Fig 1.
Exposure and progression dynamics.
CoPE is a bottom-up model of the way individuals interact with one another both in a social sphere and in a professional sphere. Professional sphere includes on-the-job essential interactions, as well as non-job essential interactions such as grocery shopping. These interactions therefore capture exposure dynamics that are sensitive to policy such as which occupation is designated as an essential service. This exposure generating model is overlaid on the compartmental model so that once exposed, individuals progress through the disease and behaviors change for both the infected and others along the way. Each agent in our model is a representative householder, whose demographic and location information is drawn from the joint distributions in the American Community Survey. This allows the researcher to get a granular understanding of the distributional equity among different demographic groups. In the epidemiological progression figure, S is susceptible, E is exposed, PA is pre-asymptomatic, PY is pre-symptomatic, IA is asymptomatic, IY is symptomatic, IH is hospitalized, R is recovered, and D is dead. For models details and parameter values refer to [71].
Fig 2.
Risk tolerance and protective behavior.
Agents with high risk tolerance are likely to continue to participate in the social sphere despite a shelter in place order. Agents start off with a “baseline” risk tolerance that is a decreasing function of age and update it over time as other agents in their social networks become symptomatic. In CoPE, a 25 percent non-compliance rate refers to the top 25 percent of agents who have a high tolerance to risk (rather than a random 25 percent of agents).
Fig 3.
Behavioral adaptation to SIP and disease.
How agents schedule their interactions is governed by a combination of the policy in effect, their individual risk tolerance, and the infection state of the agent and those in their social network at that time. When SIP is in effect, compliant individuals in essential occupations cease social interactions, and continue non-job essential interactions (as service providers). Compliant individuals in non-essential occupations cease on-the-job and social interactions but continue non-job essential interactions (as service seekers). Once individuals are infected and symptomatic, they cease all interactions.
Fig 4.
Visual summary of baseline and alternative SIP scenarios.
Fig 5.
Percentage change in hospitalizations in each individual scenario compared to the baseline scenario.
The y-axis on the left represents the percentage change in the percent hospitalized compared to the baseline scenario and corresponds to the orange dots in the plot. The y-axis on the right represents the percent change in peak hospitalization percent compared to the baseline scenario and corresponds to the blue dots in the plot. The black solid line along 0% represents the percentage of population hospitalized in the baseline scenario.
Fig 6.
Variation of total percent of population hospitalized under a range of SIP design configurations.
The three panels along the x-axis represent increasing level of SIP targeting, and the three panels along the y-axis represent increasing level of compliance. In each panel, the x-axis represents the incremental delay in timing of the SIP, and the y-axis represents the incremental increase in the duration of SIP. The variation in percentage of population hospitalized under each scenario is represented by the color gradient, where red indicates a lower percentage hospitalized and yellow indicates a higher percentage hospitalized. The black lines show the contours of equal percentage of hospitalization.
Fig 7.
Percent daily hospitalizations and proportion of daily hospitalizations by income in early and late timing scenarios.
Panels A and C show the percent of population hospitalized daily in the early and late scenarios respectively. The grey line shows the daily percentage and the solid black line shows a 7-day moving average. The solid-colored lines in Panels B and D show the proportion of daily hospitalized broken down by the agents’ income categories in early and late timing scenarios respectively. The dashed colored lines represent the base percent of population in each income category. When the solid line is above the dashed line for a particular income category on a particular day, it indicates a disproportionately higher proportion of hospitalizations faced by that income category on that day.