Age-dependent influenza infection patterns and subtype circulation in Denmark, in seasons 2015/16 to 2021/22.

BackgroundInfluenza was almost absent for 2 years following the implementation of strict public health measures to prevent the spread of SARS-CoV-2. The consequence of this on infections in different age groups is not yet known.AimTo describe the age groups infected with the influenza virus in 2021/22, the first post-pandemic influenza season in Denmark, compared with the previous six seasons, and subtypes circulating therein.MethodsInfection and hospitalisation incidences per season and age group were estimated from data in Danish registries. Influenza virus subtypes and lineages were available from samples sent to the National Influenza Centre at Statens Serum Institut.ResultsTest incidence followed a similar pattern in all seasons, being highest in 0-1-year-olds and individuals over 75 years, and lowest in 7-14-year-olds and young people 15 years to late twenties. When the influenza A virus subtypes A(H3N2) and A(H1N1)pdm09 co-circulated in seasons 2015/16 and 2017/18 to 2019/20, the proportion of A(H1N1)pdm09 was higher in 0-1-year-olds and lower in the over 85-year-olds compared with the overall proportion of A(H1N1)pdm09 in these seasons. The proportion of A(H3N2) was higher in the over 85 years age group compared with the overall proportion of A(H3N2). The 2016/17 and 2021/22 seasons were dominated by A(H3N2) but differed in age-specific trends, with the over 85 years age group initiating the 2016/17 season, while the 2021/22 season was initiated by the 15-25-year-olds, followed by 7-14-year-olds.ConclusionThe 2021/22 influenza season had a different age distribution compared with pre-COVID-19 pandemic seasons.

The Sialyl Lewis X Glycan Receptor Facilitates Infection of Subtype H7 Avian Influenza A Viruses.

Subtype H7 avian influenza A viruses (IAVs) are enzootic in wild aquatic birds and have caused sporadic spillovers into domestic poultry and humans. Here, we determined the distribution of fucosylated α2,3 sialoglycan (i.e., sialyl Lewis X [SLeX]) in chickens and five common dabbling duck species and the association between SLeX and cell/tissue/host tropisms of H7 IAVs. Receptor binding analyses showed that H7 IAVs bind to both α2,3-linked (SA2,3Gal) and α2,6-linked sialic acids (SA2,6Gal), but with a higher preference for SLeX; H7 IAVs replicated more efficiently in SLeX-overexpressed than SLeX-deficient MDCK cells. While chickens and all tested dabbling ducks expressed abundant SA2,3Gal and SA2,6Gal, SLeX was detected in both respiratory and gastrointestinal tissues of chickens and mallard ducks and in only the respiratory tissues of gadwall, green-wing teal, and northern shoveler but not in wood ducks. Viral-tissue binding assays showed that H7 IAVs bind to chicken colon crypt cells that express SLeX but fewer bind to mallard colon crypt cells, which do not express SLeX; H7 IAVs bind efficiently to epithelial cells of all tissues expressing SA2,3Gal. High viral replication was identified in both chickens and mallards infected with an H7 virus, regardless of SLeX expression, and viruses were detected in all cells to the same degree as viruses detected in the viral-tissue binding assays. In summary, this study suggests that SLeX facilitates infection of H7 viruses, but other types of SA2,3Gal glycan receptors shape the tissue/host tropisms of H7 IAVs. IMPORTANCE In addition to causing outbreaks in domestic poultry, subtype H7 IAVs can cause sporadic spillover infections in lower mammals and humans. In this study, we showed that SLeX expression varies among wild dabbling ducks. Although it facilitated virus binding and affected infection of H7 IAV in cells, SLeX expression is not the only determinant of viral replication at either the tissue or host level. This study suggested that access to heterologous SA2,3Gal glycan receptors, including fucosylated α2,3-linked sialoglycans, shape tissue and host tropism of H7 IAVs in aquatic wild birds.

Healthcare-Seeking Behavior for Respiratory Illness Among Flu Near You Participants in the United States During the 2015-2016 Through 2018-2019 Influenza Seasons.

BACKGROUND: Flu Near You (FNY) is an online participatory syndromic surveillance system that collects health-related information. In this article, we summarized the healthcare-seeking behavior of FNY participants who reported influenza-like illness (ILI) symptoms. METHODS: We applied inverse probability weighting to calculate age-adjusted estimates of the percentage of FNY participants in the United States who sought health care for ILI symptoms during the 2015-2016 through 2018-2019 influenza season and compared seasonal trends across different demographic and regional subgroups, including age group, sex, census region, and place of care using adjusted χ 2 tests. RESULTS: The overall age-adjusted percentage of FNY participants who sought healthcare for ILI symptoms varied by season and ranged from 22.8% to 35.6%. Across all seasons, healthcare seeking was highest for the <18 and 65+ years age groups, women had a greater percentage compared with men, and the South census region had the largest percentage while the West census region had the smallest percentage. CONCLUSIONS: The percentage of FNY participants who sought healthcare for ILI symptoms varied by season, geographical region, age group, and sex. FNY compliments existing surveillance systems and informs estimates of influenza-associated illness by adding important real-time insights into healthcare-seeking behavior.

Prevalence of COVID-19 and the Continued Citizen-Based Control in Japan.

Since an outbreak of COVID-19 was detected among the crew and passengers of the Diamond Princess cruise ship in early 2020, the total number of cases of SARS-CoV-2 has surpassed 440,000 in Japan. However, that number remains small compared with other countries, such as the United States, a few European countries, and China. Despite the Japanese government not imposing a lockdown or implementing large-scale testing at the municipal level, the country has managed to contain the smaller outbreaks. To avoid infection, it is important to wear a face mask, wash one's hands, and observe social distancing. In addition, we focus on the clinical laboratory testing performed using the latest technology to detect SARS-CoV-2 RNA in a hospital in Yokohama, Japan. Large-scale testing of viral RNA would be useful for detecting asymptomatic virus carriers as is done in other countries, and could be carried out as a future measure for controlling COVID-19.

Risk-adjusted zero-inflated Poisson CUSUM charts for monitoring influenza surveillance data.

BACKGROUND: The influenza surveillance has been received much attention in public health area. For the cases with excessive zeroes, the zero-inflated Poisson process is widely used. However, the traditional control charts based on zero-inflated Poisson model, ignore the association between influenza cases and risk factors, and thus may lead to unexpected mistakes when implementing monitoring charts. METHOD: In this paper, we proposed risk-adjusted zero-inflated Poisson cumulative sum control charts, in which the risk factors were put to adjust the risk of influenza and the adjustment was made by zero-inflated Poisson regression. We respectively proposed the control chart monitoring the parameters individually and simultaneously. RESULTS: The performance of our proposed risk-adjusted zero-inflated Poisson cumulative sum control chart was evaluated and compared with the unadjusted standard cumulative sum control charts in simulation studies. The results show that for different distribution of impact factors and different coefficients, the risk-adjusted cumulative sum charts can generate much less false alarm than the standard ones. Finally, the influenza surveillance data from Hong Kong is used to illustrate the application of the proposed chart. CONCLUSIONS: Our results suggest that the adjusted cumulative sum control chart we proposed is more accurate and credible than the unadjusted standard control charts because of the lower false alarm rate of the adjusted ones. Even the unadjusted control charts may signal a little faster than the adjusted ones, the alarm they raise may have low credibility since they also raise alarm frequently even the processes are in control. Thus we suggest using the risk-adjusted cumulative sum control charts to monitor the influenza surveillance data to alert accurately, credibly and relatively quickly.

Locally Acquired Human Infection with Swine-Origin Influenza A(H3N2) Variant Virus, Australia, 2018.

In 2018, a 15-year-old female adolescent in Australia was infected with swine influenza A(H3N2) variant virus. The virus contained hemagglutinin and neuraminidase genes derived from 1990s-like human seasonal viruses and internal protein genes from influenza A(H1N1)pdm09 virus, highlighting the potential risk that swine influenza A virus poses to human health in Australia.

Epidemiology of Influenza among patients with influenza-like illness and severe acute respiratory illness in Pakistan: A 10-year surveillance study 2008-17.

In Pakistan, the burden of influenza was largely unknown, as no formal surveillance system was in place. In 2008, an influenza surveillance system was set up in eight sentinel sites. This study describes the epidemiology of influenza virus using a 10-year surveillance data from 2008 to 2017. Nasopharyngeal/throat swabs were collected from patients with influenza-like illness (ILI) and severe acute respiratory illness (SARI) along with relevant epidemiological information. The samples were tested using real-time reverse transcriptase-polymerase chain reaction for the detection and characterization of influenza viruses. A total of 17 209 samples were tested for influenza, out of which 3552 (20.6%) were positive; 2151/11 239 (19.1%) were patients with ILI, whereas 1401/5970 (23.5%) were patients with SARI. Influenza A/H1N1pdm09 was the predominant strain with 40.6% (n = 1442) followed by influenza B (936, 26.4%). Influenza A/H1N1pdm09 was predominant among the children (5-14 years) and adults (15-64 years). Influenza B strain was predominantly found in the elderly age group (≥ 65 years) accounting for 48% of cases followed by children (2-4 years) accounting for 37% of cases. This 10-year surveillance data provides evidence of influenza activity in the country throughout the year with seasonal winter peaks. The results could be used to strengthen the epidemic preparedness and response plan.

Birth Cohort Effects in Influenza Surveillance Data: Evidence That First Influenza Infection Affects Later Influenza-Associated Illness.

BACKGROUND: The evolution of influenza A viruses results in birth cohorts that have different initial influenza virus exposures. Historically, A/H3 predominant seasons have been associated with more severe influenza-associated disease; however, since the 2009 pandemic, there are suggestions that some birth cohorts experience more severe illness in A/H1 predominant seasons. METHODS: United States influenza virologic, hospitalization, and mortality surveillance data during 2000-2017 were analyzed for cohorts born between 1918 and 1989 that likely had different initial influenza virus exposures based on viruses circulating during early childhood. Relative risk/rate during H3 compared with H1 predominant seasons during prepandemic versus pandemic and later periods were calculated for each cohort. RESULTS: During the prepandemic period, all cohorts had more influenza-associated disease during H3 predominant seasons than H1 predominant seasons. During the pandemic and later period, 4 cohorts had higher hospitalization and mortality rates during H1 predominant seasons than H3 predominant seasons. CONCLUSIONS: Birth cohort differences in risk of influenza-associated disease by influenza A virus subtype can be seen in US influenza surveillance data and differ between prepandemic and pandemic and later periods. As the population ages, the amount of influenza-associated disease may be greater in future H1 predominant seasons than H3 predominant seasons.

Emergence of Influenza A(H7N4) Virus, Cambodia.

Active surveillance in high-risk sites in Cambodia has identified multiple low-pathogenicity influenza A(H7) viruses, mainly in ducks. None fall within the A/Anhui/1/2013(H7N9) lineage; however, some A(H7) viruses from 2018 show temporal and phylogenetic similarity to the H7N4 virus that caused a nonfatal infection in Jiangsu Province, China, in December 2017.

Divergent Human-Origin Influenza Viruses Detected in Australian Swine Populations.

Global swine populations infected with influenza A viruses pose a persistent pandemic risk. With the exception of a few countries, our understanding of the genetic diversity of swine influenza viruses is limited, hampering control measures and pandemic risk assessment. Here we report the genomic characteristics and evolutionary history of influenza A viruses isolated in Australia from 2012 to 2016 from two geographically isolated swine populations in the states of Queensland and Western Australia. Phylogenetic analysis with an expansive human and swine influenza virus data set comprising >40,000 sequences sampled globally revealed evidence of the pervasive introduction and long-term establishment of gene segments derived from several human influenza viruses of past seasons, including the H1N1/1977, H1N1/1995, H3N2/1968, and H3N2/2003, and the H1N1 2009 pandemic (H1N1pdm09) influenza A viruses, and a genotype that contained gene segments derived from the past three pandemics (1968, reemerged 1977, and 2009). Of the six human-derived gene lineages, only one, comprising two viruses isolated in Queensland during 2012, was closely related to swine viruses detected from other regions, indicating a previously undetected circulation of Australian swine lineages for approximately 3 to 44 years. Although the date of introduction of these lineages into Australian swine populations could not be accurately ascertained, we found evidence of sustained transmission of two lineages in swine from 2012 to 2016. The continued detection of human-origin influenza virus lineages in swine over several decades with little or unpredictable antigenic drift indicates that isolated swine populations can act as antigenic archives of human influenza viruses, raising the risk of reemergence in humans when sufficient susceptible populations arise.IMPORTANCE We describe the evolutionary origins and antigenic properties of influenza A viruses isolated from two separate Australian swine populations from 2012 to 2016, showing that these viruses are distinct from each other and from those isolated from swine globally. Whole-genome sequencing of virus isolates revealed a high genotypic diversity that had been generated exclusively through the introduction and establishment of human influenza viruses that circulated in past seasons. We detected six reassortants with gene segments derived from human H1N1/H1N1pdm09 and various human H3N2 viruses that circulated during various periods since 1968. We also found that these swine viruses were not related to swine viruses collected elsewhere, indicating independent circulation. The detection of unique lineages and genotypes in Australia suggests that isolated swine populations that are sufficiently large can sustain influenza virus for extensive periods; we show direct evidence of a sustained transmission for at least 4 years between 2012 and 2016.

Detecting influenza and emerging avian influenza virus by influenza and pneumonia surveillance systems in a large city in China, 2005 to 2016.

BACKGROUND: Detecting avian influenza virus has become an important public health strategy for controlling the emerging infectious disease. METHODS: The HIS (hospital information system) modified influenza surveillance system (ISS) and a newly built pneumonia surveillance system (PSS) were used to monitor the influenza viruses in Changsha City, China. The ISS was used to monitor outpatients in two sentinel hospitals and to detect mild influenza and avian influenza cases, and PSS was used to monitor inpatients in 49 hospitals and to detect severe and death influenza cases. RESULTS: From 2005 to 2016, there were 3,551,917 outpatients monitored by the ISS system, among whom 126,076 were influenza-like illness (ILI) cases, with the ILI proportion (ILI%) of 3.55%. After the HIS was used, the reported incident cases of ILI and ILI% were increased significantly. From March, 2009 to September, 2016, there were 5,491,560 inpatient cases monitored by the PSS system, among which 362,743 were pneumonia cases, with a proportion of 6.61%. Among pneumonia cases, about 10.55% (38,260/362,743) of cases were severe or death cases. The pneumonia incidence increased each year in the city. Among 15 avian influenza cases reported from January, 2005 to September, 2016, there were 26.7% (4/15) mild cases detected by the HIS-modified ISS system, while 60.0% (9/15) were severe or death cases detected by the PSS system. Two H5N1 severe cases were missed by the ISS system in January, 2009 when the PSS system was not available. CONCLUSIONS: The HIS was able to improve the efficiency of the ISS for monitoring ILI and emerging avian influenza virus. However, the efficiency of the system needs to be verified in a wider area for a longer time span in China.

Circulation of influenza A and B in the Czech Republic from 2000-2001 to 2015-2016.

BACKGROUND: To improve national influenza vaccination recommendations, additional data on influenza A and B virus circulation are needed. Here, we describe the circulation of influenza A and B in the Czech Republic during 16 seasons. METHODS: This was a retrospective analysis of data collected from the 2000-2001 to 2015-2016 influenza seasons by the Czech Republic national influenza surveillance network. Influenza was confirmed and viral isolates subtyped by virological assays followed by antigen detection or by reverse transcriptase-polymerase chain reaction. RESULTS: Of 16,940 samples collected, 5144 (30.4%) were influenza-positive. Influenza A represented 78.6% of positive cases overall and accounted for more than 55.0% of all influenza cases in every season, except for 2005-2006 (6.0%). Both A/H1N1 and A/H3N2 were detected in most seasons, except for 2001-2002 and 2003-2004 (only A/H3N2), and 2007-2008 and 2009-2010 (only A/H1N1). Influenza B represented 21.4% of positive cases overall (range, 0.0-94.0% per season). Both influenza B lineages were detected in three seasons, a single B lineage in 11, and no B strain in two. For the 11 seasons where influenza B accounted for ≥20% of positive cases, the dominant lineage was Yamagata in six and Victoria in four. In the remaining season, the two lineages co-circulated. For two seasons (2005-2006 and 2007-2008), the B lineage in the trivalent influenza vaccine did not match the dominant circulating B lineage. CONCLUSIONS: In the Czech Republic, during the 2000-2001 to 2015-2016 influenza seasons, influenza virus circulation varied considerably. Although influenza A accounted for the most cases in almost all seasons, influenza B made a substantial, sometimes dominant, contribution to influenza disease.

A maximum curvature method for estimating epidemic onset of seasonal influenza in Japan.

BACKGROUND: Detecting the onset of influenza epidemic is important for epidemiological surveillance and for investigating the factors driving spatiotemporal transmission patterns. Most approaches define the epidemic onset based on thresholds, which use subjective criteria and are specific to individual surveillance systems. METHODS: We applied the empirical threshold method (ETM), together with two non-thresholding methods, including the maximum curvature method (MCM) that we proposed and the segmented regression method (SRM), to determine onsets of influenza epidemics in each prefecture of Japan, using sentinel surveillance data of influenza-like illness (ILI) from 2012/2013 through 2017/2018. Performance of the MCM and SRM was evaluated, in terms of epidemic onset, end, and duration, with those derived from the ETM using the nationwide epidemic onset indicator of 1.0 ILI case per sentinel per week. RESULTS: The MCM and SRM yielded complete estimates for each of Japan's 47 prefectures. In contrast, ETM estimates for Kagoshima during 2012/2013 and for Okinawa during all six influenza seasons, except 2013/2014, were invalid. The MCM showed better agreement in all estimates with the ETM than the SRM (R2 = 0.82, p < 0.001 vs. R2 = 0.34, p < 0.001 for epidemic onset; R2 = 0.18, p < 0.001 vs. R2 = 0.05, p < 0.001 for epidemic end; R2 = 0.28, p < 0.001 vs. R2 < 0.01, p = 0.35 for epidemic duration). Prefecture-specific thresholds for epidemic onset and end were established using the MCM. CONCLUSIONS: The Japanese national epidemic onset threshold is not applicable to all prefectures, particularly Okinawa. The MCM could be used to establish prefecture-specific epidemic thresholds that faithfully characterize influenza activity, serving as useful complements to the influenza surveillance system in Japan.

Influenza infections in Australia 2009-2015: is there a combined effect of age and sex on susceptibility to virus subtypes?

BACKGROUND: Influenza is a global infectious disease with a large burden of illness and high healthcare costs. Those who experience greater burden of disease include younger and older people, and pregnant women. Although there are known age and sex susceptibilities, little is known about how the interaction of age and sex may affect a population's vulnerability to infection with different subtypes of influenza virus. METHODS: Laboratory-confirmed cases of influenza notified between 1 January 2009 and 31 December 2015 obtained from the Australian Government National Notifiable Diseases Surveillance System Influenza Public Data Set were analysed by age, sex and virus subtype. Age standardised notification rates per 100,000 population were calculated separately for females and males and used to generate female-to-male ratios with 95% confidence intervals for influenza A and B, and for virus subtypes A(H1N1)pdm09 and A(H3N2). RESULTS: 334,560 notifications for influenza A (all notifications), A(H1N1)pmd09, A(H3N2) and B subtypes from a total of 335,414 influenza notifications were analysed. Male notification rates were significantly higher for the 0 to 4 years old age group regardless of virus type or subtype; and higher for those aged 0 to 14 years and those 85 years and older for influenza types A and B and subtype A(H1N1)pdm09. Female notification rates were significantly higher for A(H1N1)pdm09 in those aged 15 to 54 years, for Type A and sub-type A(H3N2) in those aged 15 to 69 years, and for Influenza B in those aged 20 to 74 years. CONCLUSIONS: We observed a female dominance in notification rates throughout the adult age groups, which could possibly be related to health seeking behaviours. However, differences in health seeking behaviours cannot explain the variations observed across virus subtypes in the particular age groups with higher female notifications. Depending on their age, females may be more susceptible to certain subtypes of influenza virus. These observations suggest that there is an interaction between age and sex on susceptibility to influenza infection which varies by the subtype of the virus. The inclusion of pregnancy and menopausal status in surveillance data may assist development of targeted public health approaches during the emergence of new subtypes of influenza virus. Targeted vaccination campaigns may need to take into consideration specific age and sex groups who have a greater susceptibility to influenza infection as well as those who experience a greater burden of illness.

Respiratory Viruses in Different Provinces of Poland During the Epidemic Season 2016/2017.

In Poland, influenza surveillance is conducted by 16 Provincial Sanitary Epidemiological Stations, headed by the Department of Influenza Research, National Influenza Center at the National Institute of Health - National Institute of Hygiene (NIPH-NIH). During the epidemic season 2016/2017, more than 4000 samples were tested for respiratory infections, with approximately 1800 positive results, the most of which were among patients over 65 years old. Most samples were tested in the Western Pomeranian province, but the greatest proportion of positively diagnosed influenza infections, amounting to 72.7% was noted in the Lodz metropolitan area in central Poland. Twenty five deaths due to post-influenza infections and complications were recorded across the country, of which 20 were among individuals over 65 years of age. During the 2016/2017 season, the dominant subtype was A/H3N2/, unlike the subtype A/H1N1/California/7/2009 during the previous season. A high number of confirmed infections of subtype A/H3N2/can attest to low vaccination rates.

An Integrated Influenza Surveillance Framework Based on National Influenza-Like Illness Incidence and Multiple Hospital Electronic Medical Records for Early Prediction of Influenza Epidemics: Design and Evaluation.

BACKGROUND: Influenza is a leading cause of death worldwide and contributes to heavy economic losses to individuals and communities. Therefore, the early prediction of and interventions against influenza epidemics are crucial to reduce mortality and morbidity because of this disease. Similar to other countries, the Taiwan Centers for Disease Control and Prevention (TWCDC) has implemented influenza surveillance and reporting systems, which primarily rely on influenza-like illness (ILI) data reported by health care providers, for the early prediction of influenza epidemics. However, these surveillance and reporting systems show at least a 2-week delay in prediction, indicating the need for improvement. OBJECTIVE: We aimed to integrate the TWCDC ILI data with electronic medical records (EMRs) of multiple hospitals in Taiwan. Our ultimate goal was to develop a national influenza trend prediction and reporting tool more accurate and efficient than the current influenza surveillance and reporting systems. METHODS: First, the influenza expertise team at Taipei Medical University Health Care System (TMUHcS) identified surveillance variables relevant to the prediction of influenza epidemics. Second, we developed a framework for integrating the EMRs of multiple hospitals with the ILI data from the TWCDC website to proactively provide results of influenza epidemic monitoring to hospital infection control practitioners. Third, using the TWCDC ILI data as the gold standard for influenza reporting, we calculated Pearson correlation coefficients to measure the strength of the linear relationship between TMUHcS EMRs and regional and national TWCDC ILI data for 2 weekly time series datasets. Finally, we used the Moving Epidemic Method analyses to evaluate each surveillance variable for its predictive power for influenza epidemics. RESULTS: Using this framework, we collected the EMRs and TWCDC ILI data of the past 3 influenza seasons (October 2014 to September 2017). On the basis of the EMRs of multiple hospitals, 3 surveillance variables, TMUHcS-ILI, TMUHcS-rapid influenza laboratory tests with positive results (RITP), and TMUHcS-influenza medication use (IMU), which reflected patients with ILI, those with positive results from rapid influenza diagnostic tests, and those treated with antiviral drugs, respectively, showed strong correlations with the TWCDC regional and national ILI data (r=.86-.98). The 2 surveillance variables-TMUHcS-RITP and TMUHcS-IMU-showed predictive power for influenza epidemics 3 to 4 weeks before the increase noted in the TWCDC ILI reports. CONCLUSIONS: Our framework periodically integrated and compared surveillance data from multiple hospitals and the TWCDC website to maintain a certain prediction quality and proactively provide monitored results. Our results can be extended to other infectious diseases, mitigating the time and effort required for data collection and analysis. Furthermore, this approach may be developed as a cost-effective electronic surveillance tool for the early and accurate prediction of epidemics of influenza and other infectious diseases in densely populated regions and nations.

Performance of surveillance case definitions for respiratory syncytial virus infections through the sentinel influenza surveillance system, Portugal, 2010 to 2018.

BackgroundWell-established influenza surveillance systems (ISS) can be used for respiratory syncytial virus (RSV) surveillance. In Portugal, RSV cases are detected through the ISS using the European Union (EU) influenza-like illness (ILI) case definition.AimTo investigate clinical predictors for RSV infection and how three case definitions (EU ILI, a modified EU acute respiratory infection, and one respiratory symptom) performed in detecting RSV infections in Portugal.MethodsThis observational retrospective study used epidemiological and laboratory surveillance data (October 2010-May 2018). Associations between clinical characteristics and RSV detection were analysed using logistic regression. Accuracy of case definitions was assessed through sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). A 0.05 significance level was accepted.ResultsThe study involved 6,523 persons, including 190 (2.9%) RSV cases. Among 183 cases with age information, RSV infection was significantly more frequent among individuals < 5 years (n = 23; 12.6%) and ≥ 65 years (n = 45; 24.6%) compared with other age groups (p < 0.0001). Cough (odds ratio (OR): 2.4; 95% confidence interval (CI): 1.2-6.5) was the best RSV-infection predictor considering all age groups, while shortness of breath was particularly associated with RSV-positivity among ≤ 14 year olds (OR: 6.7; 95% CI: 2.6-17.4 for 0-4 year olds and OR: 6.7; 95% CI: 1.5-28.8 for 5-14 year olds). Systemic symptoms were significantly associated with RSV-negative and influenza-positive cases. None of the case definitions were suitable to detect RSV infections (AUC = 0.51).ConclusionTo avoid underestimating the RSV disease burden, RSV surveillance within the Portuguese sentinel ISS would require a more sensitive case definition than ILI and, even a different case definition according to age.

Assessing baloxavir susceptibility of influenza viruses circulating in the United States during the 2016/17 and 2017/18 seasons.

The anti-influenza therapeutic baloxavir targets cap-dependent endonuclease activity of polymerase acidic (PA) protein. We monitored baloxavir susceptibility in the United States with next generation sequencing analysis supplemented by phenotypic one-cycle infection assay. Analysis of PA sequences of 6,891 influenza A and B viruses collected during 2016/17 and 2017/18 seasons showed amino acid substitutions: I38L (two A(H1N1)pdm09 viruses), E23G (two A(H1N1)pdm09 viruses) and I38M (one A(H3N2) virus); conferring 4-10-fold reduced susceptibility to baloxavir.

Amino acid substitutions in low pathogenic avian influenza virus strains isolated from wild birds in Korea.

Wild birds are natural hosts and reservoirs for influenza A viruses. However, many species, such as many waterfowl, are asymptomatic when infected and so facilitate the generation of viral genetic diversity. Mutations of key genes affect the replicability, pathogenicity, transmissibility, and antiviral resistance of influenza A viruses. In this study, we isolated avian influenza (AI) viruses from wild bird fecal samples and analyzed changes in amino acids over time and geographic region to monitor the biological change of the AI virus. Between 2014 and 2016, we collected 38,921 fresh fecal samples from major wild bird habitats located throughout Korea and isolated 123 AI viruses. We subsequently selected 22 amino acid sites to analyze for changes. These sites included ten sites associated with replication, ten sites associated with pathogenicity, three sites associated with transmission, and seven sites associated with antiviral resistance. We found substitution rates of 71.7% at the C38Y amino acid site within the polymerase basic protein 1 (PB1) gene, 66.7% at the D222G site within the hemagglutinin (HA) 1 gene, and 75.6% at the A184 site within the nucleoprotein (NP) gene. Alterations of the PB1, HA1, and NP genes are closely associated with increased pathogenicity in chickens and mammals. The remaining sites of interest exhibited few modifications. In this study, we confirmed that AI viruses circulating among wild birds in Korea consistently exhibit modifications at amino acid sites linked with replication and pathogenicity.

Feral Swine in the United States Have Been Exposed to both Avian and Swine Influenza A Viruses.

Influenza A viruses (IAVs) in swine can cause sporadic infections and pandemic outbreaks among humans, but how avian IAV emerges in swine is still unclear. Unlike domestic swine, feral swine are free ranging and have many opportunities for IAV exposure through contacts with various habitats and animals, including migratory waterfowl, a natural reservoir for IAVs. During the period from 2010 to 2013, 8,239 serum samples were collected from feral swine across 35 U.S. states and tested against 45 contemporary antigenic variants of avian, swine, and human IAVs; of these, 406 (4.9%) samples were IAV antibody positive. Among 294 serum samples selected for antigenic characterization, 271 cross-reacted with ≥1 tested virus, whereas the other 23 did not cross-react with any tested virus. Of the 271 IAV-positive samples, 236 cross-reacted with swine IAVs, 1 with avian IAVs, and 16 with avian and swine IAVs, indicating that feral swine had been exposed to both swine and avian IAVs but predominantly to swine IAVs. Our findings suggest that feral swine could potentially be infected with both avian and swine IAVs, generating novel IAVs by hosting and reassorting IAVs from wild birds and domestic swine and facilitating adaptation of avian IAVs to other hosts, including humans, before their spillover. Continued surveillance to monitor the distribution and antigenic diversities of IAVs in feral swine is necessary to increase our understanding of the natural history of IAVs.IMPORTANCE There are more than 5 million feral swine distributed across at least 35 states in the United States. In contrast to domestic swine, feral swine are free ranging and have unique opportunities for contact with wildlife, livestock, and their habitats. Our serological results indicate that feral swine in the United States have been exposed to influenza A viruses (IAVs) consistent with those found in both domestic swine and wild birds, with the predominant infections consisting of swine-adapted IAVs. Our findings suggest that feral swine have been infected with IAVs at low levels and could serve as hosts for the generation of novel IAVs at the interface of feral swine, wild birds, domestic swine, and humans.