The DOI matches its Crossref record; 52 of the 53 references it cites were found in a registry or an index.
Super-spreaders in infectious diseases
Open accessAbstract
Early studies that explored host-pathogen interactions assumed that infected individuals within a population have equal chances of transmitting the infection to others. Subsequently, in what became known as the 20/80 rule, a small percentage of individuals within any population was observed to control most transmission events. This empirical rule was shown to govern inter-individual transmission dynamics for many pathogens in several species, and individuals who infect disproportionately more secondary contacts, as compared to most others, became known as super-spreaders. Studies conducted in the wake of the severe acute respiratory syndrome (SARS) pandemic revealed that, in the absence of super-spreading events, most individuals infect few, if any, secondary contacts. The analysis of SARS transmission, and reports from other outbreaks, unveil a complex scenario in which super-spreading events are shaped by multiple factors, including co-infection with another pathogen, immune suppression, changes in airflow dynamics, delayed hospital admission, misdiagnosis, and inter-hospital transfers. Predicting and identifying super-spreaders open significant medical and public health challenges, and represent important facets of infectious disease management and pandemic preparedness plans.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Major Outbreak of Severe Acute Respiratory Syndrome in Hong Kong
Lee, N. L. S., Hui, D. S. C., Wu, A. K. L., Chan, P. K. S., Cameron, P. A., Joynt, G. M., Ahuja, A. T., Yung, M. Y., Leung, C. B., To, K. F., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa030685 · Cited by 2,638
Superspreading and the effect of individual variation on disease emergence
Lloyd-Smith, J. O., Schreiber, S. J., Kopp, P. E., & Getz, W. M. (2005) · Nature · doi:10.1038/nature04153 · Cited by 2,514
Transmission Dynamics and Control of Severe Acute Respiratory Syndrome
Lipsitch, M., Cohen, T., Cooper, B. S., Robins, J. M., Ma, S., James, L., Gopalakrishna, G., Chew, S. K., Tan, C. C., Samore, M. H., et al. (2003) · Science · doi:10.1126/science.1086616 · Cited by 1,485
Evidence of Airborne Transmission of the Severe Acute Respiratory Syndrome Virus
Yu, I. T. S., Li, Y., Wong, T. W., Tam, W., Chan, A., Lee, J. H. W., Leung, D. Y. C., & Ho, T. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa032867 · Cited by 1,255
Perspectives on the basic reproductive ratio
Heffernan, J. M., Smith, R. J., & Wahl, L. M. (2005) · Journal of The Royal Society Interface · doi:10.1098/rsif.2005.0042 · Cited by 1,232
Woolhouse, M. E. J., Dye, C., Etard, J.-F., Smith, T., Charlwood, J. D., Garnett, G. P., Hagan, P., Hii, J. L. K., Ndhlovu, P. D., Quinnell, R. J., et al. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.1.338 · Cited by 1,194
Riley, S., Fraser, C., Donnelly, C. A., Ghani, A. C., Abu-Raddad, L. J., Hedley, A. J., Leung, G. M., Ho, L., Lam, T.-H., Thach, T., et al. (2003) · Science · doi:10.1126/science.1086478 · Cited by 1,152
Cohen, M. S., Hoffman, I., Royce, R. A., Kazembe, P. N., Dyer, J. R., Daly, C. C., Zimba, D., Vernazza, P., Maida, M., Fiscus, S. A., et al. (1997) · The Lancet · doi:10.1016/s0140-6736(97)02190-9 · Cited by 873
Host heterogeneity dominates West Nile virus transmission
Marm Kilpatrick, A., Daszak, P., Jones, M. J., Marra, P. P., & Kramer, L. D. (2006) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2006.3575 · Cited by 533
The Reemergence of Ebola Hemorrhagic Fever, Democratic Republic of the Congo, 1995
Khan, A. S., Tshioko, F. K., Heymann, D. L., Guenno, B. L., Nabeth, P., Kerstiëns, B., Fleerackers, Y., Kilmarx, P. H., Rodier, G. R., Nkuku, O. B., et al. (1999) · The Journal of Infectious Diseases · doi:10.1086/514306 · Cited by 460
Cited by
Sorted by citations
Items 301–376 of 376
Salam, M., Dhaybe, S. E., Ghannam, L., Serhan, M., & Hassan, M. (2026) · JMIR Research Protocols · doi:10.2196/89474 · Cited by 1
Harris, M., Sinclair, A. H., Pullano, G., Beckett, S. J., LeJeune, L., Agusto, F. B., Bauch, C. T., Baur, C., Berestycki, H., Dushoff, J. G., et al. (2026) · Royal Society Open Science · doi:10.1098/rsos.260369 · Cited by 1
MERS: an emerging disease of the 21st century
Bala, M. O., Chehab, M. A. H., & Selim, N. A. A. (2017) · International Journal of Community Medicine and Public Health · doi:10.18203/2394-6040.ijcmph20172806 · Cited by 1
The COVID-19 Pandemic: Exploring Its Future through Rhizomatic Thinking
Jayasinghe, S. (2022) · World Futures · doi:10.1080/02604027.2021.2014748 · Cited by 1
METAPHORIC COVID NEOLOGISMS AND THEIR TRANSLATION PECULIARITIES
Gasparyan, N., & Ohanyan, M. (2022) · Armenian Folia Anglistika · doi:10.46991/afa/2022.18.2.132 · Cited by 1
Fromme, H. (2023) · Springer eBooks · doi:10.1007/978-3-031-40078-0_6 · Cited by 1
George, J., Singh, A., & Shukla, A. (2021) · Journal of Indian Dental Association · doi:10.33882/jida.15.27548 · Cited by 1
Rossi, T. M., O’Sullivan, T. L., & Greer, A. J. (2025) · BMC Veterinary Research · doi:10.1186/s12917-025-05248-z · Cited by 1
Ayoade, A. A., Latunde, T., & Folaranmi, R. O. (2021) · Journal of Fundamental and Applied Sciences · doi:10.4314/jfas.v13i3.7 · Cited by 1
Pooled testing of traced contacts under superspreading dynamics
Tsirtsis, S., De, A., Lorch, L., & Gomez-Rodriguez, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010008 · Cited by 1
Sapoval, N., de Mesquita, P. J. B., Liu, Y., Wang, R., Liu, T. R., Garza, J., Williams, T., Cadiz, C., Tan, G. S., van Bakel, H., et al. (2021) · medRxiv · doi:10.1101/2021.10.27.21265424 · Cited by 1
Do Some Super-Spreaders Spread Better? Effects of individual heterogeneity in epidemiological traitsPreprint
Beagle, A. S., Budischak, S. A., Craft, M. E., Forbes, K. M., Hall, R. J., Nguyen, D., & Cressler, C. E. (2022) · medRxiv · doi:10.1101/2022.04.19.22273976 · Cited by 1
Founder effects arising from gathering dynamics systematically bias emerging pathogen surveillancePreprint
Taylor, B. P., & Hanage, W. P. (2025) · eLife · doi:10.7554/elife.104201.1 · Cited by 1
Bartlett, S., Rocha, H. L., Hsieh, L. L., Yeung, S. T., Wang, C., Ciabattoni, G. O., Loomis, C. A., Li, H., tenOever, B. R., & Ortigoza, M. B. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.06.698034 · Cited by 1
Romano, V. (2017) · theses.fr (ABES) · doi:10.70675/f70af640z4487z412fz8448zff17c4cdc483 · Cited by 1
Posibilidades diagnósticas de la PPD aviar en la paratuberculosis bovina en animales jóvenes
Pinedo, M. F. A. (2015) · El Servicio de Difusión de la Creación Intelectual (National University of La Plata) · doi:10.35537/10915/48228
Factors shaping the infection success of a bumblebee parasite
Cisarovsky, G. (2013) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-a-010015995
Moyano, R. D. (2017) · El Servicio de Difusión de la Creación Intelectual (National University of La Plata) · doi:10.35537/10915/59644
Basic concepts and prevention strategies
Damani, N. (2019) · Oxford University Press eBooks · doi:10.1093/med/9780198815938.003.0001
Use of Whole Genome Sequencing in Understanding Transmission Dynamics of Tuberculosis
Jones, R. C. (2018) · Cronfa (Swansea University) · doi:10.23889/suthesis.44995
Potential Super Spreading’s of SARS-2 Pandemic. A Short ReviewPreprint
Kyriakopoulos, A. M. (2020) · Preprints.org · doi:10.20944/preprints202004.0139.v1
Review: A New Natural Defense Against Airborne Pathogens — R0/PR2
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr2
Review: A New Natural Defense Against Airborne Pathogens — R1/PR5
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr5
Wilson, A. M. (2020) · UA Campus Repository (The University of Arizona)
Review: A New Natural Defense Against Airborne Pathogens — R0/PR1
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr1
Review: A New Natural Defense Against Airborne Pathogens — R1/PR4
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr4
Musa, M. D. (2020) · The Medical Journal of Basrah University · doi:10.33762/mjbu.2020.128230.1033
Chhezom, K. (2020) · Bhutan Health Journal · doi:10.47811/bhj.90
Does the Pareto Principle describe parasite counts in humans? The case of hookworm in pregnant womenPreprint
Orobio, Y., & Alexander, N. D. E. (2021) · medRxiv · doi:10.1101/2020.12.30.20249036
Multiagent Epidemiologic Inference through Realtime Contact Tracing
Sharon, G., Ault, J., Stone, P., Kompella, V. R., & Capobianco, R. (2021) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/gqac3892
Covid-19 Superspreading Events Network Analysis from Agent-Based Model with Mobility Restriction
Lima, L. L., & Atman, A. P. F. (2021) · Springer eBooks · doi:10.1007/978-3-030-73241-7_21
GUDIE: a flexible, user-defined method to extract subgraphs of interest from large graphsPreprint
Silva, M. I., Aparício, D., Malveiro, B., Ascensão, J. T., & Bizarro, P. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.09200
Ghoshdastidar, B., Ghoshdastidar, S., & Sarkar, K. (2021) · Indian Journal of Community Medicine · doi:10.4103/ijcm.ijcm_817_20
Sapoval, N., & Treangen, T. J. (n.d.) · OSF Preprints (OSF Preprints) · doi:10.17605/osf.io/bgt3n
Aneesh Kumar, K., V (2020) · doi:10.2196/preprints.20607
O’Sullivan, D., & Perry, G. L. W. (2013) · Wiley eBooks · doi:10.1002/9781118527085.refs
Vernon, A. A., & Villarino, M. E. (2012) · Clinical Infectious Diseases · doi:10.1093/cid/cir947
Superdiseminadores durante la pandemia del SARS-CoV-2 en Cartagena, Colombia
Coronell-Rodríguez, W., Arteta-Acosta, C., & Castell, C. R. D. (2022) · IATREIA · doi:10.17533/udea.iatreia.128
Geospatial analysis of COVID-19 distribution and its relation to public transportation services
Saldaña-Pérez, M., Garrido-Gutierrez, V., Yáñez-Márquéz, C., Torres-Ruiz, M. J., & Moreno-Ibarra, M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821318-6.00006-2
Decision: A New Natural Defense Against Airborne Pathogens — R1/PR6
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr6
Decision: A New Natural Defense Against Airborne Pathogens — R0/PR3
(2020) · QRB Discovery · doi:10.1017/qrd.2020.9.pr3
Tuteja, G. S., & Lal, T. (2024) · Journal of the Nigerian Society of Physical Sciences · doi:10.46481/jnsps.2024.1828
Elliott, J., & Thomas, G. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.5043185
COVID-19 transmission dynamics in close-contacts facilities: Optimizing control strategies
Ghosh, A., Castillo, Y., Armendariz, D. N. G., Arriola, L. M., & Mubayi, A. (2024) · Computational and Mathematical Biophysics · doi:10.1515/cmb-2024-0012
Founder effects arising from gathering dynamics systematically bias emerging pathogen surveillancePreprint
Taylor, B. P., & Hanage, W. P. (2025) · eLife · doi:10.7554/elife.104201
The influence of superspreaders in a viral epidemic
Andreeva, R., & Tarnev, K. (2025) · AIP conference proceedings · doi:10.1063/5.0246466
Influenza Vaccination and Occupational Social Intensity: Evidence From U.S. Workers
Xiao, Y., Harris, M., O’Halloran, A. C., & Pike, J. J. (2025) · Health Economics · doi:10.1002/hec.4974
Bisanzio, D., Reithinger, R., Alqunaibet, A., Almudarra, S., Alsukait, R. F., Dong, D., Zhang, Y., El-Saharty, S., & Herbst, C. H. (2022) · Figshare · doi:10.6084/m9.figshare.19129144
Carson, B. D., Orians, C. M., & Crone, E. E. (2024) · Figshare · doi:10.6084/m9.figshare.25727852
Enriquez, G. F., Macchiaverna, N. P., Garbossa, G., Palacio, L. P. Q., Ojeda, B. L., Búa, J., Gaspe, M. S., Cimino, R. O., Gürtler, R. E., Postan, M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26549437
Sansone, M., Holmström, P., Hallberg, S., Nordén, R., Andersson, L.-M., & Westin, J. (2022) · Figshare · doi:10.6084/m9.figshare.19915435
Enriquez, G. F., Macchiaverna, N. P., Garbossa, G., Palacio, L. P. Q., Ojeda, B. L., Búa, J., Gaspe, M. S., Cimino, R. O., Gürtler, R. E., Postan, M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26549285
Weissberg, D., Böni, J., Rampini, S. K., Kufner, V., Zaheri, M., Schreiber, P. W., Abela, I. A., Huber, M., Sax, H., & Wolfensberger, A. (2020) · Figshare · doi:10.6084/m9.figshare.13323782
Sansone, M., Holmström, P., Hallberg, S., Nordén, R., Andersson, L.-M., & Westin, J. (2022) · Figshare · doi:10.6084/m9.figshare.19915432
Additional file 1 of Urine shedding patterns of pathogenic Leptospira spp. in dairy cows
Monti, G., Montes, V., Tortosa, P., Tejeda, C., & Salgado, M. (2023) · Figshare · doi:10.6084/m9.figshare.23812592
Enriquez, G. F., Macchiaverna, N. P., Garbossa, G., Palacio, L. P. Q., Ojeda, B. L., Búa, J., Gaspe, M. S., Cimino, R. O., Gürtler, R. E., Postan, M., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26759507
Mukherjee, A., Mishra, S., Murty, V. K., & Chaudhuri, S. (2026) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2025.0291
Oh, W. S., Bae, S., Kim, E., Kim, S., Lim, C., Lee, Y., Kim, Y., & Jeong, S. (2026) · Scandinavian Journal of Infectious Diseases · doi:10.1080/23744235.2026.2637791
Scheffer, M. (2026) · Cambridge University Press eBooks · doi:10.1017/9781009699785.013
Deep learning from phylogenies
Voznica, J. (2021) · theses.fr (ABES) · doi:10.70675/2a30342bz42dfz4c7az871cza4830f7c63f0
Écologie de la transmission des vers parasites du genre Schistosoma
Douchet, P. (2023) · theses.fr (ABES) · doi:10.70675/30411a19z0896z4332z83dbz8ff777bb95a6
Séparation des préoccupations dans les modèles compartimentaux étendus
Fodjo, A. Y. G. (2023) · theses.fr (ABES) · doi:10.70675/3c9de1b2z27a0z4987zb978z290e9b37e5ae
(2026) · Elsevier eBooks · doi:10.1016/b978-0-44-355525-1.00020-5
The biology, epidemiology, psychological, economic, and governance aspects of pandemics
Lazebnik, T. (2026) · Elsevier eBooks · doi:10.1016/b978-0-44-355525-1.00008-4
COVID-19 Pandemic: Factors Contributing to Persistent Infection and Severe Cases
Mahuob, A., Alkhali, K., & Irawati, L. (2026) · Journal of 21 September university for medical and applied sciences · doi:10.65693/j21umas.2026.v5i1.369
Gupta, Y., Verma, A., Bhardwaj, Y., Rastogi, M., & Katiyar, A. (2026) · Reviews in Medical Virology · doi:10.1002/rmv.70194
Salam, M., Bader, Z. S., Itani, A., Balawi, A. A. S., Assaf, A. A. H., & Mansour, M. (2026) · Risk Management and Healthcare Policy · doi:10.2147/rmhp.s609392
Salam, M., Honein-AbouHaidar, G. N., Melhem, N. M., Reynolds, N. R., Salloum, R. G., Abdulrahim, S., Fares, S., & Noureddine, S. (2026) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2026.2712139
Dabai, A. I., Ibrahim, U. B., Abdulkadir, N., Dandare, S. U., & Rao, J. R. (2026) · Frontiers in Microbiology · doi:10.3389/fmicb.2026.1800305
A model for within- and between-host evolution in pathogensPreprint
Crescenzi, J., McAvoy, A., & Johri, P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.09.24.754225
Modeling the Impact of Superspreaders in Respiratory Disease Transmission Dynamics
Senbu, F. H., Thillaigovindan, N., & Alemneh, H. T. (2026) · Discrete Dynamics in Nature and Society · doi:10.1155/ddns/7137328
Metadata
- Authors
- Stein, R. A.
- Affiliations
- Princeton University (US)
- Corresponding author
- Stein, Richard A.
- ORCID
- Stein, Richard A.
- Venue
- International Journal of Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2011-08
- Volume
- 15
- Issue
- 8
- Pages
- e510-e513
- ISSN
- 1201-9712 (ISSN-L)
- PMC
- PMC7110524
- OpenAlex
- W2007300619
- Cited by
- 388
- References
- 53
- Citations by year
- 2026: 18 · 2025: 17 · 2024: 23 · 2023: 16 · 2022: 44 · 2021: 61 · 2020: 90 · 2019: 24 · 2018: 16 · 2017: 15 · 2016: 18 · 2015: 22 · 2014: 12 · 2013: 8 · 2012: 4
- FWCI
- 8.40
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Infectious Diseases (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Keywords
- superspreaders, superspreading events, Pareto principle, SARS, infectious disease transmission, host-pathogen interaction, co-infection, immunosuppression, airflow dynamics, misdiagnosis, interhospital transfer, pandemic preparedness, transmission dynamics
- MeSH terms
- Animals, Communicable Diseases, Environment, Humans, Public Health, Severe Acute Respiratory Syndrome, Host-Pathogen Interactions, Pandemics, Coinfection
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review