The world is in the midst of a global pandemic and all countries have been impacted significantly. In Europe, the most successful policy response to the pandemic has been by Germany, as measured by the decline in new COVID-19 cases in recent weeks and consistent increase in recovered’ cases. This is also reflected in the COVID-19 related mortality rate per million people, it is 58.63 per million people as compared to that of Spain, which is 446.28. One critical aspect of German policy response has been in their systematic reporting of daily data that is highly disaggregated, which makes it possible to analyze key characteristics of the COVID-19 outbreak in Germany and improve our collective understanding of the global pandemic.
Using data from the situation reports made by the Robert Koch Institute, the German government’s central scientific institution in the field of biomedicine, we present some fundamental features of the COVID-19 outbreak in Germany. By looking at systematic trends in individual-level data from the German Ministry of Health, we are able to study three questions:
- Are men and women impacted differently?
- Are different age groups impacted differently?
- Is there a relationship between mortality rate and age? And does this vary with gender?
Figure 1 shows the proportion of females among all COVID-19 cases in Germany. Over a short period of time, the proportion of females among confirmed COVID-19 cases has been rising. While most confirmed cases were male in the early stage of the outbreak, the proportion of females now comprises the majority of cases in the country. Identifying the exact causes for this gendered nature of COVID-19 growth in Germany will require a more detailed analysis and understanding of the virus. It is likely to be biological factors, behavioral factors, or a combination of both.
Next, we analyze the COVID-19-related mortality rates across age and gender in Germany. Overall, Germany has reported far lower mortality (less than 6 per 100,000 population on April 20) than countries with smaller population like Italy (40 per 100,000 population) or Belgium (51 per 100,000 population). Figure 2 shows mortality rate per 100,000 population for different age groups in Germany, which are normalized by the population size of each group. We study population below 60 years of age as one group, and analyze people in their 60s, 70s, 80s and 90s separately.
The results show that the COVID-19 related mortality rate in Germany is rising significantly with age and over time, for all age groups in the population; the mortality rate is systematically higher for men compared to women in all age groups; and the difference in the mortality rates of men and women have increased with time. In the early stage of the COVID-19 outbreak in Germany, mortality rate of men (for all age groups) was only slightly higher than mortality rate of women. This difference, however, has grown significantly to the point that the overall mortality rate of men is now 50% greater than the mortality rate of women.
COVID-19 related mortality rate is higher for men than women across several countries. Existing studies have documented biological as well as behavioral reasons for this. A 2017 study in the Journal of Immunology studied the SARS outbreak in 2003 to determine the reasons why coronavirus that causes SARS seems to affect men more than women. In that study, researchers found that male mice were more susceptible to the virus. But when they blocked estrogen from working normally in the female mice, the females fell ill at higher rates. Behaviorally, smoking is a common explanation for gendered outcome of respiratory ailments. Existing research shows that 54% of Chinese adult men are smokers while only 2.6% Chinese women smoke. Similarly, a World Bank report states that 41% of South Korean men smoked, versus as against 6% of women. The trends are similar in Spain and U.S., but the difference in smoking between genders in Germany is not as large.
Finally, we analyze how the COVID-19 infection is spread across different age groups in the German population. Figure 3 shows the distribution of total confirmed cases per 100,000 population across age groups. The main results show that distributions of confirmed COVID-19 cases across all age groups show an increase with time, and that the infection is not linearly related to age. While population above 80 years of age are most susceptible, it is people in the working age group (15-59 years) that are more susceptible than people 60-79 years of age. This is an important feature of the COVID-19 outbreak in Germany. This could be due to early policies enacted to isolate and safeguard the older population, while working age groups are physically more mobile and have a higher probability of contracting the virus from others. The results show that the younger age groups have significantly lower infection rates.
Using individual level data, we discover some critical trends in the COVID-19 outbreak in Germany. The trends reveal that the majority of COVID-19 cases now are females, even though they were a smaller proportion in the beginning of the outbreak. The mortality rate per 100,000 population has been increasing with time, for all age groups in the population. Remarkably, the mortality rate of men is rising significantly faster than mortality rate for women in Germany, for all age groups. The infection rate across age groups show that people in the working age group (15-59) are far more susceptible than older population in age group 60-79 years. The overall infection rate is growing with time for all age groups.
Germany’s response to the COVID-19 outbreak is of enormous interest to the ‘hotspot’ nations on account of its population size and early successes. Germany has managed to lower the number of active COVID-19 cases while simultaneously improving the recovery rate and maintaining a low mortality rate. There are, however, significant variations across gender and age groups in the spread of the infection and lives lost to it. While Germany is ahead of its neighbors in managing the pandemic, these critical trends hold potential lessons for other countries tracking the spread of the pandemic among various subpopulations.