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      H3N2v and Other Influenza Epidemic Risk Based on Age-Specific Estimates of Sero-Protection and Contact Network Interactions

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          Abstract

          Cases of a novel swine-origin influenza A(H3N2) variant (H3N2v) have recently been identified in the US, primarily among children. We estimated potential epidemic attack rates (ARs) based on age-specific estimates of sero-susceptibility and social interactions. A contact network model previously established for the Greater Vancouver Area (GVA), Canada was used to estimate average epidemic (infection) ARs for the emerging H3N2v and comparator viruses (H1N1pdm09 and an extinguished H3N2 seasonal strain) based on typical influenza characteristics, basic reproduction number (R 0), and effective contacts taking into account age-specific sero-protection rates (SPRs). SPRs were assessed in sera collected from the GVA in 2009 or earlier (pre-H1N1pdm09) and fall 2010 (post-H1N1pdm09, seasonal A/Brisbane/10/2007(H3N2), and H3N2v) by hemagglutination inhibition (HI) assay. SPR was assigned per convention based on proportion with HI antibody titre ≥40 (SPR40). Recognizing that the HI titre ≥40 was established as the 50%sero-protective threshold we also explored for ½SPR40, SPR80 and a blended gradient defined as: ¼SPR20, ½SPR40, ¾SPR80, SPR160. Base case analysis assumed R 0 = 1.40, but we also explored R 0 as high as 1.80. With R 0 = 1.40 and SPR40, simulated ARs were well aligned with field observations for H1N1pdm09 incidence (AR: 32%), sporadic detections without a third epidemic wave post-H1N1pdm09 (negligible AR<0.1%) as well as A/Brisbane/10/2007(H3N2) seasonal strain extinction and antigenic drift replacement (negligible AR<0.1%). Simulated AR for the novel swine-origin H3N2v was 6%, highest in children 6–11years (16%). However, with modification to SPR thresholds per above, H3N2v AR ≥20% became possible. At SPR40, H3N2v AR ≥10%, ≥15% or ≥30%, occur if R 0≥1.48, ≥1.56 or ≥1.86, respectively. Based on conventional assumptions, the novel swine-origin H3N2v does not currently pose a substantial pandemic threat. If H3N2v epidemics do occur, overall community ARs are unlikely to exceed typical seasonal influenza experience. However risk assessment may change with time and depends crucially upon the validation of epidemiological features of influenza, notably the serologic correlate of protection and R 0.

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          Network theory and SARS: predicting outbreak diversity

          Many infectious diseases spread through populations via the networks formed by physical contacts among individuals. The patterns of these contacts tend to be highly heterogeneous. Traditional “compartmental” modeling in epidemiology, however, assumes that population groups are fully mixed, that is, every individual has an equal chance of spreading the disease to every other. Applications of compartmental models to Severe Acute Respiratory Syndrome (SARS) resulted in estimates of the fundamental quantity called the basic reproductive number R 0 —the number of new cases of SARS resulting from a single initial case—above one, implying that, without public health intervention, most outbreaks should spark large-scale epidemics. Here we compare these predictions to the early epidemiology of SARS. We apply the methods of contact network epidemiology to illustrate that for a single value of R 0 , any two outbreaks, even in the same setting, may have very different epidemiological outcomes. We offer quantitative insight into the heterogeneity of SARS outbreaks worldwide, and illustrate the utility of this approach for assessing public health strategies.
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            Hemagglutination inhibition antibody titers as a correlate of protection for inactivated influenza vaccines in children.

            The hemagglutination inhibition (HI) titer of 1:40, which has been recognized as an immunologic correlate corresponding to a 50% reduction in the risk of contracting influenza, is based on studies in adults. Neither seasonal nor challenge-based correlates have been evaluated in children. A total of 4707 influenza vaccine-naive healthy children 6 to 72 months old were randomized in a ratio of 2:2:1 to receive 2 doses of MF-59-adjuvanted influenza vaccine (Novartis Vaccines), trivalent inactivated influenza vaccine subunit (trivalent inactivated influenza vaccine control, GSK), or a saline placebo during the 2007 to 2008 and 2008 to 2009 influenza seasons. The second dose was given 30 days after dose 1. Clinical influenza-like illnesses cases identified by active surveillance were confirmed by reverse transcription polymerase chain reaction testing for influenza. Vaccine immunogenicity 50 days after dose 1 was evaluated in a subset of 777 children. Immunogenicity and efficacy results for H3N2 were evaluated against the Prentice criteria, which confirmed that the immunogenicity results warranted estimation of an immunologic correlate. We then used the Dunning model fitting the H3N2 antibody titers at day 50 and the influenza cases observed in the immunogenicity subset to estimate a correlate of protection. This analysis revealed that a cutoff HI titer of 1:110 was associated with the conventional 50% clinical protection rate against infection during the entire season, and titers of 1:215, 1:330, and 1:629 predicated protection rates of 70%, 80%, and 90%, respectively. The conventional adult HI titer of 1:40 was only associated with 22% protection. The use of the 1:40 HI adult correlate of protection is not appropriate when evaluating influenza vaccines in children. Although a cutoff of 1:110 may be used to predict the conventional 50% clinical protection rate, a titer of 1:330 would predict an 80% protective level, which would seem to be more desirable from a public health perspective.
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              Estimated epidemiologic parameters and morbidity associated with pandemic H1N1 influenza.

              In the face of an influenza pandemic, accurate estimates of epidemiologic parameters are required to help guide decision-making. We sought to estimate epidemiologic parameters for pandemic H1N1 influenza using data from initial reports of laboratory-confirmed cases. We obtained data on laboratory-confirmed cases of pandemic H1N1 influenza reported in the province of Ontario, Canada, with dates of symptom onset between Apr. 13 and June 20, 2009. Incubation periods and duration of symptoms were estimated and fit to parametric distributions. We used competing-risk models to estimate risk of hospital admission and case-fatality rates. We used a Markov Chain Monte Carlo model to simulate disease transmission. The median incubation period was 4 days and the duration of symptoms was 7 days. Recovery was faster among patients less than 18 years old than among older patients (hazard ratio 1.23, 95% confidence interval 1.06-1.44). The risk of hospital admission was 4.5% (95% CI 3.8%-5.2%) and the case-fatality rate was 0.3% (95% CI 0.1%-0.5%). The risk of hospital admission was highest among patients less than 1 year old and those 65 years or older. Adults more than 50 years old comprised 7% of cases but accounted for 7 of 10 initial deaths (odds ratio 28.6, 95% confidence interval 7.3-111.2). From the simulation models, we estimated the following values (and 95% credible intervals): a mean basic reproductive number (R0, the number of new cases created by a single primary case in a susceptible population) of 1.31 (1.25-1.38), a mean latent period of 2.62 (2.28-3.12) days and a mean duration of infectiousness of 3.38 (2.06-4.69) days. From these values we estimated a serial interval (the average time from onset of infectiousness in a case to the onset of infectiousness in a person infected by that case) of 4-5 days. The low estimates for R0 indicate that effective mitigation strategies may reduce the final epidemic impact of pandemic H1N1 influenza.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                11 January 2013
                : 8
                : 1
                : e54015
                Affiliations
                [1 ]Communicable Disease Prevention and Control Services, British Columbia Centre for Disease Control, Vancouver, Canada
                [2 ]School of Population and Public Health, University of British Columbia, Vancouver, Canada
                [3 ]BC Biomedical Laboratories Ltd, Surrey, Canada
                [4 ]Public Health Microbiology and Reference Laboratory, British Columbia Centre for Disease Control, Vancouver, Canada
                [5 ]Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
                Melbourne School of Population Health, Australia
                Author notes

                Competing Interests: DP is a shareholder with BC Biomedical Laboratories Ltd. which contributed anonymized sera included in the original sero-prevalence surveys; however, he received no direct compensation for previous or current contributions to this H3N2v analysis. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

                Provided critical feedback and input for manuscript revision and approval: FSM NZJ BD KME DP MP BP. Conceived and designed the experiments: DMS FSM NZJ BP BD KME DP MP. Performed the experiments: FSM MP. Analyzed the data: DMS FSM NZJ BP. Contributed reagents/materials/analysis tools: BD KME DP MP. Wrote the paper: DMS.

                Article
                PONE-D-12-21738
                10.1371/journal.pone.0054015
                3543419
                23326561
                55b89068-087a-410a-9808-76a449a62c1f
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 July 2012
                : 5 December 2012
                Page count
                Pages: 10
                Funding
                This work was supported by the Canadian Institutes of Health Research (PTL-97126) and the Michael Smith Foundation for Health Research (Grant numbers CI-SSH-00931(06-1) and 20R45696). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Population Biology
                Epidemiology
                Infectious Disease Epidemiology
                Medicine
                Clinical Immunology
                Immunity
                Humoral Immunity
                Clinical Research Design
                Epidemiology
                Epidemiology
                Clinical Epidemiology
                Infectious Disease Epidemiology
                Infectious Diseases
                Viral Diseases
                Influenza
                Infectious Disease Modeling

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                Uncategorized

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