ArticleVirulence2016
Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control.
Article in Virulence, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 46 citations in OpenAlex.
- Structural network characteristics affect epidemic severity and prediction in social contact networks.Infectious Disease Modelling · 2024Article
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- Inferring generation-interval distributions from contact-tracing data.Journal of the Royal Society, Interface · 2020Article
- The hearth of mathematical and statistical modelling during the Coronavirus pandemic.Interactive cardiovascular and thoracic surgery · 2020Article
- Modelling the pandemic: attuning models to their contexts.BMJ global health · 2020Review
- Development of a Multi-Dimensional Parametric Model With Non-Pharmacological Policies for Predicting the COVID-19 Pandemic Casualties.IEEE access : practical innovations, open solutions · 2020Article
- A Novel Parametric Model for the Prediction and Analysis of the COVID-19 Casualties.IEEE access : practical innovations, open solutions · 2020Article
- Vaccination strategies to control Ebola epidemics in the context of variable household inaccessibility levels.PLoS neglected tropical diseases · 2019Article
- A novel sub-epidemic modeling framework for short-term forecasting epidemic waves.BMC medicine · 2019Article
- Article
- Modeling spatial invasion of Ebola in West Africa.Journal of theoretical biology · 2017Article
- Spatial Determinants of Ebola Virus Disease Risk for the West African Epidemic.PLoS currents · 2017Article
- Is it growing exponentially fast? -- Impact of assuming exponential growth for characterizing and forecasting epidemics with initial near-exponential growth dynamics.Infectious Disease Modelling · 2016Article
- Characterizing the reproduction number of epidemics with early subexponential growth dynamics.Journal of the Royal Society, Interface · 2016Article
- Mathematical models to characterize early epidemic growth: A review.Physics of life reviews · 2016Review
- The role of interconnectivity in control of an Ebola epidemic.Scientific reports · 2016Article
- A generalized-growth model to characterize the early ascending phase of infectious disease outbreaks.Epidemics · 2016Article
- Editorial: Mathematical modeling of infectious disease dynamics.Virulence · 2016Article
- Comparing the accuracy of several network-based COVID-19 prediction algorithms.International journal of forecastingArticle
- Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The mechanisms behind the sub-exponential growth dynamics of the West Africa Ebola virus disease epidemic could be related to improved control of the epidemic and the result of reduced disease transmission in spatially constrained contact structures. An individual-based, stochastic network model is used to model immediate and delayed epidemic control in the context of social contact networks and investigate the extent to which the relative role of these factors may be determined during an outbreak. We find that in general, epidemics quickly establish a dynamic equilibrium of infections in the form of a wave of fixed size and speed traveling through the contact network. Both greater epidemic control and limited community mixing decrease the size of an infectious wave. However, for a fixed wave size, epidemic control (in contrast with limited community mixing) results in lower community saturation and a wave that moves more quickly through the contact network. We also found that the level of epidemic control has a disproportionately greater reductive effect on larger waves, so that a small wave requires nearly as much epidemic control as a larger wave to end an epidemic.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.