A mathematical model to assess the effectiveness of test-trace-isolate-and-quarantine under limited capacities

• Verfasst von: Heidecke, Julian [VerfasserIn]
• Verfasst von: Fuhrmann, Jan [VerfasserIn]
• Verfasst von: Barbarossa, Maria Vittoria [VerfasserIn]
• Titel: A mathematical model to assess the effectiveness of test-trace-isolate-and-quarantine under limited capacities
• Verf.angabe: Julian Heidecke, Jan Fuhrmann, Maria Vittoria Barbarossa
• E-Jahr: 2024
• Jahr: March 12, 2024
• Umfang: 31 S.
• Illustrationen: Illustrationen
• Fussnoten: Gesehen am 15.102.2024
• Titel Quelle: Enthalten in: PLOS ONE
• Ort Quelle: San Francisco, California, US : PLOS, 2006
• Jahr Quelle: 2024
• Band/Heft Quelle: 19(2024), 3, Artikel-ID e0299880, Seite 1-31
• ISSN Quelle: 1932-6203
• DOI: doi:10.1371/journal.pone.0299880
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: COVID 19
• Sach-SW: Epidemiology
• Sach-SW: Hygiene
• Sach-SW: Infectious disease control
• Sach-SW: Infectious disease epidemiology
• Sach-SW: Quarantines
• Sach-SW: Respiratory infections
• Sach-SW: Virus testing
• K10plus-PPN: 1905727070

Abstract

Diagnostic testing followed by isolation of identified cases with subsequent tracing and quarantine of close contacts—often referred to as test-trace-isolate-and-quarantine (TTIQ) strategy—is one of the cornerstone measures of infectious disease control. The COVID-19 pandemic has highlighted that an appropriate response to outbreaks of infectious diseases requires a firm understanding of the effectiveness of such containment strategies. To this end, mathematical models provide a promising tool. In this work, we present a delay differential equation model of TTIQ interventions for infectious disease control. Our model incorporates the assumption of limited TTIQ capacities, providing insights into the reduced effectiveness of testing and tracing in high prevalence scenarios. In addition, we account for potential transmission during the early phase of an infection, including presymptomatic transmission, which may be particularly adverse to a TTIQ based control. Our numerical experiments inspired by the early spread of COVID-19 in Germany demonstrate the effectiveness of TTIQ in a scenario where immunity within the population is low and pharmaceutical interventions are absent, which is representative of a typical situation during the (re-)emergence of infectious diseases for which therapeutic drugs or vaccines are not yet available. Stability and sensitivity analyses reveal both disease-dependent and disease-independent factors that impede or enhance the success of TTIQ. Studying the diminishing impact of TTIQ along simulations of an epidemic wave, we highlight consequences for intervention strategies.