Evidence map›Paper›PMID 34243834›Full record

ArticleValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research2021

Where Do We Go From Here? A Framework for Using Susceptible-Infectious-Recovered Models for Policy Making in Emerging Infectious Diseases.

Roy S Zawadzki, Cynthia L Gong, Sang K Cho, Jan E Schnitzer, Nadine K Zawadzki, Joel W Hay, Emmanuel F Drabo

Open access · bronzeAbstract read
In one paragraph

Article in Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers' perspective, 2020 to 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025
    Article
  3. Review
  4. Review
  5. Rigorous Policy-Making Amid COVID-19 and Beyond: Literature Review and Critical Insights.International journal of environmental research and public health · 2021
    Review
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 at 5 institutions in 1 country.

Roy S ZawadzkiDepartment of Statistics, Donald Bren School of Information and Computer Sciences, University of California, Irvine, CA, USA.
Cynthia L GongFetal and Neonatal Institute, Division of Neonatology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. Electronic address: gongc@usc.edu.
Sang K ChoCollege of Pharmacy, University of Houston, Houston, TX, USA.
Jan E SchnitzerProteogenomics Research Institute for Systems Medicine (PRISM), San Diego, CA, USA.
Nadine K ZawadzkiSchaeffer Center for Health Policy & Economics, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
Joel W HaySchaeffer Center for Health Policy & Economics, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
Emmanuel F DraboDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
University of Southern California · USJohns Hopkins University · USProteogenomics Research Institute for Systems Medicine · USUniversity of California, Irvine · USUniversity of Houston · US

Funding

Targeting TGF-b Inhibitors and PPAR-y Agonists To Enhance IPF TherapyP01HL119165 · NHLBI · PROTEOGENOMICS RESEARCH INSTIT/SYS/ MED · PI HAGOOD, JAMES S. · 2015 to 2019
$13.6M
NHLBI NIH HHS P01 HL119165
6 · The paper itself

Abstract

objectivesThroughout the coronavirus disease 2019 pandemic, susceptible-infectious-recovered (SIR) modeling has been the preeminent modeling method to inform policy making worldwide. Nevertheless, the usefulness of such models has been subject to controversy. An evolution in the epidemiological modeling field is urgently needed, beginning with an agreed-upon set of modeling standards for policy recommendations. The objective of this article is to propose a set of modeling standards to support policy decision making.

methodsWe identify and describe 5 broad standards: transparency, heterogeneity, calibration and validation, cost-benefit analysis, and model obsolescence and recalibration. We give methodological recommendations and provide examples in the literature that employ these standards well. We also develop and demonstrate a modeling practices checklist using existing coronavirus disease 2019 literature that can be employed by readers, authors, and reviewers to evaluate and compare policy modeling literature along our formulated standards.

resultsWe graded 16 articles using our checklist. On average, the articles met 6.81 of our 19 categories (36.7%). No articles contained any cost-benefit analyses and few were adequately transparent.

conclusionsThere is significant room for improvement in modeling pandemic policy. Issues often arise from a lack of transparency, poor modeling assumptions, lack of a system-wide perspective in modeling, and lack of flexibility in the academic system to rapidly iterate modeling as new information becomes available. In anticipation of future challenges, we encourage the modeling community at large to contribute toward the refinement and consensus of a shared set of standards for infectious disease policy modeling.

Indexed as

Epidemiologic MethodsCommunicable Diseases, EmergingCost-Benefit AnalysisDisease OutbreaksForecastingHumansPolicy MakingReference Standardscost benefitCOVID-19epidemiologyhealth services researchpolicySIR modeling

Identifiers

PMID34243834
PMCPMC8110035
OpenAlexW3163124098

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.