Evidence map›Paper›PMID 37610124›Full record

ReviewEmerging infectious diseases2023

Participatory Mathematical Modeling Approach for Policymaking during the First Year of the COVID-19 Crisis, Jordan.

Saverio Bellizzi, Nicholas Letchford, Keyrellous Adib, William J M Probert, Penelope Hancock, Lora Alsawalha, Alessio Santoro, Maria C Profili, Ricardo Aguas, Christian Popescu and 5 more

Abstract readReview
In one paragraph

Review in Emerging infectious diseases, 2023. 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

15 authors.

Saverio Bellizzi
Nicholas Letchford
Keyrellous Adib
William J M Probert
Penelope Hancock
Lora Alsawalha
Alessio Santoro
Maria C Profili
Ricardo Aguas
Christian Popescu
Lubna Al Ariqi
Lisa White
Wail Hayajneh
Nathir Obeidat
Pierre Nabeth

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We engaged in a participatory modeling approach with health sector stakeholders in Jordan to support government decision-making regarding implementing public health measures to mitigate COVID-19 disease burden. We considered the effect of 4 physical distancing strategies on reducing COVID-19 transmission and mortality in Jordan during March 2020-January 2021: no physical distancing; intermittent physical distancing where all but essential services are closed once a week; intermittent physical distancing where all but essential services are closed twice a week; and a permanent physical distancing intervention. Modeling showed that the fourth strategy would be most effective in reducing cases and deaths; however, this approach was only marginally beneficial to reducing COVID-19 disease compared with an intermittently enforced physical distancing intervention. Scenario-based model influenced policy-making and the evolution of the pandemic in Jordan confirmed the forecasting provided by the modeling exercise and helped confirm the effectiveness of the policy adopted by the government of Jordan.

Indexed as

COVID-19Cost of IllnessExerciseGovernmentHumansJordancoronavirus diseaseCOVID-19curfewdecision-makingJordanmodelingrespiratory infectionsSARS-CoV-2severe acute respiratory syndrome coronavirus 2vaccine-preventable diseasesviruseszoonoses

Identifiers

PMID37610124
PMCPMC10461658

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.