Epidemiological intelligence community network intervention: a community response for COVID-19 community transmission.

BACKGROUND: Expanding and providing access to early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) through testing community-based strategies among socially vulnerable communities (SVC) are critical to reducing health disparities. The Epidemiological Intelligence Community Network (EpI-Net) community-based intervention sought to increase coronavirus 2019 (COVID-19) testing uptake and prevention practices among SVC in Puerto Rico (PR). We evaluated EpI-Net's community leaders' capacity-building component by assessing pre-post COVID-19 public health workshops' tests' score changes and satisfaction among trained community leaders. METHODS: A total of 24 community leaders from SVC in PR have completed four community workshops. Pre- and post-assessments were completed as part of the health promotors training program to evaluate participants' tests score changes and satisfaction outcomes. RESULTS: Preliminary results showed: (1) high intervention retention levels of community leaders (85.7% acceptance rate); (2) change in post-test scores for community engagement strategies (p = 0.012); (3) change in post-test educational scores in COVID-19 prevention practices (p = 0.014); and (4) a change in scores in public health emergency management strategies (p < 0.001). CONCLUSIONS: The overall workshop satisfaction was 99.6%. Community leaders have shown the importance of community capacity building as a key component for intervention feasibility and impact. TRIAL REGISTRATION: Our study was retrospectively registered under the ClinicalTrial.gov ID NCT04910542.

Resource Savings Associated With Use of an Automated Symptom Monitoring Tool for COVID-19 Public Health Response, Summer 2020-Summer 2021.

CONTEXT: Active symptom monitoring is a key component of the public health response to COVID-19, but these activities are resource-intensive. Digital tools can help reduce the burden of staff time required for active symptom monitoring by automating routine outreach activities. PROGRAM: Sara Alert is an open-source, Web-based automated symptom monitoring tool launched in April 2020 to support state, tribal, local, and territorial jurisdictions in their symptom monitoring efforts. IMPLEMENTATION: As of October 2021, a total of 23 public health jurisdictions in the United States had used Sara Alert to perform daily symptom monitoring for more than 6.1 million individuals. This analysis estimates staff time and cost saved in 3 jurisdictions that used Sara Alert as part of their COVID-19 response, across 2 use cases: monitoring of close contacts exposed to COVID-19 (Arkansas; Fairfax County, Virginia), and traveler monitoring (Puerto Rico). EVALUATION: A model-based approach was used to estimate the additional staff resources that would have been required to perform the active symptom monitoring automated by Sara Alert, if monitoring instead relied on traditional methods such as telephone outreach. Arkansas monitored 283 705 individuals over a 10-month study period, generating estimated savings of 61.9 to 100.6 full-time equivalent (FTE) staff, or $2 798 922 to $4 548 249. Fairfax County monitored 63 989 individuals over a 13-month study period, for an estimated savings of 24.8 to 41.4 FTEs, or $2 826 939 to $4 711 566. In Puerto Rico, where Sara Alert was used to monitor 2 631 306 travelers over the 11-month study period, estimated resource savings were 849 to 1698 FTEs, or $26 243 161 to $52 486 322. DISCUSSION: Automated symptom monitoring helped reduce the staff time required for active symptom monitoring activities. Jurisdictions reported that this efficiency supported a rapid and comprehensive COVID-19 response even when experiencing challenges with quickly scaling up their public health workforce.

Risk for COVID-19 infection and death among Latinos in the United States: examining heterogeneity in transmission dynamics.

PURPOSE: The purpose of this study was to ascertain COVID-19 transmission dynamics among Latino communities nationally. METHODS: We compared predictors of COVID-19 cases and deaths between disproportionally Latino counties (≥17.8% Latino population) and all other counties through May 11, 2020. Adjusted rate ratios (aRRs) were estimated using COVID-19 cases and deaths via zero-inflated binomial regression models. RESULTS: COVID-19 diagnoses rates were greater in Latino counties nationally (90.9 vs. 82.0 per 100,000). In multivariable analysis, COVID-19 cases were greater in Northeastern and Midwestern Latino counties (aRR: 1.42, 95% CI: 1.11-1.84, and aRR: 1.70, 95% CI: 1.57-1.85, respectively). COVID-19 deaths were greater in Midwestern Latino counties (aRR: 1.17, 95% CI: 1.04-1.34). COVID-19 diagnoses were associated with counties with greater monolingual Spanish speakers, employment rates, heart disease deaths, less social distancing, and days since the first reported case. COVID-19 deaths were associated with household occupancy density, air pollution, employment, days since the first reported case, and age (fewer <35 yo). CONCLUSIONS: COVID-19 risks and deaths among Latino populations differ by region. Structural factors place Latino populations and particularly monolingual Spanish speakers at elevated risk for COVID-19 acquisition.