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ABSTRACT: SUMMARY We investigated the cost-effectiveness of different influenza control strategies in a school setting in Taiwan. A susceptible-exposure-infected-recovery (SEIR) model was used to simulate influenza transmission and we used a basic reproduction number (R 0)-asymptomatic proportion (θ) control scheme to develop a cost-effectiveness model. Based on our dynamic transmission model and economic evaluation, this study indicated that the optimal cost-effective strategy for all modelling scenarios was a combination of natural ventilation and respiratory masking. The estimated costs were US$10/year per person in winter for one kindergarten student. The cost for hand washing was estimated to be US$32/year per person, which was much lower than that of isolation (US$55/year per person) and vaccination (US$86/year per person) in containing seasonal influenza. Transmission model-based, cost-effectiveness analysis can be a useful tool for providing insight into the impacts of economic factors and health benefits on certain strategies for controlling seasonal influenza.
Epidemiology and Infection 03/2013; · 2.84 Impact Factor
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ABSTRACT: The aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 10(3)-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.
Epidemiology and Infection 11/2011; 140(9):1557-68. · 2.84 Impact Factor
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ABSTRACT: This study aimed to estimate the natural history and transmission parameters based on experimental viral shedding and symptom dynamics in order to understand the key epidemiological factors that characterize influenza (sub)type epidemics. A simple statistical algorithm was developed by combining a well-defined mathematical scheme of epidemiological determinants and experimental human influenza infection. Here we showed that (i) the observed viral shedding dynamics mapped successfully the estimated time-profile of infectiousness and (ii) the profile of asymptomatic probability was obtained based on observed temporal variation of symptom scores. Our derived estimates permitted evaluation of relationships between various model-derived and data-based estimations, allowing evaluation of trends proposed previously but not tested fully. As well as providing insights into the dynamics of viral shedding and symptom scores, a more profound understanding of influenza epidemiological parameters and determinants could enhance the viral kinetic studies of influenza during infection in the respiratory tracts of experimentally infected individuals.
Epidemiology and Infection 11/2009; 138(6):825-35. · 2.84 Impact Factor
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ABSTRACT: The purpose of this paper was to investigate the effects of viral kinetics and exhaled droplet size on indoor transmission dynamics of influenza infection. The target cell-limited model with delayed virus production was adopted to strengthen the inner mechanisms of virus infection on human epithelial cell. The particle number and volume involved in the viral kinetics were linked with Wells-Riley mathematical equation to quantify the infection risk. We investigated population dynamics in a specific elementary school by using the seasonal susceptible - exposed - infected - recovery (SEIR) model. We found that exhaled pulmonary bioaerosol of sneeze (particle diameter <10 microm) have 10(2)-fold estimate higher than that of cough. Sneeze and cough caused risk probabilities range from 0.075 to 0.30 and 0.076, respectively; whereas basic reproduction numbers (R(0)) estimates range from 4 to 17 for sneeze and nearly 4 for cough, indicating sneeze-posed higher infection risk. The viral kinetics and exhaled droplet size for sneeze affect indoor transmission dynamics of influenza infection since date post-infection 1-7. This study provides direct mechanistic support that indoor influenza virus transmission can be characterized by viral kinetics in human upper respiratory tracts that are modulated by exhaled droplet size. Practical Implications This paper provides a predictive model that can integrate the influenza viral kinetics (target cell-limited model), indoor aerosol transmission potential (Wells-Riley mathematical equation), and population dynamic model [susceptible - exposed - infected - recovery (SEIR) model] in a proposed susceptible population. Viral kinetics expresses the competed results of human immunity ability with influenza virus generation. By linking the viral kinetics and different exposure parameters and environmental factors in a proposed school setting with five age groups, the influenza infection risk can be estimated. On the other hand, we implicated a new simple means of inhaling to mitigate exhaled bioaerosols through an inhaled non-toxic aerosol. The proposed predictive model may serve as a tool for further investigation of specific control measure such as the personal protection masks to alter the particle size and number concentration characteristics and minimize the exhaled bioaerosol droplet to decrease the infection risk in indoor environment settings.
Indoor Air 02/2009; 19(5):401-13. · 2.55 Impact Factor
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ABSTRACT: We coupled the Wells-Riley equation and the susceptible-exposed-infected-recovery (SEIR) model to quantify the impact of the combination of indoor air-based control measures of enhanced ventilation and respiratory masking in containing pandemic influenza within an elementary school. We integrated indoor environmental factors of a real elementary school and aetiological characteristics of influenza to estimate the age-specific risk of infection (P) and basic reproduction number (R(0)). We combined the enhanced ventilation rates of 0.5, 1, 1.5, and 2/h and respiratory masking with 60%, 70%, 80%, and 95% efficacies, respectively, to predict the reducing level of R0. We also took into account the critical vaccination coverage rate among schoolchildren. Age-specific P and R(0) were estimated respectively to be 0.29 and 16.90; 0.56 and 16.11; 0.59 and 12.88; 0.64 and 16.09; and 0.07 and 2.80 for five age groups 4-6, 7-8, 9-10, 11-12, and 25-45 years, indicating pre-schoolchildren have the highest transmission potential. We conclude that our integrated approach, employing the mechanism of transmission of indoor respiratory infection, population-dynamic transmission model, and the impact of infectious control programmes, is a powerful tool for risk profiling prediction of pandemic influenza among schoolchildren.
Epidemiology and Infection 09/2008; 136(8):1035-45. · 2.84 Impact Factor
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ABSTRACT: One of the most pressing issues in facing emerging and re-emerging respiratory infections is how to bring them under control with current public health measures. Approaches such as the Wells-Riley equation, competing-risks model, and Von Foerster equation are used to prioritize control-measure efforts. Here we formulate how to integrate those three different types of functional relationship to construct easy-to-use and easy-to-interpret critical-control lines that help determine optimally the intervention strategies for containing airborne infections. We show that a combination of assigned effective public health interventions and enhanced engineering control measures would have a high probability for containing airborne infection. We suggest that integrated analysis to enhance modelling the impact of potential control measures against airborne infections presents an opportunity to assess risks and benefits. We demonstrate the approach with examples of optimal control measures to prioritize respiratory infections of severe acute respiratory syndrome (SARS), influenza, measles, and chickenpox.
Epidemiology and Infection 04/2008; 136(3):299-308. · 2.84 Impact Factor
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ABSTRACT: Vaccination has proved a powerful defence against measles. We reappraise measles seroepidemiological data in Taiwan from 1974 to 2004 having robust age-stratified serological information on exposure and immunity to quantitatively characterize measles vaccination programmes. We dynamically model measles seroepidemiology to estimate age-dependent intensity of infection associated with the effects of different contact patterns on pre- and post-vaccination. The WAIFM (who acquires infection from whom) contact matrix is employed to describe the transmission between and within each age group. A deterministic SEIR (susceptible-exposed-infected-recovery) model is used to capture subpopulation dynamics. Our study shows that mass regional or nationwide vaccination programmes could greatly reduce the potential for a major measles epidemic and have strong direct effects on the potential impact of childhood vaccination. We parameterize a predictive model that should reduce the socio-economic costs of measles surveillance in Taiwan and thereby encourage its continuance, especially for preschool children.
Epidemiology and Infection 08/2007; 135(5):775-86. · 2.84 Impact Factor
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ABSTRACT: Recently developed control measure modeling approaches for containing airborne infections, including engineering controls with respiratory protection and public health interventions, are readily amenable to an integrated-scale analysis. Here we show that such models can be derived from an integrated-scale analysis generated from three different types of functional relationship: Wells-Riley mathematical model, competing-risks model, and Von Foerster equation, both of the key epidemiological determinants involved and of the functional connections between them. We examine mathematically the impact of engineering control measures such as enhanced air exchange and air filtration rates with personal masking combined with public health interventions such as vaccination, isolation, and contact tracing in containing the spread of indoor airborne infections including influenza, chickenpox, measles, and severe acute respiratory syndrome (SARS). If enhanced engineering controls could reduce the basic reproductive number (R0) below 1.60 for chickenpox and 3 for measles, our simulations show that in such a prepared response with public health interventions would have a high probability of containing the indoor airborne infections. Combinations of engineering control measures and public health interventions could moderately contain influenza strains with an R0 as high as 4. Our analysis indicates that effective isolation of symptomatic patients with low-efficacy contact tracing is sufficient to control a SARS outbreak. We suggest that a valuable added dimension to public health inventions could be provided by systematically quantifying transmissibility and proportion of asymptomatic infection of indoor airborne infection. Practical Implications We have developed a flexible mathematical model that can help determine the best intervention strategies for containing indoor airborne infections. The approach presented here is scalable and can be extended to include additional control efficacies. If a newly emergent airborne infection should appear, the model could be quickly calibrated to data and intervention options at the early stage of the outbreak. Data could be provided from the field to estimate value of R0, the serial interval between cases, the distributions of the latent, incubation, and infectious periods, case fatality rates, and secondary spread within important mixing groups. The combination of enhanced engineering control measures and assigned effective public health interventions would have a high probability for containing airborne infection.
Indoor Air 01/2007; 16(6):469-81. · 2.55 Impact Factor
