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ZENODO
Dataset . 2022
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Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Results: Modeling the impact of the Omicron infection wave in Germany

Authors: Maier, Benjamin F.;

Results: Modeling the impact of the Omicron infection wave in Germany

Abstract

# Modeling the impact of the Omicron infection wave in Germany This repository contains results of a modelling study regarding the spread of SARS-CoV-2 VOC "Omicron" in Germany. ## Columns and values | column name | type | description EN | description DE | | -- | -- | -- | -- | | `infectious_period_both` | int | Mean infectious period (in days) for both variants | Mittlere Infektiositaetsperiode fuer beide Varianten (in Tagen) | | `omicron_latent_period` | int | Mean latent period of VOC Omicron (in days) | Mittlere Latenzzeit der VOC Omikron (in Tagen) | | `booster_reach` | str | Reach of the booster campaign | Reichweite der Auffrischkampagne | | `booster_VE` | str | Vaccine efficacy of the booster vaccination | Impfeffektivitaet der Auffrischimpfung | | `contact_reduction_scenario_id` | int | ID of the contact reduction scenario | ID des Kontaktreduktionsszenarios | | `contact_reduction_strength` | float | prefactor with which the contact modulation f(t) is multiplied | Vorfaktor, mit der die Kontaktmodulation f(t) waehrend der Kontaktreduktionsperiode skaliert wird | | `contact_reduction_start` | date (ISO 8601) | Date when contact reduction begins | Beginn der Kontaktreduktion | | `contact_reduction_end` | date (ISO 8601) | Date when contact reduction ends | Ende der Kontaktreduktion | | `relative_risk_hospitalization` | float | Relative risk (RR) of hospitalization after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Hospitalisierung nach Infektion mit Omicron gegenueber Infektion mit Delta | | `relative_risk_icu` | float | Relative risk (RR) of ICU admission after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Intensivpflichtigkeit nach Infektion mit Omicron gegenueber Infektion mit Delta | | `value_type` | str | Wich value is shown in the `value` column | Art des Wertes in der Spalte `value` | | `date` | date (ISO 8601) | Date associated with the modeling result given in column `value` | Datum assoziiert mit dem Modellergebnis des Wertes in der Spalte `value` | | `value` | int | Model result (rounded to nearest integer) | Modellergebnis (gerundet auf ganze Zahl) | Additional columns regarding combinations of plausible scenarios (rounded to nearest integer) and 180 stochastic simulations per parameter combination: | column name | type | description EN | description DE | | -- | -- | -- | -- | | `95_PI_lower` | int | 95% PI lower bound (rounded to nearest integer) | Untere Schranke des 95% PIs (gerundet auf ganze Zahl) | | `50_PI_lower` | int | 50% PI lower bound (rounded to nearest integer) | Untere Schranke des 50% PIs (gerundet auf ganze Zahl) | | `median` | int | median (rounded to nearest integer) | Median (gerundet auf ganze Zahl) | | `50_PI_upper` | int | 50% PI upper bound (rounded to nearest integer) | Obere Schranke des 50% PIs (gerundet auf ganze Zahl) | | `95_PI_upper` | int | 95% PI upper bound (rounded to nearest integer) | Obere Schranke des 95% PIs (gerundet auf ganze Zahl) | ### Values: `booster_reach` | value | description EN | description DE | | -- | -- | -- | | `md` | medium booster campaign reach (80% of those that received full vaccination in 2021 receive booster vaccination) | Medium, 80% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung | | `hi` | high booster campaign reach (100% of those that received full vaccination in 2021 receive booster vaccination) | Hoch, 100% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung | | `hi-and-90perc-2dose` | 100% receive booster vaccination and vaccine uptake of first immunization suddenly increases to 90% in Jan 2022 | 100% erhalten Auffrischimpfung und Impfquote der Erstimmunisierung erreicht schnell 90% im Januar 2022 | ### Values: `booster_VE` | value | description EN | description DE | | -- | -- | -- | | `lo` | low booster vaccine efficacy (assumption: booster protects as well against infection as 2nd dose) | Niedrige Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie 2 Dosen) | | `hi` | high booster vaccine efficacy (assumption: booster protects as well against infection as against symptomatic disease) | Hohe Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie vor symptomatischer Erkrankung) | ### Values: `value_type` | value | description EN | description DE | | -- | -- | -- | | `inc` | incidence (absolute number of new reported cases per day) | Inzidenz (Zahl der gemeldeten Neuinfektion an diesem Tag, absolut) | | `hsp` | hospitalization incidence (absolute number of new hospital admissions per day) | Hospitalisierungsinzidenz (Zahl der gemeldeten Neuhospitalisierungen an diesem Tag, absolut) | | `icu` | total number of patients in ICUs | Gesamtzahl der intensivpflichtigen Patient:innen | ## License Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).

Keywords

SARS-CoV-2, Omicron, COVID-19, infectious-disease modelling, modeling

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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