COVID-19 Vaccination and Healthcare Demand

• Published in: Bulletin of mathematical biology Vol. 85; no. 5; p. 32
• Main Authors: Betti, Matthew I., Abouleish, Amira Hassan, Spofford, Victoria, Peddigrew, Cory, Diener, Alan, Heffernan, Jane M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-05-2023; Springer Nature B.V
• Subjects: Canada; Cell Biology; Coronaviruses; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; COVID-19 Vaccines; Demand; Epidemic models; Epidemiology; Health care; Health Services Needs and Demand; Humans; Immunization; Life Sciences; Mathematical and Computational Biology; Mathematical Concepts; Mathematical models; Mathematics; Mathematics and COVID-19; Mathematics and Statistics; Models, Biological; Modules; Pandemics - prevention & control; Pharmaceuticals; Public health; SARS-CoV-2; Special Issue: Mathematics and Covid-19; Vaccination; Canada; COVID-19; Healthcare demand; Vaccination; Public health mitigation
• ISSN: 0092-8240; 1522-9602
• DOI: 10.1007/s11538-023-01130-x

One of the driving concerns during any epidemic is the strain on the healthcare system. As we have seen many times over the globe with the COVID-19 pandemic, hospitals and ICUs can quickly become overwhelmed by cases. While strict periods of public health mitigation have certainly helped decrease incidence and thus healthcare demand, vaccination is the only clear long-term solution. In this paper, we develop a two-module model to forecast the effects of relaxation of non-pharmaceutical intervention and vaccine uptake on daily incidence, and the cascade effects on healthcare demand. The first module is a simple epidemiological model which incorporates non-pharmaceutical intervention, the relaxation of such measures and vaccination campaigns to predict caseloads into the Fall of 2021. This module is then fed into a healthcare module which can forecast the number of doctor visits, the number of occupied hospital beds, number of occupied ICU beds and any excess demand of these. From this module, we can also estimate the length of stay of individuals in ICU. For model verification and forecasting, we use the four most populous Canadian provinces as a case study.