Evidence map›Paper›PMID 35190590›Full record

ArticleScientific reports2022

Model based estimation of the SARS-CoV-2 immunization level in austria and consequences for herd immunity effects.

Martin Bicher, Claire Rippinger, Günter Schneckenreither, Nadine Weibrecht, Christoph Urach, Melanie Zechmeister, Dominik Brunmeir, Wolfgang Huf, Niki Popper

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.1field-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

11 citing papers in PubMed, 25 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Martin BicherInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria. martin.bicher@dwh.at.
Claire RippingerInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria.
Günter SchneckenreitherInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria.
Nadine WeibrechtAssociation for Decision Support for Health Policy and Planning (DEXHELPP), 1070, Vienna, Austria.
Christoph UrachInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria.
Melanie ZechmeisterAssociation for Decision Support for Health Policy and Planning (DEXHELPP), 1070, Vienna, Austria.
Dominik BrunmeirInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria.
Wolfgang HufDepartment of Laboratory Medicine, Vienna Healthcare Group, Hietzing Hospital, 1140, Vienna, Austria.
Niki PopperInstitute of Information Systems Engineering, TU Wien, 1040, Vienna, Austria.
TU Wien · ATKarl Landsteiner Society · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several systemic factors indicate that worldwide herd immunity against COVID-19 will probably not be achieved in 2021. On the one hand, vaccination programs are limited by availability of doses and on the other hand, the number of people already infected is still too low to have a disease preventing impact and new emerging variants of the virus seem to partially neglect developed antibodies from previous infections. Nevertheless, by February 2021 after one year of observing high numbers of reported COVID-19 cases in most European countries, we might expect that the immunization level should have an impact on the spread of SARS-CoV-2. Here we present an approach for estimating the immunization of the Austrian population and discuss potential consequences on herd immunity effects. To estimate immunization we use a calibrated agent-based simulation model that reproduces the actual COVID-19 pandemic in Austria. From the resulting synthetic individual-based data we can extract the number of immunized persons. We then extrapolate the progression of the epidemic by varying the obtained level of immunization in simulations of an hypothetical uncontrolled epidemic wave indicating potential effects on the effective reproduction number. We compared our theoretical findings with results derived from a classic differential equation SIR-model. As of February 2021, [Formula: see text] of the Austrian population has been affected by a SARS-CoV-2 infection which causes a [Formula: see text] reduction of the effective reproduction number and a [Formula: see text] reduction of the prevalence peak compared to a fully susceptible population. This estimation is now recomputed on a regular basis to publish model based analysis of immunization level in Austria also including the fast growing effects of vaccination programs. This provides substantial information for decision makers to evaluate the necessity of non pharmaceutical intervention measures based on the estimated impact of natural and vaccinated immunization.

Indexed as

Immunity, HerdModels, StatisticalAntibodies, ViralAustriaCOVID-19COVID-19 VaccinesHumansIncidencePandemicsSARS-CoV-2VaccinationAntibodies, ViralCOVID-19 Vaccines

Identifiers

PMID35190590
PMCPMC8861103
OpenAlexW4220887625

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.