Evidence map›Paper›PMID 34039597›Full record

ReviewScience advances2021

Lessons from a pandemic for systems-oriented sustainability research.

Noelle E Selin

Abstract readReview
In one paragraph

Review in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Simulating institutional heterogeneity in sustainability science.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. Health and equity implications of individual adaptation to air pollution in a changing climate.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. Progress in modeling dynamic systems for sustainable development.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. 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

1 author.

Noelle E SelinInstitute for Data, Systems, and Society, and Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. selin@mit.edu.ORCID 0000-0002-6396-5622

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review examines research on environmental impacts of coronavirus disease 2019 (COVID-19) from a systems-oriented sustainability perspective, focusing on three areas: air quality and human health, climate change, and production and consumption. The review assesses whether and how this COVID-19-focused research (i) examines components of an integrated system; (ii) accounts for interactions including complex, adaptive dynamics; and (iii) is oriented to informing action. It finds that this research to date has not comprehensively accounted for complex, coupled interactions, especially involving societal factors, potentially leading to erroneous conclusions and hampering efforts to draw broader insights across sustainability-relevant domains. Lack of systems perspective in COVID-19 research reflects a broader challenge in environmental research, which often neglects societal feedbacks. Practical steps through which researchers can better incorporate systems perspectives include using analytical frameworks to identify important components and interactions, connecting frameworks to models and methods, and advancing sustainability science theory and methodology.

Indexed as

Air PollutionClimate ChangeCOVID-19EnvironmentHumansPandemicsSARS-CoV-2

Identifiers

PMID34039597
PMCPMC8153715

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.