Month: January 2022

There is still no widely accepted theory to explain why one wave triggered by a variant of SARS-CoV-2 has different dynamics than any other, or even why each wave should only have just a single peak.

We continue our comparison of the hospitalization curves for the Delta and Omicron waves in Florida, this time adding the curve for the Alpha wave that began in early October 2020 and peaked in the first half of January 2021.

While statewide daily hospital admissions initially accelerated much more rapidly during the current Omicron wave, the curve now appears to have peaked at about 2,200 on January 12 , just below the high point seen during this past summer’s Delta wave. Since then, Omicron hospital admissions appear to be trending downward.

Empirical Curve-Fitting

While the three curves are distinct, they do share two common features. First, they all appear to reach a single peak. Second, the faster is the acceleration phase leading up to the peak, the faster is the deceleration phase after the peak.

Based upon these observed regularities, many commentators anticipate that the Omicron wave in the U.S. will be over soon, and some have gone so far as to predict that Omicron will be the beginning of the endgame.

The main problem with these forecasts is that they are basically exercises in empirical curve-fitting. They are not derived from a widely accepted, rigorously verified theory of the epidemic waves of SARS-CoV-2. If case counts rose up and then came down last time, so the logic goes, they’ll presumably do it again, even if we don’t really know why.

SIR and Other Compartmental Models: Do They Fit the Facts?

Far and away the leading theory has been the SIR model and its numerous variations. We have been as guilty of applying this model to data on COVID-19 cases as anyone else.

The basic idea is to divide the population conceptually into compartments, such as Susceptible, Infected, and Resistant. When Susceptible people get infected, they move from the S to the I compartment, and when they recover (or die), they transition to the R compartment. What makes the epidemic curve peak and come down is the depletion of the S compartment.

The idea behind the SIR and other compartmental models, in the most fundamental terms, is that the wave subsides because the virus has run out of new susceptible people to infect.

But We Don’t Have a Closed Population.

The SIR and similar compartmental models do appear to work well when they are applied to data from isolated outbreaks in well-defined, closed populations. If our susceptible group is all the students in a university residence hall, then it makes to think about the numbers of resident students who have been infected or remain susceptible.

The problem with the application of these compartmental models to the SARS-CoV-2 global pandemic is that we’re not really dealing with closed populations. The idea that we’re somehow running out of susceptible individuals doesn’t comfortably fit the facts.

And Then There’s the Problem of Immune Escape.

What’s more, it’s become abundantly clear that the resistant people supposedly filling up the R compartment aren’t really resistant (unless they’re dead). To the contrary, they’re getting reinfected. The phenomenon of immune escape, it has now become apparent, is a fundamental characteristic of SARS-CoV-2 and other coronaviruses.

Network-Percolation Models as an Alternative

Rather than think about a closed population of susceptible, infected and resistant individuals, a better approach is to conceptualize a network.

Let’s travel back in time to March 2020, when cases first began to surge in New York City, a hub that rapidly became the epicenter of COVID-19 in the Western hemisphere. There is now substantial accumulated evidence that SARS-CoV-2 was initially propagated throughout the city via its extensive public transportation network. The New York City subways, in particular, formed an interconnected system more than 10 times larger than the next largest subway system in the U.S.

Once the virus had been dispersed throughout the 8-million-person metropolis, the evidence suggests, infections began to concentrate in specific hot spots such as the Elmhurst neighborhood of Queens, a phenomenon known as percolation.

The idea is that the initial upswing of an epidemic wave corresponds to the initial diffusion of the infectious agent throughout the network, while the peaking of cases and the reversal of the curve reflect subsequent percolation processes.

Ultimately, within the local branch of the network in the Elmhurst-Queens hot spot in New York City, the virus began to run out of susceptible cases to infect.

Partly Open, Partly Closed Populations

We need to abandon the fiction that populations are closed and begin to think about communities that are partly open and partly closed. Later on , in the fall of 2020, then-New York State Governor Cuomo, faced with a new COVID-19 outbreak in South Brooklyn, imposed graded restrictions on access to restaurants and other establishments in three concentric zones: red, orange, and yellow. Observing movements of mobile devices over a 3-week period, we found that slightly more than half of red-zone residents stayed within their zone, while nearly a quarter moved out of the regulated three-zone area entirely. The governor’s scheme ultimately failed in great part because some neighborhoods within the red zone continued to serve as foci for increased transmission in the orange and yellow zones as well.

Don’t Be Surprised by a Double Peak.

The Omicron wave indeed seems to have peaked in many places in the U.S., and the trend in Florida hospitalizations, shown above, so far does not seem to be an exception. But the reality is that we know relatively little about the dynamics underlying successive waves of SARS-CoV-2 and its numerous variants. We should not be surprised if we encounter a double peak.

We will continue to follow the Omicron wave in Florida

Technical Notes

The calculations in the figure are derived from COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries, maintained by the U.S. Department of Health and Human Services. The daily counts represent the daily sums of two variables for all Florida hospitals combined:

• previous_day_admission_adult_covid_confirmed: Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
• previous_day_admission_pediatric_covid_confirmed: Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state

Scattered reports have suggested that as many as one-half of all hospital inpatients identified as COVID-positive are incidental cases who were admitted primarily for reasons other than their viral infections. In a nationwide cohort of 250 hospitals located in 164 counties throughout the U.S., we have estimated that only 15 percent of COVID-positive hospitalizations are incidental.

Incidental COVID infections appear to be a nontrivial fraction of all COVID-positive hospitalized patients. In the aggregate, however, the burden of patients admitted for complications of their viral infections appears to be far greater.

New Pre-Print Posted on MedRxiv.

Scattered reports have suggested that as many as one-half of all hospital inpatients identified as COVID-positive are incidental cases who were admitted primarily for reasons other than their viral infections. To date, however, there are no systematic studies of a representative panel of hospitals based on pre-established criteria for determining whether an individual patient was in fact admitted as a result of the disease. To fill this gap, we developed a formula to estimate the fraction of incidental COVID hospitalizations that relies upon measurable, population-based parameters.

Among COVID-positive hospitalized patients, 15.2% were estimated to be incidental infections. Across individual counties, the median fraction of incidental COVID hospitalizations was 13.7%, with an interquartile range of 9.5 to 18.4%

There is still no widely accepted theory that explains why a wave triggered by a new variant of SARS-CoV-2 should have only a single peak.

We further update our ongoing comparison of the hospitalization curves for the Delta and Omicron waves in Florida. While statewide daily hospital admissions accelerated much more rapidly during the current Omicron wave, the Omicron curve appears to have reached a peak and may be trending downward.

Admissions appear to have peaked at about 2,200 on January 12 , just below the high point seen during this past summer’s Delta wave.

We stress that this is purely an empirical observation. There is no widely accepted theory that explains why a wave of infections triggered by the emergence of a new variant of SARS-CoV-2 should have only a single peak.

We will continue monitor trends in Florida COVID-19 hospital admissions.

Technical Notes

As we’ve repeatedly noted, we do not have data on the variant underlying each hospital admission. Still, according to the most recent CDC report on state-specific variant proportions, 99.7% of recent SARS-CoV-2 samples sequenced in the U.S. region covering Florida were attributable to the Omicron variant.

We have estimated the initial appearance of the Delta variant as June 10, 2021. There are reports that the variant was in fact detected by late May. If we translated the time axis for Delta to the right, however, the Omicron-related hospitalization curve would be running even further ahead of its predecessor.

The calculations in the figure are derived from COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries, maintained by the U.S. Department of Health and Human Services. The daily counts represent the daily sums of two variables for all Florida hospitals combined:

• previous_day_admission_adult_covid_confirmed: Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
• previous_day_admission_pediatric_covid_confirmed: Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state

Some commentators have expressed a general concern that COVID-19 hospitalization counts include patients admitted for unrelated reasons who incidentally tested positive. We are now preparing an article on this important issue.

Statewide admissions are now hovering at about 2,150 per day, just below the high point seen during this past summer’s Delta wave.

We further update our ongoing comparison of the hospitalization curves for the Delta and Omicron waves in Florida. While daily hospital admissions have accelerated much more rapidly during the current Omicron wave, the Omicron curve appears to be decelerating.

We will continue monitor trends in Florida COVID-19 hospital admissions.

Technical Notes

As we’ve repeatedly noted, we do not have data on the variant underlying each hospital admission. Still, according to the most recent CDC report on state-specific variant proportions, 99.0% of recent SARS-CoV-2 samples sequenced in the U.S. region covering Florida were attributable to the Omicron variant.

We have estimated the initial appearance of the Delta variant as June 10, 2021. There are reports that the variant was in fact detected by late May. If we translated the time axis for Delta to the right, however, the Omicron-related hospitalization curve would be running even further ahead of its predecessor.

The calculations in the figure are derived from COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries, maintained by the U.S. Department of Health and Human Services. The daily counts represent the daily sums of two variables for all Florida hospitals combined:

• previous_day_admission_adult_covid_confirmed: Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
• previous_day_admission_pediatric_covid_confirmed: Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state

Some commentators have expressed a general concern that COVID-19 hospitalization counts include patients admitted for unrelated reasons who incidentally tested positive. We will have more to say about the issue of incidental COVID-19 hospitalizations in a future article.

Hospital ED visits for COVID-19 are a more informative indicator of disease burden than total reported cases.

The above animation shows the evolution of emergency department visits for COVID-19 during five successive weeks, from the week ending 12/3/21 to the week ending 12/31/21. Each data point represents one hospital, and its size reflects the number of reported ED visits.

The map above is an annotated version of the last frame of the animation, corresponding to ED visit for COVID-19 during week ending 12/31/21. Specifically indicated are the five hospitals with the highest number of ED visits.

Hospital ED visits for COVID-19 approached 75,000 during the week ending 12/31/21, overtaking the Delta peak of 62,100 during the week ending 8/13/21.

The graph above charts ED visits to Florida hospitals for COVID-19 for each week from the week ending 6/25/21 through the week ending 12/31/21. We see a marked surge during December with the emergence of the Omicron variant. The total volume of 74,660 ED visits for COVID-19 during the week ending 12/31/21 has surpassed the peak volume of 60,777 ED visits attained during the Delta wave of last summer.

For every 100 ED visits for COVID-19, there are now 15 hospital admissions.

This graph shows the number of hospital admissions for COVID-19 per 100 ED visits for COVID-19. As discussed in an earlier article, we regard this ratio as one indicator of disease severity. While the week ending 12/31/21 saw 15.5 hospital admissions for COVID-19 per 100 ED visits, this indicator remains below the peak of 25.0 admissions per 100 ED visits seen for the week ending 8/13/21 during the Delta wave.

Why ED Visits Are a More Informative Indicator Than Total Reported COVID-19 Cases

The widespread use of home-based rapid tests has raised doubts about the adequacy of publicly reported case counts. There is a growing sentiment that we need new sentinel indicators of disease burden. Emergency department visits may be just the indicator we’re looking for.

When it comes to the detailed geography of COVID-19 spread throughout the state, our maps of hospital-specific ED visit volume are more informative than the coarse, county-based maps that are frequently posted.

What’s more, the under-reporting bias in case-based indicators of COVID-19 burden has become increasingly correlated with income. As the demand for rapid home-based tests expands in the face of a limited supply, the market price of a rapid tests rises. As the market price continues to rise, rapid tests become a luxury good. They are consumed disproportionately by higher income consumers. That means those areas with higher incomes will suffer from even more under-counting.

As an indicator of the evolution of Omicron in the state, ED visits for COVID-19 do have their own potential biases. Florida has a notably high concentration of uninsured individuals, who may preferentially seek the ED simply to get tested. Large hospitals with emergency departments may serve wide geographic areas. Residents from outside Orange County may travel to the two Orlando-based hospital EDs identified in our map.

Still, emergency department visits quite likely track cases of Omicron infection that are more severe than the self-limited syndrome of sore throat, stuff nose, headache, fever, chills, body aches and fatigue. At the very least, they capture patients who are more seriously concerned about their symptoms.

Technical Notes

The data were derived from COVID-19 Reported Patient Impact and Hospital Capacity by Facility, posted by the U.S. Department of Health and Human Services (HHS). The database is updated weekly. The most recent update, on which this article is based, covers the week ending 12/31/21. An obvious disadvantage of this data source is the 11-day lag between the end of the reporting period and the date of posting.

The data on emergency department visits for COVID-19 are based upon the variable previous_day_covid_ED_visits_7_day_sum, defined as “Sum of total number of ED visits who were seen on the previous calendar day who had a visit related to COVID-19 (meets suspected or confirmed definition or presents for COVID diagnostic testing – do not count patients who present for pre-procedure screening) reported in 7-day period.”

We calculated hospital admissions for COVID-19 as the sum of two variables:

• previous_day_admission_adult_covid_confirmed_7_day_sum, defined as “Sum of number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission reported in the 7-day period.”
• previous_day_admission_pediatric_covid_confirmed_7_day_sum, defined as “Sum of number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission.”

Both of these definitions are confined to admitted patients who were diagnosed with confirmed COVID-19 at the time of admission, and thus tend to attenuate the potential problem of so-called incidental admissions.

The maps were based upon the geocodes (longitude and latitude) of each hospital, which were already included in the HHS database. We relied on the Texas A&M interactive geocoding website to fill in the missing geocodes for 18 hospitals. The size of each point was based upon the weighting scheme built into the Stata scatter command.

Nearly one in four hospital beds is now located in a hospital reporting a critical staffing shortage.

This post continues to update our earlier summary of trends in U.S. hospital staffing. During the Delta wave in the United States, the percentage of hospitals reporting critical staffing shortages rose from 12 to 19 percent. Even as hospital admission rates declined in October and November, the critical staffing percentage remained elevated at 19 percent. Over the past four weeks, as the Omicron variant has begun to spread, this percentage has increased to 23.2 percent.

To determine each data point in the figure, we first ascertained the percentage of hospitals in each state reporting a critical staffing shortage, as reported by the Department of Health and Human Services. We then computed the weighted average across all states, where the weights were each state’s inpatient bed capacity. During the week ending January 7, 2022, we’ve thus calculated that 23.2 percent of all U.S. hospital beds were located in a hospital reporting a critical staffing shortage.

Trends Vary Across States: New Mexico and Rhode Island

Trends in staffing shortages vary across states. Below we plot the percentage of hospitals with critical staffing shortages in two of the hardest hit states: New Mexico and Rhode Island.

The critical staffing shortage percentage in New Mexico has increased steadily from 24.9 during the week ending May 28 to 52.3 during the most recent reporting week ending January 7. By contrast, the proportion of Rhode Island hospitals with a critical staffing shortage shot up to about 50 percent with the emergence of the Delta wave in August and has remained at that level.

Vaccine Mandates are Unlikely to be the Primary Cause.

Some have contended that vaccine mandates are contributing to the emerging shortage of healthcare workers. But there is little concrete evidence to back up this contention. While a small minority of healthcare employees have chosen to leave their jobs, the vast majority have opted for vaccine protection. At large healthcare systems like Houston Methodist, Truman Medical Centers/University Health in Kansas City, the North Carolina hospital system, Advocate Aurora Health in Chicago, Mount Sinai Health System in New York, St. Claire Regional Medical Center in Kentucky, and Henry Ford Health System in Detroit, less than 1 percent of employees have had to be let go.

The Labor Market for Skilled Nursing Care was Already Tight.

Still others have pointed to the increasing fees charged by traveling nurses and nurse staffing agencies to compensate for growing vacancies among nurse employees. The plain fact, however, is that the tight labor market for hospital-based nursing care predated the COVID-19 pandemic. Annual turnover among hospital-based registered nurses was already up to 15.9% in 2019 and increased to 18.7% in 2020.

It’s All About Pandemic Burnout.

Far and away the most critical determinant of rising staff shortages has been burnout and peritraumatic stress among healthcare workers, with more nurses leaving their employment as the pandemic drags on. While burnout among frontline healthcare workers has always been a serious problem, the percent of surveyed hospitals reporting 10% or more vacancies for RNs abruptly rose from 23.7% in 2019 to 31.8% in 2020 to 35.8% by early 2021.

The evidence of burnout among frontline workers is overwhelming not only in the U.S., but many other healthcare systems, including China during the initial Wuhan outbreak. The president of the American Nurses Association recently asked the U.S. Secretary of Health and Human Services to declare a national nursing shortage crisis. A national strategy to address healthcare worker burnout as been repeatedly urged.

We’re talking about continuous exposure to traumatic stress from extended hours, time away from family, near-continuous use of personal protective equipment, fear of personally contracting COVID-19, loss of patients with whom workers have become emotionally attached, and the rising frequency of medical errors as emergency rooms and ICUs fill up. We’re talking not only about ordinary job burnout, but also compassion burnout.

The anti-vaccination movement is driven in part by conspiracy theories that sow doubt about the integrity of medical professionals. Has the resulting loss of confidence caused some healthcare workers to experience a disconnect from their beliefs in the value of their work?

Stay Tuned.

We will continue to follow the aggregate U.S. hospital staffing situation as the Omicron wave plays out.

Daily admissions to Florida hospitals for confirmed adult and pediatric cases continue to double every 6.7 days, now at nearly three times the daily admissions registered at the same point during this past summer’s Delta wave.

We further update our comparison of the hospitalization curves for the Delta and Omicron waves in Florida. By day 15 from the initial appearance of each variant, statewide confirmed COVID-19 admissions among adults and children combined were running at about 250 per day. By day 36, however, Delta-wave admissions were 734, while Omicron-wave admissions have reached 2009. That’s nearly three times the number of admissions registered at the same point during this past summer’s wave.

Omicron-Related Hospitalizations Continue to Double Every 6.7 Days

Log-linear regressions on the data points from days 10 to 34 now give doubling times of 20.6 days for Delta and 6.72 days for Omicron. (The 95% confidence interval for the Omicron doubling time is 6.28 – 7.27 days.) As we have repeatedly stressed, these early findings do not necessarily mean that the Omicron curve will reach the Delta peak of 2,360 statewide hospital admissions attained on August 17, 2021 (that is, day 68 from initial appearance).

Hospitalization Rates Matter.

Public officials and some commentators have noted that COVID-19 hospitalization rates are not rising nearly so fast as total case counts. The fact that hospitalization-to-case ratios are now lower than during the past summer’s wave has been highlighted as favorable news. With rapid home-based COVID-19 tests now in abundance, it is unclear what case counts reported by public health departments are supposed to represent.

We continue to focus here on severe disease and its impact on our already stressed healthcare system.

Technical Notes

As we’ve repeatedly noted, we do not have data on the variant underlying each hospital admission. Still, according to the most recent CDC report on state-specific variant proportions, 82.4% of recent SARS-CoV-2 samples sequenced in the U.S. region covering Florida were attributable to the Omicron variant.

We have estimated the initial appearance of the Delta variant as June 10, 2021. There are reports that the variant was in fact detected by late May. If we translated the time axis for Delta to the right, however, the Omicron-related hospitalization curve would be running even further ahead of its predecessor.

The calculations in the figure are derived from COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries, maintained by the U.S. Department of Health and Human Services. The daily counts represent the daily sums of two variables for all Florida hospitals combined:

• previous_day_admission_adult_covid_confirmed: Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
• previous_day_admission_pediatric_covid_confirmed: Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state

Some commentators have expressed a general concern that COVID-19 hospitalization counts include patients admitted for unrelated reasons who incidentally tested positive. Since confirmation of a COVID-19 diagnosis is made by PCR test results that are not immediately available at the time of admission, it is unlikely that the calculations in our figure above suffer from such a potential bias.

We will have more to say about the issue of incidental COVID-19 hospitalizations in a future article.

Daily admissions to Florida hospitals for confirmed adult and pediatric cases continue to double every 6.7 days.

We further update our comparison of the hospitalization curves for the Delta and Omicron waves in Florida. By day 15 from the initial appearance of each variant, statewide confirmed COVID-19 admissions among adults and children combined were running at about 250 per day. By day 34, however, Delta-wave admissions were 672, while Omicron-wave admissions have reached 1620. That’s nearly 2.5 time the number of admissions registered at the same point during this past summer’s wave.

Omicron-Related Hospitalizations Now Doubling Every 6.7 Days

Log-linear regressions on the data points from days 10 to 34 now give doubling times of 20.6 days for Delta and 6.71 days for Omicron. (The 95% confidence interval for the Omicron doubling time is 6.21 – 7.33 days.) As we have repeatedly stressed, these early findings do not necessarily mean that the Omicron curve will reach the Delta peak of 2,360 statewide hospital admissions attained on August 17, 2021 (that is, day 68 from initial appearance).

Hospitalization Rates Matter.

Public officials and some commentators have noted that COVID-19 hospitalization rates are not rising nearly so fast as total case counts. The fact that hospitalization-to-case ratios are now lower than during the past summer’s wave has been highlighted as favorable news. With rapid home-based COVID-19 tests now in abundance, it is unclear what case counts reported by public health departments are supposed to represent.

We continue to focus here on severe disease and its impact on our already stressed healthcare system.

Technical Notes

As we’ve repeatedly noted, we do not have data on the variant underlying each hospital admission. Still, according to the most recent CDC report on state-specific variant proportions, 82.4% of recent SARS-CoV-2 samples sequenced in the U.S. region covering Florida were attributable to the Omicron variant.

We have estimated the initial appearance of the Delta variant as June 10, 2021. There are reports that the variant was in fact detected by late May. If we translated the time axis for Delta to the right, however, the Omicron-related hospitalization curve would be running even further ahead of its predecessor.

The calculations in the figure are derived from COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries, maintained by the U.S. Department of Health and Human Services. The daily counts represent the daily sums of two variables for all Florida hospitals combined:

• previous_day_admission_adult_covid_confirmed: Number of patients who were admitted to an adult inpatient bed on the previous calendar day who had confirmed COVID-19 at the time of admission in this state
• previous_day_admission_pediatric_covid_confirmed: Number of pediatric patients who were admitted to an inpatient bed, including NICU, PICU, newborn, and nursery, on the previous calendar day who had confirmed COVID-19 at the time of admission in this state

Some commentators have expressed a general concern that COVID-19 hospitalization counts include patients admitted for unrelated reasons who incidentally tested positive. Since confirmation of a COVID-19 diagnosis is made by PCR test results that are not immediately available at the time of admission, it is unlikely that the calculations in our figure above suffer from such a potential bias.

If hospitals were backdating COVID-19 diagnoses to the date of admission once they received one- or two-day delayed PCR results, we would detect significant backdating through comparison of serially posted databases. During the past 10 days, we estimate that such backdating accounted for less than 4 percent of all admissions.