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Journal ArticleDOI

Estimating the impact of school closure on influenza transmission from Sentinel data

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TLDR
It is shown that holidays lead to a 20–29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults, as well as predicting the effect of school closure during a pandemic.
Abstract
The threat posed by the highly pathogenic H5N1 influenza virus requires public health authorities to prepare for a human pandemic. Although pre-pandemic vaccines and antiviral drugs might significantly reduce illness rates, their stockpiling is too expensive to be practical for many countries. Consequently, alternative control strategies, based on non-pharmaceutical interventions, are a potentially attractive policy option. School closure is the measure most often considered. The high social and economic costs of closing schools for months make it an expensive and therefore controversial policy, and the current absence of quantitative data on the role of schools during influenza epidemics means there is little consensus on the probable effectiveness of school closure in reducing the impact of a pandemic. Here, from the joint analysis of surveillance data and holiday timing in France, we quantify the role of schools in influenza epidemics and predict the effect of school closure during a pandemic. We show that holidays lead to a 20-29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults. Holidays prevent 16-18% of seasonal influenza cases (18-21% in children). By extrapolation, we find that prolonged school closure during a pandemic might reduce the cumulative number of cases by 13-17% (18-23% in children) and peak attack rates by up to 39-45% (47-52% in children). The impact of school closure would be reduced if it proved difficult to maintain low contact rates among children for a prolonged period.

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Citations
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Posted ContentDOI

Projecting social contact matrices to different demographic structures

TL;DR: The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.
Proceedings ArticleDOI

A pandemic influenza simulation model for preparedness planning

TL;DR: A geospatial and temporal disease spread model for pandemic influenza affecting multiple communities and one of the social distancing policies, school closure, is investigated in this paper.
Journal ArticleDOI

How to minimize the attack rate during multiple influenza outbreaks in a heterogeneous population.

TL;DR: For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger.
Journal ArticleDOI

Social contact patterns of school-age children in Taiwan: comparison of the term time and holiday periods.

TL;DR: The result presented in this study provide an indication of the likely reduction in daily contact frequency that might occur if a school closure policy was adopted in the event of an influenza pandemic in Taiwan.
Journal ArticleDOI

Optimizing interpretation of the tuberculin test using an interferon-gamma release assay as a reference standard.

TL;DR: The interferon-gamma release assays have greater specificity than the tuberculin skin test (TST), and at least equal sensitivity.
References
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BookDOI

Markov Chain Monte Carlo in Practice

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Jun Liu
TL;DR: This book provides a self-contained and up-to-date treatment of the Monte Carlo method and develops a common framework under which various Monte Carlo techniques can be "standardized" and compared.
Journal ArticleDOI

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TL;DR: It is found that border restrictions and/or internal travel restrictions are unlikely to delay spread by more than 2–3 weeks unless more than 99% effective, and vaccine stockpiled in advance of a pandemic could significantly reduce attack rates even if of low efficacy.
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Monte Carlo Strategies in Scientific Computing

Tim Hesterberg
- 01 Nov 2002 - 
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