{"file":[{"content_type":"application/pdf","file_name":"2022_PLoSONE_Budanur.pdf","creator":"dernst","access_level":"open_access","relation":"main_file","checksum":"1ddd9b91e6dec31ab0e7a8433ca2d452","file_id":"11712","success":1,"file_size":1421256,"date_created":"2022-08-01T08:02:38Z","date_updated":"2022-08-01T08:02:38Z"}],"type":"journal_article","day":"18","month":"07","article_processing_charge":"No","tmp":{"image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"date_updated":"2023-08-03T12:24:22Z","date_published":"2022-07-18T00:00:00Z","publication_status":"published","issue":"7","department":[{"_id":"BjHo"}],"abstract":[{"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.","lang":"eng"}],"oa":1,"oa_version":"Published Version","date_created":"2022-07-31T22:01:48Z","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","publisher":"Public Library of Science","scopus_import":"1","title":"An autonomous compartmental model for accelerating epidemics","quality_controlled":"1","related_material":{"record":[{"relation":"research_data","id":"11711","status":"public"}]},"status":"public","doi":"10.1371/journal.pone.0269975","has_accepted_license":"1","author":[{"orcid":"0000-0003-0423-5010","full_name":"Budanur, Nazmi B","id":"3EA1010E-F248-11E8-B48F-1D18A9856A87","first_name":"Nazmi B","last_name":"Budanur"},{"id":"3A374330-F248-11E8-B48F-1D18A9856A87","full_name":"Hof, Björn","first_name":"Björn","last_name":"Hof","orcid":"0000-0003-2057-2754"}],"publication":"PLoS ONE","external_id":{"isi":["000911392100055"]},"publication_identifier":{"eissn":["1932-6203"]},"citation":{"ama":"Budanur NB, Hof B. An autonomous compartmental model for accelerating epidemics. PLoS ONE. 2022;17(7). doi:10.1371/journal.pone.0269975","apa":"Budanur, N. B., & Hof, B. (2022). An autonomous compartmental model for accelerating epidemics. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0269975","chicago":"Budanur, Nazmi B, and Björn Hof. “An Autonomous Compartmental Model for Accelerating Epidemics.” PLoS ONE. Public Library of Science, 2022. https://doi.org/10.1371/journal.pone.0269975.","ista":"Budanur NB, Hof B. 2022. An autonomous compartmental model for accelerating epidemics. PLoS ONE. 17(7), e0269975.","short":"N.B. Budanur, B. Hof, PLoS ONE 17 (2022).","mla":"Budanur, Nazmi B., and Björn Hof. “An Autonomous Compartmental Model for Accelerating Epidemics.” PLoS ONE, vol. 17, no. 7, e0269975, Public Library of Science, 2022, doi:10.1371/journal.pone.0269975.","ieee":"N. B. Budanur and B. Hof, “An autonomous compartmental model for accelerating epidemics,” PLoS ONE, vol. 17, no. 7. Public Library of Science, 2022."},"article_type":"original","language":[{"iso":"eng"}],"article_number":"e0269975","_id":"11704","intvolume":" 17","volume":17,"year":"2022","isi":1,"file_date_updated":"2022-08-01T08:02:38Z","ddc":["510"]}