Open AccessModelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices
Author(s) -
Mohammadali Tofighi,
Ali Asgary,
Asad A. Merchant,
Mohammad Shafiee,
Mahdi M. Najafabadi,
Nazanin Nadri,
Mahmoud Aarabi,
Jane M. Heffernan,
Jianhong Wu
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0259970
Subject(s) - dialysis , hemodialysis , pandemic , transmission (telecommunications) , scale (ratio) , covid-19 , renal replacement therapy , end stage renal disease , intensive care medicine , medicine , disease transmission , computer science , outbreak , simulation , disease , virology , infectious disease (medical specialty) , physics , telecommunications , quantum mechanics
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.