---
_id: '11704'
abstract:
- lang: eng
  text: In Fall 2020, several European countries reported rapid increases in COVID-19
    cases along with growing estimates of the effective reproduction rates. Such an
    acceleration in epidemic spread is usually attributed to time-dependent effects,
    e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc.
    In this case however the acceleration occurred when counter measures such as testing
    and contact tracing exceeded their capacity limit. Considering Austria as an example,
    here we show that this dynamics can be captured by a time-independent, i.e. autonomous,
    compartmental model that incorporates these capacity limits. In this model, the
    epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting
    in an increasing fraction of undetected cases that drive the effective reproduction
    rate progressively higher. We demonstrate that standard models which does not
    include this effect necessarily result in a systematic underestimation of the
    effective reproduction rate.
article_number: e0269975
article_processing_charge: No
article_type: original
author:
- first_name: Nazmi B
  full_name: Budanur, Nazmi B
  id: 3EA1010E-F248-11E8-B48F-1D18A9856A87
  last_name: Budanur
  orcid: 0000-0003-0423-5010
- first_name: Björn
  full_name: Hof, Björn
  id: 3A374330-F248-11E8-B48F-1D18A9856A87
  last_name: Hof
  orcid: 0000-0003-2057-2754
citation:
  ama: Budanur NB, Hof B. An autonomous compartmental model for accelerating epidemics.
    <i>PLoS ONE</i>. 2022;17(7). doi:<a href="https://doi.org/10.1371/journal.pone.0269975">10.1371/journal.pone.0269975</a>
  apa: Budanur, N. B., &#38; Hof, B. (2022). An autonomous compartmental model for
    accelerating epidemics. <i>PLoS ONE</i>. Public Library of Science. <a href="https://doi.org/10.1371/journal.pone.0269975">https://doi.org/10.1371/journal.pone.0269975</a>
  chicago: Budanur, Nazmi B, and Björn Hof. “An Autonomous Compartmental Model for
    Accelerating Epidemics.” <i>PLoS ONE</i>. Public Library of Science, 2022. <a
    href="https://doi.org/10.1371/journal.pone.0269975">https://doi.org/10.1371/journal.pone.0269975</a>.
  ieee: N. B. Budanur and B. Hof, “An autonomous compartmental model for accelerating
    epidemics,” <i>PLoS ONE</i>, vol. 17, no. 7. Public Library of Science, 2022.
  ista: Budanur NB, Hof B. 2022. An autonomous compartmental model for accelerating
    epidemics. PLoS ONE. 17(7), e0269975.
  mla: Budanur, Nazmi B., and Björn Hof. “An Autonomous Compartmental Model for Accelerating
    Epidemics.” <i>PLoS ONE</i>, vol. 17, no. 7, e0269975, Public Library of Science,
    2022, doi:<a href="https://doi.org/10.1371/journal.pone.0269975">10.1371/journal.pone.0269975</a>.
  short: N.B. Budanur, B. Hof, PLoS ONE 17 (2022).
corr_author: '1'
date_created: 2022-07-31T22:01:48Z
date_published: 2022-07-18T00:00:00Z
date_updated: 2025-06-11T13:37:36Z
day: '18'
ddc:
- '510'
department:
- _id: BjHo
doi: 10.1371/journal.pone.0269975
external_id:
  isi:
  - '000911392100055'
  pmid:
  - '35849565'
file:
- access_level: open_access
  checksum: 1ddd9b91e6dec31ab0e7a8433ca2d452
  content_type: application/pdf
  creator: dernst
  date_created: 2022-08-01T08:02:38Z
  date_updated: 2022-08-01T08:02:38Z
  file_id: '11712'
  file_name: 2022_PLoSONE_Budanur.pdf
  file_size: 1421256
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file_date_updated: 2022-08-01T08:02:38Z
has_accepted_license: '1'
intvolume: '        17'
isi: 1
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS ONE
publication_identifier:
  eissn:
  - 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
  record:
  - id: '11711'
    relation: research_data
    status: public
scopus_import: '1'
status: public
title: An autonomous compartmental model for accelerating epidemics
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2022'
...