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).
We propose to assess the impact of a text message-based educational intervention aimed to reduce transmission of influenza and other respiratory infectiojns to household members. Information gathered from this study could provide new insights in decreasing influenza transmission, which could be useful for both seasonal and pandemic influenza.
