Evidence map›Paper›PMID 32536749›Full record

ArticleSafety science2020

A multicriteria approach for risk assessment of Covid-19 in urban district lockdown.

Valentino Sangiorgio, Fabio Parisi

Open access · greenAbstract read
In one paragraph

Article in Safety science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
2.3field-weighted citation impact, top 8% of its field
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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 81 citations in OpenAlex.

  1. Pooled it
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  10. Nexus between drivers of COVID-19 and country risks.Socio-economic planning sciences · 2023
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  18. Prioritizing Multidimensional Interdependent Factors Influencing COVID-19 Risk.Risk analysis : an official publication of the Society for Risk Analysis · 2022
    Review
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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

2 authors at 1 institution in 1 country.

Valentino SangiorgioDepartment of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic of Bari, Bari, Italy.
Fabio ParisiDepartment of Electrical and Information Engineering (DEI), Polytechnic of Bari, Bari, Italy.
Polytechnic University of Bari · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At the beginning of 2020, the spread of a new strand of Coronavirus named SARS-CoV-2 (COVID-19) raised the interest of the scientific community about the risk assessment related to the viral infection. The contagion became pandemic in few months forcing many Countries to declare lockdown status. In this context of quarantine, all commercial and productive activities are suspended, and many Countries are experiencing a serious crisis. To this aim, the understanding of risk of contagion in every urban district is fundamental for governments and administrations to establish reopening strategies. This paper proposes the calibration of an index able to predict the risk of contagion in urban districts in order to support the administrations in identifying the best strategies to reduce or restart the local activities during lockdown conditions. The objective regards the achievement of a useful tool to predict the risk of contagion by considering socio-economic data such as the presence of activities, companies, institutions and number of infections in urban districts. The proposed index is based on a factorial formula, simple and easy to be applied by practitioners, calibrated by using an optimization-based procedure and exploiting data of 257 urban districts of Apulian region (Italy). Moreover, a comparison with a more refined analysis, based on the training of

Indexed as

Apulian Region (Italy)Artificial neural networksCalibrationMathematical programming problemMulticriteria analysisRisk of Covid-19 contagion

Identifiers

PMID32536749
PMCPMC7275161
OpenAlexW3033912750

What OpenQuestion holds

Textmetadata
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.