Study population and setting
The study’s primary data source was the number of COVID-19 cases requiring critical care in Wuhan during the period of January to February 2020. Also, the mortality risk by age (over/under 65 years) and co-morbidity (whether the patient had hypertension) was obtained from China CDC case reports. The authors used these data to calculate the probability that an individual in each of these risk groups needed critical care at the peak of the epidemic in Wuhan.
The authors then used data on the proportion of the population over 65 and/or with hypertension in the 30 most populous US cities to predict peak ICU bed requirements in these cities. The study also extracted data from situation reports from Chinese health authorities, including the daily number of confirmed, severe, and critical cases, as well as the number of deaths, in Wuhan and Guangzhou, from January to February.
Summary of Main Findings
The data from Wuhan and Guangzhou showed that even with strict lockdown measures, there was a delay between the start of these measures and the peak in hospitalised cases. Therefore, although these measures reduced the burden on healthcare, the burden in Wuhan in particular was still large. The authors predicted that depending on the US city, 2-5 per 10,000 adults would require critical care at the peak of a Wuhan-like epidemic. This number only differed slightly when taking into account differences in age structure (2.1-4.0 requiring critical care) versus differences in co-morbidity (2.6-4.9 requiring critical care). Since there are 2.8 ICU beds per 10,000 adults in the US, the authors concluded that healthcare capacity could be exceeded if a Wuhan-like outbreak were to occur in some of these cities.
This study was posted on a preprint server on March 13, 2020. At this time, about 500 cases were confirmed in the US daily, and stay-at-home orders were not in place in any states. It was therefore not possible at this early stage to predict ICU bed requirements conditional on lockdown, without extrapolating from other countries. By doing so, this study identified the need to increase healthcare capacity, even with strict physical distancing measures.
This study made one major assumption: that the risk of requiring critical care at the peak of an epidemic in a US city would be the same as in Wuhan, for a given risk group. A more common approach is to estimate many epidemiological quantities, such as the reproductive number, the average number of contacts between people of different ages, and the effectiveness of interventions. These estimates are then used in a model to project the number of cases or hospitalisations. Errors in each of these estimates are large at the start of an epidemic of an emerging infectious disease, and can compound to produce large errors in model predictions. Hence, most mechanistic models do not attempt to predict beyond a few weeks. This study circumvents the need to estimate many unknown quantities.
Epidemics in US cities could differ in many ways from the Wuhan epidemic. The major difference is the effectiveness of physical distancing measures. The authors argued that lockdown measures in the US were unlikely to be stricter than those in Wuhan, so their estimates of ICU bed requirements were likely to be conservative. Other potential differences include different interventions, different population densities, and different contact rates between age groups. Also, risk factors other than age and hypertension were not considered. Together, these could make a large difference to ICU bed requirements. The authors also did not consider differences in ICU capacity between US cities.
The pandemic has progressed vastly since this manuscript; we now have data on the lockdown measures introduced in each city, and the number of cases and hospitalizations since then. Researchers are thus in a much better position to use local data to estimate the parameters of transmission and predict healthcare burden, rather than extrapolating from other countries.
This study sounded an early warning on the potential of COVID-19 to overwhelm healthcare capacity, under conservative assumptions. It accounted for differences in the need for ICU care based on age and hypertension.