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Cited by 24COVID-19 epidemiological studiesCOVID-19 Clinical Research StudiesInsurance, Mortality, Demography, Risk Management

Reflection with ChatGPT about the excess death after the COVID-19 pandemic

Open access
Temsah, Mohamad-Hani, Jamal, Amr, Al-Tawfiq, Jaffar A.·2023·New Microbes and New Infections
DOI 10.1016/j.nmni.2023.101103PMC PMC9937725
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AI snapshot

Written from the paper’s full text.

TL;DR

This correspondence reports a brief ChatGPT interaction about global excess mortality after the COVID-19 pandemic and how stakeholders might reduce excess deaths in 2023. It presents ChatGPT’s general explanations and recommendations, while noting that ChatGPT use in medicine needs further exploration.

Key findings

  • The paper notes that despite an apparent decrease in COVID-19 mortality in 2022, there has still been a universal increase in excess deaths across nations, with conflicting estimates; one cited study estimated 14.83 million excess deaths worldwide.
  • ChatGPT attributed excess mortality to direct and indirect pandemic effects, including COVID-19 deaths, disruptions to healthcare systems, delayed or deferred medical treatments, and social and economic consequences such as mental health disorders, economic distress, and reduced access to education.
  • For 2022 specifically, ChatGPT said causes are difficult to predict but could include continued COVID-19 spread, new variants, healthcare disruptions, indirect pandemic consequences, natural disasters, conflicts, and other public health crises.
  • To reduce excess deaths in 2023, ChatGPT recommended accelerating COVID-19 vaccination, improving healthcare systems, increasing access to healthcare, addressing social and economic factors, and promoting healthy behaviors.

Methods

  • This is a letter/reflection, not an empirical study; the author asked ChatGPT three questions on 12 Feb 2023 about excess mortality during and after the COVID-19 pandemic and how stakeholders could decrease excess death in 2023.
  • The text consists of the human questions and ChatGPT’s responses, with no formal sample, data collection, or statistical analysis reported.

Limitations

  • The paper states that “the utilization of ChatGPT in medicine is yet to be explored further across different disciplines.”
  • ChatGPT itself states that it cannot think, speculate, or predict future events, and that exact causes of 2022 excess mortality are difficult to predict.
  • Evident from the text: the piece provides no original data, no systematic review, no quantitative analysis, and no independent verification of ChatGPT’s claims.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.nmni.2023.101103

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 2 cited sources checked · 0 supported · 0 flagged

    • Classified as probably not a substantial claim. 2
    • May combine two claims. 1

    • Probably not a substantial claim: may not pass S3 (load-bearing).

      Premisecitation

      Estimates of excess deaths across nations are conflicting.

      “with conflicting estimates [2]”
      Quote in the paperNot a substantial claim0 of 1 sources checked
      • cites [2] Schöley, 2023, Conflicting COVID-19 excess mortality estimates, Lancet source

        Not checked in the free run.

    • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

      Interpretationnone given

      The utilization of ChatGPT in medicine is yet to be explored further across different disciplines.

      “The utilization of ChatGPT in medicine is yet to be explored further across different disciplines.”
      Quote in the paperNot a substantial claim
      • Rests on an assumption: ChatGPT can provide useful insights into excess mortality and healthcare.

    • May combine two claims.

      Premisecitation

      Despite an apparent decrease in COVID-19 mortality in 2022, there has been a universal increase in excess deaths across nations.

      “Despite the apparent decrease in Coronavirus Disease 2019 (COVID-19) mortality in 2022, still, there has been a universal increase in the excess deaths across nations [1] with conflicting estimates [2].”
      Quote in the paperNot a substantial claim0 of 1 sources checked
      • cites [1] ourworldindata

        Not checked in the free run.

    3 of 3

    • The paper relies on this without support.

      ChatGPT can provide useful insights into excess mortality and healthcare.

      “To explore how Artificial Intelligence (AI) Chatbot may address such issues, we asked the following three questions to Generative Pre-trained Transformer (ChatGPT) [4] on 12 Feb 2023, hoping that sharing these could enrich the literature with new dimensions on AI and humans, working together for rapid insights in healthcare.”

    • The paper relies on this without support.

      Sharing the ChatGPT dialogue can enrich the literature with new dimensions on AI and humans working together for rapid insights in healthcare.

      “hoping that sharing these could enrich the literature with new dimensions on AI and humans, working together for rapid insights in healthcare.”
    2 of 2

    Claims other papers make about this one

    Each is checked against this paper’s own text: does it say what the citing paper says it does?

    Cites

    Flagged first, then by citations

    Cited by

    Sorted by citations

    Related

    Authors
    Temsah, M.-H., Jamal, A., & Al-Tawfiq, J. A.
    Affiliations
    • King Saud University (SA)
    • King Saud Medical City (SA)
    ORCID
    Venue
    New Microbes and New Infections
    Publisher
    Elsevier BV
    Published
    2023-03
    Volume
    52
    Pages
    101103
    ISSN
    2052-2975 (ISSN-L)
    DOI
    10.1016/j.nmni.2023.101103
    PMC
    PMC9937725
    OpenAlex
    W4321189504
    Cited by
    23
    References
    2
    Citations by year
    2026: 1 · 2025: 2 · 2024: 6 · 2023: 14
    FWCI
    4.84
    Type
    journal article
    Language
    en
    Open access
    Licence
    Locations
    • New Microbes and New Infections (publishedVersion, cc-by-nc-nd)
    • PubMed Central (publishedVersion, cc-by-nc-nd)
    • PubMed (publishedVersion)
    • IUScholarWorks (Indiana University) (submittedVersion, cc-by-nc-nd)
    • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
    Topics
    • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
    • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
    • Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
    Keywords
    excess mortality, COVID-19 pandemic, ChatGPT, large language models

    About these checks

    Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

    Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.

    Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.

    Statistics and arithmetic are recomputed, not judged.

    Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

    What counts as a claim ›How we measure confidence ›How we check this ›

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