{"title":"基于社会媒体和互联网的公共卫生疾病监测。","authors":"Allison E Aiello, Audrey Renson, Paul N Zivich","doi":"10.1146/annurev-publhealth-040119-094402","DOIUrl":null,"url":null,"abstract":"<p><p>Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.</p>","PeriodicalId":50752,"journal":{"name":"Annual Review of Public Health","volume":"41 ","pages":"101-118"},"PeriodicalIF":21.4000,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-publhealth-040119-094402","citationCount":"140","resultStr":"{\"title\":\"Social Media- and Internet-Based Disease Surveillance for Public Health.\",\"authors\":\"Allison E Aiello, Audrey Renson, Paul N Zivich\",\"doi\":\"10.1146/annurev-publhealth-040119-094402\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.</p>\",\"PeriodicalId\":50752,\"journal\":{\"name\":\"Annual Review of Public Health\",\"volume\":\"41 \",\"pages\":\"101-118\"},\"PeriodicalIF\":21.4000,\"publicationDate\":\"2020-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1146/annurev-publhealth-040119-094402\",\"citationCount\":\"140\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Public Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-publhealth-040119-094402\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/1/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Public Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1146/annurev-publhealth-040119-094402","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/1/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Social Media- and Internet-Based Disease Surveillance for Public Health.
Disease surveillance systems are a cornerstone of public health tracking and prevention. This review addresses the use, promise, perils, and ethics of social media- and Internet-based data collection for public health surveillance. Our review highlights untapped opportunities for integrating digital surveillance in public health and current applications that could be improved through better integration, validation, and clarity on rules surrounding ethical considerations. Promising developments include hybrid systems that couple traditional surveillance data with data from search queries, social media posts, and crowdsourcing. In the future, it will be important to identify opportunities for public and private partnerships, train public health experts in data science, reduce biases related to digital data (gathered from Internet use, wearable devices, etc.), and address privacy. We are on the precipice of an unprecedented opportunity to track, predict, and prevent global disease burdens in the population using digital data.
期刊介绍:
The Annual Review of Public Health has been a trusted publication in the field since its inception in 1980. It provides comprehensive coverage of important advancements in various areas of public health, such as epidemiology, biostatistics, environmental health, occupational health, social environment and behavior, health services, as well as public health practice and policy.
In an effort to make the valuable research and information more accessible, the current volume has undergone a transformation. Previously, access to the articles was restricted, but now they are available to everyone through the Annual Reviews' Subscribe to Open program. This open access approach ensures that the knowledge and insights shared in these articles can reach a wider audience. Additionally, all the published articles are licensed under a CC BY license, allowing users to freely use, distribute, and build upon the content, while giving appropriate credit to the original authors.