scispace - formally typeset
Journal ArticleDOI

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

Reads0
Chats0
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.

read more

Citations
More filters
Dissertation

Stationary and temporal structure of antibody titer distributions to human influenza A virus in southern Vietnam

TL;DR: This thesis investigates 20,152 general-population serum samples from southern Vietnam collected between 2009 and 2013 from which antibody titers to the influenza virus HA1 protein are reported using a continuous titer measurement from a protein microarray assay and develops two methods for analyzing this serum collection as a time series.
Journal ArticleDOI

An Iterated Block Particle Filter for Inference on Coupled Dynamic Systems With Shared and Unit-Specific Parameters

TL;DR: A new iterated block particle filter algorithm applicable when parameters are unit-specific or shared between units, and demonstrated by performing inference on a coupled epidemiological model describing spatiotemporal measles case report data for twenty towns.
Journal ArticleDOI

An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling

TL;DR: This work proposes to model the time-varying transmission-potential as an approximate diffusion process using a path-wise series expansion of Brownian motion, which replaces the ``missing data" imputation step with the inference of the expansion coefficients: a simpler and computationally cheaper task.

Age-stratified epidemic model using a latent marked Hawkes process (preprint)

TL;DR: In this article , the authors extend the unstructured homogeneously mixing epidemic model introduced by Lamprinakou et al. considering a finite population stratified by age bands and apply a Kernel Density Particle Filter (KDPF) to infer the marked counting process, the instantaneous reproduction number for each age group and forecast the epidemic's future trajectory in the near future.
Book ChapterDOI

Network and Epidemic Model

TL;DR: In this paper , the authors proposed a model for the prediction of epidemic patterns, its dynamics and the characteristics of the population can be understood only with the help of the deep study of the networks.
References
More filters
BookDOI

Markov Chain Monte Carlo in Practice

TL;DR: The Markov Chain Monte Carlo Implementation Results Summary and Discussion MEDICAL MONITORING Introduction Modelling Medical Monitoring Computing Posterior Distributions Forecasting Model Criticism Illustrative Application Discussion MCMC for NONLINEAR HIERARCHICAL MODELS.
BookDOI

Sequential Monte Carlo methods in practice

TL;DR: This book presents the first comprehensive treatment of Monte Carlo techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modeling, neural networks, optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection.
Book

Monte Carlo strategies in scientific computing

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

Strategies for mitigating an influenza pandemic

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.
Journal ArticleDOI

Monte Carlo Strategies in Scientific Computing

Tim Hesterberg
- 01 Nov 2002 - 
TL;DR: The strength of this book is in bringing together advanced Monte Carlo methods developed in many disciplines, including the Ising model, molecular structure simulation, bioinformatics, target tracking, hypothesis testing for astronomical observations, Bayesian inference of multilevel models, missing-data problems.
Related Papers (5)