Real World Feedback: How Well Did the Virtual Training Academy Prepare California's COVID-19 Contact Tracing Workforce?

To effectively respond to the COVID-19 pandemic, California had to quickly mobilize a substantial number of case investigators (CIs) and contact tracers (CTs). This workforce was comprised primarily of redirected civil servants with diverse educational and professional backgrounds. The purpose of this evaluation was to understand whether the weeklong, remote course developed to train California's CI/CT workforce (i.e., Virtual Training Academy) adequately prepared trainees for deployment. From May 2020 to February 2021, 8,141 individuals completed the training. A survey administered ~3 weeks post-course assessed two measures of overall preparedness: self-perceived interviewing proficiency and self-perceived job preparedness. Bivariate analyses were used to examine differences in preparedness scores by education level, career background, and whether trainees volunteered to join the COVID-19 workforce or were assigned by their employers. There were no significant differences in preparedness by education level. Compared to trainees from non-public health backgrounds, those from public health fields had higher self-perceived interviewing proficiency (25.1 vs. 23.3, p < 0.001) and job preparedness (25.7 vs. 24.0, p < 0.01). Compared to those who were assigned, those who volunteered to join the workforce had lower self-perceived job preparedness (23.8 vs. 24.9, p = 0.02). While there were some statistically significant differences by trainee characteristics, the practical significance was small (<2-point differences on 30-point composite scores), and it was notable that there were no differences by education level. Overall, this evaluation suggests that individuals without bachelor's degrees or health backgrounds can be rapidly trained and deployed to provide critical disease investigation capacity during public health emergencies.

Virtual Trainings Effectively Prepared the Public Health Workforce to Support Schools During the COVID-19 Pandemic in California in 2021.

CONTEXT: School closures in California due to COVID-19 have had a negative impact on the learning advancement and social development of K-12 students. Since March 2020, the achievement gap has grown between high-income and low-income students and between White students and students of color. PROGRAM: In November 2020, a team from the California Department of Public Health, University of California, San Francisco, and University of California, Los Angeles, developed the School Specialist training for local health department and state employee redirected staff to the COVID-19 response to equip them to support schools as they reopen. IMPLEMENTATION: A pilot of the virtual School Specialist training was carried out in December 2020, which informed subsequent biweekly half-day virtual trainings. The training consisted of lectures from experts and skill development activities led by trained facilitators. EVALUATION: The objectives of the evaluation of the training were to understand whether (1) knowledge of key concepts improved from pre- to posttraining; (2) confidence in skills central to the role of a School Specialist improved from pre- to posttraining; and (3) course learners who were activated to work as School Specialists felt the training adequately prepared them for the role. The School Specialist training team sent pre- and posttraining surveys to learners between February 8 and May 18, 2021. Of the 262 learners who responded, a significant improvement was seen in knowledge, with a mean score increase of 15.6%. Significant improvement was also observed for confidence, with a 20.1% score improvement seen posttraining. DISCUSSION: Overall, the School Specialist training was shown to be effective in increasing knowledge and confidence in preparation for School Specialist deployment. Adequate training and partnerships for local health department and school staff are critical to keep K-12 students safe and to reduce the learning achievement gap during the ongoing COVID-19 pandemic.

Best Practices to Support Early-Stage Career URM Students with Virtual Enhancements to In-Person Experiential Learning.

STEM training of college-bound and college students has reliably employed hands-on experiential learning by placing students in on-campus research settings. Dana-Farber/Harvard Cancer Center's Young Empowered Scientists for ContinUed Research Engagement (DF/HCC's YES for CURE) program introduces Massachusetts high school and college students from underrepresented populations to cancer research by immersing them in scientific and nursing research environments. Amidst the COVID-19 pandemic, the 2020 summer program was re-designed and delivered virtually for 45 students. Because the program spans three years, we could evaluate the experiences of 18 students (cohort 2) who completed the 2019 (pre-pandemic) and 2020 (pandemic) summer programs. Analysis of cohort 2 data revealed three areas where students felt their competence improved with virtual programming (i.e., effective communication of ideas, access to high caliber speakers, engagement with program leaders) and two areas where it declined significantly (i.e., engaging other students, learning lab material). Additionally, student-reported competence to perform 21 scientific research and seven critical thinking processes were not negatively impacted by the virtual transition. Herein, we describe the adaptation of DF/HCC's YES for CURE program to a virtual format and the impact on students as a resource for institutions interested in enhancing their STEM training programs with virtual programming.

Microfluidic point-of-care device for detection of early strains and B.1.1.7 variant of SARS-CoV-2 virus.

Since the beginning of the COVID-19 pandemic, several mutations of the SARS-CoV-2 virus have emerged. Current gold standard detection methods for detecting the virus and its variants are based on PCR-based diagnostics using complex laboratory protocols and time-consuming steps, such as RNA isolation and purification, and thermal cycling. These steps limit the translation of technology to the point-of-care and limit accessibility to under-resourced regions. While PCR-based assays currently offer the possibility of multiplexed gene detection, and commercial products of single gene PCR and isothermal LAMP at point-of-care are also now available, reports of isothermal assays at the point-of-care with detection of multiple genes are lacking. Here, we present a microfluidic assay and device to detect and differentiate the Alpha variant (B.1.1.7) from the SARS-CoV-2 virus early strains in saliva samples. The detection assay, which is based on isothermal RT-LAMP amplification, takes advantage of the S-gene target failure (SGTF) to differentiate the Alpha variant from the SARS-CoV-2 virus early strains using a binary detection system based on spatial separation of the primers specific to the N- and S-genes. We use additively manufactured plastic cartridges in a low-cost optical reader system to successfully detect the SARS-CoV-2 virus from saliva samples (positive amplification is detected with concentration ≥10 copies per µL) within 30 min. We demonstrate that our platform can discriminate the B.1.1.7 variant (USA/CA_CDC_5574/2020 isolate) from SARS-CoV-2 negative samples, but also from the SARS-CoV-2 USA-WA1/2020 isolate. The reliability of the developed point-of-care device was confirmed by testing 38 clinical saliva samples, including 20 samples positive for Alpha variant (sensitivity > 90%, specificity = 100%). This study highlights the current relevance of binary-based testing, as the new Omicron variant also exhibits S-gene target failure and could be tested by adapting the approach presented here.

Establishment and Evaluation of a Large Contact-Tracing and Case Investigation Virtual Training Academy.

During the COVID-19 pandemic, the Virtual Training Academy (VTA) was established to rapidly develop a contact-tracing workforce for California. Through June 2021, more than 10 000 trainees enrolled in a contact-tracing or case investigation course at the VTA. To evaluate program effectiveness, we analyzed trainee pre- and postassessment results using the Wilcoxon signed-rank test. There was a statistically significant (P < .001) improvement in knowledge and self-perceived skills after course completion, indicating success in training a competent contact-tracing workforce. (Am J Public Health. 2021;111(11):1934-1938. https://doi.org/10.2105/AJPH.2021.306468).

California's COVID-19 Virtual Training Academy: Rapid Scale-Up of a Statewide Contact Tracing and Case Investigation Workforce Training Program.

Case investigation (CI) and contact tracing (CT) are key to containing the COVID-19 pandemic. Widespread community transmission necessitates a large, diverse workforce with specialized knowledge and skills. The University of California, San Francisco and Los Angeles partnered with the California Department of Public Health to rapidly mobilize and train a CI/CT workforce. In April through August 2020, a team of public health practitioners and health educators constructed a training program to enable learners from diverse backgrounds to quickly acquire the competencies necessary to function effectively as CIs and CTs. Between April 27 and May 5, the team undertook a curriculum design sprint by performing a needs assessment, determining relevant goals and objectives, and developing content. The initial four-day curriculum consisted of 13 hours of synchronous live web meetings and 7 hours of asynchronous, self-directed study. Educational content emphasized the principles of COVID-19 exposure, infectious period, isolation and quarantine guidelines and the importance of prevention and control interventions. A priority was equipping learners with skills in rapport building and health coaching through facilitated web-based small group skill development sessions. The training was piloted among 31 learners and subsequently expanded to an average weekly audience of 520 persons statewide starting May 7, reaching 7,499 unique enrollees by August 31. Capacity to scale and sustain the training program was afforded by the UCLA Extension Canvas learning management system. Repeated iteration of content and format was undertaken based on feedback from learners, facilitators, and public health and community-based partners. It is feasible to rapidly train and deploy a large workforce to perform CI and CT. Interactive skills-based training with opportunity for practice and feedback are essential to develop independent, high-performing CIs and CTs. Rigorous evaluation will continue to monitor quality measures to improve the training experience and outcomes.

The SARS-CoV-2 pandemic: the race to trace: contact tracing scale-up in San Francisco-early lessons learned.

In order to effectively control spread of coronavirus 2019 (COVID-19), it is essential that jurisdictions have the capacity to rapidly trace close contacts of each and every case. Best practice guidance on how to implement such programs is urgently needed. We describe the early experience in the City and County of San Francisco (CCSF), where the City's Department of Health expanded contact tracing capability in anticipation of changes in San Francisco's 'shelter in place' order between April and June 2020. Important prerequisites to successful scale-up included a rapid expansion of the COVID-19 response workforce, expansion of testing capability, and other containment resources. San Francisco's scale-up offers a model for how other jurisdictions can rapidly mobilize a workforce. We underscore the importance of an efficient digital case management system, effective training, and expansion of supportive service programs for those in quarantine or isolation, and metrics to ensure continuous performance improvement.

Reverse Transcription Loop-Mediated Isothermal Amplification Assay for Ultrasensitive Detection of SARS-CoV-2 in Saliva and Viral Transport Medium Clinical Samples.

The COVID-19 pandemic has underscored the shortcomings in the deployment of state-of-the-art diagnostics platforms. Although several polymerase chain reaction (PCR)-based techniques have been rapidly developed to meet the growing testing needs, such techniques often need samples collected through a swab, the use of RNA extraction kits, and expensive thermocyclers in order to successfully perform the test. Isothermal amplification-based approaches have also been recently demonstrated for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection by minimizing sample preparation while also reducing the instrumentation and reaction complexity. In addition, there are limited reports of saliva as the sample source, and some of these indicate inferior sensitivity when comparing reverse transcription loop-mediated isothermal amplification (RT-LAMP) with PCR-based techniques. In this paper, we demonstrate an improved sensitivity assay from saliva using a two-step RT-LAMP assay, where a short 10 min RT step is performed with only B3 and backward inner primers before the final reaction. We show that while the one-step RT-LAMP demonstrates satisfactory results, the optimized two-step approach allows detection of only few molecules per reaction and performs significantly better than the one-step RT-LAMP and conventional two-step RT-LAMP approaches with all primers included in the RT step. We show control measurements with RT-PCR, and importantly, we demonstrate RNA extraction-free RT-LAMP-based assays for detection of SARS-CoV-2 from viral transport media and saliva clinical samples.

COVID-19 Point-of-Care Diagnostics: Present and Future.

Point-of-care (POC) detection technologies that enable decentralized, rapid, sensitive, low-cost diagnostics of COVID-19 infection are urgently needed around the world. With many technologies approved for commercialization in the past 10 months, the field of COVID-19 POC diagnostics is rapidly evolving. In this Perspective, we analyze the current state of POC technologies for the diagnosis and monitoring of COVID-19 infection and discuss future challenges in COVID-19 diagnostics. As the COVID-19 pandemic becomes endemic, the advances gained during this past year will likely also be utilized for future prediction of emerging outbreaks and pandemics.

Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm.

In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm system for pressure-cycled ventilators that estimates clinically useful metrics such as pressure and respiratory rate and sounds an alarm when the ventilator malfunctions. A low-complexity signal processing algorithm uses a pair of nonlinear recursive envelope trackers to monitor the signal from an electronic pressure sensor connected to the patient airway. The algorithm, inspired by those used in hearing aids, requires little memory and performs only a few calculations on each sample so that it can run on nearly any microcontroller.