COVID-19 Regional Models for Colorado

Summary

Key messages in this report are:

• Infections are increasing in most of the state, but more slowly than last month. Contacts remain very risky in most areas, as infection prevalence (the percent of the population infectious) remains high.

• Infections are increasing in six Local Public Health Agency (LPHA) regions across the state, and flat or decreasing in 5 LPHA regions. The estimated effective reproductive number varies from 0.9 to 1.5. Infections are spreading most rapidly in the Central Mountains and Southeast regions.

• Infection prevalence is higher than it has ever been in most regions. More than 2 out of every 100 people are estimated to be infectious in the East Central, Northeast, South Central and Southwest LPHA regions.

• The data used for this report extend through November 30. Due to lags between infection and hospitalization, these estimates do not yet capture the impact of Thanksgiving holidays on the spread of infections.

Introduction

This report provides the results of epidemic models for regions of Colorado, using methods similar to that used for the state-level model. Estimates are presented for the 11 Local Public Health Agencies (LPHAs) regions in the state and for 7 counties within the Metro LPHA region with populations that are sufficiently large to allow for county-level estimates. The model results are subject to greater uncertainty than those for the entire state because there are fewer hospitalizations and cases in each region than in the state as a whole. Estimates are most uncertain for the regions with the smallest population size. We use the model as well as COVID-19 hospital and case data to generate three measures for each region. These measures can be used to gauge the current state of SARS-CoV-2 in each region.

• The effective reproduction number (Re) is a measure of how rapidly infections are spreading or declining in a region.

• Infection prevalence is an estimate of the portion of the population currently infected and capable of spreading infections. It can be used to gauge how risky contacts are.

• Percent of population recovered from infection to date is an approximation of the proportion of the population immune to SARS-CoV-2. As the immune population grows, due to immunity or infection, the spread of infection slows. We still do not know how long immunity lasts after infections with SARS-CoV-2.

Table 1. The estimated effective reproductive number, prevalence of infections and the percent of the population recovered to date by region. These metrics are estimated using hospitalization data from the Colorado COVID Patient Hospitalization Surveillance (COPHS) through 11/30/2020. In regions with smaller populations, reported cases are also used to generate these estimates.

	Are infections increasing or decreasing?		How many people are infectious?		How many people have been infected to date?
	Re	Infections are…	Prevalence per 100,000	People infectious	Cumulative Infections to Date	Proportion of population infected to date
LPHA Regions
Central	1.2	Increasing	1,297	1 in 77	55,200	6.8
Central Mountains	1.5	Increasing	778	1 in 129	13,200	7.2
East Central	1.1	Increasing	2,877	1 in 35	10,000	23.2
Metro	1.0	Flat	1,427	1 in 70	513,000	15.6
Northeast	1.1	Increasing	2,262	1 in 44	134,000	17.5
Northwest	0.9	Decreasing	1,020	1 in 98	15,600	7.7
San Luis Valley	0.9	Decreasing	785	1 in 127	3,680	7.9
South Central	1.0	Flat	3,607	1 in 28	40,900	16.8
Southeast	1.4	Increasing	6,819	1 in 15	8,110	17.3
Southwest	1.1	Increasing	750	1 in 133	4,480	4.4
West Central Partnership	1.0	Flat	1,122	1 in 89	7,070	6.6
Metro LPHA region counties
Adams	1.0	Flat	2,278	1 in 44	139,000	26.3
Arapahoe	1.2	Increasing	1,952	1 in 51	125,000	18.8
Boulder	1.2	Increasing	1,013	1 in 99	29,100	8.8
Broomfield	0.8	Decreasing	731	1 in 137	6,200	8.5
Denver	1.1	Increasing	2,282	1 in 44	189,000	25.6
Douglas	1.1	Increasing	675	1 in 148	24,500	6.9
Jefferson plus	1.0	Flat	783	1 in 128	40,200	6.7
Due to the small population sizes of Gilpin and Clear Creek counties, these counties are combined with Jefferson County. Jefferson County comprises 97% of the population in the Jefferson plus county cluster.
Due to lags between infection and hospitalization, the estimated effective reproductive number (Re) reflects the spread of infections approximately two weeks prior to the data of the last observed hospitalization.

Effective Reproductive Number

The figure below shows the estimated effective reproductive number for each region since March.

The effective reproduction number (Re) is a measure of how rapidly infections are spreading or declining in a region at a given point in time. When the effective reproductive number is below 1, infections are decreasing. When the effective reproductive number is above 1, infections are increasing.

The effective reproductive number is estimated using our age-structured SEIR model fit to hospitalization data. In the four LPHA regions with smaller populations, reported SARS-CoV-2 case data are also used (San Luis Valley, Southeast, Southwest, and West Central Partnership). Because we base our parameter estimates primarily on COVID-19 hospitalization data, and hospitalizations today generally reflect infections occurring approximately 13 days prior, our most recent estimates of the effective reproductive number likely reflect the spread of infections occurring on approximately 11/17/2020.

Figure 1. The estimated effective reproductive number (Re) over time in the 11 LPHA regions in Colorado, and 7 Metro LPHA region counties and county clusters. Estimates shown using COVID-19 hospitalization data through 11/30/2020.

Infection prevalence

Infection prevalence provides an estimate of the proportion of the population that is currently infected with SARS-CoV-2 and capable of spreading infections. At higher levels of infection prevalence, individuals are more likely to encounter infectious individuals among their contacts. Because many people experience no symptoms or mild symptoms of COVID-19, many infections are not identified by surveillance systems. The estimates we present here are intended to provide an approximation of all infections, including those not detected by the Colorado Electronic Disease Reporting System (CEDRS).

The figure below shows the estimated infection prevalence per 100,000 individuals for each region. These are estimated from SEIR models fit separately to each area’s reported data.

Figure 2. Estimated prevalence per 100,000 population for each of the 11 LPHA regions (top), plus the 7 Metro LPHA region counties and county clusters (bottom). All prevalence values over 1,000 per 100,000 are shown in dark red. Prevalence values estimated up to 11/30/2020.

The percent of the population recovered from infections to date

As more people develop immunity, due to vaccination or prior infection, the spread of infections slows because infectious individuals are less likely to encounter individuals that are not immune. At present, immunity to SARS-CoV-2 is incompletely understood and a vaccine is not yet available.

The figure below shows model-generated estimates of the percent of the population that has been infected and is now recovered to date for each region. This provides an estimate of the percent of the population that may be immune, although we still do not know how long immunity lasts after an infection. As a vaccine becomes available and our understanding of SARS-CoV-2 immunity changes, these estimates will be updated.

Figure 3. Estimated proportion of the population recovered to date for each of the 11 LPHA regions in Colorado (top) and each of the 7 Metro region counties and county clusters (bottom). Exposed proportion values estimated up to 11/30/2020. Black dashed line indicates mean of Colorado (top) and Metro Region (bottom).

COVID-19 hospitalizations

The figures below show the daily number of individuals hospitalized with COVID-19 from each region. Hospitalization data are from the COVID Patient Hospitalization Surveillance (COPHS) maintained by the Colorado Department of Public Health and the Environment (CDPHE). Each COVID-19 patient is assigned to a region based on their home zip code. COVID-19 hospitalizations are shown per 100,000 population to allow comparability across regions.

COVID-19 hospitalizations are a sensitive measure of SARS-CoV-2 transmission and are an important indicator of the severity of infections in a region. While many SARS-CoV-2 infections are not captured by state surveillance systems, we expect that almost all COVID-19 hospitalizations are identified.

Figure 4. The daily number of people hospitalized with COVID-19 per capita for the 11 LPHA regions and the 7 Metro LPHA region counties and county clusters in Colorado over the past 12 weeks. Hospitalization data are from the COPHS hospital census data through 11/30/2020.

Figure 5. The daily number of people hospitalized with COVID-19 hospitalizations per capita for the 11 LPHA regions and the 7 Metro LPHA region counties and county clusters in Colorado since the first case was reported in March 2020. Hospitalization data are from the COPHS hospital census data through 11/30/2020.

Technical Summary

Within the State of Colorado, as for other states, the spread of SARS-CoV-2 varies across the regions of the state, differing between urban and rural locations and resort and non-resort areas, for example. The modeling carried out by the Colorado COVID-19 Modeling Group was initiated at the state level providing a picture that does not give detail at the regional or county-level. Such detail is needed for public health planning and action, and many local public health agencies have asked for model simulations for their jurisdictions.

To provide the needed detail, the Modeling Group has developed regional -level models, using approaches similar to those for the overall Colorado model. The models are generated for the 11 local public health agency (LPHA) regions, which cover the full state and for counties in the Metro LPHA region. County-level estimation is possible in the Metro LPHA region due to the large population size of most counties. In providing the results for regions within Colorado, the model results are subject to greater uncertainty than those for the entire state because there are fewer hospitalizations and cases in each region than in the state as a whole. Estimates are most uncertain for the regions with the smallest population size. Additional details about the methods used to generate regional estimates are described in the Technical Summary, below.

Methods. We use data on COVID-19 hospitalizations and reported cases, and a mathematical model of SARS-CoV-2 transmission to estimate the current state of infections in each region. The approach follows that used for the state-wide model, adapted for the smaller population sizes of the LPHA regions and Denver metro counties. A full description of the model and estimation approaches are provided in the documentation, available here. Prior modeling reports and documentation can be found here. Briefly, the model is a deterministic age-structured susceptible, exposed, infected, recovered (SEIR) model. It has been parameterized to Colorado-specific data whenever possible - for example, the length of time a COVID-19 patient spends in the hospital varies by age and is based on data provided by Colorado hospitals. We use model fitting approaches to estimate the level of transmission control for each two-week period of the outbreak. Transmission control is estimated by fitting the model to hospitalization data for each region. In the four regions where population size is small (San Luis Valley, Southeast, Southwest, and West Central Partnership), we fit the model to reported case data, using information from the state-level model to infer the proportion of infections detected by state surveillance systems.

Data Sources: COVID-19 hospitalizations are obtained from COPHS reported through 12/04/2020. Due to lags in reporting, these data are cleaved 4 days prior such that hospitalizations through 11/30/2020 are used in modeling and shown in this report.

Case data are based on CEDRS through 12/05/2020. Due to lags in reporting, these data are cleaved ten days prior on 11/25/2020. Both data sources are provided by CDPHE.

Limitations: These estimates are based on the available data and the assumptions in the SEIR model. Assumptions in the model are based on Colorado data when available and the current scientific understanding of SARS-CoV-2, which is evolving rapidly. Estimated prevalence and the percent of the population recovered are sensitive to model assumptions, which include: the probability an infected individual will be symptomatic and require hospital care and the estimated length of hospital stay, which varies over time and by age. Estimates for the smallest regions are subject to greater uncertainty than larger regions and may experience greater variation from week to week due to the limited data available in these regions.

Region	Population	Counties
LPHA Regions
Central	810,420	Chaffee, El Paso, Lake, Park, Teller
Central Mountains	182,689	Eagle, Garfield, Grand, Pitkin, Summit
East Central	43,032	Cheyenne, Elbert, Kit Carson, Lincoln
Metro	3,291,794	Adams, Arapahoe, Boulder, Broomfield, Clear Creek, Denver, Douglas, Gilpin, Jefferson*
Northeast	765,265	Larimer, Logan, Morgan, Phillips, Sedgwick, Washington, Weld, Yuma
Northwest	203,301	Jackson, Mesa, Moffat, Rio Blanco, Routt
San Luis Valley	46,472	Alamosa, Conejos, Costilla, Rio Grande, Saguache
South Central	243,196	Custer, Fremont, Huerfano, Las Animas, Pueblo
Southeast	46,938	Baca, Bent, Crowley, Kiowa, Otero, Prowers
Southwest	102,154	Archuleta, Dolores, La Plata, Montezuma, San Juan
West Central Partnership	106,839	Delta, Gunnison, Hinsdale, Mineral, Montrose, Ouray, San Miguel
Metro LPHA region counties
Adams	528,857	Adams
Arapahoe	664,988	Arapahoe
Boulder	330,978	Boulder
Broomfield	72,827	Broomfield
Denver	737,854	Denver
Douglas	354,331	Douglas
Jefferson plus	601,959	Clear Creek, Gilpin, Jefferson

Table 2: Description of the regions used in this report, including the 11 LPHA Regions. Population estimates are based on 2020 US Census Projections provided by the Colorado Demography Office.

*Clear Creek, Gilpin Counties and Jefferson counties are modeled as a single unit due to the small population of Clear Creek (9,379 residents) and Gilpin (5,924 residents) – populations too small to allow for stable estimation.

Figure 6. Map showing the 11 LPHA regions and 7 Metro LPHA region counties and county clusters for which estimates were generated.

Figure 7. Comparison of daily active COVID-19 hospitalizations by data source.

*EMResource recently began including VA hospitals and other institutions that may not be captured in current COPHS data sources, potentially explaining the under estimation of total hospitalizations from COPHS.