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1.
Health Data Sci ; 2022: 9830476, 2022.
Article in English | MEDLINE | ID: covidwho-2286297

ABSTRACT

Background: During the COVID-19 pandemic, mobile sensing and data analytics techniques have demonstrated their capabilities in monitoring the trajectories of the pandemic, by collecting behavioral, physiological, and mobility data on individual, neighborhood, city, and national scales. Notably, mobile sensing has become a promising way to detect individuals' infectious status, track the change in long-term health, trace the epidemics in communities, and monitor the evolution of viruses and subspecies. Methods: We followed the PRISMA practice and reviewed 60 eligible papers on mobile sensing for monitoring COVID-19. We proposed a taxonomy system to summarize literature by the time duration and population scale under mobile sensing studies. Results: We found that existing literature can be naturally grouped in four clusters, including remote detection, long-term tracking, contact tracing, and epidemiological study. We summarized each group and analyzed representative works with regard to the system design, health outcomes, and limitations on techniques and societal factors. We further discussed the implications and future directions of mobile sensing in communicable diseases from the perspectives of technology and applications. Conclusion: Mobile sensing techniques are effective, efficient, and flexible to surveil COVID-19 in scales of time and populations. In the post-COVID era, technical and societal issues in mobile sensing are expected to be addressed to improve healthcare and social outcomes.

2.
Health data science ; 2022, 2022.
Article in English | EuropePMC | ID: covidwho-2112024

ABSTRACT

Background During the COVID-19 pandemic, mobile sensing and data analytics techniques have demonstrated their capabilities in monitoring the trajectories of the pandemic, by collecting behavioral, physiological, and mobility data on individual, neighborhood, city, and national scales. Notably, mobile sensing has become a promising way to detect individuals' infectious status, track the change in long-term health, trace the epidemics in communities, and monitor the evolution of viruses and subspecies. Methods We followed the PRISMA practice and reviewed 60 eligible papers on mobile sensing for monitoring COVID-19. We proposed a taxonomy system to summarize literature by the time duration and population scale under mobile sensing studies. Results We found that existing literature can be naturally grouped in four clusters, including remote detection, long-term tracking, contact tracing, and epidemiological study. We summarized each group and analyzed representative works with regard to the system design, health outcomes, and limitations on techniques and societal factors. We further discussed the implications and future directions of mobile sensing in communicable diseases from the perspectives of technology and applications. Conclusion Mobile sensing techniques are effective, efficient, and flexible to surveil COVID-19 in scales of time and populations. In the post-COVID era, technical and societal issues in mobile sensing are expected to be addressed to improve healthcare and social outcomes.

3.
J Public Health Manag Pract ; 28(6): 682-692, 2022.
Article in English | MEDLINE | ID: covidwho-2107680

ABSTRACT

CONTEXT: Between April 2020 and May 2021, the Centers for Disease Control and Prevention (CDC) awarded more than $40 billion to health departments nationwide for COVID-19 prevention and response activities. One of the identified priorities for this investment was improving infection prevention and control (IPC) in nursing homes. PROGRAM: CDC developed a virtual course to train new and less experienced public health staff in core healthcare IPC principles and in the application of CDC COVID-19 healthcare IPC guidance for nursing homes. IMPLEMENTATION: From October 2020 to August 2021, the CDC led training sessions for 12 cohorts of public health staff using pretraining reading materials, case-based scenarios, didactic presentations, peer-learning opportunities, and subject matter expert-led discussions. Multiple electronic assessments were distributed to learners over time to measure changes in self-reported knowledge and confidence and to collect feedback on the course. Participating public health programs were also assessed to measure overall course impact. EVALUATION: Among 182 enrolled learners, 94% completed the training. Most learners were infection preventionists (42%) or epidemiologists (38%), had less than 1 year of experience in their health department role (75%), and had less than 1 year of subject matter experience (54%). After training, learners reported increased knowledge and confidence in applying the CDC COVID-19 healthcare IPC guidance for nursing homes (≥81%) with the greatest increase in performing COVID-19 IPC consultations and assessments (87%). The majority of participating programs agreed that the course provided an overall benefit (88%) and reduced training burden (72%). DISCUSSION: The CDC's virtual course was effective in increasing public health capacity for COVID-19 healthcare IPC in nursing homes and provides a possible model to increase IPC capacity for other infectious diseases and other healthcare settings. Future virtual healthcare IPC courses could be enhanced by tailoring materials to health department needs, reinforcing training through applied learning experiences, and supporting mechanisms to retain trained staff.


Subject(s)
COVID-19 , COVID-19/epidemiology , COVID-19/prevention & control , Health Personnel/education , Humans , Infection Control , Nursing Homes , Public Health
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