Rising Hospital Census of Diagnosed or Suspected COVID-19 Patients, Orange County, California, April 1 – July 6, 2020

The graphic plots the combined number of beds in all Orange County, California hospitals that have been occupied by patients diagnosed with or suspected of having COVID-19 during each day from April 1 – July 6, 2020. These hospital daily census counts, depicted as green data points and measured on a logarithmic scale along the left-hand vertical axis, are reported by the California Open Data Portal. This state-issued data series appears to be more comprehensive than the series earlier reported by the local Orange County Health Care Agency and relied upon in Reopening Under COVID-19: What To Watch For.

Overlapping the hospital census data is a red connected line showing changes from March 1 onward in one particular dimension of the Google Mobility index, namely, the relative number of visits to retail stores and entertainment venues. This index, measured along the right-hand axis, is gauged as a percentage of the baseline level of activity, which is calculated in relation to the median value for the 5-week period from January 3 – February 6, 2020. For example, a value of –20 would correspond to a 20 percent decline compared to baseline. For other examples of the overlaying of social mobility indices on COVID-19 incidence and morbidity data, see Daily New COVID-19 Cases and Google Mobility Index of Retail Visits and Recreational Activity, Los Angeles County, March 1 – June 28, 2020, as well as Data From the COVID-19 Epidemic in Florida Suggest That Younger Cohorts Have Been Transmitting Their Infections to Less Socially Mobile Older Adults.

The Back Story

The story behind the trends shown in the graphic is a saga of public policy flip-flops. As the weather improved during the spring in Southern California, people from all over began flocking to beaches in Orange County, culminating in the arrival of an estimated 40 thousand beach goers at Newport Beach on the April 25-26 weekend. A few days later, on April 30, California Gov. Newsom ordered the county’s beaches closed. Two cities in the county sought preliminary injunctions in court to block the governor’s orders, but ultimately without success. Yet on May 23, the state government issued a variance to Orange County, permitting accelerated reopening of local businesses.

To enforce the state-issued variance, then County Health Officer Dr. Nicole Quick issued an order expanding the requirement for residents and visitors to wear face coverings in public places, in businesses such as retail stores, restaurants and hair salons, and at work when 6-foot distancing was infeasible. Quick’s order was apparently met with vociferous local disapproval, and on June 9, she resigned her post. On June 11, the County rescinded the mask requirement, converting it into a “strong recommendation.” Since then, the acting Health Officer’s orders have undergone several additional updates, most recently in a version issued July 3, which mandates the use of face coverings in certain high-risk situations enumerated by the California Department of Public Health, which in turn appear even more restrictive than Dr. Quick’s ill-fated order.

Non-Linearity

What is so striking about the graphic is the apparent acceleration in the COVID-19 hospital census starting in the week of June 21, but without a corresponding acceleration in the index of social mobility. Both diagnosed and suspected cases have been accelerating during this time period. So, the so-called suspected cases are, in all likelihood, no more than genuine cases with a delay in diagnostic confirmation. The rise in hospital census could in principle reflect increasingly delayed discharge of COVID-19 patients. But that would go against the general trend to send not-too-sick COVID-19 patients home earlier with portable oxygen, prophylactic anticoagulants, and a tapering dose of steroids.

We would ordinarily expect a delay between increases in social contact and consequent changes in hospitalization rates. Once an individual is infected, there will be an incubation period – about 5 days on average – followed by an additional week or so before the patient develops complications warranting hospital admission. Still, a lagged response does not alone explain the recent acceleration in the graphic.

The evidence here raises the possibility of non-linearity in the relation between social contact rates and disease incidence. In terms of the graphic above, once the frequency of visits to retail stores and entertainment venues reaches a threshold, transmission takes off. A model an infectious individual who can transmit the virus only to those within a certain radius would readily predict such non-linearity. A more interesting explanation is that younger individuals, having acquired their infections through increasingly lax compliance with social distancing measures, are now bringing their infections home to older, less mobile persons. And those elderly individuals are now ending up in the hospital.

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