Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System.
Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System.
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DOI：
10.2196/publichealth.7304
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发表时间：
2017-04-07
影响因子：
8.5
通讯作者：
Brownstein JS
中科院分区：
文献类型：
--
作者：
Baltrusaitis K;Santillana M;Crawley AW;Chunara R;Smolinski M;Brownstein JS
Flu Near You (FNY) 是美国和加拿大的一个基于互联网的参与式监测系统，允许志愿者使用简短的每周症状报告来报告流感样症状。我们的目标是评估 FNY 人群与美国普通人群相比的代表性，探索与 FNY 高参与度用户相关的人口统计和行为特征，并总结 FNY 参与者队列的用户调查结果。我们比较了 (1) 2014-2015 年流感季节 FNY 参与者的性别和年龄组代表性与美国普通人群的代表性，以及 (2) FNY 参与者与美国普通人群的人类发展指数 (HDI) 得分的分布情况。我们分析了人口统计和行为因素与参与者随访水平（即高与低）之间的关联。最后，对 FNY 2015 年和 2016 年季末用户调查的回复进行了描述性统计。在 2014-2015 流感季节期间，47,234 名独特的参与者至少有一份 FNY 症状报告，该报告要么是自我报告（用户），要么是代表他们提交（家庭成员）。 FNY 女性参与者的比例显着高于美国普通人口的比例 (n=28,906, 61.2% vs 51.1%, P<.001)。尽管 FNY 人口中每个年龄组都有代表，但年龄分布与美国人口显着不同 (P<.001)。与美国人口相比，FNY 的 HDI > 5.0 的个体比例更高，这表明 FNY 用户分布比美国人口基线更加富裕和受教育程度更高。我们发现，高参与度使用（即较高的后续症状报告参与度）与性别（女性成为高参与度用户的可能性比男性低 25%）、较高的 HDI、在首次症状报告时未报告流感样疾病、年龄较大以及家庭成员的报告有关（高参与度用户和低参与度用户之间的所有差异 P<.001）。大约 10% 的 FNY 用户在流感季节结束时完成了另一项调查，评估了详细的用户特征（2015 年为 3217/33,324；2016 年为 4850/44,313）。在这些用户中，大多数人已退休或在健康、教育和社会服务领域工作，并表示他们获得了学士学位或更高学位。 FNY 人群的代表性及其高参与度用户的特征与其他基于互联网的流感监测系统中观察到的情况一致。通过有针对性地招募代表性不足的人群，FNY 可能会作为及时跟踪流感活动的补充系统得到改进，特别是在不寻求医疗救助的人群和官方监测数据较差的地区。
Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report. Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY’s high-participation users, and summarize results from a user survey of a cohort of FNY participants. We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY’s 2015 and 2016 end-of-season user surveys were calculated. During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P<.001). Although each age group was represented in the FNY population, the age distribution was significantly different from that of the US population (P<.001). Compared with the US population, FNY had a greater proportion of individuals with HDI >5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first symptom report, older age, and reporting for household members (all differences between high- and low-participation users P<.001). Approximately 10% of FNY users completed an additional survey at the end of the flu season that assessed detailed user characteristics (3217/33,324 in 2015; 4850/44,313 in 2016). Of these users, most identified as being either retired or employed in the health, education, and social services sectors and indicated that they achieved a bachelor’s degree or higher. The representativeness of the FNY population and characteristics of its high-participation users are consistent with what has been observed in other Internet-based influenza surveillance systems. With targeted recruitment of underrepresented populations, FNY may improve as a complementary system to timely tracking of flu activity, especially in populations that do not seek medical attention and in areas with poor official surveillance data.