Knowledge Discovery of the Delays Experienced in Reporting COVID-19 Confirmed Positive Cases Using Time to Event Models

Autor:	Carolyn McGregor, Adele H. Marshall, Aleksandar Novakovic
Rok vydání:	2021
Předmět:	medicine.medical_specialty Coronavirus disease 2019 (COVID-19) business.industry Process mining Disease Knowledge extraction Pandemic Multiple time Medicine Artificial Intelligence & Image Processing business Intensive care medicine Survival analysis Event (probability theory)
Zdroj:	Discovery Science ISBN: 9783030889418 DS
DOI:	10.1007/978-3-030-88942-5_14
Popis:	Survival analysis techniques model the time to an event where the event of interest traditionally is recovery or death from a disease. The distribution of survival data is generally highly skewed in nature and characteristically can include patients in the study who never experience the event of interest. Such censored patients can be accommodated in survival analysis approaches. During the COVID-19 pandemic, the rapid reporting of positive cases is critical in providing insight to understand the level of infection while also informing policy. In this research, we introduce the very novel application of survival models to the time that suspected COVID-19 patients wait to receive their positive diagnosis. In fact, this paper not only considers the application of survival techniques for the time period from symptom onset to notification of the positive result but also demonstrates the application of survival analysis for multiple time points in the diagnosis pathway. The approach is illustrated using publicly available data for Ontario, Canada for one year of the pandemic beginning in March 2020.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27f5776bb6974b5803b22dc433571b5e https://doi.org/10.1007/978-3-030-88942-5_14 Zobrazit plný text záznamu