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      Reproductive Number and Serial Interval of the First Wave of Influenza A(H1N1)pdm09 Virus in South Africa

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          Abstract

          Background/Objective

          Describing transmissibility parameters of past pandemics from diverse geographic sites remains critical to planning responses to future outbreaks. We characterize the transmissibility of influenza A(H1N1)pdm09 (hereafter pH1N1) in South Africa during 2009 by estimating the serial interval (SI), the initial effective reproductive number (initial R t ) and the temporal variation of R t .

          Methods

          We make use of data from a central registry of all pH1N1 laboratory-confirmed cases detected throughout South Africa. Whenever date of symptom onset is missing, we estimate it from the date of specimen collection using a multiple imputation approach repeated 100 times for each missing value. We apply a likelihood-based method (method 1) for simultaneous estimation of initial R t and the SI; estimate initial R t from SI distributions established from prior field studies (method 2); and the Wallinga and Teunis method (method 3) to model the temporal variation of R t .

          Results

          12,360 confirmed pH1N1 cases were reported in the central registry. During the period of exponential growth of the epidemic (June 21 to August 3, 2009), we simultaneously estimate a mean R t of 1.47 (95% CI: 1.30–1.72) and mean SI of 2.78 days (95% CI: 1.80–3.75) (method 1). Field studies found a mean SI of 2.3 days between primary cases and laboratory-confirmed secondary cases, and 2.7 days when considering both suspected and confirmed secondary cases. Incorporating the SI estimate from field studies using laboratory-confirmed cases, we found an initial R t of 1.43 (95% CI: 1.38–1.49) (method 2). The mean R t peaked at 2.91 (95% CI: 0.85–2.91) on June 21, as the epidemic commenced, and R t >1 was sustained until August 22 (method 3).

          Conclusions

          Transmissibility characteristics of pH1N1 in South Africa are similar to estimates reported by countries outside of Africa. Estimations using the likelihood-based method are in agreement with field findings.

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          Most cited references25

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          Transmissibility of 1918 pandemic influenza

          The 1918 influenza pandemic killed 20–40 million people worldwide 1 , and is seen as a worst-case scenario for pandemic planning. Like other pandemic influenza strains, the 1918 A/H1N1 strain spread extremely rapidly. A measure of transmissibility and of the stringency of control measures required to stop an epidemic is the reproductive number, which is the number of secondary cases produced by each primary case 2 . Here we obtained an estimate of the reproductive number for 1918 influenza by fitting a deterministic SEIR (susceptible-exposed-infectious-recovered) model to pneumonia and influenza death epidemic curves from 45 US cities: the median value is less than three. The estimated proportion of the population with A/H1N1 immunity before September 1918 implies a median basic reproductive number of less than four. These results strongly suggest that the reproductive number for 1918 pandemic influenza is not large relative to many other infectious diseases 2 . In theory, a similar novel influenza subtype could be controlled. But because influenza is frequently transmitted before a specific diagnosis is possible and there is a dearth of global antiviral and vaccine stores, aggressive transmission reducing measures will probably be required. Supplementary information The online version of this article (doi:10.1038/nature03063) contains supplementary material, which is available to authorized users.
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            Containing pandemic influenza with antiviral agents.

            I Longini (2004)
            For the first wave of pandemic influenza or a bioterrorist influenza attack, antiviral agents would be one of the few options to contain the epidemic in the United States until adequate supplies of vaccine were available. The authors use stochastic epidemic simulations to investigate the effectiveness of targeted antiviral prophylaxis to contain influenza. In this strategy, close contacts of suspected index influenza cases take antiviral agents prophylactically. The authors compare targeted antiviral prophylaxis with vaccination strategies. They model an influenza pandemic or bioterrorist attack for an agent similar to influenza A virus (H2N2) that caused the Asian influenza pandemic of 1957-1958. In the absence of intervention, the model predicts an influenza illness attack rate of 33% of the population (95% confidence interval (CI): 30, 37) and an influenza death rate of 0.58 deaths/1,000 persons (95% Cl: 0.4, 0.8). With the use of targeted antiviral prophylaxis, if 80% of the exposed persons maintained prophylaxis for up to 8 weeks, the epidemic would be contained, and the model predicts a reduction to an illness attack rate of 2% (95% Cl: 0.2, 16) and a death rate of 0.04 deaths/1,000 persons (95% CI: 0.0003, 0.25). Such antiviral prophylaxis is nearly as effective as vaccinating 80% of the population. Vaccinating 80% of the children aged less than 19 years is almost as effective as vaccinating 80% of the population. Targeted antiviral prophylaxis has potential as an effective measure for containing influenza until adequate quantities of vaccine are available.
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              Household transmission of 2009 pandemic influenza A (H1N1) virus in the United States.

              As of June 11, 2009, a total of 17,855 probable or confirmed cases of 2009 pandemic influenza A (H1N1) had been reported in the United States. Risk factors for transmission remain largely uncharacterized. We characterize the risk factors and describe the transmission of the virus within households. Probable and confirmed cases of infection with the 2009 H1N1 virus in the United States were reported to the Centers for Disease Control and Prevention with the use of a standardized case form. We investigated transmission of infection in 216 households--including 216 index patients and their 600 household contacts--in which the index patient was the first case patient and complete information on symptoms and age was available for all household members. An acute respiratory illness developed in 78 of 600 household contacts (13%). In 156 households (72% of the 216 households), an acute respiratory illness developed in none of the household contacts; in 46 households (21%), illness developed in one contact; and in 14 households (6%), illness developed in more than one contact. The proportion of household contacts in whom acute respiratory illness developed decreased with the size of the household, from 28% in two-member households to 9% in six-member households. Household contacts 18 years of age or younger were twice as susceptible as those 19 to 50 years of age (relative susceptibility, 1.96; Bayesian 95% credible interval, 1.05 to 3.78; P=0.005), and household contacts older than 50 years of age were less susceptible than those who were 19 to 50 years of age (relative susceptibility, 0.17; 95% credible interval, 0.02 to 0.92; P=0.03). Infectivity did not vary with age. The mean time between the onset of symptoms in a case patient and the onset of symptoms in the household contacts infected by that patient was 2.6 days (95% credible interval, 2.2 to 3.5). The transmissibility of the 2009 H1N1 influenza virus in households is lower than that seen in past pandemics. Most transmissions occur soon before or after the onset of symptoms in a case patient. 2009 Massachusetts Medical Society
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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
                2012
                16 November 2012
                : 7
                : 11
                : e49482
                Affiliations
                [1 ]National Institute for Communicable Diseases (NICD), National Health Laboratory Service (NHLS), Johannesburg, Gauteng, South Africa
                [2 ]United States Centers for Disease Control and Prevention, Attaché to the National Institute for Communicable Diseases (NICD), National Health Laboratory Service (NHLS), Johannesburg, Gauteng, South Africa
                [3 ]Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, United States of America
                [4 ]School of Public Health, Harvard University, Cambridge, Massachusetts, United States of America
                [5 ]School of Public Health, University of Witwatersrand, Johannesburg, Gauteng, South Africa
                University of Hong Kong, Hong Kong
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: BA ST LFW MP CC. Performed the experiments: BA ST LW. Analyzed the data: BA ST LW. Contributed reagents/materials/analysis tools: BA ST LFW MP CC. Wrote the paper: BA ST LFW MP CC.

                Article
                PONE-D-12-17363
                10.1371/journal.pone.0049482
                3500305
                23166682
                07d1e88e-1a67-47ff-9c4f-52989ddaac99
                Copyright @ 2012

                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
                : 11 June 2012
                : 9 October 2012
                Page count
                Pages: 7
                Funding
                This work was partly supported by the National Institute for Communicable Diseases (NICD), a division of the National Health Laboratory Service (NHLS). Laboratory testing and influenza surveillance activities at the NICD are funded, in part, by an unrestricted grant from the United States Centers for Disease Control and Prevention (CDC) [grant number 5U51/IP000155]. Dr. White and Dr. Pagano were supported by the National Institute of General Medical Sciences (NIGMS) [award number U54GM088558]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NICD, NHLS, US CDC, NIGMS, NIH or the affiliated universities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Microbiology
                Virology
                Viral Transmission and Infection
                Population Biology
                Epidemiology
                Infectious Disease Epidemiology
                Medicine
                Epidemiology
                Infectious Disease Epidemiology
                Infectious Diseases
                Viral Diseases
                Influenza
                Infectious Disease Modeling

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