Evidence map›Paper›PMID 36593336›Full record

ArticleEuropean journal of epidemiology2023

Age-specific contribution of contacts to transmission of SARS-CoV-2 in Germany.

Isti Rodiah, Patrizio Vanella, Alexander Kuhlmann, Veronika K Jaeger, Manuela Harries, Gerard Krause, Andre Karch, Wolfgang Bock, Berit Lange

Abstract read
In one paragraph

Article in European journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

9 authors.

Isti RodiahDepartment of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, DE-38124, Brunswick, Germany. Isti.Rodiah@helmholtz-hzi.de.ORCID http://orcid.org/0000-0003-4365-1615
Patrizio VanellaDepartment of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, DE-38124, Brunswick, Germany.
Alexander KuhlmannFaculty of Medicine, Martin Luther University Halle-Wittenberg, Magdeburgerstr. 8, DE-06112, Halle (Saale), Germany.
Veronika K JaegerInstitute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, DE-48149, Münster, Germany.
Manuela HarriesDepartment of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, DE-38124, Brunswick, Germany.
Gerard KrauseDepartment of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, DE-38124, Brunswick, Germany.
Andre KarchInstitute of Epidemiology and Social Medicine, University of Münster, Albert-Schweitzer-Campus 1, DE-48149, Münster, Germany.
Wolfgang Bock *Technomathematics Group, Department of Mathematics, TU Kaiserslautern, Gottlieb-Daimler-Straße 48, DE-67663, Kaiserslautern, Germany.
Berit Lange *Department of Epidemiology, Helmholtz Centre for Infection Research (HZI), Inhoffenstr. 7, DE-38124, Brunswick, Germany. Berit.Lange@helmholtz-hzi.de.

Funding

Bundesministerium für Bildung und Forschung FKZ: 01KX2021 (Project COVIM: "NaFOUniMedCovid19")H2020 European Research Council 101003480 (Project CORESMA)Standing Conference of the Ministers of Education and Cultural Affairs (KMK) Project COVID-SCHULEN
6 · The paper itself

Abstract

Current estimates of pandemic SARS-CoV-2 spread in Germany using infectious disease models often do not use age-specific infection parameters and are not always based on age-specific contact matrices of the population. They also do usually not include setting- or pandemic phase-based information from epidemiological studies of reported cases and do not account for age-specific underdetection of reported cases. Here, we report likely pandemic spread using an age-structured model to understand the age- and setting-specific contribution of contacts to transmission during different phases of the COVID-19 pandemic in Germany. We developed a deterministic SEIRS model using a pre-pandemic contact matrix. The model was optimized to fit age-specific SARS-CoV-2 incidences reported by the German National Public Health Institute (Robert Koch Institute), includes information on setting-specific reported cases in schools and integrates age- and pandemic period-specific parameters for underdetection of reported cases deduced from a large population-based seroprevalence studies. Taking age-specific underreporting into account, younger adults and teenagers were identified in the modeling study as relevant contributors to infections during the first three pandemic waves in Germany. For the fifth wave, the Delta to Omicron transition, only age-specific parametrization reproduces the observed relative and absolute increase in pediatric hospitalizations in Germany. Taking into account age-specific underdetection did not change considerably how much contacts in schools contributed to the total burden of infection in the population (up to 12% with open schools under hygiene measures in the third wave). Accounting for the pandemic phase and age-specific underreporting is important to correctly identify those groups of the population in which quarantine, testing, vaccination, and contact-reduction measures are likely to be most effective and efficient. Age-specific parametrization is also highly relevant to generate informative age-specific output for decision makers and resource planers.

Indexed as

COVID-19SARS-CoV-2AdolescentAdultAge FactorsChildGermanyHumansPandemicsSeroepidemiologic StudiesAge-specific viral spreadCompartment modelsCOVID-19Epidemiological modelingInfection severitySARS-CoV-2Underdetection

Identifiers

PMID36593336
PMCPMC9807433

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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.