Evidence map›Paper›PMID 37628560›Full record

ArticleHealthcare (Basel, Switzerland)2023

Fitting Early Phases of the COVID-19 Outbreak: A Comparison of the Performances of Used Models.

Veronica Sciannameo, Danila Azzolina, Corrado Lanera, Aslihan Şentürk Acar, Maria Assunta Corciulo, Rosanna Irene Comoretto, Paola Berchialla, Dario Gregori

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Veronica SciannameoUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.ORCID 0000-0002-0499-0131
Danila AzzolinaUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.ORCID 0000-0002-8185-5742
Corrado LaneraUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.ORCID 0000-0002-0520-7428
Aslihan Şentürk AcarDepartment of Actuarial Sciences, Hacettepe University, 06230 Ankara, Turkey.ORCID 0000-0002-1708-2028
Maria Assunta CorciuloUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.
Rosanna Irene ComorettoUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.ORCID 0000-0002-8601-1899
Paola BerchiallaCenter of Biostatistics, Epidemiology and Public Health, Department of Clinical and Biological Sciences, University of Torino, 10124 Turin, Italy.ORCID 0000-0001-5835-5638
Dario GregoriUnit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences, and Public Health, University of Padova, 35131 Padova, Italy.ORCID 0000-0001-7906-0580

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 outbreak involved a spread of prediction efforts, especially in the early pandemic phase. A better understanding of the epidemiological implications of the different models seems crucial for tailoring prevention policies. This study aims to explore the concordance and discrepancies in outbreak prediction produced by models implemented and used in the first wave of the epidemic. To evaluate the performance of the model, an analysis was carried out on Italian pandemic data from February 24, 2020. The epidemic models were fitted to data collected at 20, 30, 40, 50, 60, 70, 80, 90, and 98 days (the entire time series). At each time step, we made predictions until May 31, 2020. The Mean Absolute Error (

Indexed as

COVID-19early phaseepidemic modelsprediction modelprevention policy

Identifiers

PMID37628560
PMCPMC10454512

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.