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Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
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Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
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Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic

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Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic
Journal Article

Excess Mortality Stratified by Age and Sex for Croatia and Croatian Counties during the 2020–2021 COVID-19 Pandemic

2024
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Overview
Excess mortality is often used to estimate the effect of a certain crisis on the population. It is defined as the number of deaths during a crisis exceeding the expected number based on historical trends. Here, we calculated excess mortality due to the COVID-19 pandemic for Croatia in the 2020–2021 period. The excess was calculated on the national and county level for different age and sex categories. In addition to the absolute number, the excess mortality was also expressed as a ratio of excess deaths to the predicted baseline and excess mortality rate. We showed that using both measures is necessary to avoid incorrect conclusions. The estimated excess mortality on the national level was 14,963, corresponding to an excess percentage of 14.3%. With respect to sex, there was a higher excess mortality rate for men compared to women. An exponential relationship was observed between age and the excess mortality rate.These trends wee representative of most counties as well, with large variations in the magnitude of the effect. However, there were also exceptions to the general rule. The reasons for these deviations were discussed in terms of between-county differences in demographic structure, population density and special events that took place during the pandemic.