COVID19 epidemic growth rates have declined since early March in U.S. regions with active hospitalized case surveillance
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Abstract
Introduction
Optimal pandemic monitoring and management requires unbiased and regionally specific estimates of disease incidence and epidemic growth.
Methods
I estimated growth rates and doubling times across a 22-week period of the SARS-COV-2 pandemic using hospital admissions incidence data collected through the US CDC COVID-NET surveillance program which operates in 98 U.S. counties located in 13 states. I cross validated the growth measures using mortality incidence data for the same regions and time periods.
Results
Between March 1 and August 8, 2020, two distinct waves of epidemic activity occurred. During the first wave in the COVID-NET monitoring regions, the harmonic mean of the maximum weekly growth rate was 534% (Median: 575; Range: 250 to 2250) and this maximum occurred in the second or third week of March in different regions. The harmonic mean of the minimum doubling time occurred with maximum growth rate and was 0.35 weeks (Median 0.36 weeks; Range: 0.22 to 0.55 weeks). The harmonic mean of the maximum incidence rate during the first wave of the epidemic was 8.5 hospital admissions per 100,000 people per week (Median: 9.2, Range: 4 to 40.5) and the peak of epidemic infection transmission associated with this maximum occurred on or before March 27, 2020 in eight of the 13 regions. Dividing the 22-week observed period into four intervals, the harmonic mean of the weekly hospitalization incidence rate was highest during the second interval (4.6 hospitalizations per week per 100,000), then fell during the third and fourth intervals. Growth rates declined from 101 percent per week in the first interval to 2.5 percent per week in the last. Doubling time have lengthened from 3/5 th of a week in the first interval to 12.5 weeks in the last. Period by period, the cumulative incidence has grown primarily in a linear mode. The mean cumulative incidence of hospitalizations on Aug 8 th , 2020 in the COVID-NET regions is 96 hospitalizations per 100,000. Regions which experienced the highest maximum weekly incidence rates or greatest cumulative incidence rates in the first wave, generally, but not uniformly, observed the lower incidence rates in the second wave. Growth measures calculated based on mortality incidence data corroborate these findings.
Conclusions
Declining epidemic growth rates of SARS-COV-2 infection appeared in early March in the first observations of nationwide hospital admissions surveillance program in multiple U.S. regions. A sizable fraction of the U.S. population may have been infected in a cryptic February epidemic acceleration phase. To more accurately monitor epidemic trends and inform pandemic mitigation planning going forward, the US CDC needs measures of epidemic disease incidence that better reflect clinical disease and account for large variations in case ascertainment strategies over time.
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SciScore for 10.1101/2020.08.19.20178228: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:(Table 4) The COVID-NET hospital admissions incidence data used in this study is has several limitations. Even though COVID-NET investigators used standard ascertainment methodology, the laboratory-based case definition did not require a compatible clinical syndrome nor physician’s diagnosis of COVID-19. Furthermore, testing …
SciScore for 10.1101/2020.08.19.20178228: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:(Table 4) The COVID-NET hospital admissions incidence data used in this study is has several limitations. Even though COVID-NET investigators used standard ascertainment methodology, the laboratory-based case definition did not require a compatible clinical syndrome nor physician’s diagnosis of COVID-19. Furthermore, testing for ascertain laboratory-positive SARS-COV-2 individuals has increased significantly across the observed epidemic period. The various ascertainment biases that affect COVID-NET data are unlikely to change the conclusions here as they would have likely progressively increased ascertainment and thus observed growth rates during the month of March. Before February 28th, the CDC’s SARS-CoV-2 persons-under-investigation criteria required both compatible symptoms and close contact with a known case or travel within a high-risk country.29 On February 28th, the CDC broadened the criteria to include severe febrile pulmonary disease without an alternative explanation and without a known exposure to SARS-COV-2.30 On March 8th, CDC expanded SARS-COV-2 testing priorities to include hospitalized patients and symptomatic high-risk individuals.31 The latest CDC guidance advises the testing for asymptomatic individuals who subjectively suspect exposure.4 More recently, many jurisdictions in the US, have promoted “testing-ondemand” for asymptomatic individuals for any reason without a medical evaluation.32 Changes in testing rates have a large impact on incidence rates.33 ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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