Evidence map›Paper›PMID 35860220›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Infectious disease dynamics and restrictions on social gathering size.

Christopher B Boyer, Eva Rumpler, Stephen M Kissler, Marc Lipsitch

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Christopher B BoyerDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Eva RumplerDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Stephen M KisslerDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Marc LipsitchDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Harvard University · US

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BUCKEE, CAROLINE O'FLAHERTY · 2009 to 2018
$26.4M
CVD Epidemiology Training Program in Behavior, the Environment and Global HealthT32HL098048 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI Goodarz Danaei, ERIC B RIMM · 2009 to 2026
$6.9M
Casual, Statistical and Mathematical Modeling with Serologic DataU01CA261277 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM, LIPSITCH, MARC · 2020 to 2023
$2.8M
NCI NIH HHS U01 CA261277NHLBI NIH HHS T32 HL098048NIGMS NIH HHS U54 GM088558
6 · The paper itself

Abstract

Social gatherings can be an important locus of transmission for many pathogens including SARS-CoV-2. During an outbreak, restricting the size of these gatherings is one of several non-pharmaceutical interventions available to policy-makers to reduce transmission. Often these restrictions take the form of prohibitions on gatherings above a certain size. While it is generally agreed that such restrictions reduce contacts, the specific size threshold separating "allowed" from "prohibited" gatherings often does not have a clear scientific basis, which leads to dramatic differences in guidance across location and time. Building on the observation that gathering size distributions are often heavy-tailed, we develop a theoretical model of transmission during gatherings and their contribution to general disease dynamics. We find that a key, but often overlooked, determinant of the optimal threshold is the distribution of gathering sizes. Using data on pre-pandemic contact patterns from several sources as well as empirical estimates of transmission parameters for SARS-CoV-2, we apply our model to better understand the relationship between restriction threshold and reduction in cases. We find that, under reasonable transmission parameter ranges, restrictions may have to be set quite low to have any demonstrable effect on cases due to relative frequency of smaller gatherings. We compare our conceptual model with observed changes in reported contacts during lockdown in March of 2020.

Identifiers

PMID35860220
PMCPMC9298137
OpenAlexW4206396634

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.