How Can Nursing Teams Respond to Large-Scale COVID-19 Screening?

Zhao, Huihan; He, Yu; Brister, Fang; Yang, Li; Li, Gaoye; Ling, Ying; Ying, Yanping

doi:10.3389/fpubh.2021.681255

Cited by 4 publications

(2 citation statements)

References 10 publications

(11 reference statements)

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“…Public health centers are basic but core institutions within the public healthcare network, while public health nurses (PHNs) provide primary healthcare services to community residents for disease prevention and health promotion [ 1 ]. However, during the global pandemic crisis, PHNs have faced a sharp increase in their workload for infection control and dealing with complaints [ 2 ], screening [ 3 ], as well as added work for cohort isolation, contact tracing, and self-isolation training; vaccination; and follow-up actions for adverse symptoms after vaccination [ 4 ]. Accordingly, PHNs are suffering from physical and mental fatigue and burnout due to increased workload, emergency shifts, task shifting, and role changes caused by the pandemic [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Emotional Labor and Burnout of Public Health Nurses during the COVID-19 Pandemic: Mediating Effects of Perceived Health Status and Perceived Organizational Support

Kim

Yoo

Cho

et al. 2022

IJERPH

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The purpose of this study was to identify the mediating effects of perceived health status (PHS) and perceived organizational support (POS) in the association between emotional labor and burnout in public health nurses (PHNs). The participants were 207 PHNs convenience sampled from 30 public health centers and offices in Jeju, Korea. Data regarding emotional labor, PHS, POS, and burnout were collected between February and March 2021 using a structured questionnaire. Collected data were analyzed by Pearson’s correlation coefficient and multiple regression analysis. Burnout of PHNs was positively correlated with emotional labor (r = 0.64, p < 0.001) and negatively correlated with PHS (r = −0.51, p < 0.001) and POS (r = −0.51, p < 0.001). In the association between emotional labor and burnout, PHS (B = −1.36, p < 0.001) and POS (B = −0.42, p = 0.001) had a partial mediating effect. Reduction of burnout among PHNs requires not only effective management of emotional labor but also personal and organizational efforts to improve PHS and POS.

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Section: Introductionmentioning

confidence: 99%

Emotional Labor and Burnout of Public Health Nurses during the COVID-19 Pandemic: Mediating Effects of Perceived Health Status and Perceived Organizational Support

Kim

Yoo

Cho

et al. 2022

IJERPH

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“…Sample pooling speeds up the whole disease screening process. When conducting large-scale population testing, typically 5–10 samples can be mixed for preliminary screening to improve testing efficiency and reduce testing costs [ 7 , 8 ]. Sample pooling is a solution to the testing pressure of large samples [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

All-People-Test-Based Methods for COVID-19 Infectious Disease Dynamics Simulation Model: Towards Citywide COVID Testing

Liu

Yang

Fong

et al. 2022

IJERPH

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The conversion rate between asymptomatic infections and reported/unreported symptomatic infections is a very sensitive parameter for model variables that spread COVID-19. This is important information for follow-up use in screening, prediction, prognostics, contact tracing, and drug development for the COVID-19 pandemic. The model described here suggests that there may not be enough researchers to solve all of these problems thoroughly and effectively, and it requires careful selection of what we are doing and rapid sharing of results and models and optimizing modeling simulations with value to reduce the impact of COVID-19. Exploring simulation modeling will help decision makers make the most informed decisions. In order to fight against the “Delta” virus, the establishment of a line of defense through all-people testing (APT) is not only an effective method summarized from past experience but also one of the best means to effectively cut the chain of epidemic transmission. The effect of large-scale testing has been fully verified in the international community. We developed a practical dynamic infectious disease model-SETPG (A + I) RD + APT by considering the effects of the all-people test (APT). The model is useful for studying effects of screening measures and providing a more realistic modelling with all-people-test strategies, which require everybody in a population to be tested for infection. In prior work, a total of 370 epidemic cases were collected. We collected three kinds of known cases: the cumulative number of daily incidences, daily cumulative recovery, and daily cumulative deaths in Hong Kong and the United States between 22 January 2020 and 13 November 2020 were simulated. In two essential strategies of the integrated SETPG (A + I) RD + APT model, comparing the cumulative number of screenings in derivative experiments based on daily detection capability and tracking system application rate, we evaluated the performance of the timespan required for the basic regeneration number (R0) and real-time regeneration number (R0t) to reach 1; the optimal policy of each experiment is available, and the screening effect is evaluated by screening performance indicators. with the binary encoding screening method, the number of screenings for the target population is 8667 in HK and 1,803,400 in the U.S., including 6067 asymptomatic cases in HK and 1,262,380 in the U.S. as well as 2599 cases of mild symptoms in HK and 541,020 in the U.S.; there were also 8.25 days of screening timespan in HK and 9.25 days of screening timespan required in the U.S. and a daily detectability of 625,000 cases in HK and 6,050,000 cases in the U.S. Using precise tracking technology, number of screenings for the target population is 6060 cases in HK and 1,766,420 cases in the U.S., including 4242 asymptomatic cases in HK and 1,236,494 cases in the U.S. as well as 1818 cases of mild symptoms in HK and 529,926 cases in the U.S. Total screening timespan (TS) is 8.25~9.25 days. According to the proposed infectious dynamics model that adapts to the all-people test, all of the epidemic cases were reported for fitting, and the result seemed more reasonable, and epidemic prediction became more accurate. It adapted to densely populated metropolises for APT on prevention.

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A two-stage location model covering COVID-19 sampling, transport and DNA diagnosis: design of a national scheme for infection control

Fei,

Jiamin,

Chunting

et al. 2024

Geospat Health

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During the COVID-19 pandemic, a system was established in China that required testing of all residents for COVID-19. It consisted of sampling stations, laboratories capable of carrying out DNA investigations and vehicles carrying out immediate transfer of all samples from the former to the latter. Using Beilin District, Xi’an City, Shaanxi Province, China as example, we designed a genetic algorithm based on a two-stage location coverage model for the location of the sampling stations with regard to existing residencies as well as the transfer between the sampling stations and the laboratories. The aim was to estimate the minimum transportation costs between these units. In the first stage, the model considered demands for testing in residential areas, with the objective of minimizing the costs related to travel between residencies and sampling stations. In the second stage, this approach was extended to cover the location of the laboratories doing the DNAinvestigation, with the aim of minimizing the transportation costs between them and the sampling stations as well as the estimating the number of laboratories needed. Solutions were based on sampling stations and laboratories existing in 2022, with the results visualized by geographic information systems (GIS). The results show that the genetic algorithm designed in this paper had a better solution speed than the Gurobi algorithm. The convergence was better and the larger the network size, the more efficient the genetic algorithm solution time.

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How Can Nursing Teams Respond to Large-Scale COVID-19 Screening?

Cited by 4 publications

References 10 publications

Emotional Labor and Burnout of Public Health Nurses during the COVID-19 Pandemic: Mediating Effects of Perceived Health Status and Perceived Organizational Support

Emotional Labor and Burnout of Public Health Nurses during the COVID-19 Pandemic: Mediating Effects of Perceived Health Status and Perceived Organizational Support

All-People-Test-Based Methods for COVID-19 Infectious Disease Dynamics Simulation Model: Towards Citywide COVID Testing

A two-stage location model covering COVID-19 sampling, transport and DNA diagnosis: design of a national scheme for infection control

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