Evidence map›Paper›PMID 34230767›Full record

ArticleSystem dynamics review

Behavioral dynamics of COVID-19: estimating underreporting, multiple waves, and adherence fatigue across 92 nations.

Hazhir Rahmandad, Tse Yang Lim, John Sterman

Abstract read
In one paragraph

Article in System dynamics review. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 3 pooled it
–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

50 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Faster Uptake, Slower Let-Down: Asymmetric Community Responses to Changing Risks During a Pandemic.Risk analysis : an official publication of the Society for Risk Analysis · 2026
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  18. Predictors and moderators of COVID-19 pandemic fatigue in Hong Kong.Journal of infection and public health · 2023
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  19. Article
  20. Leveraging Serosurveillance and Postmortem Surveillance to Quantify the Impact of Coronavirus Disease 2019 in Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
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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

3 authors.

Hazhir RahmandadMassachusetts Institute of Technology Cambridge MA USA.ORCID https://orcid.org/0000-0002-2784-9042
Tse Yang LimMassachusetts Institute of Technology Cambridge MA USA.
John StermanMassachusetts Institute of Technology Cambridge MA USA.ORCID https://orcid.org/0000-0001-7476-6760

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Effective responses to the COVID-19 pandemic require integrating behavioral factors such as risk-driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51 percent, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47 percent lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14 percent, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per-capita deaths despite reproduction numbers fluctuating around one across nations. A public online simulator facilitates scenario analysis over the coming months. © 2021 System Dynamics Society.

Identifiers

PMID34230767
PMCPMC8250772

What OpenQuestion holds

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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.