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Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices.
Tofighi, Mohammadali; Asgary, Ali; Merchant, Asad A; Shafiee, Mohammad Ali; Najafabadi, Mahdi M; Nadri, Nazanin; Aarabi, Mehdi; Heffernan, Jane; Wu, Jianhong.
Afiliação
  • Tofighi M; ADERSIM (Advanced Disaster, Emergency, and Rapid Response Simulation), York University, Toronto, Ontario, Canada.
  • Asgary A; ADERSIM (Advanced Disaster, Emergency, and Rapid Response Simulation), York University, Toronto, Ontario, Canada.
  • Merchant AA; University Health Network (UHN), Toronto, Ontario, Canada.
  • Shafiee MA; University Health Network (UHN), Toronto, Ontario, Canada.
  • Najafabadi MM; ADERSIM (Advanced Disaster, Emergency, and Rapid Response Simulation), York University, Toronto, Ontario, Canada.
  • Nadri N; ADERSIM (Advanced Disaster, Emergency, and Rapid Response Simulation), York University, Toronto, Ontario, Canada.
  • Aarabi M; University Health Network (UHN), Toronto, Ontario, Canada.
  • Heffernan J; Modelling Infection and Immunity Lab, York University, Toronto, Ontario, Canada.
  • Wu J; LIAM (Laboratory for Industrial and Applied Mathematics), York University, Toronto, Ontario, Canada.
PLoS One ; 16(11): e0259970, 2021.
Article em En | MEDLINE | ID: mdl-34797862
The COVID-19 pandemic has been particularly threatening to patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.
Assuntos

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Busca de Comunicante / Transmissão de Doença Infecciosa / COVID-19 / Unidades Hospitalares de Hemodiálise Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS One Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Busca de Comunicante / Transmissão de Doença Infecciosa / COVID-19 / Unidades Hospitalares de Hemodiálise Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: PLoS One Ano de publicação: 2021 Tipo de documento: Article