Standardization and Age-Distribution of COVID-19: Implications for Variability in Case Fatality and Outbreak Identification
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Abstract
Background
Epidemiological data from the COVID-19 pandemic has demonstrated variability in attack rates by age, and country-to-country variability in case fatality ratio (CFR).
Objective
To use direct and indirect standardization for insights into the impact of age-specific under-reporting on between-country variability in CFR, and apparent size of COVID-19 epidemics.
Design
Post-hoc secondary data analysis (“case studies”), and mathematical modeling.
Setting
China, global.
Interventions
None.
Measurements
Data were extracted from a sentinel epidemiological study by the Chinese Center for Disease Control (CCDC) that describes attack rates and CFR for COVID-19 in China prior to February 12, 2020. Standardized morbidity ratios (SMR) were used to impute missing cases and adjust CFR. Age-specific attack rates and CFR were applied to different countries with differing age structures (Italy, Japan, Indonesia, and Egypt), in order to generate estimates for CFR, apparent epidemic size, and time to outbreak recognition for identical age-specific attack rates.
Results
SMR demonstrated that 50-70% of cases were likely missed during the Chinese epidemic. Adjustment for under-recognition of younger cases decreased CFR from 2.4% to 0.8% (assuming 50% case ascertainment in older individuals). Standardizing the Chinese epidemic to countries with older populations (Italy, and Japan) resulted in larger apparent epidemic sizes, higher CFR and earlier outbreak recognition. The opposite effect was demonstrated for countries with younger populations (Indonesia, and Egypt).
Limitations
Secondary data analysis based on a single country at an early stage of the COVID-19 pandemic, with no attempt to incorporate second order effects (ICU saturation) on CFR.
Conclusion
Direct and indirect standardization are simple tools that provide key insights into between-country variation in the apparent size and severity of COVID-19 epidemics.
Funding
The research was supported by a grant to DNF from the Canadian Institutes for Health Research (2019 COVID-19 rapid researching funding OV4-170360).
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SciScore for 10.1101/2020.04.09.20059832: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:A key limitation of this work is that much of the work focusses on an epidemic in a single country, at an early point in the COVID-19 pandemic. Indeed, the observable case-fatality in China now approximates 4%, rather than 2.4% as reported earlier, which is likely to reflect lags between clinical onset and death from COVID-19, especially …
SciScore for 10.1101/2020.04.09.20059832: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:A key limitation of this work is that much of the work focusses on an epidemic in a single country, at an early point in the COVID-19 pandemic. Indeed, the observable case-fatality in China now approximates 4%, rather than 2.4% as reported earlier, which is likely to reflect lags between clinical onset and death from COVID-19, especially in individuals who receive intensive care with mechanical ventilation. We have, furthermore, not attempted to incorporate second order effects, such as the resulting rapid saturation of ICU resources, with resultant upwards inflection in case fatality, in countries with older populations (e.g. Italy). Such effects may be operative in the devastating COVID- 19 epidemics in Western Europe, which have CFR well beyond what our standardization of the Chinese epidemic data would predict. In conclusion, we find that standardization, both direct and indirect, provides a simple, widely understood toolbox for explaining and understanding several of the unusual features of COVID-19, including under-representation of pediatric cases and geographic variability in apparent epidemic size and severity (measured as CFR). While we are living in frightening and emotionally charged times, we suggest that demographic variation, rather than misrepresentation (21, 22), is likely to explain much of the between-country variability seen in the current pandemic.
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.
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- No protocol registration statement was detected.
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