Predictions from standard epidemiological models of consequences of segregating and isolating vulnerable people into care facilities

Abstract

Objectives Since the declaration of the COVID-19 pandemic, many governments have imposed policies to reduce contacts between people who are presumed to be particularly vulnerable to dying from respiratory illnesses and the rest of the population. These policies typically address vulnerable individuals concentrated in centralized care facilities and entail limiting social contacts with visitors, staff members, and other care home residents. We use a standard epidemiological model to investigate the impact of such circumstances on the predicted infectious disease attack rates, for interacting robust and vulnerable populations. Methods We implement a general susceptible-infectious-recovered (SIR) compartmental model with two populations: robust and vulnerable. The key model parameters are the per-individual frequencies of within-group (robust-robust and vulnerable-vulnerable) and between-group (robust-vulnerable and vulnerable-robust) infectious-susceptible contacts and the recovery times of individuals in the two groups, which can be significantly longer for vulnerable people. Results Across a large range of possible model parameters including degrees of segregation versus intermingling of vulnerable and robust individuals, we find that concentrating the most vulnerable into centralized care facilities virtually always increases the infectious disease attack rate in the vulnerable group, without significant benefit to the robust group. Conclusions Isolated care homes of vulnerable residents are predicted to be the worst possible mixing circumstances for reducing harm in epidemic or pandemic conditions.

Viral Respiratory Epidemic Modeling of Societal Segregation Based on Vaccination Status

“…this paper, without any loss of generality. This implies that, by definition (since β = 1), the contact frequencies "c" in our model are conceptually for contacts that are of sufficiently close proximity and long duration that an infection is guaranteed to occur when a susceptible and an infectious person meet [7,8]. For a more contagious virus, more of an individual's contacts are long and close enough that transmission would be guaranteed, corresponding to higher and .…”

“…In this endeavour, there are advantages to working with the simplest possible but sufficiently realistic models [1,2], where one should exclude simple models that are not sufficiently realistic for the intended application, either because of their structure or because of incorrect assumptions about the underlying mechanisms. Following this approach, researchers have extended the foundational simple susceptible-infectious-recovered (SIR)-type model to explore diseases with birth and death dynamics, maternal-or vaccine-derived immunity, latency of infection, patterns of contact mixing between different societal groups, and so on [3][4][5][6][7], and to study the effect of isolating vulnerable individuals from the general population during a pandemic, in the absence of vaccination [8].…”

Viral respiratory epidemic modelling of societal segregation based on vaccination status

“…In this endeavour, there are advantages to working with simplest-possible but sufficiently realistic models [1,2], where one should exclude simple models that are not sufficiently realistic for the intended application, either because of their structure or because of incorrect assumptions about the underlying mechanisms. Following this approach, researchers have extended the foundational simple susceptible-infectious-recovered (SIR)-type model to explore diseases with birth and death dynamics, maternal-or vaccine-derived immunity, latency of infection, patterns of contact mixing between different societal groups, and so on [3][4][5][6][7], and to study the effect of isolating vulnerable individuals from the general population during a pandemic, in the absence of vaccination [8].…”