Design of COVID-19 Staged Alert Systems to Ensure Healthcare Capacity with Minimal Closures.
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ABSTRACT:
SUBMITTER: Yang H
PROVIDER: S-EPMC7709193 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France's ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.
| S-EPMC8213780 | biostudies-literature
Project description:Objective To determine how COVID-19-related healthcare closures affect the health, recovery and access to resources of preoperative and postoperative orthopaedic sport medicine patients. Methods Patients whose orthopaedic restorative surgeries were postponed as well as those within 3 months postoperative completed electronic questionnaires assessing physical health, emotional health, virtual care and access to resources. The EuroQoL-five-dimensional-three level (EQ-5D-3L) was included as a quantitative and standardised measure of general health status. Data were descriptively analysed using means, SD and qualitative measures. Results A total of 115 patients whose surgeries were postponed completed the survey. Notable findings included that 41.7% of patients reported an increase in their symptoms during the COVID-19-related closures, and 68.7% described a negative impact on their physical health. Furthermore, 62.6% of patients reported that the postponement of their surgery would negatively affect their ability to return to work. A substantial percentage of patients (71.3%) reported that postponement of their surgery had an overall negative impact on their physical and/or emotional health. The mean health state on the EQ-5D-3L visual analogue scale (VAS) scale was 69.9 (SD=18.7). A total of 198 patients within 3 months postoperative completed the survey. A majority of patients (69.7%) indicated that COVID-19-related healthcare closures had an overall negative affect on their recovery. One-third of patients (35.4%) stated that they experienced increased symptoms as a direct result of limited postoperative follow-up. Less than half (41.4%) of patients accessed virtual physiotherapy, and only 42.9% of those that did found it to be helpful in some way. Virtual orthopaedic follow-up was deemed helpful by 61.3% of patients but many commented that it did not replace inperson visits. The mean health state reported on the EQ-5D-3L VAS scale was 76.9 (SD=15.6). Conclusion This study highlighted the significant impact of COVID-19-related healthcare closures on preoperative and postoperative orthopaedic sport medicine patients. It revealed that restorative procedures play an important role in maintaining physical and emotional health, as well as returning individuals to work and leisure activities. It also showed that virtual care did not adequately replace the hands-on assessments of allied care and orthopaedic specialists. Level of Evidence V.
| S-EPMC7476420 | biostudies-literature
Project description:Although molecular self-organization and pattern formation are key features of life, only very few pattern-forming biochemical systems have been identified that can be reconstituted and studied in vitro under defined conditions. A systematic understanding of the underlying mechanisms is often hampered by multiple interactions, conformational flexibility and other complex features of the pattern forming proteins. Because of its compositional simplicity of only two proteins and a membrane, the MinDE system from Escherichia coli has in the past years been invaluable for deciphering the mechanisms of spatiotemporal self-organization in cells. Here, we explored the potential of reducing the complexity of this system even further, by identifying key functional motifs in the effector MinE that could be used to design pattern formation from scratch. In a combined approach of experiment and quantitative modeling, we show that starting from a minimal MinE-MinD interaction motif, pattern formation can be obtained by adding either dimerization or membrane-binding motifs. Moreover, we show that the pathways underlying pattern formation are recruitment-driven cytosolic cycling of MinE and recombination of membrane-bound MinE, and that these differ in their in vivo phenomenology.
| S-EPMC6922632 | biostudies-literature
Project description:The process of inferring parameter values from experimental data can be a cumbersome task. In addition, the collection of experimental data can be time consuming and costly. This paper covers both these issues by addressing the following question: "Which experimental outputs should be measured to ensure that unique model parameters can be calculated?". Stated formally, we examine the topic of minimal output sets that guarantee a model's structural identifiability. To that end, we introduce an algorithm that guides a researcher as to which model outputs to measure. Our algorithm consists of an iterative structural identifiability analysis and can determine multiple minimal output sets of a model. This choice in different output sets offers researchers flexibility during experimental design. Our method can determine minimal output sets of large differential equation models within short computational times.
| S-EPMC6231658 | biostudies-literature
Project description:RNA was extracted from whole blood of subjects collected in Tempus tubes prior to COVID-19 mRNA booster vaccination. D01 and D21 correspond to samples collected at pre-dose 1 and pre-dose 2 respectively. RNA was also extracted from blood collected at indicated time points post-vaccination. DB1, DB2, DB4 and DB7 correspond to booster day 1 (pre-booster), booster day 2, booster day 4 and booster day 7 respectively. The case subject experienced cardiac complication following mRNA booster vaccination. We performed gene expression analysis of case versus controls over time.
2023-03-20 | E-MTAB-12829 | biostudies-arrayexpress
Project description: Not available
| S-BSST563 | biostudies-other
Project description:Declines in health service use during the Coronavirus Disease 2019 (COVID-19) pandemic could have important effects on population health. In this study, we used an interrupted time series design to assess the immediate effect of the pandemic on 31 health services in two low-income (Ethiopia and Haiti), six middle-income (Ghana, Lao People's Democratic Republic, Mexico, Nepal, South Africa and Thailand) and high-income (Chile and South Korea) countries. Despite efforts to maintain health services, disruptions of varying magnitude and duration were found in every country, with no clear patterns by country income group or pandemic intensity. Disruptions in health services often preceded COVID-19 waves. Cancer screenings, TB screening and detection and HIV testing were most affected (26-96% declines). Total outpatient visits declined by 9-40% at national levels and remained lower than predicted by the end of 2020. Maternal health services were disrupted in approximately half of the countries, with declines ranging from 5% to 33%. Child vaccinations were disrupted for shorter periods, but we estimate that catch-up campaigns might not have reached all children missed. By contrast, provision of antiretrovirals for HIV was not affected. By the end of 2020, substantial disruptions remained in half of the countries. Preliminary data for 2021 indicate that disruptions likely persisted. Although a portion of the declines observed might result from decreased needs during lockdowns (from fewer infectious illnesses or injuries), a larger share likely reflects a shortfall of health system resilience. Countries must plan to compensate for missed healthcare during the current pandemic and invest in strategies for better health system resilience for future emergencies.
| S-EPMC9205770 | biostudies-literature
Project description:BackgroundOur healthcare institution was one of the first to see SARS CoV-2 cases in the country. We describe the early COVID-19 experience of a private hospital in the Philippines and discuss the healthcare system response in the setting of surge capacity.MethodsWe reviewed the medical records of adult COVID-19 hospitalized patients admitted in March 2020. We reported their demographic and clinical characteristics using descriptive statistics.ResultsOf 40 patients admitted, 23 (57.5%) were male and 19 (47.5%) were aged <60 years. Most (n = 27, 67.5%) had moderate-risk, 9 (22.5%) had high-risk, and 4 (10%) had low-risk COVID-19. SARS-CoV-2 testing took 5.5 (range 1-10) days. Overall mortality rate was 6/40 (15.0%). Clinical cure was documented in all low-risk patients, 25 (92.6%) moderate-risk patients, and only 1 (11.1%) high-risk patient. In response to the surge, the hospital rapidly introduced one-way traffic systems, dedicated screening, triage and Emergency Department areas for COVID-19, a clinical pathway, engineering controls, patient cohorting, and strict infection prevention and control measures.ConclusionMajority of patients recovered from COVID-19. Older age and high-risk pneumonia were associated with poor outcomes. Adaptations to hospital structure and staff were quickly made in response to surge capacity, although our response was hampered by prolonged time to COVID-19 confirmation. Our study underscores the urgent need for rapid adaptive response by the healthcare system to address the surge of cases.
| S-EPMC7813488 | biostudies-literature
Project description:ObjectivesPrevious studies have looked at National Early Warning Score performance in predicting in-hospital deterioration and death, but data are lacking with respect to patient outcomes following implementation of National Early Warning Score. We sought to determine the effectiveness of National Early Warning Score implementation on predicting and preventing patient deterioration in a clinical setting.DesignRetrospective cohort study.SettingTertiary care academic facility and a community hospital.PatientsPatients 18 years old or older hospitalized from March 1, 2014, to February 28, 2015, during preimplementation of National Early Warning Score to August 1, 2015, to July 31, 2016, after National Early Warning Score was implemented.InterventionsImplementation of National Early Warning Score within the electronic health record and associated best practice alert.Measurements and main resultsIn this study of 85,322 patients (42,402 patients pre-National Early Warning Score and 42,920 patients post-National Early Warning Score implementation), the primary outcome of rate of ICU transfer or death did not change after National Early Warning Score implementation, with adjusted hazard ratio of 0.94 (0.84-1.05) and 0.90 (0.77-1.05) at our academic and community hospital, respectively. In total, 175,357 best practice advisories fired during the study period, with the best practice advisory performing better at the community hospital than the academic at predicting an event within 12 hours 7.4% versus 2.2% of the time, respectively. Retraining National Early Warning Score with newly generated hospital-specific coefficients improved model performance.ConclusionsAt both our academic and community hospital, National Early Warning Score had poor performance characteristics and was generally ignored by frontline nursing staff. As a result, National Early Warning Score implementation had no appreciable impact on defined clinical outcomes. Refitting of the model using site-specific data improved performance and supports validating predictive models on local data.
| S-EPMC6298839 | biostudies-literature
Project description:BackgroundThe adoption of contact tracing apps worldwide has been low. Although considerable research has been conducted on technology acceptance, little has been done to show the benefit of incorporating persuasive principles.ObjectiveThis research aimed to investigate the effect of persuasive features in the COVID Alert app, created by Health Canada, by focusing on the no-exposure status, exposure status, and diagnosis report interfaces.MethodsWe conducted a study among 181 Canadian residents, including 65 adopters and 116 nonadopters. This study was based on screenshots of the 3 interfaces, of which each comprised a persuasive design and a control design. The persuasive versions of the first two interfaces supported self-monitoring (of exposure levels), and that of the third interface supported social learning (about how many other users have reported their diagnosis). The 6 screenshots were randomly assigned to 6 groups of participants to provide feedback on perceived persuasiveness and adoption willingness.ResultsA multivariate repeated-measure ANOVA showed that there is an interaction among interface, app design, and adoption status regarding the perceived persuasiveness of the interfaces. This resulted in a 2-way ANOVA for each interface. For the no-exposure interface, there was an interaction between adoption status and app design. Among adopters, there was no significant difference P=.31 between the persuasive design (mean 5.36, SD 1.63) and the control design (mean 5.87, SD 1.20). However, among nonadopters, there was an effect of app design (P<.001), with participants being more motivated by the persuasive design (mean 5.37, SD 1.30) than by the control design (mean 4.57, SD 1.19). For the exposure interface, adoption status had a main effect (P<.001), with adopters (mean 5.91, SD 1.01) being more motivated by the designs than nonadopters (mean 4.96, SD 1.43). For the diagnosis report interface, there was an interaction between adoption status and app design. Among nonadopters, there was no significant difference P=.99 between the persuasive design (mean 4.61, SD 1.84) and the control design (mean 4.77, SD 1.21). However, among adopters, there was an effect of app design (P=.006), with participants being more likely to report their diagnosis using the persuasive design (mean 6.00, SD 0.97) than using the control design (mean 5.03, SD 1.22). Finally, with regard to willingness to download the app, pairwise comparisons showed that nonadopters were more likely to adopt the app after viewing the persuasive version of the no-exposure interface (13/21, 62% said yes) and the diagnosis report interface (12/17, 71% said yes) than after viewing the control versions (3/17, 18% and 7/16, 44%, respectively, said yes).ConclusionsExposure notification apps are more likely to be effective if equipped with persuasive features. Incorporating self-monitoring into the no-exposure status interface and social learning into the diagnosis report interface can increase adoption by >30%.
| S-EPMC9450945 | biostudies-literature