Chisato Ito, Bernhard T Baune, Tobias Kurth, Ralph Brinks
{"title":"利用疾病-死亡模型预测德国 COVID-19 大流行期间及之后的焦虑症发病率。","authors":"Chisato Ito, Bernhard T Baune, Tobias Kurth, Ralph Brinks","doi":"10.1192/bjo.2024.754","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Although there is now substantial evidence on the acute impacts of the COVID-19 pandemic on anxiety disorders, the long-term population impact of the pandemic remains largely unexplored.</p><p><strong>Aims: </strong>To quantify a possible longitudinal population-level impact of the pandemic by projecting the prevalence of anxiety disorders through 2030 among men and women aged up to 95 years in Germany under scenarios with varying impacts of the pandemic on the incidence of anxiety disorders.</p><p><strong>Method: </strong>We used a three-state illness-death model and data from the Global Burden of Disease Study to model historical trends of the prevalence and incidence of anxiety disorders. The German population projections determined the initial values for projections. The COVID-19 incidence rate data informed an additional incidence model, which was parameterised with a wash-in period, delay, wash-out period, incidence increase level and decay constant.</p><p><strong>Results: </strong>When no additional increase in the incidence during the pandemic waves during 2020-2022 was assumed, it was estimated that 3.86 million women (9.96%) and 2.13 million men (5.40%) would have anxiety disorders in 2030. When increases in incidence following pandemic waves were assumed, the most extreme scenario projected 5.67 million (14.02%) women and 3.30 million (8.14%) men with the mental disorder in 2030.</p><p><strong>Conclusions: </strong>Any increased incidence during the pandemic resulted in elevated prevalence over the projection period. Projection of anxiety disorder prevalence based on the illness-death model enables simulations with varying assumptions and provides insight for public health planning. These findings should be refined as trend data accumulate and become available.</p>","PeriodicalId":9038,"journal":{"name":"BJPsych Open","volume":"10 5","pages":"e174"},"PeriodicalIF":3.9000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536217/pdf/","citationCount":"0","resultStr":"{\"title\":\"Projections of anxiety disorder prevalence during and beyond the COVID-19 pandemic in Germany using the illness-death model.\",\"authors\":\"Chisato Ito, Bernhard T Baune, Tobias Kurth, Ralph Brinks\",\"doi\":\"10.1192/bjo.2024.754\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Although there is now substantial evidence on the acute impacts of the COVID-19 pandemic on anxiety disorders, the long-term population impact of the pandemic remains largely unexplored.</p><p><strong>Aims: </strong>To quantify a possible longitudinal population-level impact of the pandemic by projecting the prevalence of anxiety disorders through 2030 among men and women aged up to 95 years in Germany under scenarios with varying impacts of the pandemic on the incidence of anxiety disorders.</p><p><strong>Method: </strong>We used a three-state illness-death model and data from the Global Burden of Disease Study to model historical trends of the prevalence and incidence of anxiety disorders. The German population projections determined the initial values for projections. The COVID-19 incidence rate data informed an additional incidence model, which was parameterised with a wash-in period, delay, wash-out period, incidence increase level and decay constant.</p><p><strong>Results: </strong>When no additional increase in the incidence during the pandemic waves during 2020-2022 was assumed, it was estimated that 3.86 million women (9.96%) and 2.13 million men (5.40%) would have anxiety disorders in 2030. When increases in incidence following pandemic waves were assumed, the most extreme scenario projected 5.67 million (14.02%) women and 3.30 million (8.14%) men with the mental disorder in 2030.</p><p><strong>Conclusions: </strong>Any increased incidence during the pandemic resulted in elevated prevalence over the projection period. Projection of anxiety disorder prevalence based on the illness-death model enables simulations with varying assumptions and provides insight for public health planning. These findings should be refined as trend data accumulate and become available.</p>\",\"PeriodicalId\":9038,\"journal\":{\"name\":\"BJPsych Open\",\"volume\":\"10 5\",\"pages\":\"e174\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536217/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BJPsych Open\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1192/bjo.2024.754\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BJPsych Open","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1192/bjo.2024.754","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Projections of anxiety disorder prevalence during and beyond the COVID-19 pandemic in Germany using the illness-death model.
Background: Although there is now substantial evidence on the acute impacts of the COVID-19 pandemic on anxiety disorders, the long-term population impact of the pandemic remains largely unexplored.
Aims: To quantify a possible longitudinal population-level impact of the pandemic by projecting the prevalence of anxiety disorders through 2030 among men and women aged up to 95 years in Germany under scenarios with varying impacts of the pandemic on the incidence of anxiety disorders.
Method: We used a three-state illness-death model and data from the Global Burden of Disease Study to model historical trends of the prevalence and incidence of anxiety disorders. The German population projections determined the initial values for projections. The COVID-19 incidence rate data informed an additional incidence model, which was parameterised with a wash-in period, delay, wash-out period, incidence increase level and decay constant.
Results: When no additional increase in the incidence during the pandemic waves during 2020-2022 was assumed, it was estimated that 3.86 million women (9.96%) and 2.13 million men (5.40%) would have anxiety disorders in 2030. When increases in incidence following pandemic waves were assumed, the most extreme scenario projected 5.67 million (14.02%) women and 3.30 million (8.14%) men with the mental disorder in 2030.
Conclusions: Any increased incidence during the pandemic resulted in elevated prevalence over the projection period. Projection of anxiety disorder prevalence based on the illness-death model enables simulations with varying assumptions and provides insight for public health planning. These findings should be refined as trend data accumulate and become available.
期刊介绍:
Announcing the launch of BJPsych Open, an exciting new open access online journal for the publication of all methodologically sound research in all fields of psychiatry and disciplines related to mental health. BJPsych Open will maintain the highest scientific, peer review, and ethical standards of the BJPsych, ensure rapid publication for authors whilst sharing research with no cost to the reader in the spirit of maximising dissemination and public engagement. Cascade submission from BJPsych to BJPsych Open is a new option for authors whose first priority is rapid online publication with the prestigious BJPsych brand. Authors will also retain copyright to their works under a creative commons license.