Analyzing How Changes in the Health Status of Healthcare Workers Affects Epidemic Outcomes

Open Access
Author:
Phadke, Ishan
Area of Honors:
Mathematics
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
  • Katriona Shea, Thesis Supervisor
  • Aissa Wade, Honors Advisor
Keywords:
  • quality of care
  • epidemic model
  • mathematical modeling
Abstract:
During a disease outbreak, healthcare professionals are essential to treat patients and prevent new cases. However, these healthcare professionals are themselves susceptible to contracting the disease. As more healthcare workers get infected, fewer are available to provide care for others, and the overall quality of care available to patients diminishes. This depletion of healthcare workers may contribute to the severity of the epidemic. To examine this decline in quality of care, we explicitly include a quality of care term in a differential equation-based SIRV model. We assume quality of care for a health force declines as the proportion of healthy healthcare workers declines. We analyze the resulting time series dynamics, cumulative cases and mortality during an outbreak. We assume that vaccination, recovery, and survival rates are impacted by the quality of care function. We compare 4 models: 1) a standard SIRV model, 2) an SIRV model with a separate class for healthcare workers, 3) an SIRV model where transitions are dependent on a quality of care function, and 4) an SIRV model with a separate class of healthcare workers and where transitions are dependent on a quality of care function. Quality of care is described by a function with two shape parameters: the loss impact parameter, which defines the negative impact on the quality of care arising from the loss of a single healthcare worker; and the redundancy parameter, which defines the number of healthcare workers that may be lost before collapse in the healthcare system. By comparing these models, we show that explicitly modelling healthcare workers and accounting for declining quality of care changes our predictions of epidemic outcomes. Our results show an increase in the number of individuals who get infected in both models that consider the quality of care function, with a greater increase occurring when healthcare workers are considered separately from the general population. The models also project larger epidemic outcomes when the healthcare system is fragile. This occurs when the loss impact parameter is high (i.e. each lost healthcare worker has a relatively large negative impact on the quality of care) and the redundancy parameter is low (i.e. when there is little built-in redundancy in the healthcare system). These differences between the models show the importance of including quality of care in epidemic models that include management techniques. As more notable differences were seen when healthcare workers were considered separately, our full model (IV) can likely best be used to inform health policy that may differ for healthcare workers and the general population. This may help to improve the choice of management interventions considered to mitigate the effects of a future outbreak.