Department of Government, Cornell University, Ithaca, NY, United States of America.
Institutions and Political Inequality Unit, WZB Berlin Social Science Center, Berlin, Germany.
PLoS One. 2020 Dec 23;15(12):e0242652. doi: 10.1371/journal.pone.0242652. eCollection 2020.
To study the U.S. public's attitudes toward surveillance measures aimed at curbing the spread of COVID-19, particularly smartphone applications (apps) that supplement traditional contact tracing.
We deployed a survey of approximately 2,000 American adults to measure support for nine COVID-19 surveillance measures. We assessed attitudes toward contact tracing apps by manipulating six different attributes of a hypothetical app through a conjoint analysis experiment.
A smaller percentage of respondents support the government encouraging everyone to download and use contact tracing apps (42%) compared with other surveillance measures such as enforcing temperature checks (62%), expanding traditional contact tracing (57%), carrying out centralized quarantine (49%), deploying electronic device monitoring (44%), or implementing immunity passes (44%). Despite partisan differences on a range of surveillance measures, support for the government encouraging digital contact tracing is indistinguishable between Democrats (47%) and Republicans (46%), although more Republicans oppose the policy (39%) compared to Democrats (27%). Of the app features we tested in our conjoint analysis experiment, only one had statistically significant effects on the self-reported likelihood of downloading the app: decentralized data architecture increased the likelihood by 5.4 percentage points.
Support for public health surveillance policies to curb the spread of COVID-19 is relatively low in the U.S. Contact tracing apps that use decentralized data storage, compared with those that use centralized data storage, are more accepted by the public. While respondents' support for expanding traditional contact tracing is greater than their support for the government encouraging the public to download and use contact tracing apps, there are smaller partisan differences in support for the latter policy.
研究美国公众对旨在遏制 COVID-19 传播的监测措施的态度,特别是补充传统接触者追踪的智能手机应用程序(apps)。
我们对大约 2000 名美国成年人进行了一项调查,以衡量对九项 COVID-19 监测措施的支持程度。我们通过联合分析实验通过操纵假设应用程序的六个不同属性来评估对接触者追踪应用程序的态度。
与其他监测措施相比,如鼓励所有人下载和使用接触者追踪应用程序(42%)的比例较小,其他监测措施的支持率较高,如实施体温检查(62%)、扩大传统接触者追踪(57%)、实施集中隔离(49%)、部署电子设备监测(44%)或实施免疫通行证(44%)。尽管在一系列监测措施上存在党派分歧,但政府鼓励数字接触者追踪的支持率在民主党(47%)和共和党(46%)之间没有区别,尽管更多的共和党人(39%)反对该政策,而民主党人(27%)则不反对。在我们的联合分析实验中测试的应用程序功能中,只有一个对自我报告下载应用程序的可能性有统计学上的显著影响:去中心化的数据架构增加了 5.4 个百分点。
在美国,遏制 COVID-19 传播的公共卫生监测政策的支持率相对较低。与使用集中式数据存储的应用程序相比,使用分散式数据存储的接触者追踪应用程序更受公众欢迎。虽然受访者对扩大传统接触者追踪的支持率高于他们对政府鼓励公众下载和使用接触者追踪应用程序的支持率,但后者政策的党派分歧较小。