High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2
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Abstract
Abstract The novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R 0 , was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R 0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus. One-sentence summary By collecting and analyzing spatiotemporal data, we estimated the transmission potential for 2019-nCoV.
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A novel COVID-19 vaccine will need to be accepted by at least 55% of the population to provide herd immunity, with estimates reaching as high as 85% depending on country and infection rate.
“It is estimated that a novel COVID-19 vaccine will need to be accepted by at least 55% of the population to provide herd immunity, with estimates reaching as high as 85% depending on country and infection rate 15,16 .”
From Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA (2021) · cites this paper as [16]
In Results, “Implications for Intervention Strategies” (page not provided), the paper gives herd-immunity thresholds of 55% at R₀ = 2.2 and 82% at R₀ = 5.7. It does not give an 85% estimate or equate the proportion accepting a vaccine with the proportion becoming immune; it also does not establish country-specific thresholds. (LLM, conf=0.90)
Experimental — accuracy not yet measuredIn both countries, as of September 2020, fewer people would 'definitely' take a COVID-19 vaccine than is likely required for herd immunity.
“Here we show that in both countries-as of September 2020-fewer people would 'definitely' take a vaccine than is likely required for herd immunity”
From Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA (2021) · cites this paper as [16]
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- Authors
- Sanche, S., Lin, Y. T., Xu, C., Romero-Severson, E., Hengartner, N., & Ke, R.
- Affiliations
- Los Alamos National Laboratory (US)
- Corresponding author
- Ke, Ruian
- Venue
- Emerging Infectious Diseases
- Published
- 2020-07
- Volume
- 26
- Issue
- 7
- Pages
- 1470-1477
- ISSN
- 1080-6040 (ISSN-L)
- 1080-6059
- PMC
- PMC7323562
- OpenAlex
- W3014712943
- Cited by
- 1,619
- References
- 29
- Citations by year
- 2026: 13 · 2025: 25 · 2024: 58 · 2023: 119 · 2022: 231 · 2021: 529 · 2020: 642
- FWCI
- 60.69
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Emerging infectious diseases (publishedVersion, cc-by)
- medRxiv (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Energy (#89233218CNA000001)
- Defense Advanced Research Projects Agency (HR0011938513)
- National Nuclear Security Administration (89233218C-NA000001)
- Advanced Research Projects Agency
- National Institute of Allergy and Infectious Diseases (R01AI135946)
- Laboratory Directed Research and Development
- Los Alamos National Laboratory (89233218CNA 000001)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Keywords
- SARS-CoV-2, COVID-19 pandemic, basic reproduction number, doubling time, incubation period, serial interval, outbreak dynamics, Wuhan, transmission dynamics, contact tracing, quarantine, social distancing, epidemic modeling
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, China, Disease Outbreaks, Humans, Models, Theoretical, Pneumonia, Viral, Travel, Coronavirus Infections, Basic Reproduction Number, Pandemics
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