ArticleEpidemics2019
Transmission on empirical dynamic contact networks is influenced by data processing decisions.
Article in Epidemics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Social Structure of Sheep Flocks at Points of the Production Cycle and Relationship to Disease Spread, Using a Simulated Epidemic of Footrot.Animals : an open access journal from MDPI · 2026Article
- The effect of temporal resolution and contact duration on Real-Time location system-based contact networks for confined feedlot cattle.Preventive veterinary medicine · 2025Article
- A protocol for assessing bias and robustness of social network metrics using GPS based radio-telemetry data.Movement ecology · 2024Article
- Analysis of within-pen and between-pen fenceline temporal contact networks in confined feedlot cattle.Preventive veterinary medicine · 2024Article
- Social behaviour and transmission of lameness in a flock of ewes and lambs.Frontiers in veterinary science · 2022Article
- Combining epidemiological and ecological methods to quantify social effects onRoyal Society open science · 2021Article
- Spatial and temporal variation in proximity networks of commercial dairy cattle in Great Britain.Preventive veterinary medicine · 2021Article
- Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen.Journal of the Royal Society, Interface · 2021Article
- Modeling Infectious Diseases in Healthcare Network (MInD-Healthcare) Framework for Describing and Reporting Multidrug-resistant Organism and Healthcare-Associated Infections Agent-based Modeling Methods.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2020Article
- Social network analysis of COVID-19 transmission in Karnataka, India.Epidemiology and infection · 2020Article
- Accounting for space and uncertainty in real-time location system-derived contact networks.Ecology and evolution · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Dynamic contact data can be used to inform disease transmission models, providing insight into the dynamics of infectious diseases. Such data often requires extensive processing for use in models or analysis. Therefore, processing decisions can potentially influence the topology of the contact network and the simulated disease transmission dynamics on the network. In this study, we examine how four processing decisions, including temporal sampling window (TSW), spatial threshold of contact (SpTh), minimum contact duration (MCD), and temporal aggregation (daily or hourly) influence the information content of contact data (indicated by changes in entropy) as well as disease transmission model dynamics. We found that changes made to information content by processing decisions translated to significant impacts to the transmission dynamics of disease models using the contact data. In particular, we found that SpTh had the largest independent influence on information content, and that some output metrics (R
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Registered trials
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