Superspreading and the effect of individual variation on disease emergence
Open accessAbstract
Population-level analyses often use average quantities to describe heterogeneous systems, particularly when variation does not arise from identifiable groups. A prominent example, central to our current understanding of epidemic spread, is the basic reproductive number, R0, which is defined as the mean number of infections caused by an infected individual in a susceptible population. Population estimates of R0 can obscure considerable individual variation in infectiousness, as highlighted during the global emergence of severe acute respiratory syndrome (SARS) by numerous ‘superspreading events’ in which certain individuals infected unusually large numbers of secondary cases. For diseases transmitted by non-sexual direct contacts, such as SARS or smallpox, individual variation is difficult to measure empirically, and thus its importance for outbreak dynamics has been unclear. Here we present an integrated theoretical and statistical analysis of the influence of individual variation in infectiousness on disease emergence. Using contact tracing data from eight directly transmitted diseases, we show that the distribution of individual infectiousness around R0 is often highly skewed. Model predictions accounting for this variation differ sharply from average-based approaches, with disease extinction more likely and outbreaks rarer but more explosive. Using these models, we explore implications for outbreak control, showing that individual-specific control measures outperform population-wide measures. Moreover, the dramatic improvements achieved through targeted control policies emphasize the need to identify predictive correlates of higher infectiousness. Our findings indicate that superspreading is a normal feature of disease spread, and to frame ongoing discussion we propose a rigorous definition for superspreading events and a method to predict their frequency.
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This characteristic of airborne viral transmission makes SARS particularly threatening because enhanced superspreading complicates the control of epidemics once community transmission is established.
“This characteristic of airborne viral transmission makes SARS particularly threatening because enhanced superspreading complicates the control of epidemics once community transmission is established.35,62”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [35]
The Main section (page unavailable) links SARS superspreading to explosive outbreaks and says that undiagnosed cases can cause further superspreading events despite control measures. It lists airborne spread as one possible contributor to superspreading across several infections, but does not establish it as the characteristic of SARS responsible for the claimed difficulty of control once community transmission is established. The paper also notes that high variation can make outbreaks more likely to die out. (LLM, conf=0.84)
Experimental — accuracy not yet measuredFor SARS-CoV-1, airborne viral transmission across entire buildings through ventilation or drainage systems, as part of so-called superspreading events, is apparently a key driver.
“For SARS-CoV-1, airborne viral transmission across entire buildings through ventilation or drainage systems, as part of so-called superspreading events, is apparently a key driver.”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [35]
The Main section reports SARS superspreading and identifies airborne spread as one possible contributor to superspreading events across the infections reviewed. It does not say that SARS spread across entire buildings through ventilation or drainage systems, or establish that this route was a key driver. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe superspreading of SARS-CoV-1 was more prominent than that of many other viruses, including SARS-CoV-2.
“Thus, the superspreading of SARS-CoV-1 was more prominent than that of many other viruses, 35 including SARS-CoV-2.117”
From Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review (2025) · cites this paper as [35]
The Main section reports highly uneven SARS transmission in the Singapore outbreak, and the Abstract describes SARS as having a strong tendency toward superspreading while contrasting it with the steadier growth of smallpox and pneumonic plague. The paper does not compare SARS-CoV-1 with SARS-CoV-2, so it cannot support that part of the claim. (LLM, conf=0.88)
Experimental — accuracy not yet measured
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- Authors
- Lloyd-Smith, J. O., Schreiber, S. J., Kopp, P. E., & Getz, W. M.
- Affiliations
- William & Mary (US)
- University of Hull (GB)
- University of California, Berkeley (US)
- Venue
- Nature
- Published
- 2005-11-17
- Volume
- 438
- Issue
- 7066
- Pages
- 355-359
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7094981
- OpenAlex
- W2069251911
- Semantic Scholar
- 65ea54a56f038c37e42bee21729153540ca9b301
- Cited by
- 2,514
- References
- 101
- Citations by year
- 2026: 131 · 2025: 124 · 2024: 136 · 2023: 148 · 2022: 216 · 2021: 356 · 2020: 343 · 2019: 102 · 2018: 99 · 2017: 86 · 2016: 108 · 2015: 110 · 2014: 86 · 2013: 88 · 2012: 74
- FWCI
- 48.22
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Zenodo (CERN European Organization for Nuclear Research)
- Funders
- National Science Foundation
- James S. McDonnell Foundation
- National Institutes of Health
- National Institute on Drug Abuse
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Keywords
- superspreading events, disease emergence, basic reproduction number, outbreak dynamics, contact tracing, infectious disease transmission, SARS, measles, smallpox, pneumonic plague, avian influenza, bioterrorism agents, disease extinction
- MeSH terms
- Disease Outbreaks, Disease Susceptibility, Humans, Models, Biological, Singapore, Contact Tracing, Disease Transmission, Infectious, Severe Acute Respiratory Syndrome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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