Early dynamics of transmission and control of COVID-19: a mathematical modelling study

The Lancet Infectious Diseases - Tập 20 Số 5 - Trang 553-558 - 2020
Adam J. Kucharski1, Timothy Russell1, Charlie Diamond1, Yang Liu1, John Edmunds1, Sebastian Funk1, Rosalind M. Eggo1, Billy J. Quilty, Mark Jit, James D. Munday, Nicholas G. Davies, Amy Gimma, Kevin van Zandvoort, Hamish Gibbs, Joel Hellewell, Christopher I Jarvis, Sam Abbott, Nikos I Bosse, Petra Klepac, Stefan Flasche
1Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK

Tóm tắt

Từ khóa


Tài liệu tham khảo

2020

Camacho, 2015, Temporal changes in Ebola transmission in Sierra Leone and implications for control requirements: a real-time modelling study, PLoS Curr, 7

Funk, 2017, The impact of control strategies and behavioural changes on the elimination of Ebola from Lofa County, Liberia, Philos Trans R Soc Lond B Biol Sci, 372, 20160302, 10.1098/rstb.2016.0302

Riley, 2003, Transmission dynamics of the etiological agent of SARS in Hong Kong: impact of public health interventions, Science, 300, 1961, 10.1126/science.1086478

Viboud, 2018, The RAPIDD Ebola forecasting challenge: synthesis and lessons learnt, Epidemics, 22, 13, 10.1016/j.epidem.2017.08.002

Cooper, 2006, Delaying the international spread of pandemic influenza, PLoS Med, 3, e212, 10.1371/journal.pmed.0030212

Kucharski, 2015, Evaluation of the benefits and risks of introducing Ebola community care centers, Sierra Leone, Emerg Infect Dis, 21, 393, 10.3201/eid2103.141892

Aylward, 2014, Ebola virus disease in West Africa—the first 9 months of the epidemic and forward projections, N Engl J Med, 371, 1481, 10.1056/NEJMoa1411100

Nishiura, 2009, Early epidemiological assessment of the virulence of emerging infectious diseases: a case study of an influenza pandemic, PLoS One, 4, e6852, 10.1371/journal.pone.0006852

Birrell, 2018, Evidence synthesis for stochastic epidemic models, Stat Sci, 33, 34, 10.1214/17-STS631

Baguelin, 2013, Assessing optimal target populations for influenza vaccination programmes: an evidence synthesis and modelling study, PLoS Med, 10, e1001527, 10.1371/journal.pmed.1001527

Dureau, 2013, Capturing the time-varying drivers of an epidemic using stochastic dynamical systems, Biostatistics, 14, 541, 10.1093/biostatistics/kxs052

Li, 2020, Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia, N Engl J Med, 10.1056/NEJMoa2001316

Liu, 2020, Transmission dynamics of 2019 novel coronavirus (2019-nCoV), bioRxiv

Riou, 2020, Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020, Euro Surveill, 10.2807/1560-7917.ES.2020.25.4.2000058

Lloyd-Smith, 2005, Superspreading and the effect of individual variation on disease emergence, Nature, 438, 355, 10.1038/nature04153

Kucharski, 2015, The role of superspreading in Middle East respiratory syndrome coronavirus (MERS-CoV) transmission, Euro Surveill, 20, 14, 10.2807/1560-7917.ES2015.20.25.21167

Hellewell, 2020, Feasibility of controlling 2019-nCoV outbreaks by isolation of cases and contacts, medRxiv

Imai

Pullano, 2020, Novel coronavirus (2019-nCoV) early-stage importation risk to Europe, January 2020, Euro Surveill, 25, 2000057, 10.2807/1560-7917.ES.2020.25.4.2000057

Lai

Rothe, 2020, Transmission of 2019-nCoV infection from an asymptomatic contact in Germany, N Engl J Med, 10.1056/NEJMc2001468