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. 2020 Jun 2:5:117.
doi: 10.12688/wellcomeopenres.15996.1. eCollection 2020.

Assessing the age- and gender-dependence of the severity and case fatality rates of COVID-19 disease in Spain

Affiliations

Assessing the age- and gender-dependence of the severity and case fatality rates of COVID-19 disease in Spain

Paula Moraga et al. Wellcome Open Res. .

Abstract

Background: The assessment of the severity and case fatality rates of coronavirus disease 2019 (COVID-19) and the determinants of its variation is essential for planning health resources and responding to the pandemic. The interpretation of case fatality rates (CFRs) remains a challenge due to different biases associated with surveillance and reporting. For example, rates may be affected by preferential ascertainment of severe cases and time delay from disease onset to death. Using data from Spain, we demonstrate how some of these biases may be corrected when estimating severity and case fatality rates by age group and gender, and identify issues that may affect the correct interpretation of the results. Methods: Crude CFRs are estimated by dividing the total number of deaths by the total number of confirmed cases. CFRs adjusted for preferential ascertainment of severe cases are obtained by assuming a uniform attack rate in all population groups, and using demography-adjusted under-ascertainment rates. CFRs adjusted for the delay between disease onset and death are estimated by using as denominator the number of cases that could have a clinical outcome by the time rates are calculated. A sensitivity analysis is carried out to compare CFRs obtained using different levels of ascertainment and different distributions for the time from disease onset to death. Results: COVID-19 outcomes are highly influenced by age and gender. Different assumptions yield different CFR values but in all scenarios CFRs are higher in old ages and males. Conclusions: The procedures used to obtain the CFR estimates require strong assumptions and although the interpretation of their magnitude should be treated with caution, the differences observed by age and gender are fundamental underpinnings to inform decision-making.

Keywords: COVID-19; age; case fatality rate; epidemics; gender; mortality.

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Conflict of interest statement

No competing interests were disclosed.

Figures

Figure 1.
Figure 1.. Population by age group and gender in Spain, 2019.
Figure 2.
Figure 2.. Proportion of confirmed cases by age group and gender.
Figure 3.
Figure 3.. Proportion of deaths by age group and gender.
Figure 4.
Figure 4.. Cumulative total number of confirmed cases and deaths over time.
Figure 5.
Figure 5.. Log-normal distribution of the time from disease onset to death with mean 13 days and standard deviation 12.7 days.
Figure 6.
Figure 6.. Cumulative confirmed and adjusted cases over time for each age group in males.
Adjusted cases 1 are cases adjusted for preferential ascertainment of severe cases. Adjusted cases 2 are cases adjusted for preferential ascertainment of severe cases and time delay between confirmation and death.
Figure 7.
Figure 7.. Cumulative confirmed and adjusted cases over time for each age group in females.
Adjusted cases 1 are cases adjusted for preferential ascertainment of severe cases. Adjusted cases 2 are cases adjusted for preferential ascertainment of severe cases and time delay between confirmation and death.
Figure 8.
Figure 8.. Relative risk of each population group.
Figure 9.
Figure 9.. Gamma distribution of the time from disease onset to death with mean 18.8 days and coefficient of variation 0.45 days.

References

    1. World Health Organization: Coronavirus disease (COVID-19) Pandemic. Reference Source
    1. Lipsitch M, Donnelly CA, Fraser C, et al. : Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks. PLoS Negl Trop Dis. 2015;9(7):e0003846. 10.1371/journal.pntd.0003846 - DOI - PMC - PubMed
    1. National Institute of Statistics: España en cifras.2019. Reference Source
    1. National Institute of Statistics: Population by age group and sex. Reference Source
    1. Datadista: Datasets related to COVID-19 in Spain. Reference Source

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