Influenza Activity Research Articles

Epidemiological characteristics and analysis of related infection risk factors for influenza in Anhui Province from 2013 to 2021

Objective: Analysis of the characteristics of influenza epidemic in Anhui Province and quantification of the impact of different factors on influenza occurrence, providing scientific basis for better influenza prevention and control. Methods: Descriptive analysis and factor analysis were conducted on influenza-like illness (ILI) cases and RT-PCR results in Anhui Province from 2013 to 2021 using data from China's Influenza Monitoring Information System. Results: The percentage of influenza-like illness (ILI%) of sentinel hospitals in Anhui Province from April 1, 2013 to March 31, 2021 was 3.80% (1 209 142/31 779 987), showing an overall increasing trend, with a relatively high proportion in 2017-2018 at 4.30% (191 148/4 448 211). The proportion of ILI cases in infants and young children aged 0-4 years was a relatively high at 54.14% (654 676/1 209 142), and the highest ILI% was observed in Fuyang City, Anhui Province (6.25%, 236 863/3 788 863). Laboratory monitoring results showed that the positive rate of ILI cases in sentinel hospitals in 8 influenza monitoring years was 16.38% (34 868/212 912), showing an increasing trend year by year, with a relatively proportion in 2017-2018 at 26.19% (6 936/26 488). The detection rate of school-age children aged 5-14 years was a relativelyhigh at 28.81% (13 869/48 144), and the positive rate was a relatively high in Wuhu City among the 16 cities, reaching 22.01% (2 693/122 237). Influenza activity showed a single peak in winter-spring and alternating double peaks in winter-spring and summer, with different subtypes alternating, and A (H3N2) was the dominant subtype in summer. The results of a multiple logistic regression model showed that the positive rate was higher in 2017-2018, among children aged 5-14 years, in winter, and in southern Anhui. Conclusions: Influenza epidemic in Anhui Province has a clear seasonal pattern, and the ILI% and detection rate have shown an upward trend from 2013 to 2021. Therefore, it is suggested to ensure vaccine supply before the winter-spring influenza season arrives, and to strengthen vaccine uptake and health education to avoid the risk of infection during the peak period of influenza.

Changes in Influenza Activities Impacted by NPI Based on 4-Year Surveillance in China: Epidemic Patterns and Trends.

Since the Non-pharmaceutical Intervention (NPI) by COVID-19 emerged, influenza activity has been somewhat altered. The aim of this study was to explore changes in influenza activities in the context of COVID-19 based on the sentinel hospitals/units in Guangdong, southern China. The surveillance data in influenza-like illness (ILI) were collected from 21 cities in Guangdong between September 2017 and August 2021, while 43 hospitals/units were selected to analyze the predominant types of influenza, population characteristics, and seasonal features by three methods (the concentration ratio, the seasonal index, and the circulation distribution), based on a descriptive epidemiological approach. During the four consecutive influenza seasons, a total of 157345 ILIs were tested, of which 9.05% were positive for influenza virus (n = 14238), with the highest positive rates for both IAV (13.20%) and IBV (5.41%) in the 2018-2019 season. After the emergence of COVID-19, influenza cases decreased near to zero from March 2020 till March 2021, and the dominant type of influenza virus changed from IAV to IBV. The highest positive rate of influenza existed in the age-group of 5 ~ < 15years in each season for IAV (P < 0.001), which was consistent with that for IBV (P < 0.001). The highest annual positive rates for IBV emerged in eastern Guangdong, while the highest annual positive rates of IAV in different seasons existed in different regions. Furthermore, compared with the epidemic period (ranged from December to June) during 2017-2019, the period ended three months early (March 2020) in 2019-2020, and started by five months behind (April 2021) during 2020-2021. The highest positive rates in 5 ~ < 15 age-group suggested the susceptible in this age-group mostly had infected with infected B/Victoria. Influenced by the emergence of COVID-19 and NPI responses, the epidemic patterns and trends of influenza activities have changed in Guangdong, 2017-2021.

Influenza A Virus in Pigs in Senegal and Risk Assessment of Avian Influenza Virus (AIV) Emergence and Transmission to Human.

We conducted an active influenza surveillance in the single pig slaughterhouse in Dakar to investigate the epidemiology and genetic characteristics of influenza A viruses (IAVs) and to provide serologic evidence of avian influenza virus (AIV) infection in pigs at interfaces with human populations in Senegal. Nasal swab and blood samples were collected on a weekly basis from the same animal immediately after slaughter. Influenza A viruses were diagnosed using RT-qPCR and a subset of positive samples for H3 and H1 subtypes were selected for full genome amplification and NGS sequencing. Serum samples were tested by HI assay for the detection of antibodies recognizing four AIVs, including H9N2, H5N1, H7N7 and H5N2. Between September 2018 and December 2019, 1691 swine nasal swabs were collected and tested. Influenza A virus was detected in 30.7% (520/1691), and A/H1N1pdm09 virus was the most commonly identified subtype with 38.07% (198/520), followed by A/H1N2 (16.3%) and A/H3N2 (5.2%). Year-round influenza activity was noted in pigs, with the highest incidence between June and September. Phylogenetic analyses revealed that the IAVs were closely related to human IAV strains belonging to A/H1N1pdm09 and seasonal H3N2 lineages. Genetic analysis revealed that Senegalese strains possessed several key amino acid changes, including D204 and N241D in the receptor binding site, S31N in the M2 gene and P560S in the PA protein. Serological analyses revealed that 83.5% (95%CI = 81.6-85.3) of the 1636 sera tested were positive for the presence of antibodies against either H9N2, H5N1, H7N7 or H5N2. Influenza H7N7 (54.3%) and H9N2 (53.6%) were the dominant avian subtypes detected in Senegalese pigs. Given the co-circulation of multiple subtypes of influenza viruses among Senegalese pigs, the potential exists for the emergence of new hybrid viruses of unpredictable zoonotic and pandemic potential in the future.

Resuspension of Seeded Particles Containing Live Influenza A Virus in a Full-Scale Laboratory

Many respiratory viruses, including influenza and SARS-CoV-2, are transmitted via the emission and inhalation of infectious respiratory aerosols in indoor environments. Resuspended particles from indoor surfaces and clothing can be a major source of airborne microbiological contaminants in indoor environments; however, it is unknown whether resuspended viruses contribute substantially to disease transmission. In this study, we investigated the resuspension via human walking activity of influenza A virus H3N2 laboratory strain, which was generated through a nebulizer into a sealed, unventilated biosafety level 2 (BSL-2) laboratory. The mean airborne viral concentrations following the resuspension events (3.7×103 viral RNA copies m−3) were two orders of magnitude lower than those following direct emission via the nebulizer (1.1×105 viral RNA copies m−3). The calculated resuspension emission factor (normalized ratio of the airborne mass to mass available for resuspension on the surface) of 10−3 was similar to reported values for 1–2 μm particles. Thus, depending on the infectious dose and viability of the virus, resuspension of settled respiratory viruses could lead to transmission, but the risk appears to be much lower than for direct respiratory emissions. To our knowledge, this is the first full-scale experimental study designed to quantify virus resuspension.

Global variability of influenza activity and virus subtype circulation from 2011 to 2023

BackgroundAlthough decreased influenza activity has been reported in many countries during the COVID-19 pandemic, it remains unknown how global influenza activity has changed. We described the global variability of influenza...

Effects of non-pharmaceutical interventions for COVID-19 on influenza incidence: A systematic review

Introduction Since the outbreak of coronavirus disease 2019 (COVID-19), non-pharmaceutical interventions (NPIs) have been the primary preventative measure to mitigate the COVID-19 burden. However, these NPIs have also altered the pattern and incidence of other respiratory pathogens. This review aims to explore the effects of NPIs used against COVID-19, on influenza incidence.Methods A systematic literature search was conducted in selected databases (PubMed, Medline, Embase). Documents that highlighted a change in influenza epidemiology during the COVID-19 pandemic and were linked to NPIs were included. The search covered articles from 1 January 2020 to 7 December 2022.Results This review included 13 studies reporting data from three different continents. A 14-100% decrease of influenza activity was observed since the enforcement of NPIs in early 2020.Conclusion This study suggests that the NPIs implemented during the COVID-19 pandemic have also significantly reduced influenza incidence. This is most likely because both coronavirus and influenza are transmitted through a similar route and the NPIs prevent this. The use of NPIs is suggested to overcome some burden of future influenza epidemics.

Cluster randomized trial of influenza vaccination in patients with acute heart failure in China: A mixed-methods feasibility study.

Uncertainties about the efficacy of influenza vaccination for populations with heart failure (HF) in preventing cardiovascular outcomes, as well as lack of effective vaccination strategies, may contribute to low vaccine coverage rate (VCR) in China and globally. We assessed the feasibility of a strategy to promote influenza vaccines in patients hospitalized with acute HF in China and to inform the design of a hybrid effectiveness-implementation cluster randomized trial to evaluate this strategy on mortality and hospital re-admission. We conducted a cluster randomized pilot trial involving 11 hospitals in Henan Province in China, with mixed-methods evaluation between December 2020 and April 2021. A process evaluation involved interviews with 51 key informants (patients, health professionals, policy makers). The intervention included education about influenza vaccination and availability of free vaccines administered prior to hospital discharge for HF patients, while usual care included attending community-based points of vaccination (PoV) for screening and vaccination. Implementation outcomes focused on reach, fidelity, adoption, and acceptability. Recruitment rates were assessed for trial feasibility. Effectiveness outcomes were influenza VCR, HF-specific rehospitalizations and mortality at 90 days. A total of 518 HF patients were recruited from 7 intervention and 4 usual care hospitals (mean of 45 participants per hospital per month). VCR was 89.9% (311/346, 86.1-92.8%) in the intervention group and 0.6% (1/172, 0.0-3.7%) in the control group. The process evaluation demonstrated reach to patients with lower socioeconomic and education status. There was good fidelity of the intervention components, with education and PoV set up processes being adapted to local hospital workflow and workforce capacity. Intervention was acceptable and adopted by patients and health professionals. However, outside of a trial setting, concerns were raised around vaccination reimbursement costs, workforce accountability and capacity. The intervention strategy appears feasible and acceptable for improving VCR in HF patients at county-level hospitals in China. Trial registration: This pilot trial is registered with the acronym PANDA II Pilot (Population Assessment of Influenza and Disease Activity) at ChiCTR.org.cn (ChiCTR2000039081).

Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis

Seasonal influenza activity showed a sharp decline in activity at the beginning of the Corona Virus Disease 2019 (COVID-19) emergence. Whether there is an epidemiological correlation between the dynamic of two respiratory infectious diseases and their future trends needs to be explored. To assess the correlation between COVID-19 and influenza activity and estimate their upcoming epidemiological trends. We retrospectively described the dynamics of COVID-19 and influenza in six World Health Organization (WHO) regions from January 2020-March 2023, and used the long short-term memory (LSTM) machine learning model to learn potential patterns of previously observed activity to predict trends for the next sixteen weeks. Finally, the past and future correlation in epidemiology between two respiratory infectious diseases was assessed by the Spearman correlation coefficients. With the emergence of original strain and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, influenza activity kept below 10% for more than one year in the six WHO regions. Subsequently, it gradually rose as the Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the upcoming period, the two increased as each other's activity decreased, becoming interactively dominant more than once and lasting 3-4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the estimated upcoming period. They had a transient positive correlation in the European Region of WHO (EURO), and the Western Pacific Region of WHO (WPRO) when multiple dominant strains were mixed pandemic. Influenza activity and former seasonal epidemiological patterns are shaken by the COVID-19 pandemic. Their activities are moderately and above inversely correlated, oppressing and competing with each other, showing a seesaw effect. In the post-pandemic era of COVID-19, the seesaw trends may be more prominent, prompting the possibility of using one another as early warning signals for future estimates and conducting optimized annual vaccine campaigns.

A discrete-time susceptible-infectious-recovered-susceptible model for the analysis of influenza data.

We develop a discrete time compartmental model to describe the spread of seasonal influenza virus. As time and disease state variables are assumed to be discrete, this model is considered to be a discrete time, stochastic, Susceptible-Infectious-Recovered-Susceptible (DT-SIRS) model, where weekly counts of disease are assumed to follow a Poisson distribution. We allow the disease transmission rate to also vary over time, and the disease can only be reintroduced after extinction if there is a contact with infected individuals from other host populations. To capture the variability of influenza activities from one season to the next, we define the seasonality with a 4-week period effect that may change over years. We examine three different transmission rates and compare their performance to that of existing approaches. Even though there is limited information for susceptible and recovered individuals, we demonstrate that the simple models for transmission rates effectively capture the behaviour of the disease dynamics. We use a Bayesian approach for inference. The framework is applied in an analysis of the temporal spread of influenza in the province of Manitoba, Canada, 2012-2015.

Epidemiological characteristics of seasonal influenza under implementation of zero-COVID-19 strategy in China

ObjectiveRespiratory viral diseases have posed a persistent threat to public health due to their high transmissibility. Influenza virus and SARS-Cov-2 are both respiratory viruses that have caused global pandemics. A zero-COVID-19 strategy is a public health policy imposed to stop community transmission of COVID-19 as soon as it is detected. In this study, we aim to examine the epidemiological characteristics of seasonal influenza in the past five years before and after the emergence of COVID-19 in China and observe the possible impact of the strategy on influenza. MethodsData from two data sources were retrospectively analyzed. A comparison on influenza incidence rate between Hubei and Zhejiang provinces was conducted based on data from the Chinese Center for Disease Control and Prevention (CDC). Then a descriptive and comparative analysis on seasonal influenza based on data from Zhongnan Hospital of Wuhan University and Hangzhou Ninth People`s Hospital before and after the outbreak of SARS-CoV-2 was conducted. ResultsFrom 2010–2017, both provinces experienced relatively low influenza activity until the 1st week of 2018, when they reached peak incidence rates of 78.16/100000PY, 34.05/100000PY respectively. Since then, influenza showed an obvious seasonality in Hubei and Zhejiang until the onset of COVID-19. During 2020 and 2021, there was a dramatic decline in influenza activity compared to 2018 and 2019. However, influenza activity seemed to rebound at the beginning of 2022 and surged in summer, with positive rates of 20.52% and 31.53% in Zhongnan Hospital of Wuhan University and Hangzhou Ninth People`s Hospital respectively as of the time writing this article. ConclusionsOur results reinforce the hypothesis that zero-COVID-19 strategy may impact the epidemiological pattern of influenza. Under the complex pandemic situation, implementation of NPIs could be a beneficial strategy containing not only COVID-19 but also influenza.

ATQ: alert time quality, an evaluation metric for assessing timely epidemic detection models within a school absenteeism-based surveillance system

BackgroundWellington-Dufferin-Guelph Public Health (WDGPH) has conducted an absenteeism-based influenza surveillance program in the WDG region of Ontario, Canada since 2008, using a 10% absenteeism threshold to raise an alert for the implementation of mitigating measures. A recent study indicated that model-based alternatives, such as distributed lag seasonal logistic regression models, provided improved alerts for detecting an upcoming epidemic. However model evaluation and selection was primarily based on alert accuracy, measured by the false alert rate (FAR), and failed to optimize timeliness. Here, a new metric that simultaneously evaluates epidemic alert accuracy and timeliness is proposed. The alert time quality (ATQ) metric is investigated as a model selection criterion on both a simulated and real data set.MethodsThe ATQ assessed alerts on a gradient, where alerts raised incrementally before or after an optimal day were considered informative, but were penalized for lack of timeliness. Summary statistics of ATQ, average alert time quality (AATQ) and first alert time quality (FATQ), were used for model evaluation and selection. Alerts raised by ATQ and FAR selected models were compared. Daily elementary school absenteeism and laboratory-confirmed influenza case data collected by WDGPH were used for demonstration and evaluation of the proposed metric. A simulation study that mimicked the WDG population and influenza demographics was conducted for further evaluation of the proposed metric.ResultsThe FATQ-selected model raised acceptable first alerts most frequently, while the AATQ-selected model raised first alerts within the ideal range most frequently.ConclusionsModels selected by either FATQ or AATQ would more effectively predict community influenza activity with the local community than those selected by FAR.

Avian influenza at the human-animal crossroad.

Veterinary RecordVolume 192, Issue 9 p. 378-379 Avian Influenza Avian influenza at the human-animal crossroad Giovanni Di Guardo, Corresponding Author Giovanni Di Guardo retired professor of general pathology and veterinary pathophysiology [email protected] Rome, ItalySearch for more papers by this author Giovanni Di Guardo, Corresponding Author Giovanni Di Guardo retired professor of general pathology and veterinary pathophysiology [email protected] Rome, ItalySearch for more papers by this author First published: 05 May 2023 https://doi.org/10.1002/vetr.3028Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. References 1Leguia M, Garcia-Glaessner A, Muñoz-Saavedra, et al. Highly pathogenic avian influenza A (H5N1) in marine mammals and seabirds in Peru. bioRxiv 2023; doi:10.1101/2023.03.03.531008 2Montserrat A, Monne I, Sánchez A, et al. Highly pathogenic avian influenza A(H5N1) virus infection in farmed mink, Spain, October 2022. Euro Surveill 2023; 28:2302300001 3Sun H, Li F, Liu Q, et al. Mink is a highly susceptible host species to circulating human and avian influenza viruses. Emerg Microbes Infect 2021; 10: 472– 80 4Bussey KA, Bousse TL, Desmet EA, et al. PB2 residue 271 plays a key role in enhanced polymerase activity of influenza A viruses in mammalian host cells. J Virol 2010; 84: 4395– 406 5Mallapaty S. Girl who died of bird flu did not have widely circulating variant. Nature https://go.nature.com/40IJ7xb (accessed 28 April 2023) Volume192, Issue96/13 May 2023Pages 378-379 ReferencesRelatedInformation

Quantifying the rebound of influenza epidemics after the adjustment of zero-COVID policy in China.

The coexistence of coronavirus disease 2019 (COVID-19) and seasonal influenza epidemics has become a potential threat to human health, particularly in China in the oncoming season. However, with the relaxation of nonpharmaceutical interventions (NPIs) during the COVID-19 pandemic, the rebound extent of the influenza activities is still poorly understood. In this study, we constructed a susceptible-vaccinated-infectious-recovered-susceptible (SVIRS) model to simulate influenza transmission and calibrated it using influenza surveillance data from 2018 to 2022. We projected the influenza transmission over the next 3 years using the SVIRS model. We observed that, in epidemiological year 2021-2022, the reproduction numbers of influenza in southern and northern China were reduced by 64.0 and 34.5%, respectively, compared with those before the pandemic. The percentage of people susceptible to influenza virus increased by 138.6 and 57.3% in southern and northern China by October 1, 2022, respectively. After relaxing NPIs, the potential accumulation of susceptibility to influenza infection may lead to a large-scale influenza outbreak in the year 2022-2023, the scale of which may be affected by the intensity of the NPIs. And later relaxation of NPIs in the year 2023 would not lead to much larger rebound of influenza activities in the year 2023-2024. To control the influenza epidemic to the prepandemic level after relaxing NPIs, the influenza vaccination rates in southern and northern China should increase to 53.8 and 33.8%, respectively. Vaccination for influenza should be advocated to reduce the potential reemergence of the influenza epidemic in the next few years.

The impact of the SARS-CoV-2 pandemic on global influenza surveillance: Insights from 18 National Influenza Centers based on a survey conducted between November 2021 and March 2022.

National Influenza Centers (NICs) have played a crucial role in the surveillance of SARS-CoV-2. The FluCov project, covering 22 countries, was initiated to monitor the impact of the SARS-CoV-2 pandemic on influenza activity. This project consisted of an epidemiological bulletin and NIC survey. The survey, designed to assess the impact of the pandemic on the influenza surveillance system, was shared with 36 NICs located across 22 countries. NICs were invited to reply between November 2021 and March 2022. We received 18 responses from NICs in 14 countries. Most NICs (76%) indicated that the number of samples tested for influenza decreased. Yet, many NICs (60%) were able to increase their laboratory testing capacity and the "robustness" (e.g., number of sentinel sites) (59%) of their surveillance systems. In addition, sample sources (e.g., hospital or outpatient setting) shifted. All NICs reported a higher burden of work following the onset of the pandemic, with some NICs hiring additional staff or partial outsourcing to other institutes or departments. Many NICs anticipate the future integration of SARS-CoV-2 surveillance into the existing respiratory surveillance system. The survey shows the profound impact of SARS-CoV-2 on national influenza surveillance in the first 27 months of the pandemic. Surveillance activities were temporarily disrupted, whilst priority was given to SARS-CoV-2. However, most NICs have shown rapid adaptive capacity underlining the importance of strong national influenza surveillance systems. These developments have the potential to benefit global respiratory surveillance in the years to come; however, questions about sustainability remain.

The early use of Antibiotics for At-risk children with InfluEnza in Primary Care (the ARCHIE programme)

The early use of Antibiotics for At-risk children with InfluEnza in Primary Care (the ARCHIE programme)

Behavioral changes of preventive activities of influenza among children in satellite cities of a metropolitan area of Tokyo, Japan, by the COVID-19 pandemic

ObjectiveIn children in a metropolitan area of Tokyo, Japan, behavioral change and influenza infection associated with the frequency of nonpharmaceutical interventions (NPI) was assessed from the 2018–2019 season (Preseason) and the 2020–2021 season (coronavirus disease 2019 [COVID-19] season).MethodsWe conducted an exclusive survey among children attending preschool, elementary school, and junior high school in the Toda and Warabi regions, Japan, during the 2018–2019 (Preseason, distributed via mail) and 2020–2021 seasons (COVID-19 season, conducted online). The proportion of preventive activities (hand washing, face mask-wearing, and vaccination) was compared in the Preseason with that of the COVID-19 season. The multivariate logistic regression model was further applied to calculate the adjusted odds ratio (AOR) with 95% confidence intervals (CIs) for influenza infection associated with NPI frequency (hand washing and face mask wearing) in each Preseason and COVID-19 season.ResultsThe proportion of vaccinated children who carried out hand washing and face mask wearing was remarkably higher during the COVID-19 season (48.8%) than in the Preseason (18.2%). A significant influenza infection reduction was observed among children who washed hands and wore face masks simultaneously (AOR, 0.87; 95% CI, 0.76–0.99; P = 0.033).ConclusionsA strong interest and performance in the intensive measures for the prevention of influenza under the COVID-19 pandemic was demonstrated. Positive association was observed from a combination of NPI, hand washing, and face mask-wearing and influenza infection. This study’s findings could help in activities or preventive measures against influenza and other communicable diseases in children.

Timing of seasonal influenza epidemics for 25 countries in Africa during 2010–19: a retrospective analysis

Using country-specific surveillance data to describe influenza epidemic activity could inform decisions on the timing of influenza vaccination. We analysed surveillance data from African countries to characterise the timing of seasonal influenza epidemics to inform national vaccination strategies. We used publicly available sentinel data from African countries reporting to the WHO Global Influenza Surveillance and Response FluNet platform that had 3-10 years of data collected during 2010-19. We calculated a 3-week moving proportion of samples positive for influenza virus and assessed epidemic timing using an aggregate average method. The start and end of each epidemic were defined as the first week when the proportion of positive samples exceeded or went below the annual mean, respectively, for at least 3 consecutive weeks. We categorised countries into five epidemic patterns: northern hemisphere-dominant, with epidemics occurring in October-March; southern hemisphere-dominant, with epidemics occurring in April-September; primarily northern hemisphere with some epidemic activity in southern hemisphere months; primarily southern hemisphere with some epidemic activity in northern hemisphere months; and year-round influenza transmission without a discernible northern hemisphere or southern hemisphere predominance (no clear pattern). Of the 34 countries reporting data to FluNet, 25 had at least 3 years of data, representing 46% of the countries in Africa and 89% of Africa's population. Study countries reported RT-PCR respiratory virus results for a total of 503 609 specimens (median 12 971 [IQR 9607-20 960] per country-year), of which 74 001 (15%; median 2078 [IQR 1087-3008] per country-year) were positive for influenza viruses. 248 epidemics occurred across 236 country-years of data (median 10 [range 7-10] per country). Six (24%) countries had a northern hemisphere pattern (Algeria, Burkina Faso, Egypt, Morocco, Niger, and Tunisia). Eight (32%) had a primarily northern hemisphere pattern with some southern hemisphere epidemics (Cameroon, Ethiopia, Mali, Mozambique, Nigeria, Senegal, Tanzania, and Togo). Three (12%) had a primarily southern hemisphere pattern with some northern hemisphere epidemics (Ghana, Kenya, and Uganda). Three (12%) had a southern hemisphere pattern (Central African Republic, South Africa, and Zambia). Five (20%) had no clear pattern (Côte d'Ivoire, DR Congo, Madagascar, Mauritius, and Rwanda). Most countries had identifiable influenza epidemic periods that could be used to inform authorities of non-seasonal and seasonal influenza activity, guide vaccine timing, and promote timely interventions. None. For the Berber, Luganda, Xhosa, Chewa, Yoruba, Igbo, Hausa and Afan Oromo translations of the abstract see Supplementary Materials section.

Acute Effects of Ambient Air Pollution on Asthma Emergency Department Visits in Ten U.S. States.

Previous studies of short-term ambient air pollution exposure and asthma morbidity in the United States have been limited to a small number of cities and/or pollutants and with limited consideration of effects across ages. To estimate acute age group-specific effects of fine and coarse particulate matter (PM), major PM components, and gaseous pollutants on emergency department (ED) visits for asthma during 2005-2014 across the United States. We acquired ED visit and air quality data in regions surrounding 53 speciation sites in 10 states. We used quasi-Poisson log-linear time-series models with unconstrained distributed exposure lags to estimate site-specific acute effects of air pollution on asthma ED visits overall and by age group (1-4, 5-17, 18-49, 50-64, and y), controlling for meteorology, time trends, and influenza activity. We then used a Bayesian hierarchical model to estimate pooled associations from site-specific associations. Our analysis included asthma ED visits. We observed positive associations for multiday cumulative exposure to all air pollutants examined [e.g., 8-d exposure to : rate ratio of 1.016 with 95% credible interval (CI) of (1.008, 1.025) per increase, : 1.014 (95% CI: 1.007, 1.020) per increase, organic carbon: 1.016 (95% CI: 1.009, 1.024) per increase, and ozone: 1.008 (95% CI: 0.995, 1.022) per increase]. and ozone showed stronger effects at shorter lags, whereas associations of traffic-related pollutants (e.g., elemental carbon and oxides of nitrogen) were generally stronger at longer lags. Most pollutants had more pronounced effects on children ( y old) than adults; had strong effects on both children and the elderly ( y old); and ozone had stronger effects on adults than children. We reported positive associations between short-term air pollution exposure and increased rates of asthma ED visits. We found that air pollution exposure posed a higher risk for children and older populations. https://doi.org/10.1289/EHP11661.

ARIH1 inhibits influenza A virus replication and facilitates RIG-I dependent immune signaling by interacting with SQSTM1/p62

BackgroundMultiple host factors are involved in modulating type I interferon expression induced by viruses; however, the mechanism is not fully elucidated. Influenza A virus infection causes severe respiratory symptoms and triggers a series of signaling cascades and host innate immune responses, including interferon production. The co-IP/MS technology was used to screen several antiviral factors in the early stage. Among these factors, ariadne-1 homolog (ARIH1) caught our attention.MethodsWestern blot assay was performed to detect the level of proteins and software ImageJ was used to analyze the band intensities. Polymerase activity assay was conducted to evaluate the polymerase activity of influenza A virus. Tissue culture infective dose (TCID50) assay was performed to measure influenza A virus titers, and quantitative RT-PCR assay was applied to test the mRNA level of IFN-β, ISG56, and CXCL10. Luciferase reporter assay was used to confirm the target of ARIH1 in RIG-I signaling. Immunoprecipitation assay was performed to detect the interaction and the ubiquitination of the proteins. All data were analyzed by biostatistical methods and presented as means ± standard deviation from three independent experiments. Statistical significance was determined using two-tailed student’s t test. A P value of less than 0.05 was considered statistically significant, and a P value of less than 0.01 was considered highly significant (ns, P ≥ 0.05; *, P < 0.05; and **, P < 0.01).ResultsWe found that ARIH1, a member of E3 ubiquitin ligases, enhanced cellular antiviral responses. Subsequent study showed that ARIH1 was up-regulated during influenza A virus infection. Further analysis showed that ARIH1 enhanced IFN-β and downstream gene expression by affecting the degradation of RIG-I through the SQSTM1/p62 signaling pathway.ConclusionThis newly revealed mechanism shows that cellular response increases of ARIH1 and promotes IFN-β expression to boost host survival during viral infection.

Patient and Epidemiological Factors Associated With Influenza Testing in Hospitalized Adults With Acute Respiratory Illnesses, 2016-2017 to 2019-2020.

Data are limited on influenza testing among adults with acute respiratory illness (ARI)-associated hospitalizations. We identified factors associated with influenza testing in adult ARI-associated hospitalizations across the 2016-2017 through 2019-2020 influenza seasons. Using data from 4 health systems in the United States, we identified hospitalizations that had an ARI discharge diagnosis or respiratory virus test. A hospitalization with influenza testing was based on testing performed within 14 days before through 72 hours after admission. We used random forest analysis to identify patient characteristics and influenza activity indicators that were most important in terms of their relationship to influenza testing. Across 4 seasons, testing rates ranged from 14.8%-19.4% at 3 pooled sites and 60.1%-78.5% at a fourth site with different testing practices. Discharge diagnoses of pneumonia or infectious disease of noninfluenza etiology, presence of ARI signs/symptoms, hospital admission month, and influenza-like illness activity level were consistently among the variables with the greatest relative importance. Select ARI diagnoses and indicators of influenza activity were the most important factors associated with influenza testing among ARI-associated hospitalizations. Improved understanding of which patients are tested may enhance influenza burden estimates and allow for more timely clinical management of influenza-associated hospitalizations.