Evidence map›Paper›PMID 34512113›Full record

ArticleComputational and mathematical organization theory2021

Measuring the impact of suspending Umrah, a global mass gathering in Saudi Arabia on the COVID-19 pandemic.

Sultanah M Alshammari, Waleed K Almutiry, Harsha Gwalani, Saeed M Algarni, Kawther Saeedi

Abstract read
In one paragraph

Article in Computational and mathematical organization theory, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Sultanah M AlshammariDepartment of Computer Science, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0000-0003-0042-7429
Waleed K AlmutiryDepartment of Mathematics, College of Arts and Science in Ar Rass, Qassim University, Qassim, Saudi Arabia.
Harsha GwalaniDepartment of Computer Science and Engineering, University of North Texas, Denton, TX USA.
Saeed M AlgarniSaudi Center for Disease Prevention and Control, Jeddah, Saudi Arabia.
Kawther SaeediDepartment of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the early days of the coronavirus (COVID-19) outbreak in Wuhan, China, Saudi Arabia started to implement several preventative measures starting with the imposition of travel restrictions to and from China. Due to the rapid spread of COVID-19, and with the first confirmed case in Saudi Arabia in March 2019, more strict measures, such as international travel restriction, and suspension or cancellation of major events, social gatherings, prayers at mosques, and sports competitions, were employed. These non-pharmaceutical interventions aim to reduce the extent of the epidemic due to the implications of international travel and mass gatherings on the increase in the number of new cases locally and globally. Since this ongoing outbreak is the first of its kind in the modern world, the impact of suspending mass gatherings on the outbreak is unknown and difficult to measure. We use a stratified SEIR epidemic model to evaluate the impact of Umrah, a global Muslim pilgrimage to Mecca, on the spread of the COVID-19 pandemic during the month of Ramadan, the peak of the Umrah season. The analyses shown in the paper provide insights into the effects of global mass gatherings such as Hajj and Umrah on the progression of the COVID-19 pandemic locally and globally.

Indexed as

CoronavirusCOVID-19Epidemic modelingHajjInfectious diseasesMass gatheringsSEIR modelTravel restrictionUmrah

Identifiers

PMID34512113
PMCPMC8421017

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.