Cluster Of Influenza Research Articles

Cluster of Influenza A(H5) Cases Associated with Poultry Exposure at Two Facilities - Colorado, July 2024.

Persons who work in close contact with dairy cattle and poultry that are infected with highly pathogenic avian influenza (HPAI) A(H5N1) virus are at increased risk for infection. In July 2024, the Colorado Department of Public Health & Environment responded to two poultry facilities with HPAI A(H5N1) virus detections in poultry. Across the two facilities, 663 workers assisting with poultry depopulation (i.e., euthanasia) received screening for illness; 109 (16.4%) reported symptoms and consented to testing. Among those who received testing, nine (8.3%) received a positive influenza A(H5) virus test result, and 19 (17.4%) received a positive SARS-CoV-2 test result. All nine workers who received positive influenza A(H5) test results had conjunctivitis, experienced mild illness, and received oseltamivir. This poultry exposure-associated cluster of human cases of influenza A(H5) is the first reported in the United States. The identification of these cases highlights the ongoing risk to persons who work in close contact with infected animals. Early response to each facility using multidisciplinary, multilingual teams facilitated case-finding, worker screening, and treatment. As the prevalence of HPAI A(H5N1) virus clade 2.3.4.4b genotype B3.13 increases, U.S. public health agencies should prepare to rapidly investigate and respond to illness in agricultural workers, including workers with limited access to health care.

Spatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China

BackgroundCurrently, the influenza epidemic in China is at a high level and mixed with other respiratory diseases. Current studies focus on regional influenza and the impact of environmental pollutants on time series, and lack of overall studies on the national influenza epidemic and the nonlinear correlation between environmental pollutants and influenza. The unclear spatial and temporal evolution patterns of influenza as well as the unclear correlation effect between environmental pollutants and influenza epidemic have greatly hindered the prevention and treatment of influenza epidemic by relevant departments, resulting in unnecessary economic and human losses.MethodThis study used Chinese influenza incidence data for 2007–2017 released by the China CDC and air pollutant site monitoring data. Seasonal as well as inter monthly differences in influenza incidence across 31 provinces of China have been clarified through time series. Space-Time Cube model (STC) was used to investigate the spatio-temporal evolution of influenza incidence in 315 Chinese cities during 2007–2017. Then, based on the spatial heterogeneity of influenza incidence in China, Generalized additive model (GAM) was used to identify the correlation effect of environmental pollutants (PM2.5, PM10, CO, SO2, NO2, O3) and influenza incidence.ResultThe influenza incidence in China had obvious seasonal changes, with frequent outbreaks in winter and spring. The influenza incidence decreased significantly after March, with only sporadic outbreaks occurring in some areas. In the past 11 years, the influenza epidemic had gradually worsened, and the clustering of influenza had gradually expanded, which had become a serious public health problem. The correlation between environmental pollutants and influenza incidence was nonlinear. Generally, PM2.5, CO and NO2 were positively correlated at high concentrations, while PM10 and SO2 were negatively correlated. O3 was not strongly correlated with the influenza incidence.ConclusionThe study found that the influenza epidemic in China was in a rapidly rising stage, and several regions had a multi-year outbreak trend and the hot spots continue to expand outward. The association between environmental pollutants and influenza incidence was nonlinear and spatially heterogeneous. Relevant departments should improve the monitoring of influenza epidemic, optimize the allocation of resources, reduce environmental pollution, and strengthen vaccination to effectively prevent the aggravation and spread of influenza epidemic in the high incidence season and areas.

Analysis of spatial-temporal distribution of notifiable respiratory infectious diseases in Shandong Province, China during 2005\u20132014

BackgroundLittle comprehensive information on overall epidemic trend of notifiable respiratory infectious diseases is available in Shandong Province, China. This study aimed to determine the spatiotemporal distribution and epidemic characteristics of notifiable respiratory infectious diseases.MethodsTime series was firstly performed to describe the temporal distribution feature of notifiable respiratory infectious diseases during 2005–2014 in Shandong Province. GIS Natural Breaks (Jenks) was applied to divide the average annual incidence of notifiable respiratory infectious diseases into five grades. Spatial empirical Bayesian smoothed risk maps and excess risk maps were further used to investigate spatial patterns of notifiable respiratory infectious diseases. Global and local Moran’s I statistics were used to measure the spatial autocorrelation. Spatial-temporal scanning was used to detect spatiotemporal clusters and identify high-risk locations.ResultsA total of 537,506 cases of notifiable respiratory infectious diseases were reported in Shandong Province during 2005–2014. The morbidity of notifiable respiratory infectious diseases had obvious seasonality with high morbidity in winter and spring. Local Moran’s I analysis showed that there were 5, 23, 24, 4, 20, 8, 14, 10 and 7 high-risk counties determined for influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella, respectively. The spatial-temporal clustering analysis determined that the most likely cluster of influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella included 74, 66, 58, 56, 22, 64, 2, 75 and 56 counties, and the time frame was November 2009, March 2008, January 2007, February 2005, July 2007, December 2011, November 2009, June 2012 and May 2005, respectively.ConclusionsThere were obvious spatiotemporal clusters of notifiable respiratory infectious diseases in Shandong during 2005–2014. More attention should be paid to the epidemiological and spatiotemporal characteristics of notifiable respiratory infectious diseases to establish new strategies for its control.

Emergence of a novel cluster of influenza A(H5N1) virus clade 2.2.1.2 with putative human health impact in Egypt, 2014/15.

A distinct cluster of highly pathogenic avian influenzaviruses of subtype A(H5N1) has been found to emergewithin clade 2.2.1.2 in poultry in Egypt since summer2014 and appears to have quickly become predominant.Viruses of this cluster may be associated withincreased incidence of human influenza A(H5N1) infectionsin Egypt over the last months.

Cluster of influenza A cases in vaccinated population of adults in Virology Laboratory in Glasgow in December 2012

The majority of influenza infections during the 2012/2013 influenza season in Scotland have been due to influenza A H3N2. We report an outbreak of influenza A H3N2 in a vaccinated population of adults in the Regional Virology Laboratory in Glasgow. This investigation was carried out to confirm the epidemiological link between cases. Staff with clinical symptoms of influenza-like illness were included. Samples were tested by real-time polymerase chain reaction and sequencing. Staff were interviewed to obtain information regarding symptom onset and vaccination status. Eight confirmed cases and six clinically diagnosed cases were reported, which all occurred within 4 days of a lunchtime Christmas quiz. The eight samples subtyped as H3 virus. The haemagglutinin gene in the confirmed cases was sequenced and shown to be identical. Most of the attendees had been immunised against influenza with the same vaccine batch at least 6 weeks earlier. This outbreak appears to have been an isolated incident, which arose due to a social event that provided the ideal conditions for transmission of a respiratory disease. It may have been compounded by low-vaccine effectiveness this season. Sequence data supported the epidemiological link.

Geographic Co-distribution of Influenza Virus Subtypes H7N9 and H5N1 in Humans, China

To the Editor: Human infection with a novel low pathogenicity influenza A(H7N9) virus in eastern China has recently raised global public health concerns (1). The geographic sources of infection have yet to be fully clarified, and confirmed human cases from 1 province have not been linked to those from other provinces. While some studies have identified epidemiologic characteristics of subtype H7N9 cases and clinical differences between these cases and cases of highly pathogenic influenza A(H5N1), another avian influenza affecting parts of China (2–4), the spatial epidemiology of human infection with influenza subtypes H7N9 and H5N1 in China has yet to be elucidated. To test the hypothesis of co-distribution of high-risk clusters of both types of infection, we used all available data on human cases in mainland China and investigated the geospatial epidemiologic features. Data on individual confirmed human cases of influenza (H7N9) from February 19, 2013, through May 17, 2013, and of influenza (H5N1) from October 14, 2005, through May 17, 2013, were collected from the Chinese Center for Disease Control and Prevention. The definitions of these cases have been described (3,5). A total of 129 confirmed cases of influenza (H7N9) (male:female ratio 2.39:1) and 40 confirmed cases of influenza (H5N1) (male:female ratio 0.90:1) were included in the analysis. The median age of persons with influenza (H7N9) was higher than for persons with influenza (H5N1) (58 years vs. 27 years; z = −7.73; p<0.01). Most (75.0%) persons with influenza (H5N1) had direct contact (e.g., occupational contact) with poultry (including dead and live birds) or their excrement and urine, whereas most (64.3%) persons with influenza (H7N9) had only indirect exposure to live poultry, mainly during visits to live poultry markets. Reported cases of influenza (H5N1) were distributed over 40 townships in 16 provinces, whereas cases of influenza (H7N9) were relatively more concentrated, in 108 townships but only 10 provinces (Figure). To identify a spatial overlap between the primary cluster of influenza (H7N9) cases, detected in April 2013 (relative risk [RR] 78.40; p<0.01), and the earliest space-time cluster of influenza (H5N1) cases, detected during November 2005–February 2006 (RR 65.27; p<0.01), we used spatiotemporal scan statistics with a maximum spatial cluster size of 5% of the population at risk in the spatial window and a maximum temporal cluster size of 25% of the study period in the temporal window (6) (Figure). The results suggest that the overlap is not perfect and is concentrated around an area southeast of Taihu Lake (south of Jiangsu Province), bordering the provinces of Anhui and Zhejiang. Smaller clusters of influenza (H7N9) cases were identified in the boundary of Jiangsu and Anhui Province (8 cases; RR 64.86; p<0.01) and Jiangxi Province (Nanchang County and Qingshanhu District) (4 cases; RR 105.67; p<0.01). A small cluster of influenza (H5N1) cases was detected during 2012–2013 along the boundaries of Guanshanhu, Yunyan, and Nanming Counties in Guizhou Province (3 cases; RR 496.60; p<0.01). Figure Geographic and temporal distribution of human cases of infection with avian influenza subtypes H7N9 (circles) and H5N1 (triangles), China. A) Distribution and space-time clusters of human influenza (H7N9) and influenza (H5N1) cases, calculated by using ... In addition, family clustering, defined as >2 family members with laboratory-confirmed cases, was found for influenza (H7N9) cases during March–April 2013 in Shanghai and Jiangsu Provinces and for influenza (H5N1) cases during December 2007 in Jiangsu Province. Family clustering may indicate person-to-person viral transmission or may reflect common exposure to infected poultry or their excrement in the household or in a contaminated environment (7). No evidence supports person-to-person viral transmission as the means of transmission in family clusters. In conclusion, we found compelling evidence that the high-risk areas for human infection with subtype H7N9 and H5N1 viruses are co-distributed in an area bordering the provinces of Anhui and Zhejiang, which suggests that this area might be a common ground for the transmission of emerging avian influenza viruses in China. We also found that visits to live poultry markets or exposure to contaminated environments are a pathway to infection with influenza (H7N9) virus, whereas infection with influenza (H5N1) is more tied to occupational hazards. These differences may reflect the differences in the pathogenicity of the viruses in poultry, which influences disease progression and identification of clinical signs further down the poultry market chain. Further empirical investigation into our findings could identify risk factors that might be involved in disease transmission to humans in high-risk areas and could help public health authorities develop targeted control and surveillance strategies to prevent disease transmission.

Modeling influenza sequence evolution for vaccination

The rapid evolution of the influenza A virus poses a global challenge to public health. Recent events, such as the spread of highly pathogenic H5N1 influenza virus, have heightened concerns of potential pandemics. Thus, there is an urgent need for a better understanding of influenza virus evolution. Due to the development of high-throughput sequencing technologies, large-scale sequencing of influenza viruses has become routine work in influenza surveillance, and analyses of these large-scale viral sequence data have significantly enhanced our understanding of influenza evolution. However, opportunities remain to extract even more useful information to inform influenza prevention and control strategy. As we know, seasonal influenza prevention and control rely largely on the availability of effective vaccines. However, timely and accurate recommendation of vaccine strains is quite challenging, as evidenced by frequent antigenic mismatches between the recommended vaccine strains and circulating strains. Our recent work has shown that development of sequence-based computational approaches to modeling the antigenic evolution of the influenza virus holds great promise for more effective vaccine strain recommendation [1,2]. Based on whole-genome information, we have developed a network model to represent each H3N2 virus as a nucleotide-co-occurrence network [1]. The network model effectively captures the evolutionary antigenic features of H3N2 virus at the whole-genome level and accurately describes the complex evolutionary patterns between individual gene segments. Our analyses show that the co-occurring nucleotide modules apparently underpin the dynamics of human H3N2 evolution, and that amino acid substitutions corresponding to nucleotide co-changes cluster preferentially in known antigenic regions of the viral surface protein hemagglutinin (HA). Therefore, our study demonstrates that nucleotide co-occurrence networks represent a powerful method for tracking influenza A virus evolution, and that cooperative genomic interaction is a major force underlying influenza virus evolution. Based on the sequences of HA, the major antigen of influenza virus, we have developed a computational method, denoted as PREDAC, to predict antigenic clusters of influenza A (H3N2) viruses with high accuracy from viral HA sequences [2]. Application of PREDAC to large-scale HA sequence data from H3N2 viruses isolated from diverse regions of mainland China identified 17 antigenic clusters that have dominated for at least one season between 1968 and 2010. By tracking the dynamics of the dominant antigenic clusters, we not only find that dominant antigenic clusters change more frequently in China than in the United States and Europe, but also characterize the antigenic patterns of seasonal H3N2 viruses within China. Furthermore, we demonstrate that the coupling of large-scale HA sequencing with PREDAC can significantly improve vaccine strain recommendation for China.

Travel‐Related Influenza A/H1N1 Infection at a Rock Festival in Hungary: One Virus May Hide Another One

Mass gathering is well known to concentrate and amplify the transmission of infectious respiratory diseases. Here we report a possible case of coinfection with influenza A/H1N1 and varicella in a young French traveler returning from a rock festival in Hungary. We report a cluster of influenza A/H1N1 cases at this festival.

The importance of school and social activities in the transmission of influenza A(H1N1)v: England, April – June 2009

During the containment phase in the United Kingdom (April to June 2009), a cluster of influenza A(H1N1)v cases was identified prompting further investigation and public health action by the Health Protection Agency. The first confirmed case, a pupil at a school in England, was imported. During the following two weeks, 16 further cases were confirmed with epidemiological links to the first imported case. In this cluster, we found that significant transmission occurred in two classes with attack rates of 17.4% and 7.4%. In each of the two classes a case had attended school whilst symptomatic. Other settings included a choir and a party. Minimum and maximum attack rates were 3.6% and 4.2% for the choir and 14.3% and 25% for the party. We did not find any evidence of transmission on two school bus trips despite exposure over 50 minutes to a symptomatic case and over two periods of 30 minutes to a case during the prodromal phase (i.e. within 12 hours of symptom onset). Nor was there onward transmission in another school despite exposure over several hours to two cases, both of whom attended school during the prodromal phase.