Flu SAFE: Flu SMS Alerts to Freeze Exposure

问题：流感感染导致约3100万人次的门诊就诊，即5.5万至97.42万人次 住院人数，3,000至49,000人死亡。其他人患上流感的家庭成员资格 是感染流感的主要风险因素。家庭二次侵袭率(SAR)高达19% 根据实验室确认的流感和30%的症状。非药物预防 包括教育在内的措施可能会在减少传播方面发挥作用，但只有在启动的情况下才有效 首发病例在症状出现后36小时内。然而，大多数干预措施之所以被推迟，是因为它们没有 开始治疗，直到寻求治疗。我们已经在一个主要是拉丁裔的城市社区样本中展示了这篇文章 消息传递可用于在早期快速识别患有流感样疾病(ILI)的社区成员 生病了。这一早期识别将使教育干预能够在最佳状态下实施 减少流感传播的时间框架。在短信中提供教育被证明是成功的 影响行为的策略。短信本身是可扩展的、低成本的，并且可以在识字率低的情况下使用 人口。然而，使用基于短信的监控来触发实时短信行为 尚未对减少家庭流感传播的教育干预措施进行评估。 目的：评估通过短信传递的教育干预对传播的影响 流感在家庭中的传播 探索性目标：比较不同亚组人群对短信ILI/ARI监测的效果 多样化的社区样本 方法：我们将招募400个家庭(n=~1500个人)，从4个家庭中招募≥1儿童 纽约市的毗连社区。我们将把按社区1：1分层的家庭随机分配到 仅接受监控(无短信教育)与监控加短信教育 干预。在症状监测方面，双方家庭都将每周收到3次短信 在每个流感季节(11月至3月)，并报告家庭中是否有人有ILI症状。为 在教育干预部门，当ILI/ARI被报告时，一系列教育文本消息 将与信息一起发送，以减少家庭传播。两只手臂都将获得一枚自拭子 索引病例，以及从索引开始的第3天和第5天所有其他家庭成员的自我拭子。要确定 呼吸道病原菌、拭子将用RT-PCR进行分析。 结果：主要结果将是实验室确认的流感的SAR。其次，我们会 根据ILI/ARI症状和非流感病毒评估SAR。我们将比较应答率 武器和人口因素(年龄、教育程度、种族/族裔)之间的差异。

Problem: Influenza infection results in an estimated 31 million outpatient visits, 55,000 to 974,200 hospitalizations, and 3,000 to 49,000 deaths. Membership in household in which someone else has influenza is the major risk factor for contracting influenza. The household secondary attack rate (SAR) is as high as 19% based on laboratory-confirmed influenza and 30% based on symptoms. Non-pharmaceutical preventive measures, including education, may play a role in decreasing transmission, but are only effective if started within 36 hours of symptom onset in index cases. Yet, most interventions are delayed because they are not initiated until care is sought. We have demonstrated in one primarily Latino, urban community sample, that text messaging can be used to rapidly identify community members with influenza-like illness (ILI) early in an illness. This early identification would enable implementation of an educational intervention in the optimal timeframe to reduce influenza transmission. Providing education within a text message is a proven successful strategy to influence behavior. Text messaging itself is scalable, low-cost, and can be used in low literacy populations. However, using text-message based surveillance to trigger a real-time text-message behavioral educational intervention to decrease household influenza transmission has not been assessed. Aim: To assess the impact of an educational intervention delivered by text messaging on transmission of influenza within households Exploratory Aim: To compare the yield of text message ILI/ARI surveillance among subgroups in a diverse, community sample Methods: We will enroll 400 households (n=~1500 individuals) with ≥1 child recruited from four contiguous communities in New York City. We will randomize households stratified by community 1:1 to receive surveillance-only (no text message education) vs. surveillance plus text message educational intervention. For symptom surveillance, households in both arms will receive text messages 3x/week during each influenza season (November-March) and report if someone in the household has ILI symptoms. For those in the educational intervention arm, when an ILI/ARI is reported, a series of educational text messages will be sent with information to decrease household transmission. Both arms will obtain one self-swab of the index case, and self-swabs of all other household members on days 3 and 5 from index onset. To identify respiratory tract pathogens, swabs will be analyzed using RT-PCR. Outcomes: The primary outcome will be SAR of laboratory-confirmed influenza. Secondarily, we will assess SAR based on ILI/ARI symptoms, and of non-influenza viruses. Response rates will be compared between arms and by demographic factors (age, education, race/ethnicity).