Doherty Institute - Research Publications
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ItemImpact of Emerging Antiviral Drug Resistance on Influenza Containment and Spread: Influence of Subclinical Infection and Strategic Use of a Stockpile Containing One or Two Drugs(PUBLIC LIBRARY SCIENCE, 2008-06-04)BACKGROUND: Wide-scale use of antiviral agents in the event of an influenza pandemic is likely to promote the emergence of drug resistance, with potentially deleterious effects for outbreak control. We explored factors promoting resistance within a dynamic infection model, and considered ways in which one or two drugs might be distributed to delay the spread of resistant strains or mitigate their impact. METHODS AND FINDINGS: We have previously developed a novel deterministic model of influenza transmission that simulates treatment and targeted contact prophylaxis, using a limited stockpile of antiviral agents. This model was extended to incorporate subclinical infections, and the emergence of resistant virus strains under the selective pressure imposed by various uses of one or two antiviral agents. For a fixed clinical attack rate, R(0) rises with the proportion of subclinical infections thus reducing the number of infections amenable to treatment or prophylaxis. In consequence, outbreak control is more difficult, but emergence of drug resistance is relatively uncommon. Where an epidemic may be constrained by use of a single antiviral agent, strategies that combine treatment and prophylaxis are most effective at controlling transmission, at the cost of facilitating the spread of resistant viruses. If two drugs are available, using one drug for treatment and the other for prophylaxis is more effective at preventing propagation of mutant strains than either random allocation or drug cycling strategies. Our model is relatively straightforward, and of necessity makes a number of simplifying assumptions. Our results are, however, consistent with the wider body of work in this area and are able to place related research in context while extending the analysis of resistance emergence and optimal drug use within the constraints of a finite drug stockpile. CONCLUSIONS: Combined treatment and prophylaxis represents optimal use of antiviral agents to control transmission, at the cost of drug resistance. Where two drugs are available, allocating different drugs to cases and contacts is likely to be most effective at constraining resistance emergence in a pandemic scenario.
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ItemA Small Community Model for the Transmission of Infectious Diseases: Comparison of School Closure as an Intervention in Individual-Based Models of an Influenza Pandemic(PUBLIC LIBRARY SCIENCE, 2008-12-23)BACKGROUND: In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic. METHOD: We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world. RESULTS: We showed that published individual based models estimate similar final attack rates over a range of values for R(0) in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R(0) values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure. CONCLUSION: Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.
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ItemA Biological Model for Influenza Transmission: Pandemic Planning Implications of Asymptomatic Infection and Immunity(PUBLIC LIBRARY SCIENCE, 2007-11-28)BACKGROUND: The clinical attack rate of influenza is influenced by prior immunity and mixing patterns in the host population, and also by the proportion of infections that are asymptomatic. This complexity makes it difficult to directly estimate R(0) from the attack rate, contributing to uncertainty in epidemiological models to guide pandemic planning. We have modelled multiple wave outbreaks of influenza from different populations to allow for changing immunity and asymptomatic infection and to make inferences about R(0). DATA AND METHODS: On the island of Tristan da Cunha (TdC), 96% of residents reported illness during an H3N2 outbreak in 1971, compared with only 25% of RAF personnel in military camps during the 1918 H1N1 pandemic. Monte Carlo Markov Chain (MCMC) methods were used to estimate model parameter distributions. FINDINGS: We estimated that most islanders on TdC were non-immune (susceptible) before the first wave, and that almost all exposures of susceptible persons caused symptoms. The median R(0) of 6.4 (95% credibility interval 3.7-10.7) implied that most islanders were exposed twice, although only a minority became ill in the second wave because of temporary protection following the first wave. In contrast, only 51% of RAF personnel were susceptible before the first wave, and only 38% of exposed susceptibles reported symptoms. R(0) in this population was also lower [2.9 (2.3-4.3)], suggesting reduced viral transmission in a partially immune population. INTERPRETATION: Our model implies that the RAF population was partially protected before the summer pandemic wave of 1918, arguably because of prior exposure to interpandemic influenza. Without such protection, each symptomatic case of influenza would transmit to between 2 and 10 new cases, with incidence initially doubling every 1-2 days. Containment of a novel virus could be more difficult than hitherto supposed.
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ItemModel answers or trivial pursuits? The role of mathematical models in influenza pandemic preparedness planning(WILEY, 2007-03-01)The panzootic of H5N1 influenza in birds has raised concerns that the virus will mutate to spread more readily in people, leading to a human pandemic. Mathematical models have been used to interpret past pandemics and outbreaks, and to thus model possible future pandemic scenarios and interventions. We review historical influenza outbreak and transmission data, and discuss the way in which modellers have used such sources to inform model structure and assumptions. We suggest that urban attack rates in the 1918-1919 pandemic were constrained by prior immunity, that R(0) for influenza is higher than often assumed, and that control of any future pandemic could be difficult in the absence of significant prior immunity. In future, modelling assumptions, parameter estimates and conclusions should be tested against as many relevant data sets as possible. To this end, we encourage researchers to access FluWeb, an on-line influenza database of historical pandemics and outbreaks.
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ItemUnderstanding influenza transmission, immunity and pandemic threats(WILEY, 2009-07-01)The current pandemic threat can be best understood within an ecological framework that takes account of the history of past pandemics caused by influenza A, the relationships between pandemic and seasonal spread of influenza viruses, and the importance of immunity and behavioural responses in human populations. Isolated populations without recent exposure to seasonal influenza seem more susceptible to new pandemic viruses, and much collateral evidence suggests that this is due to immunity directed against epitopes shared between pandemic and previously circulating strains of inter-pandemic influenza A virus. In the highly connected modern world, most populations are regularly exposed to non-pandemic viruses, which can even boost immunity without causing influenza symptoms. Such naturally-induced immunity helps to explain the low attack-rates of seasonal influenza, as well as the moderate attack-rates in many urbanized populations affected by 1918-1919 and later pandemics. The effectiveness of immunity, even against seasonal influenza, diminishes over time because of antigenic drift in circulating viruses and waning of post-exposure immune responses. Epidemiological evidence suggests that cross-protection against a new pandemic strain could fade even faster. Nevertheless, partial protection, even of short duration, induced by prior seasonal influenza or vaccination against it, could provide important protection in the early stages of a new pandemic.
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ItemSafety and immunogenicity of an inactivated thimerosal-free influenza vaccine in infants and children(WILEY, 2009-11-01)OBJECTIVE: Few prospective studies of inactivated split virion influenza vaccine have been conducted in infants and children. Our objective was to evaluate the safety, reactogenicity and immunogenicity of a thimerosal-free inactivated influenza vaccine (Fluvax; CSL Limited, Parkville, Australia) in children aged 6 months to <9 years. METHODS: A prospective, open-label, phase III clinical trial was conducted in 298 healthy children previously unvaccinated with influenza, commencing in the Southern Hemisphere 2005 autumn. Participants were divided into two groups (Group A: > or =6 months to <3 years; Group B: > or =3 years to <9 years), and received two doses of the 2005 vaccine, and one dose of the 2006 vaccine one year later (Group A: 0.25 ml per dose; Group B: 0.5 ml per dose). Vaccine safety and reactogenicity was evaluated for 30 days after each dose. Immunogenicity was assessed using hemagglutination inhibition and single radial hemolysis assays. RESULTS: There were no withdrawals due to adverse events (AEs). The majority of solicited local and systemic AEs were of mild severity. A maximum intensity of severe was reported for injection site pain and fever by only 3.0% and 3.4% of participants, respectively. The vaccine was immunogenic for all antigens, with > or =95% of both younger and older children achieving seroprotection after dose 2. CONCLUSIONS: This thimerosal-free inactivated influenza vaccine had a favorable safety profile and was immunogenic in children aged > or =6 months and <9 years. Primary and booster vaccination produced consistently immunogenic responses including in children under 3 years of age receiving 0.25 ml doses of vaccine.