An Evaluation of the Text Illness Monitoring (TIM) Platform for COVID-19: Cross-sectional Online Survey of Public Health Users.

BACKGROUND: The US public health response to the COVID-19 pandemic has required contact tracing and symptom monitoring at an unprecedented scale. The US Centers for Disease Control and Prevention and several partners created the Text Illness Monitoring (TIM) platform in 2015 to assist US public health jurisdictions with symptom monitoring for potential novel influenza virus outbreaks. Since May 2020, 142 federal, state, and local public health agencies have deployed TIM for COVID-19 symptom monitoring. OBJECTIVE: The aim of this study was to evaluate the utility, benefits, and challenges of TIM to help guide decision-making for improvements and expansion to support future public health emergency response efforts. METHODS: We conducted a brief online survey of previous and current TIM administrative users (admin users) from November 28 through December 21, 2020. Closed- and open-ended questions inquired about the onboarding process, decision to use TIM, groups monitored with TIM, comparison of TIM to other symptom monitoring systems, technical challenges and satisfaction with TIM, and user support. A total of 1479 admin users were invited to participate. RESULTS: A total of 97 admin users from 43 agencies responded to the survey. Most admin users represented the Indian Health Service (35/97, 36%), state health departments (26/97, 27%), and local or county health departments (18/97, 19%), and almost all were current users of TIM (85/94, 90%). Among the 43 agencies represented, 11 (26%) used TIM for monitoring staff exclusively, 13 (30%) monitored community members exclusively, and 19 (44%) monitored both staff and community members. Agencies most frequently used TIM to monitor symptom development in contacts of cases among community members (28/43, 65%), followed by symptom development among staff (27/43, 63%) and among staff contacts of cases (24/43, 56%). Agencies also reported using TIM to monitor patients with COVID-19 for the worsening of symptoms among staff (21/43, 49%) and community members (18/43, 42%). When asked to compare TIM to previous monitoring systems, 78% (40/51) of respondents rated TIM more favorably than their previous monitoring system, 20% (10/51) said there was no difference, and 2% (1/51) rated the previous monitoring system more favorably than TIM. Most respondents found TIM favorable in terms of time burden, staff burden, timeliness of the data, and the ability to monitor large population sizes. TIM compared negatively to other systems in terms of effort to enroll participants (ie, persons TIM monitors) and accuracy of the data. Most respondents (76/85, 89%) reported that they would highly or somewhat recommend TIM to others for symptom monitoring. CONCLUSIONS: This evaluation of TIM showed that agencies used TIM for a variety of purposes and rated TIM favorably compared to previously used monitoring systems. We also identified opportunities to improve TIM; for example, enhancing the flexibility of alert deliveries would better meet admin users' varying needs. We also suggest continuous program evaluation practices to assess and respond to implementation gaps.

A stakeholder-driven framework for measuring potential change in the health risks of people who inject drugs (PWID) during the COVID-19 pandemic.

BACKGROUND: People who inject drugs (PWID) have likely borne disproportionate health consequences of the COVID-19 pandemic. PWID experienced both interruptions and changes to drug supply and delivery modes of harm reduction, treatment, and other medical services, leading to potentially increased risks for HIV, hepatitis C virus (HCV), and overdose. Given surveillance and research disruptions, proximal, indirect indicators of infectious diseases and overdose should be developed for timely measurement of health effects of the pandemic on PWID. METHODS: We used group concept mapping and a systems thinking approach to produce an expert stakeholder-generated, multi-level framework for monitoring changes in PWID health outcomes potentially attributable to COVID-19 in the U.S. This socio-ecological measurement framework elucidates proximal and distal contributors to infectious disease and overdose outcomes, many of which can be measured using existing data sources. RESULTS: The framework includes multi-level components including policy considerations, drug supply/distribution systems, the service delivery landscape, network factors, and individual characteristics such as mental and general health status and service utilization. These components are generally mediated by substance use and sexual behavioral factors to cause changes in incidence of HIV, HCV, sexually transmitted infections, wound/skin infections, and overdose. CONCLUSION: This measurement framework is intended to increase the quality and timeliness of research on the impacts of COVID-19 in the context of the current pandemic and future crises. Next steps include a ranking process to narrow the drivers of change in health risks to a concise set of indicators that adequately represent framework components, can be written as measurable indicators, and are quantifiable using existing data sources, as well as a publicly available web-based platform for summary data contributions.