Evidence map›Paper›PMID 33522928›Full record

ReviewBMC public health2021

Rapid review of COVID-19 epidemic estimation studies for Iran.

Farshad Pourmalek, Mohsen Rezaei Hemami, Leila Janani, Maziar Moradi-Lakeh

Abstract readReview
In one paragraph

Review in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. U.S.-Imposed Economic Sanctions on Iran in the COVID-19 Crisis From the Human Rights Perspective.International journal of health services : planning, administration, evaluation · 2021
    Article
  12. Article
  13. COVID-19 in Iran: What was done and what should be done.Medical journal of the Islamic Republic of Iran · 2021
    Article
  14. Can Free LivingIranian journal of parasitology
    Review
  15. 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

4 authors.

Farshad PourmalekUniversity of British Columbia, Vancouver, Canada.
Mohsen Rezaei HemamiAberdeen Centre for Health Data Sciences, University of Aberdeen, Aberdeen, UK.
Leila JananiDepartment of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Maziar Moradi-LakehPreventive Medicine and Public Health Research Center, Psychosocial Health Research Institute, Community and Family Medicine Department, School of Medicine, Iran University of Medical Sciences, Tehran, Iran. moradilakeh.m@iums.ac.ir.ORCID http://orcid.org/0000-0001-7381-5305

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo inform researchers about the methodology and results of epidemic estimation studies performed for COVID-19 epidemic in Iran, we aimed to perform a rapid review.

methodsWe searched for and included published articles, preprint manuscripts and reports that estimated numbers of cumulative or daily deaths or cases of COVID-19 in Iran. We found 131 studies and included 29 of them.

resultsThe included studies provided outputs for a total of 84 study-model/scenario combinations. Sixteen studies used 3-4 compartmental disease models. At the end of month two of the epidemic (2020-04-19), the lowest (and highest) values of predictions were 1,777 (388,951) for cumulative deaths, 20,588 (2,310,161) for cumulative cases, and at the end of month four (2020-06-20), were 3,590 (1,819,392) for cumulative deaths, and 144,305 (4,266,964) for cumulative cases. Highest estimates of cumulative deaths (and cases) for latest date available in 2020 were 418,834 on 2020-12-19 (and 41,475,792 on 2020-12-31). Model estimates predict an ominous course of epidemic progress in Iran. Increase in percent population using masks from the current situation to 95% might prevent 26,790 additional deaths (95% confidence interval 19,925-35,208) by the end of year 2020.

conclusionsMeticulousness and degree of details reported for disease modeling and statistical methods used in the included studies varied widely. Greater heterogeneity was observed regarding the results of predicted outcomes. Consideration of minimum and preferred reporting items in epidemic estimation studies might better inform future revisions of the available models and new models to be developed. Not accounting for under-reporting drives the models' results misleading.

Indexed as

EpidemicsCOVID-19HumansIranCasesCOVID-19DeathsEpidemicEstimationIranModelPandemicPrediction

Identifiers

PMID33522928
PMCPMC7848865

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.