Fig 1.
General framework of the calculation of the percentage of diagnosis.
(A) Processes involved in the calculation of the percentage of diagnosis: 1. Evaluation of the estimated cases using TtD and IFR, 2. Calculation of time correlation between reported cases, Ct, and reported deaths, dt, 3. Evaluation of the time between diagnosis and death (Diagnosis to Death DtD) by the maximum of correlation (country dependent), with DD as the Delay to Detection, and 4. Evaluation of percentage of diagnosis based on estimated cases and reported cases. (B) Standard evolution of casualties by COVID-19, from the onset of the symptoms to death; times to reported cases and deaths are shown. Time-lines in the figure are not proportional to real-time delays.
Table 1.
For each age group: Number of cases and deaths reported in South Korea on April 15, 2020; percentage of population, COVID-19 cases and deaths, and case fatality ratio.
Table 2.
Percentage of population by age group for the analyzed European countries.
Table 3.
Estimated relative CFR assuming these countries have the same CFR by age group as reported by South Korea on April 15, 2020 (see Table 1), and officially reported relative CFR on that date.
CFR of South Korea on April 15, 2020 was 2.16%. The officially reported CFR on that date for each country is indicated in parentheses. Source: European Center for Disease Prevention and Control.
Fig 2.
Correlation between reported cases and deaths.
(A) Number of cumulative reported cases, (B) Number of cumulative reported deaths and (C) Correlation between reported cumulative cases and reported cumulative deaths exploring different delays between diagnosis (reported) and death, for Germany (red), Spain (green), and Switzerland (blue). (D) Maximum correlation is marked with a red square for each country. 99% correlation interval can be seen with black bars.
Fig 3.
Reported cumulative number of deaths (black squares), reported cumulative number of cases (blue circles) and estimated number of cases calculated using Eq 1 (solid blue line). To compute 7-Days Diagnostic Rate a diagnosis-to-death time of 11 days is used. Its value is calculated using the latest available points. (A) Germany. (B) Switzerland. (C) Netherlands. (D) Spain.
Fig 4.
Delay-to-Detection Diagnostic Rate (DD-DR).
Reported cumulative number of deaths (black squares), reported cumulative number of cases (blue diamonds), and estimated number of cases calculated using Eq 1 (solid blue line). To compute Delay-to-Detection Diagnostic Rate the diagnostic to death time observed in Fig 2 is used. Its value is calculated using the latest available points. (A) Germany, DtD = 10 days. (B) Switzerland, DtD = 8 days. (C) Netherlands, DtD = 5 days. (D) Spain, DtD = 4 days.
Fig 5.
(A) 7-Days Diagnostic rate over time for Germany (red), Spain (green), and Switzerland (blue). (B) Delay-to-Detection Diagnostic Rate over time. Thick lines are derived from the Diagnosis-to-Death time observed in Fig 2. Shaded areas represent the limits considering error bars observed in Fig 2.
Fig 6.
Detection Delay (DD), 7-Day Detection Rate (7D-DR), Delay-to-Detection Diagnostic Rate (DD-DR), estimated cumulative cases, and estimated attack rate.
To interpret estimated cumulative cases and estimated attack rate we must take into account Detection Delay, because these are computed using the reported data. Data updated on April 20, 2020. Belgian data are biased due to reporting of unconfirmed death cases. On that date the shift was 48% [34].
Fig 7.
Schematics of the procedure to obtain incidence A14, recovered and estimated cases using Germany as an example.
Incidence of estimated cases (blue), contagious incidence (red), and total estimated recovered cases (green). Blue shaded area is the number of cases used to compute the estimated contagious incidence. To interpret final number of total cumulative cases, recovered cumulative cases and estimated attack rate we must take into account Detection Delay, because they are computed using the reported data. Similar figures for all countries are shown in S2 Fig in S1 File.
Fig 8.
Estimated recovered and active cases, and EPG.
is computed using the mean value for the last three days.EPG: Effective Potential Growth described in the text. To interpret table data we must take into account Detection Delay, because they are computed using the reported data. Data updated on April 20, 2020. *Belgian data are biased due to reporting of unconfirmed death cases. On that date the shift was 48% [34].
Fig 9.
Attack rate and EPG for several countries.
Temporal evolution of the attack rate per 105 inhabitants (left) and the corresponding EPG (right) for four European countries with different epidemiological dynamics.
Fig 10.
Evolution of the cumulative cases and the EPG.
Evolution of the cumulative cases and the EPG. (A) The reported cases in The Republic of Iran (green line) is shown in comparison with the expected dynamics (red line) and with the calculated EPG (black line). (B) Same for the synthetic data. (C) Zoom of B panel between days 400 and 450.
Fig 11.
Reported EPG vs estimated real EPG.
Several European countries in terms of the EPG computed using the reported data on the attack rate vs the EPG using our estimation of the real attack rate. The order of the different countries should be done from right to left (for the reported state of the index) and from top to bottom (for the estimated value of the index). We observe how the comparative situation of the different countries changes as of April 20, 2020. * Belgian data are biased due to reporting of unconfirmed death cases. On that date the shift was 48% [34].