLUSIONS

Influenza activity has increased gradually since 2021. Mitigation measures for COVID-19 showed correlations with influenza activity, mainly driven by the early stage of the pandemic. During late 2021 and 2022, the influence of mitigation management for COVID-19 seemingly decreased gradually, as the activity of influenza increased compared to the 2020/2021 season.

Parental Hesitancy toward Seasonal Influenza Vaccination for Children under the Age of 18 Years and Its Determinants in the Post-Pandemic Era: A Cross-Sectional Survey among 1175 Parents in China

Children's susceptibility to influenza increased after COVID-19 control measures were lifted. This study investigated parental hesitancy toward seasonal influenza vaccination (SIV) for children and its determinants in the post-pandemic era. An online survey of full-time adult factory workers was conducted in Shenzhen, China in December 2023. This analysis was based on 1175 parents who had at least one child under the age of 18 years. Among all parents, 37.1% were hesitant to have their index child receive SIV. Mothers exhibited lower parental hesitancy toward SIV compared to fathers (31.9% versus 41.3%, p < 0.001). After adjusting for significant background characteristics, mothers and fathers who were more satisfied with the SIV health promotion materials, perceived more severe consequences of seasonal influenza for their children, and perceived more benefits, cues to action, and self-efficacy related to their children's SIV were less likely to exhibit hesitancy toward SIV. Higher frequency of exposure to information about the increasing number of patients or severe cases due to seasonal influenza and other upper respiratory infections on social media was associated with lower parental hesitancy toward SIV among fathers but not mothers. There is a strong need to address parental hesitancy toward SIV for children in the post-pandemic era.

Resurgence of seasonal influenza driven by A/H3N2 and B/Victoria in succession during the 2023-2024 season in Beijing showing increased population susceptibility

During the COVID-19 pandemic, non-pharmaceutical interventions were introduced to reduce exposure to respiratory viruses. However, these measures may have led to an "immunity debt" that could make the population more vulnerable. The goal of this study was to examine the transmission dynamics of seasonal influenza in the years 2023-2024. Respiratory samples from patients with influenza-like illness were collected and tested for influenza A and B viruses. The electronic medical records of index cases from October 2023 to March 2024 were analyzed to determine their clinical and epidemiological characteristics. A total of 48984 positive cases were detected, with a pooled prevalence of 46.9% (95% CI 46.3-47.5). This season saw bimodal peaks of influenza activity, with influenza A peaked in week 48, 2023, and influenza B peaked in week 1, 2024. The pooled positive rates were 28.6% (95% CI 55.4-59.6) and 18.3% (95% CI 18.0-18.7) for influenza A and B viruses, respectively. The median values of instantaneous reproduction number were 5.5 (IQR 3.0-6.7) and 4.6 (IQR 2.4-5.5), respectively. The hospitalization rate for influenza A virus (2.2%, 95% CI 2.0-2.5) was significantly higher than that of influenza B virus (1.1%, 95% CI 0.9-1.4). Among the 17 clinical symptoms studied, odds ratios of 15 symptoms were below 1 when comparing influenza A and B positive inpatients, with headache, weakness, and myalgia showing significant differences. This study provides an overview of influenza dynamics and clinical symptoms, highlighting the importance for individuals to receive an annual influenza vaccine.

Enhancing seasonal influenza projections: A mechanistic metapopulation model for long-term scenario planning

In temperate regions, annual preparation by public health officials for seasonal influenza requires early-season long-term projections. These projections are different from short-term (e.g., 1-4 weeks ahead) forecasts that are typically updated weekly. Whereas short-term forecasts estimate what "will" likely happen in the near term, the goal of scenario projections is to guide long-term decision-making using "what if" scenarios. We developed a mechanistic metapopulation model and used it to provide long-term influenza projections to the Flu Scenario Modeling Hub. The scenarios differed in their assumptions about influenza vaccine effectiveness and prior immunity. The parameters of the model were inferred from early season hospitalization data and then simulated forward in time until June 3, 2023. We submitted two rounds of projections (mid-November and early December), with the second round being a repeat of the first with three more weeks of data (and consequently different model parameters). In this study, we describe the model, its calibration, and projections targets. The scenario projection outcomes for two rounds are compared with each other at state and national level reported daily hospitalizations. We show that although Rounds 2 and 3 were identical in definition, the addition of three weeks of data produced an improvement to model fits. These changes resulted in earlier projections for peak incidence, lower projections for peak magnitude and relatively small changes to cumulative projections. In both rounds, all four scenarios presented conceivable outcomes, with some scenarios agreeing well with observations. We discuss how to interpret this agreement, emphasizing that this does not imply that one scenario or another provides the ground truth. Our model's performance suggests that its underlying assumptions provided plausible bounds for what could happen during an influenza season following two seasons of low circulation. We suggest that such projections would provide actionable estimates for public health officials.

Temporal shifts in 24 notifiable infectious diseases in China before and during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic, along with the implementation of public health and social measures (PHSMs), have markedly reshaped infectious disease transmission dynamics. We analysed the impact of PHSMs on 24 notifiable infectious diseases (NIDs) in the Chinese mainland, using time series models to forecast transmission trends without PHSMs or pandemic. Our findings revealed distinct seasonal patterns in NID incidence, with respiratory diseases showing the greatest response to PHSMs, while bloodborne and sexually transmitted diseases responded more moderately. 8 NIDs were identified as susceptible to PHSMs, including hand, foot, and mouth disease, dengue fever, rubella, scarlet fever, pertussis, mumps, malaria, and Japanese encephalitis. The termination of PHSMs did not cause NIDs resurgence immediately, except for pertussis, which experienced its highest peak in December 2023 since January 2008. Our findings highlight the varied impact of PHSMs on different NIDs and the importance of sustainable, long-term strategies, like vaccine development.

Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis

Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.