ArticleBMC medicine2013
A low-cost method to assess the epidemiological importance of individuals in controlling infectious disease outbreaks.
Article in BMC medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Mathematical models used to inform study design or surveillance systems in infectious diseases: a systematic review.BMC infectious diseases · 2017Pooled it
- Trial
- Assessing the usefulness of digital contact tracing using real-world contact data.Scientific reports · 2026Article
- Preserving friendships in school contacts: An algorithm to construct synthetic temporal networks for epidemic modelling.PLoS computational biology · 2024Article
- Impact of contact data resolution on the evaluation of interventions in mathematical models of infectious diseases.Journal of the Royal Society, Interface · 2022Article
- Mitigating COVID-19 outbreaks in workplaces and schools by hybrid telecommuting.PLoS computational biology · 2021Article
- Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities.PLoS computational biology · 2020Article
- Efficient sentinel surveillance strategies for preventing epidemics on networks.PLoS computational biology · 2019Article
- Assessing the Dynamics and Control of Droplet- and Aerosol-Transmitted Influenza Using an Indoor Positioning System.Scientific reports · 2019Article
- The importance of dog population contact network structures in rabies transmission.PLoS neglected tropical diseases · 2018Article
- Optimizing targeted vaccination across cyber-physical networks: an empirically based mathematical simulation study.Journal of the Royal Society, Interface · 2018Article
- Measuring distance through dense weighted networks: The case of hospital-associated pathogens.PLoS computational biology · 2017Article
- The interplay between individual social behavior and clinical symptoms in small clustered groups.BMC infectious diseases · 2017Article
- An ecological and digital epidemiology analysis on the role of human behavior on the 2014 Chikungunya outbreak in Martinique.Scientific reports · 2017Article
- Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings.BMC infectious diseases · 2016Article
- Contact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants' attitudes.BMC infectious diseases · 2016Article
- Disease Surveillance on Complex Social Networks.PLoS computational biology · 2016Article
- How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?PLoS computational biology · 2016Article
- Compensating for population sampling in simulations of epidemic spread on temporal contact networks.Nature communications · 2015Article
- Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions.Network science (Cambridge University Press) · 2015Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundInfectious disease outbreaks in communities can be controlled by early detection and effective prevention measures. Assessing the relative importance of each individual community member with respect to these two processes requires detailed knowledge about the underlying social contact network on which the disease can spread. However, mapping social contact networks is typically too resource-intensive to be a practical possibility for most communities and institutions.
methodsHere, we describe a simple, low-cost method - called collocation ranking - to assess individual importance for early detection and targeted intervention strategies that are easily implementable in practice. The method is based on knowledge about individual collocation which is readily available in many community settings such as schools, offices, hospitals, and so on. We computationally validate our method in a school setting by comparing the outcome of the method against computational predictions based on outbreak simulations on an empirical high-resolution contact network. We compare collocation ranking to other methods for assessing the epidemiological importance of the members of a population. To this end, we select subpopulations of the school population by applying these assessment methods to the population and adding individuals to the subpopulation according to their individual rank. Then, we assess how suited these subpopulations are for early detection and targeted intervention strategies.
resultsLikelihood and timing of infection during an outbreak are important features for early detection and targeted intervention strategies. Subpopulations selected by the collocation ranking method show a substantially higher average infection probability and an earlier onset of symptoms than randomly selected subpopulations. Furthermore, these subpopulations selected by the collocation ranking method were close to the optimum.
conclusionsOur results indicate that collocation ranking is a highly effective method to assess individual importance, providing critical low-cost information for the development of sentinel surveillance systems and prevention strategies.
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