{"title":"感染致死率真正衡量的是什么?","authors":"I. Korolev","doi":"10.2139/ssrn.3572891","DOIUrl":null,"url":null,"abstract":"This paper studies what the infection fatality rate (IFR) really measures using the potential outcomes framework. I show that the IFR only reflects the outcome in one state. In contrast, popular causal parameters are all functions of the difference between outcomes in two states. I then demonstrate using a simple illustrative example that a disease that has no effect of the risk of dying can have a higher IFR than a disease that increases the risk of dying for everyone in the population. As a result, the IFR may fail to reflect the causal effect of a disease on the risk of dying and hence might not be a suitable measure of how deadly the disease is.","PeriodicalId":277095,"journal":{"name":"MedRN: Other Infectious Diseases (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"What Does the Infection Fatality Rate Really Measure?\",\"authors\":\"I. Korolev\",\"doi\":\"10.2139/ssrn.3572891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies what the infection fatality rate (IFR) really measures using the potential outcomes framework. I show that the IFR only reflects the outcome in one state. In contrast, popular causal parameters are all functions of the difference between outcomes in two states. I then demonstrate using a simple illustrative example that a disease that has no effect of the risk of dying can have a higher IFR than a disease that increases the risk of dying for everyone in the population. As a result, the IFR may fail to reflect the causal effect of a disease on the risk of dying and hence might not be a suitable measure of how deadly the disease is.\",\"PeriodicalId\":277095,\"journal\":{\"name\":\"MedRN: Other Infectious Diseases (Topic)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MedRN: Other Infectious Diseases (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3572891\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MedRN: Other Infectious Diseases (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3572891","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
What Does the Infection Fatality Rate Really Measure?
This paper studies what the infection fatality rate (IFR) really measures using the potential outcomes framework. I show that the IFR only reflects the outcome in one state. In contrast, popular causal parameters are all functions of the difference between outcomes in two states. I then demonstrate using a simple illustrative example that a disease that has no effect of the risk of dying can have a higher IFR than a disease that increases the risk of dying for everyone in the population. As a result, the IFR may fail to reflect the causal effect of a disease on the risk of dying and hence might not be a suitable measure of how deadly the disease is.