An official website of the United States government
Abstract ObjectivesWe conducted interviews with state epidemiologists involved in the state-level COVID-19 response to understand the challenges and opportunities that state epidemiologists and state health departments faced during COVID-19 and consider the implications for future pandemic responses. MethodsAs part of a broader study on policymaking during COVID-19, we analyzed 12 qualitative interviews with state-epidemiologists from 11 US states regarding the challenges and opportunities they experienced during the COVID-19 response. ResultsInterviewees described the unprecedented demands COVID-19 placed on them, including increased workloads as well as political and public scrutiny. Decades of under-funding and constraints posed particular challenges for meeting these demands and compromised state responses. Emergency funding contributed to ameliorating some challenges. However, state health departments were unable to absorb the funds quickly, which created added pressure for employees. The emergency funding also did not resolve longstanding resource deficits. ConclusionsState health departments were not equipped to meet the demands of a comprehensive COVID-19 response, and increased funding failed to address shortfalls. Effective future pandemic responses will require sustained investment and adequate support to manage on-going and surge capacity needs. Increased public interest and skepticism complicated the COVID-19 response, and additional measures are needed to address these factors.
more »
« less
Work technology and Covid-19: Demands and resources
The COVID-19 pandemic has not only placed new demands on society in general but has also exacerbated the demands placed on employees in organizations. Adapting to the use of new technologies can be seen as a job demand under the JD-R framework of workplace motivation and stress. This longitudinal survey study examined the effects of multiple resources and demands on strain in employed individuals. Results indicate that the use of technology as well as the perceived threat of COVID-19 were significant predictors of reduced well-being. Implications for research and practice are discussed.
more »
« less
- Award ID(s):
- 2027332
- PAR ID:
- 10330793
- Date Published:
- Journal Name:
- Society for Industrial Organizational Psychology Annual Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in New York City. With New York City open data, human mobility pattern changes were detected by different categories of land use, including residential, parks, transportation facilities, and workplaces. This study further compares human mobility patterns by land use types based on an open social media platform (Twitter) and the human mobility patterns revealed by Google Community Mobility Report cell phone location, indicating that in some applications, open-access social media data can generate similar results to private data. The results of this study can be further used for human mobility analysis and the battle against COVID-19.more » « less
-
null (Ed.)The coronavirus disease 2019 (COVID-19) pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed epidemic modeling at the center of attention of public policymaking. Predicting the severity and speed of transmission of COVID-19 is crucial to resource management and developing strategies to deal with this epidemic. Based on the available data from current and previous outbreaks, many efforts have been made to develop epidemiological models, including statistical models, computer simulations, mathematical representations of the virus and its impacts, and many more. Despite their usefulness, modeling and forecasting the spread of COVID-19 remains a challenge. In this article, we give an overview of the unique features and issues of COVID-19 data and how they impact epidemic modeling and projection. In addition, we illustrate how various models could be connected to each other. Moreover, we provide new data science perspectives on the challenges of COVID-19 forecasting, from data collection, curation, and validation to the limitations of models, as well as the uncertainty of the forecast. Finally, we discuss some data science practices that are crucial to more robust and accurate epidemic forecasting.more » « less
-
Background The surge of telemedicine use during the early stages of the COVID-19 pandemic has been well documented. However, scarce evidence considers the use of telemedicine in the subsequent period. Objective This study aims to evaluate use patterns of video-based telemedicine visits for ambulatory care and urgent care provision over the course of recurring pandemic waves in 1 large health system in New York City (NYC) and what this means for health care delivery. Methods Retrospective electronic health record (EHR) data of patients from January 1, 2020, to February 28, 2022, were used to longitudinally track and analyze telemedicine and in-person visit volumes across ambulatory care specialties and urgent care, as well as compare them to a prepandemic baseline (June-November 2019). Diagnosis codes to differentiate suspected COVID-19 visits from non–COVID-19 visits, as well as evaluating COVID-19–based telemedicine use over time, were compared to the total number of COVID-19–positive cases in the same geographic region (city level). The time series data were segmented based on change-point analysis, and variances in visit trends were compared between the segments. Results The emergence of COVID-19 prompted an early increase in the number of telemedicine visits across the urgent care and ambulatory care settings. This use continued throughout the pandemic at a much higher level than the prepandemic baseline for both COVID-19 and non–COVID-19 suspected visits, despite the fluctuation in COVID-19 cases throughout the pandemic and the resumption of in-person clinical services. The use of telemedicine-based urgent care services for COVID-19 suspected visits showed more variance in response to each pandemic wave, but telemedicine visits for ambulatory care have remained relatively steady after the initial crisis period. During the Omicron wave, the use of all visit types, including in-person activities, decreased. Patients between 25 and 34 years of age were the largest users of telemedicine-based urgent care. Patient satisfaction with telemedicine-based urgent care remained high despite the rapid scaling of services to meet increased demand. Conclusions The trend of the increased use of telemedicine as a means of health care delivery relative to the pre–COVID-19 baseline has been maintained throughout the later pandemic periods despite fluctuating COVID-19 cases and the resumption of in-person care delivery. Overall satisfaction with telemedicine-based care is also high. The trends in telemedicine use suggest that telemedicine-based health care delivery has become a mainstream and sustained supplement to in-person-based ambulatory care, particularly for younger patients, for both urgent and nonurgent care needs. These findings have implications for the health care delivery system, including practice leaders, insurers, and policymakers. Further investigation is needed to evaluate telemedicine adoption by key demographics, identify ongoing barriers to adoption, and explore the impacts of sustained use of telemedicine on health care outcomes and experience.more » « less
-
null (Ed.)The COVID-19 pandemic has placed an overwhelming strain on our Nation's ability to treat patients; the number of patients who need to be tested continues to rise. With nurses also becoming infected, the number of trained professionals who can perform tasks such as testing of patients along with providing care involving hooking up patients to ventilators continues to decrease as well. There is a need to explore the adoption of virtual computer based training mediums which will enable new nurses and others to be trained in safe and efficient procedures involving patients during this pandemic period. In this paper, the design of a VR based simulator based on Human Centered Computing (HCC) principles is discussed. The role of HCC factors such as affordance and cognitive load on the comprehension and scene understanding of nurses during training and the acquisition of knowledge of safety procedures and detailed steps (pertaining to nasal sample collection and use of ventilators on patients) has been studied with the involvement of nurse and nurse trainee participants. Adoption of a participatory design approach involving experts (nurses, doctors involved in covid-19 testing and treatment) has provided a foundational basis for design of the training environments and assessment activities. Formal information centric process models of the nasal swabbing procedures and ventilator hookup tasks were created using the engineering Enterprise Modeling Language (eEML). The preliminary results from the assessment activities indicate the positive impact of such HCC based 3Dsimulators in such training of first responders.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
