Evidence map›Paper›PMID 25480821›Full record

ArticleAmerican journal of epidemiology2015

Formalizing the role of agent-based modeling in causal inference and epidemiology.

Brandon D L Marshall, Sandro Galea

Open access · hybridAbstract read
In one paragraph

Article in American journal of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 2 pooled it
13.1field-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

99 citing papers in PubMed, 2 syntheses or guidelines pooled it, 193 citations in OpenAlex.

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  14. Making evidence go further: Advancing synergy between agent-based modeling and randomized control trials.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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  16. Article
  17. A framework for the detection and attribution of biodiversity change.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  18. Evaluating Policies to Decrease the Risk of Introducing SARS-CoV-2 Infections to Nursing Home Facilities.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2023
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39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Brandon D L Marshall
Sandro Galea
Brown University · US

Funding

Translational ScienceP30AI042853 · NIAID · MIRIAM HOSPITAL · PI LARRY K BROWN · 1998 to 2026
$51.7M
NIAID NIH HHS P30 AI042853NIAID NIH HHS P30-AI042853
6 · The paper itself

Abstract

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry.

Indexed as

CausalityEpidemiologic MethodsModels, TheoreticalConfounding Factors, EpidemiologicEnvironmentHumansSocial Determinants of Healthagent-based modelscausal inferencecomplexitycomplex systemspopulation healthpublic health

Identifiers

PMID25480821
PMCPMC4351348
OpenAlexW2170588867

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.