What does COVID‐19 testing results really say? The real statistics concealed behind the accessible data

Abstract

Accurate and comprehensive testing is crucial for practitioners to portray the pandemic. Without testing there is no data; yet, the exact number of infected people cannot be determined due to the lack of comprehensive testing. The number of seropositive for SARS‐CoV‐2 infection is obviously relative to the extent of testing. However, the true number of infections might be still far higher than the reported values. To compare the countries based on the number of seropositive for SARS‐CoV‐2 infection is misleading, as there may not be enough tests being carried out to properly monitor the outbreak. In this paper, we closely look through the COVID‐19 testing results. Herein, we try to draw conclusions based on the reported data: first, the presence of a possible relationship between COVID‐19 transition and patients' age will be assessed. Then, the COVID‐19 case fatality rate (CFR) is compared with the age‐demographic data for different countries. Based on the results, a method for estimating a lower bound (minimum) for the number of actual positive cases will be developed and validated. Results of this study have shown that CFR is a metric reflecting the spread of the virus, but is a factor of the extent of testing and does not necessarily show the real size of the outbreak. Moreover, no large difference in susceptibility by age has been found. The results suggest the similarity between the age distribution of COVID‐19 and the population age‐demographic is improving over the course of the pandemic. In addition, countries with lower CFRs have a more similar COVID‐19 age distribution, which is a result of more comprehensive testing. Finally, a method for estimation of the real number of infected people based on the age distributions, reported CFRs, and the extent of testing will be developed and validated.

Evolution of Responses to COVID-19 and Epidemiological Characteristics in South Korea

“…Unlike past pandemics that had higher mortality but lower morbidity in the elderly, the aging populations are at higher risk [ 45 ] of contracting COVID-19. Contrary to the claim [ 17 ] that susceptibility does not differ by age, furthermore, we found that the incidence rates relative to the population size of age groups manifest substantial variation (cf. Figure 7 ) as the epidemiology evolves, i.e., the susceptibility by age depends on specific signatures of mass infections and vaccination policies.…”

“…(That is, , , count the numbers in the i th period and j th age group, where we assigned indices j to age groups in the ascending order.) Then, the differences and of the infection distribution and the population distribution measures the relative prevalence of infection according to age groups [ 17 ]. Figure 7 shows these shares of confirmed cases relative to the populations size of age groups in each period.…”

“…The population distributions by region and age were calculated by the average of the monthly population data. We compared the differences in the distribution of confirmed cases, unlinked cases, and asymptomatic cases obtained from the sources [ 17 , 26 , 27 ].…”

“…Detailed epidemiolocal characteristics were highlighted in Hong Kong for the first and second waves [ 14 ], and in Europe and Italy from January to December 2020 [ 15 ]. Age-specific confirmed cases of COVID-19 in Italy, South Korea, Spain, and the USA were compared [ 16 , 17 ], and age-dependent behaviors such as mask wearing, handwashing, physical distancing, crowd and restaurant avoidance, and cancellation of social activities were investigated [ 18 ].…”

Corrigendum

“…What does COVID‐19 testing results really say? The real statistics concealed behind the accessible data 1 …”