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Title
Dynamic network strategies for SARS-CoV-2 control on a cruise ship
Authors
Keywords
SARS-CoV-2, Network, Mathematical model, Network-based model, Prevention strategies
Journal
Epidemics
Volume 37, Issue -, Pages 100488
Publisher
Elsevier BV
Online
2021-08-19
DOI
10.1016/j.epidem.2021.100488
References
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Related references
Note: Only part of the references are listed.- Quantifying Uncertainty in Infectious Disease Mechanistic Models
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- Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility
- (2020) Melissa M. Arons et al. NEW ENGLAND JOURNAL OF MEDICINE
- Public Health Responses to COVID-19 Outbreaks on Cruise Ships — Worldwide, February–March 2020
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- Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: a systematic review and meta-analysis
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- A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy
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- Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study
- (2020) Nicholas G Davies et al. Lancet Public Health
- Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world
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- Quantifying the relative effects of environmental and direct transmission of norovirus
- (2018) S. Towers et al. Royal Society Open Science
- Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015
- (2016) Haidong Wang et al. LANCET
- Respiratory infections and gastrointestinal illness on a cruise ship: A three-year prospective study
- (2016) Androula Pavli et al. Travel Medicine and Infectious Disease
- Contact infection of infectious disease onboard a cruise ship
- (2016) Nan Zhang et al. Scientific Reports
- ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks
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- Adjusting for network size and composition effects in exponential-family random graph models
- (2011) Pavel N. Krivitsky et al. Statistical Methodology
- Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
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