Prepared by the Colorado COVID-19 Modeling Group
Colorado School of Public Health: Andrea Buchwald, Elizabeth Carlton, Debashis Ghosh, Irina Kasarskis, Jonathan Samet, Laura Timm, Emily Wu; University of Colorado School of Medicine: Kathryn Colborn; University of Colorado-Boulder Department of Applied Mathematics: Sabina Altus, David Bortz; University of Colorado-Denver: jimi adams; Colorado State University: Jude Bayham
For Contact: Jon.Samet@CUAnschutz.edu
Key messages in this report are:
COVID-19 hospitalizations and estimated new infections are decreasing in 9 regions, and increasing in 2 of 11 LPHA regions.
Infections are estimated to be increasing in the Central Mountains and West Central Partnership regions.
We estimate more than 1 in 100 people are infectious in South Central, Southeast and West Central Partnership Regions. Contacts are particularly risk in these regions. These estimates are for January 25th.
The estimated effective reproductive number varies significantly by region. Most indicate declining infections. Due to lags between infection and hospitalization, these estimates capture transmission through approximately January 12th.
Lags in reporting COVID-19 hospitalizations may be contributing to apparent steep declines in hospitalizations in some regions, leading to an artificially low estimated effective reproductive number. In the Central, East Central, San Luis Valley and Southwest LPHA regions, the estimated reproductive number has declined dramatically this week compared to last week. This may be due to lags in reporting hospital data.
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 8 selected counties 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.
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|
|Central||0.5||Decreasing||301||1 in 332||126,000||15.5|
|Central Mountains||1.2||Increasing||617||1 in 162||19,700||10.8|
|East Central||0.3||Decreasing||958||1 in 104||21,700||50.4|
|Metro||0.8||Decreasing||609||1 in 164||758,000||23.0|
|Northeast||0.9||Decreasing||866||1 in 115||206,000||26.9|
|Northwest||0.6||Decreasing||614||1 in 163||32,700||16.1|
|San Luis Valley||0.7||Decreasing||599||1 in 167||7,990||17.2|
|South Central||0.7||Decreasing||1,214||1 in 82||82,300||33.8|
|Southeast||0.9||Decreasing||2,033||1 in 49||17,600||37.6|
|Southwest||0.4||Decreasing||349||1 in 287||12,600||12.4|
|West Central Partnership||1.4||Increasing||1,119||1 in 89||11,200||10.5|
|Eight select counties|
|Adams||0.6||Decreasing||743||1 in 135||193,000||36.6|
|Arapahoe||0.8||Decreasing||864||1 in 116||180,000||27.0|
|Boulder||0.4||Decreasing||256||1 in 391||44,100||13.3|
|Broomfield||0.8||Decreasing||347||1 in 288||8,490||11.7|
|Denver||0.8||Decreasing||931||1 in 107||253,000||34.3|
|Douglas||0.9||Decreasing||626||1 in 160||43,900||12.4|
|El Paso||0.4||Decreasing||304||1 in 329||127,000||17.2|
|Jefferson plus||0.4||Decreasing||197||1 in 508||68,000||11.3|
|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.|
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 01/12/2021.
Figure 1. The estimated effective reproductive number (Re) over time in the 11 LPHA regions in Colorado, and 8 selected counties and county clusters. Estimates shown using COVID-19 hospitalization data through 01/25/2021.
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 8 selected counties and county clusters (bottom). All prevalence values over 1,000 per 100,000 are shown in dark red. Prevalence values estimated up to 01/25/2021.
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 8 selected counties and county clusters (bottom). Exposed proportion values estimated up to 01/25/2021. Black dashed line indicates mean of Colorado (top) and selected counties (bottom).
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 8 selected counties and county clusters in Colorado over the past 12 weeks. Hospitalization data are from the COPHS hospital census data through 01/25/2021.