目的:接触者追踪是指识别最近与被诊断为传染病的人接触的过程。在爆发期间,从接触者追踪中收集的数据可以为减少传染病传播的干预措施提供信息。了解与联系人追踪调查完成率相关的因素可以帮助为正在进行的和未来的计划设计改进的访谈协议。
目的:确定与纽约市(NYC)COVID-19接触者追踪调查完成率相关的因素,并评估预测模型提高完成率的效用,我们分析了2020年10月1日至2021年5月10日纽约市实验室确诊和可能的COVID-19病例及其自我报告的接触者。
方法:我们分析了在研究期间发出的742,807个病例调查电话。使用对数二项回归模型,我们研究了年龄的影响,一天中打电话的时间,以及邮政编码级别的人口和社会经济因素对面试完成率的影响。我们进一步开发了随机森林模型来预测最佳电话通话时间,并进行了反事实分析,以评估使用预测模型时完成率的变化。
结果:完成的接触者追踪调查百分比为79.4%,在邮政编码区域有很大的差异。使用对数二项回归模型,我们发现,与年轻人相比,索引病例的年龄(通过PCR或抗原检测呈阳性并因此接受病例调查的个体)对完成病例调查有重大影响(参考组,24岁<年龄<=65岁),老年人(年龄>65岁)的完成率较低12.1%(95CI:11.1%-13.3%),青年组(年龄<=24岁)的完成率降低了1.6%(95CI:0.6%-2.6%)。此外,与从下午12点和3点尝试的参考组电话相比,从下午6点至9点拨打的电话的完成率高4.1%(95%CI:1.8%-6.3%).我们进一步使用随机森林算法来评估其用于选择电话呼叫时间的潜在效用。在反事实模拟中,纽约市的整体完成率略有提高1.2%;然而,某些邮政编码区域有高达7.8%的改进。
结论:这些研究结果表明,年龄和电话时间与病例调查的完成率有关。可以开发预测模型来估计更好的电话通话时间,以提高某些社区的完成率。
OBJECTIVE: Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs.
OBJECTIVE: To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021.
METHODS: We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used.
RESULTS: The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age < = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age < = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%.
CONCLUSIONS: These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.