{"title":"对疫苗有效性的高估和低估。","authors":"Hilla De-Leon, Dvir Aran","doi":"10.1186/s12874-025-02611-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The effectiveness of SARS-CoV-2 vaccines against infection has been a subject of debate, with varying results reported in different studies, ranging from 60-95% vaccine effectiveness (VE). This range is striking when comparing two studies conducted in Israel at the same time, as one study reported VE of 90-95%, while the other study reported only ~ 80%. We argue that this variability is due to inadequate accounting for indirect protection provided by vaccines, which can block further transmission of the virus.</p><p><strong>Materials and methods: </strong>We developed a novel analytic heterogenous infection model and extended our agent-based model of disease spread to allow for heterogenous interactions between vaccinated and unvaccinated across close-contacts and regions. We applied these models on real-world regional data from Israel from early 2021 to estimate VE using two common study designs: population-based and secondary infections.</p><p><strong>Results: </strong>Our results show that the estimated VE of a vaccine with efficacy of 85% can range from 70-95% depending on the interactions between vaccinated and unvaccinated individuals. Since different study designs capture different levels of interactions, we suggest that this interference explains the variability across studies. Finally, we propose a methodology for more accurate estimation without knowledge of interactions. DISCUSSIONS AND CONCLUSIONS: Our study highlights the importance of considering indirect protection when estimating vaccine effectiveness, explains how different study designs may report biased estimations, and propose a method to overcome this bias. We hope that our models will lead to more accurate understanding of the impact of vaccinations and inform public health policy.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9114,"journal":{"name":"BMC Medical Research Methodology","volume":"25 1","pages":"163"},"PeriodicalIF":3.9000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12210928/pdf/","citationCount":"0","resultStr":"{\"title\":\"Over- and under-estimation of vaccine effectiveness.\",\"authors\":\"Hilla De-Leon, Dvir Aran\",\"doi\":\"10.1186/s12874-025-02611-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The effectiveness of SARS-CoV-2 vaccines against infection has been a subject of debate, with varying results reported in different studies, ranging from 60-95% vaccine effectiveness (VE). This range is striking when comparing two studies conducted in Israel at the same time, as one study reported VE of 90-95%, while the other study reported only ~ 80%. We argue that this variability is due to inadequate accounting for indirect protection provided by vaccines, which can block further transmission of the virus.</p><p><strong>Materials and methods: </strong>We developed a novel analytic heterogenous infection model and extended our agent-based model of disease spread to allow for heterogenous interactions between vaccinated and unvaccinated across close-contacts and regions. We applied these models on real-world regional data from Israel from early 2021 to estimate VE using two common study designs: population-based and secondary infections.</p><p><strong>Results: </strong>Our results show that the estimated VE of a vaccine with efficacy of 85% can range from 70-95% depending on the interactions between vaccinated and unvaccinated individuals. Since different study designs capture different levels of interactions, we suggest that this interference explains the variability across studies. Finally, we propose a methodology for more accurate estimation without knowledge of interactions. DISCUSSIONS AND CONCLUSIONS: Our study highlights the importance of considering indirect protection when estimating vaccine effectiveness, explains how different study designs may report biased estimations, and propose a method to overcome this bias. We hope that our models will lead to more accurate understanding of the impact of vaccinations and inform public health policy.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>\",\"PeriodicalId\":9114,\"journal\":{\"name\":\"BMC Medical Research Methodology\",\"volume\":\"25 1\",\"pages\":\"163\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12210928/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Medical Research Methodology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12874-025-02611-4\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Medical Research Methodology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12874-025-02611-4","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Over- and under-estimation of vaccine effectiveness.
Background: The effectiveness of SARS-CoV-2 vaccines against infection has been a subject of debate, with varying results reported in different studies, ranging from 60-95% vaccine effectiveness (VE). This range is striking when comparing two studies conducted in Israel at the same time, as one study reported VE of 90-95%, while the other study reported only ~ 80%. We argue that this variability is due to inadequate accounting for indirect protection provided by vaccines, which can block further transmission of the virus.
Materials and methods: We developed a novel analytic heterogenous infection model and extended our agent-based model of disease spread to allow for heterogenous interactions between vaccinated and unvaccinated across close-contacts and regions. We applied these models on real-world regional data from Israel from early 2021 to estimate VE using two common study designs: population-based and secondary infections.
Results: Our results show that the estimated VE of a vaccine with efficacy of 85% can range from 70-95% depending on the interactions between vaccinated and unvaccinated individuals. Since different study designs capture different levels of interactions, we suggest that this interference explains the variability across studies. Finally, we propose a methodology for more accurate estimation without knowledge of interactions. DISCUSSIONS AND CONCLUSIONS: Our study highlights the importance of considering indirect protection when estimating vaccine effectiveness, explains how different study designs may report biased estimations, and propose a method to overcome this bias. We hope that our models will lead to more accurate understanding of the impact of vaccinations and inform public health policy.
期刊介绍:
BMC Medical Research Methodology is an open access journal publishing original peer-reviewed research articles in methodological approaches to healthcare research. Articles on the methodology of epidemiological research, clinical trials and meta-analysis/systematic review are particularly encouraged, as are empirical studies of the associations between choice of methodology and study outcomes. BMC Medical Research Methodology does not aim to publish articles describing scientific methods or techniques: these should be directed to the BMC journal covering the relevant biomedical subject area.