Evidence map›Paper›PMID 40733598›Full record

ArticleViruses2025

Modeling the Complete Dynamics of the SARS-CoV-2 Pandemic of Germany and Its Federal States Using Multiple Levels of Data.

Yuri Kheifetz, Holger Kirsten, Andreas Schuppert, Markus Scholz

Abstract read
In one paragraph

Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Yuri KheifetzInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany.ORCID 0000-0002-8356-2724
Holger KirstenInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany.ORCID 0000-0002-3126-7950
Andreas SchuppertInstitute for Computational Biomedicine II, MTZ building, Pauwelsstraße 19, University Hospital RWTH Aachen, 52074 Aachen, Germany.
Markus ScholzInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Haertelstrasse 16-18, 04107 Leipzig, Germany.ORCID 0000-0002-4059-1779

Funding

German Federal Ministry of Education and Research BMBF 031L0296AGerman Federal Ministry of Education and Research BMBF 031L0299E
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

COVID-19Epidemiological ModelsPandemicsSARS-CoV-2GermanyHumansBayesian knowledge synthesisCOVID-19dark figureextended multi-compartment SIR-type modelinput–output non-linear dynamical systemmachine learningpandemic preparednessparameter heterogeneityparametrizationSARS-CoV-2 epidemiologic models

Identifiers

PMID40733598
PMCPMC12297911

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.