Evidence map›Paper›PMID 40304831›Full record

ArticleBulletin of mathematical biology2025

A Theoretical Framework to Quantify the Tradeoff Between Individual and Population Benefits of Expanded Antibiotic Use.

Cormac R LaPrete, Sharia M Ahmed, Damon J A Toth, Jody R Reimer, Valerie M Vaughn, Frederick R Adler, Lindsay T Keegan

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Cormac R LaPrete *Department of Mathematics, University of Utah, Salt Lake City, UT, USA.
Sharia M Ahmed *Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
Damon J A TothDivision of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
Jody R ReimerDepartment of Mathematics, University of Utah, Salt Lake City, UT, USA.
Valerie M VaughnDepartment of Internal Medicine, University of Utah, Salt Lake City, UT, USA.
Frederick R Adler *Department of Mathematics, University of Utah, Salt Lake City, UT, USA.
Lindsay T Keegan *Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA. lindsay.keegan@utah.edu.ORCID http://orcid.org/0000-0002-8526-3007

Funding

A combined epidemiologic and genomic approach to identify and control transmission events of hospital associated infectionsK01AI159519 · NIAID · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI KEEGAN, LINDSAY T. · 2021 to 2025
$678k
ACL HHS U01CK000675Agency for Healthcare Research and Quality Safety Program for Telemedicine K08HS026530-06AHRQ HHS K08 HS026530CDC HHS 1NU38FT000009-01-00CDC HHS 1U01CK000675Division of Intramural Research, National Institute of Allergy and Infectious Diseases 5K01AI159519-04NCEZID CDC HHS U01 CK000675NIAID NIH HHS K01 AI159519
6 · The paper itself

Abstract

The use of antibiotics during a disease outbreak presents a critical tradeoff between immediate treatment benefits to the individual and the long-term risk to the population. Typically, the extensive use of antibiotics has been thought to increase selective pressures, leading to resistance. This study explores scenarios where expanded antibiotic treatment can be advantageous for both individual and population health. We develop a mathematical framework to assess the impacts on outbreak dynamics of choosing to treat moderate infections not treated under current guidelines, focusing on cholera as a case study. We derive conditions under which treating moderate infections can sufficiently decrease transmission and reduce the total number of antibiotic doses administered. We identify two critical thresholds: the Outbreak Prevention Threshold (OPT), where expanded treatment reduces the reproductive number below 1 and halts transmission, and the Dose Utilization Threshold (DUT), where expanded treatment results in fewer total antibiotic doses used than under current guidelines. For cholera, we find that treating moderate infections can feasibly stop an outbreak when the untreated reproductive number is less than 1.42 and will result in fewer does used compared to current guidelines when the untreated reproductive number is less than 1.53. These findings demonstrate that conditions exist under which expanding treatment to include moderate infections can reduce disease spread and the selective pressure for antibiotic resistance. These findings extend to other pathogens and outbreak scenarios, suggesting potential targets for optimized treatment strategies that balance public health benefits and antibiotic stewardship.

Indexed as

Anti-Bacterial AgentsDisease OutbreaksModels, BiologicalBasic Reproduction NumberCholeraHumansMathematical ConceptsAnti-Bacterial AgentsAntibiotic resistanceCholeraDynamical modelingEpidemiologyPublic health interventionsReproductive numberThreshold analysis

Identifiers

PMID40304831
PMCPMC12043784

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.