Evidence map›Paper›PMID 16292310›Full record

ArticleNature2005

Superspreading and the effect of individual variation on disease emergence.

J O Lloyd-Smith, S J Schreiber, P E Kopp, W M Getz

Open access · bronzeAbstract read
In one paragraph

Article in Nature, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,256 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,256citing papers in PubMed, 2 pooled it
21.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,256 citing papers in PubMed, 2 syntheses or guidelines pooled it, 2,679 citations in OpenAlex.

  1. Pooled it
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  10. Mechanics of pandemics.EClinicalMedicine · 2026
    Review
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1,196 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 2 countries.

J O Lloyd-SmithDepartment of Environmental Science, Policy and Management, 140 Mulford Hall, University of California, Berkeley, California 94720-3114, USA. jls@nature.berkeley.edu
S J Schreiber
P E Kopp
W M Getz
University of California, Berkeley · USUniversity of Hull · GBWilliams (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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, R(0), which is defined as the mean number of infections caused by an infected individual in a susceptible population. Population estimates of R(0) 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 R(0) 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.

Indexed as

Contact TracingDisease OutbreaksDisease SusceptibilityDisease Transmission, InfectiousHumansModels, BiologicalSevere Acute Respiratory SyndromeSingapore

Identifiers

PMID16292310
PMCPMC7094981
OpenAlexW2069251911

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.