This online tool graphs projected Montana Health Region and county-level demand due to severe COVID-19 cases and estimates of hospital resource capacity available to address these demands, under various scenarios of social distancing. The charts show the expected healthcare resource needs at the projected date of peak demand for hospital beds, ICU beds, and ventilators. Graphs and charts for the projected population cumulatively infected through time and projected total deaths at given date in time are also displayed for each scenario and region.
Projections are based on the UMCPHR model, which was developed by a team at the University of Montana’s Center for Population Health Research (CPHR) and the Montana Department of Public Health and Human Services (MTDPHHS).
The modeling approach is tailored to Montana and is updated with Montana data as the disease continues to spread in the state. Our team uses a fundamental approach: the SEIR model. The basics of the models are intuitive: prior to infection, individuals are susceptible (S) and once exposed (E) and infected (I) they are contagious, whether symptomatic or asymptomatic; those infected may recover and become resistant (R) or become sufficiently ill to need hospitalization and possibly critical ICU care.
A key driver in the model is the reproductive number (Ro; “R-naught”) that refers to the number of new cases that arise from a single infectious person. The UMCPHR model uses an empirically-based Rt, i.e., the Rt on the date of the model run is based on actual case accrual from the dates prior. Beyond the date of the model run, the Rt is then projected linearly to an assumed reproductive number endpoint according to different social distancing scenarios (see Scenarios Diagram). The empirical Rt metric helps us in the following ways: (1) It helps us to understand how effective our measures have been at controlling the outbreak. (2) It helps provide us with information about whether we should increase or reduce restrictions. Tracking Rt during outbreaks, and for our local jurisdictions, can provide important information for decision-makers.
The UMCPHR model will continue to update daily as new data accumulates for Montana. In addition, we will continue to refine the model as we learn more about this novel disease, and particularly how it transmits and spreads through a rural state, such as Montana. There are other models that provide estimates for Montana (see model comparison tab). It is standard practice to compare projections from multiple, rigorous, independent, and scientifically-defensible modeling frameworks. Inter-model comparisons provide the best overall glimpse of the range of possibilities of resource needs and helps to corroborate exploratory results for what is a truly challenging modeling task.
Principal Modeler: Erin Landguth. Additional contributors: Erin Semmens, Nick Silverman, Ethan Walker, Curtis Noonan, Helen Russette, Casey Day, Zachary Holden, Allen Warren. MTDPPHS Advisors: Laura Williamson, Isaiah Reed.