Severe underestimation of COVID-19 case numbers: effect of epidemic growth rate and test restrictions
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Abstract
To understand the scope and development of the COVID-19 pandemic, knowledge of the number of infected persons is essential. Often, the number of “confirmed cases”, which is based on positive RT-PCR test results, is regarded as a reasonable indicator. However, limited COVID-19 test capacities in many countries are restricting the amount of testing that can be done. This can lead to the implementation of testing policies that restrict access to COVID-19 tests, and to testing backlogs and delays. As a result, confirmed case numbers can be significantly lower than the actual number of infections, especially during rapid growth phases of the epidemic.
This study examines the quantitative relation between infections and reported confirmed case numbers for two different testing strategies, “limited” and “inclusive” testing, in relation to the growth rate of the epidemic. The results indicate that confirmed case numbers understate the actual number of infections substantially; during rapid growth phases where the daily growth rate can reach or exceed 30%, as has been seen in many countries, the confirmed case numbers under-report actual infections by up to 50 to 100-fold.
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SciScore for 10.1101/2020.04.13.20064220: (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:These include test backlogs, like reported delays of up to 10 days to get test results in California12; additional delays by requiring symptoms to be severe; and capacity-mandated limitations to who can be tested. Our results show that these factors alone can cause a 15-fold under-reporting of infections, compared to an “inclusive” …
SciScore for 10.1101/2020.04.13.20064220: (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:These include test backlogs, like reported delays of up to 10 days to get test results in California12; additional delays by requiring symptoms to be severe; and capacity-mandated limitations to who can be tested. Our results show that these factors alone can cause a 15-fold under-reporting of infections, compared to an “inclusive” testing strategy. To reduce substantial under-estimating of the severity of the COVID-19 epidemic, it is essential to (a) include as many potentially infected persons, and (b) to have adequate test capacity with fast turnaround times. The results of this study also show that under-reporting factors go down when government interventions take effect and reduce the growth rate of an epidemic. However, underreporting factors can still be substantial even at slower growth rates, especially if testing is limited to a subset of infected persons. Often, local testing bottlenecks can create this situation even if the stated policies are not overly restrictive. While the growth rate of the epidemic appears to be slowing down in many countries, which should reduce the under-reporting of infections to some extend, regional hot spots of growth remain; in these regions, under-reporting is likely to still be a larger problem. Increased test capacities, fast turnaround times, and inclusive testing policies will also be essential when attempts are made to gradually relax restrictions; otherwise, test and reporting delays could cause a substantial undetected growth ...
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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