Design and evaluation of prophylactic interventions using infectious disease incidence data from close contact groups

Harvard University, Cambridge, Massachusetts, United States
Journal of the Royal Statistical Society Series C Applied Statistics (Impact Factor: 1.49). 04/2006; 55(3):317 - 330. DOI: 10.1111/j.1467-9876.2006.00539.x
Source: PubMed


  Prophylaxis of contacts of infectious cases such as household members and treatment of infectious cases are methods to prevent the spread of infectious diseases. We develop a method based on maximum likelihood to estimate the efficacy of such interventions and the transmission probabilities. We consider both the design with prospective follow-up of close contact groups and the design with ascertainment of close contact groups by an index case as well as randomization by groups and by individuals. We compare the designs by using simulations. We estimate the efficacy of the influenza antiviral agent oseltamivir in reducing susceptibility and infectiousness in two case-ascertained household trials.

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    • "Since it is usually impossible to measure the full state of the system, successful model driven data collection must not only measure state variables (e.g., the number susceptible or infectious), but also attempt to determine the dynamic regime in which those variables were collected. Simulation of trial design is a growing area of research, with numerous applications to vaccine trials (e.g., Van de Velde et al., 2007; Yang et al., 2006) and growing use in other settings (e.g., PopART Cori et al., 2014). The development of standard tools similar to those available for standard sample size calculations, or even a list of best practices, would go a long way to expanding the use of mechanistic models in study design. "
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    ABSTRACT: Infectious disease models are both concise statements of hypotheses and powerful techniques for creating tools from hypotheses and theories. As such, they have tremendous potential for guiding data collection in experimental and observational studies, leading to more efficient testing of hypotheses and more robust study designs. In numerous instances, infectious disease models have played a key role in informing data collection, including the Garki project studying malaria, the response to the 2009 pandemic of H1N1 influenza in the United Kingdom and studies of T-cell immunodynamics in mammals. However, such synergies remain the exception rather than the rule; and a close marriage of dynamic modeling and empirical data collection is far from the norm in infectious disease research. Overcoming the challenges to using models to inform data collection has the potential to accelerate innovation and to improve practice in how we deal with infectious disease threats. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.
    Full-text · Article · Dec 2014 · Epidemics
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    • "This common assumption appears to stem from an estimate made in [38] based on 1998–1999 trial data. Our higher value is based on a more comprehensive estimation process reported in [35], which also incorporated data from an additional study performed in 2000–2001 [39]. It is also in line with estimates of 64%-89% reported in [40]. "
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    ABSTRACT: Background The threat of emergence of a human-to-human transmissible strain of highly pathogenic influenza A(H5N1) is very real, and is reinforced by recent results showing that genetically modified A(H5N1) may be readily transmitted between ferrets. Public health authorities are hesitant in introducing social distancing interventions due to societal disruption and productivity losses. This study estimates the effectiveness and total cost (from a societal perspective, with a lifespan time horizon) of a comprehensive range of social distancing and antiviral drug strategies, under a range of pandemic severity categories. Methods An economic analysis was conducted using a simulation model of a community of ~30,000 in Australia. Data from the 2009 pandemic was used to derive relationships between the Case Fatality Rate (CFR) and hospitalization rates for each of five pandemic severity categories, with CFR ranging from 0.1% to 2.5%. Results For a pandemic with basic reproduction number R0 = 1.8, adopting no interventions resulted in total costs ranging from $441 per person for a pandemic at category 1 (CFR 0.1%) to $8,550 per person at category 5 (CFR 2.5%). For severe pandemics of category 3 (CFR 0.75%) and greater, a strategy combining antiviral treatment and prophylaxis, extended school closure and community contact reduction resulted in the lowest total cost of any strategy, costing $1,584 per person at category 5. This strategy was highly effective, reducing the attack rate to 5%. With low severity pandemics costs are dominated by productivity losses due to illness and social distancing interventions, whereas higher severity pandemic costs are dominated by healthcare costs and costs arising from productivity losses due to death. Conclusions For pandemics in high severity categories the strategies with the lowest total cost to society involve rigorous, sustained social distancing, which are considered unacceptable for low severity pandemics due to societal disruption and cost.
    Full-text · Article · Mar 2013 · BMC Public Health
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    • "An important data gap should be identified for future observational studies, because an explicit statistical analysis could be made based on a well-designed observational study [38]. The designed observational study could also satisfy other objectives including the determination of optimal duration of prophylaxis [39]. "
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    ABSTRACT: Background During the very early stage of the 2009 pandemic, mass chemoprophylaxis was implemented as part of containment measure. The purposes of the present study were to systematically review the retrospective studies that investigated the effectiveness of antiviral prophylaxis during the 2009 pandemic, and to explicitly estimate the effectiveness by employing a mathematical model. Methods A systematic review identified 17 articles that clearly defined the cases and identified exposed individuals based on contact tracing. Analysing a specific school-driven outbreak, we estimated the effectiveness of antiviral prophylaxis using a renewal equation model. Other parameters, including the reproduction number and the effectiveness of antiviral treatment and school closure, were jointly estimated. Results Based on the systematic review, median secondary infection risks (SIRs) among exposed individuals with and without prophylaxis were estimated at 2.1% (quartile: 0, 12.2) and 16.6% (quartile: 8.4, 32.4), respectively. A very high heterogeneity in the SIR was identified with an estimated I2 statistic at 71.8%. From the outbreak data in Madagascar, the effectiveness of mass chemoprophylaxis in reducing secondary transmissions was estimated to range from 92.8% to 95.4% according to different model assumptions and likelihood functions, not varying substantially as compared to other parameters. Conclusions Only based on the meta-analysis of retrospective studies with different study designs and exposure settings, it was not feasible to estimate the effectiveness of antiviral prophylaxis in reducing transmission. However, modelling analysis of a single outbreak successfully yielded an estimate of the effectiveness that appeared to be robust to model assumptions. Future studies should fill the data gap that has existed in observational studies and allow mathematical models to be used for the analysis of meta-data.
    Full-text · Article · Jan 2013 · Theoretical Biology and Medical Modelling
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