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Background: Recent research points towards age- and sex-specific transmission of COVID-19 infections and their outcomes. The effect of sex, however, has been overlooked in past modelling approaches of COVID-19 infections. Aim: The aim of our study is to develop an age- and sex-specific model of COVID-19 transmission and to explore how contact changes effect COVID-19 infection and death rates. Method: We consider a compartment model to establish forecasts of the COVID-19 epidemic, in which the compartments are subdivided into different age groups and genders. Estimated contact patterns, based on other studies, are incorporated to account for age- and sex-specific social behaviour. The model is fitted to real data and used for assessing hypothetical scenarios with regard to lockdown measures. Results: Under current mitigation measures as of mid-August, active COVID-19 cases will double by the end of October 2020. Infection rates will be highest among the young and working ages, but will also rise among the old. Sex ratios reveal higher infection risks among women than men at working ages; the opposite holds true at old age. Death rates in all age groups are twice as high among men as women. Small changes in contact rates at working and young ages may have a considerable effect on infections and mortality at old age, with elderly men being always at higher risk of infection and mortality. Discussion: Our results underline the high importance of the non-pharmaceutical mitigation measures in the current phase of the pandemic to prevent that an increase in contact rates leads to higher mortality among the elderly. Gender differences in contact rates, in addition to biological mechanisms related to the immune system, may contribute to sex-specific infection rates and their mortality outcome. To further explore possible pathways, more data on COVID-19 transmission is needed which includes socio-demographic information.
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10.1101/2020.10.06.20207951
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document_parses/pdf_json/7629eb0a2ee766f95863de2fdeb6b5a8e830383f.json
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Age- and Sex-Specific Modelling of the COVID-19 Epidemic
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