Geospatial Modeling of Health, Socioeconomic, Demographic, and Environmental Factors with COVID-19 Incidence Rate in Arkansas, US

The COVID-19 pandemic has posed numerous challenges to human society. Previous studies explored multiple factors in virus transmission. Yet, their impacts on COVID-19 are not universal and vary across geographical regions. In this study, we thoroughly quantified the spatiotemporal associations of 49 health, socioeconomic, demographic, and environmental factors with COVID-19 at the county level in Arkansas, US. To identify the associations, we applied the ordinary least squares (OLS) linear regression, spatial lag model (SLM), spatial error model (SEM), and multiscale geographically weighted regression (MGWR) model. To reveal how such associations change across different COVID-19 times, we conducted the analyses for each season (i.e., spring, summer, fall, and winter) from 2020 to 2021. We demonstrate that there are different driving factors along with different COVID-19 variants, and their magnitudes change spatiotemporally. However, our results identify that adult obesity has a positive association with the COVID-19 incidence rate over entire Arkansas, thus confirming that people with obesity are vulnerable to COVID-19. Humidity consistently negatively affects COVID-19 across all seasons, denoting that increasing humidity could reduce the risk of COVID-19 infection. In addition, diabetes shows roles in the spread of both early COVID-19 variants and Delta, while humidity plays roles in the spread of Delta and Omicron. Our study highlights the complexity of how multifactor affect COVID-19 in different seasons and counties in Arkansas. These findings are useful for informing local health planning (e.g., vaccine rollout, mask regulation, and testing/tracing) for the residents in Arkansas.

Geospatial Modeling of Health, Socioeconomic, Demographic, and Environmental Factors with COVID-19 Incidence Rate in Arkansas, US

The COVID-19 pandemic has posed numerous challenges to human society. Previous studies explored multiple factors in virus transmission. Yet, their impacts on COVID-19 are not universal and vary across geographical regions. In this study, we thoroughly quantified the spatiotemporal associations of 49 health, socioeconomic, demographic, and environmental factors with COVID-19 at the county level in Arkansas, US. To identify the associations, we applied the ordinary least squares (OLS) linear regression, spatial lag model (SLM), spatial error model (SEM), and multiscale geographically weighted regression (MGWR) model. To reveal how such associations change across different COVID-19 times, we conducted the analyses for each season (i.e., spring, summer, fall, and winter) from 2020 to 2021. We demonstrate that there are different driving factors along with different COVID-19 variants, and their magnitudes change spatiotemporally. However, our results identify that adult obesity has a positive association with the COVID-19 incidence rate over entire Arkansas, thus confirming that people with obesity are vulnerable to COVID-19. Humidity consistently negatively affects COVID-19 across all seasons, denoting that increasing humidity could reduce the risk of COVID-19 infection. In addition, diabetes shows roles in the spread of both early COVID-19 variants and Delta, while humidity plays roles in the spread of Delta and Omicron. Our study highlights the complexity of how multifactor affect COVID-19 in different seasons and counties in Arkansas. These findings are useful for informing local health planning (e.g., vaccine rollout, mask regulation, and testing/tracing) for the residents in Arkansas.

The Application of Awake-Prone Positioning Among Non-intubated Patients With COVID-19-Related ARDS: A Narrative Review.

The coronavirus disease (COVID-19) pandemic has significantly increased the number of patients with acute respiratory distress syndrome (ARDS), necessitating respiratory support. This strain on intensive care unit (ICU) resources forces clinicians to limit the use of mechanical ventilation by seeking novel therapeutic strategies. Awake-prone positioning appears to be a safe and tolerable intervention for non-intubated patients with hypoxemic respiratory failure. Meanwhile, several observational studies and meta-analyses have reported the early use of prone positioning in awake patients with COVID-19-related ARDS (C-ARDS) for improving oxygenation levels and preventing ICU transfers. Indeed, some international guidelines have recommended the early application of awake-prone positioning in patients with hypoxemic respiratory failure attributable to C-ARDS. However, its effectiveness in reducing intubation rate, mortality, applied timing, and optimal duration is unclear. High-quality evidence of awake-prone positioning for hypoxemic patients with COVID-19 is still lacking. Therefore, this article provides an update on the current state of published literature about the physiological rationale, effect, timing, duration, and populations that might benefit from awake proning. Moreover, the risks and adverse effects of awake-prone positioning were also investigated. This work will guide future studies and aid clinicians in deciding on better treatment plans.

Shared mechanisms and crosstalk of COVID-19 and osteoporosis via vitamin D.

Recently accumulated evidence implicates a close association of vitamin D (VitD) insufficiency to the incidence and clinical manifestations of the COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Populations with insufficient VitD including patients with osteoporosis are more susceptible to SARS-COV-2 infection and patients with COVID-19 worsened or developed osteoporosis. It is currently unknown, however, whether osteoporosis and COVID-19 are linked by VitD insufficiency. In this study, 42 common targets for VitD on both COVID-19 and osteoporosis were identified among a total of 243 VitD targets. Further bioinformatic analysis revealed 8 core targets (EGFR, AR, ESR1, MAPK8, MDM2, EZH2, ERBB2 and MAPT) in the VitD-COVID-19-osteoporosis network. These targets are involved in the ErbB and MAPK signaling pathways critical for lung fibrosis, bone structural integrity, and cytokines through a crosstalk between COVID-19 and osteoporosis via the VitD-mediated conventional immune and osteoimmune mechanisms. Molecular docking confirmed that VitD binds tightly to the predicted targets. These findings support that VitD may target common signaling pathways in the integrated network of lung fibrosis and bone structural integrity as well as the immune systems. Therefore, VitD may serve as a preventive and therapeutic agent for both COVID-19 and osteoporosis.

The Influence of Occupational Therapy on College Students' Home Physical Exercise Behavior and Mental Health Status under the Artificial Intelligence Technology.

The core of occupational therapy is to help patients with mental illness recover their social work, give play to their self-worth, obtain financial resources, and improve their self-confidence. Occupational therapy can help patients relieve symptoms and restore social function, reduce disease recurrence, and improve the reemployment rate and the overall health level of patients. In order to deeply excavate the inner connection between the mental health status and physical exercise status of college students, the physical exercise behavior of college students during home isolation is studied. First, the "physical exercise behavior questionnaire" and "symptom self-assessment scale" were used to investigate the physical exercise behavior and mental health status of college students. Second, descriptive statistics, correlation analysis, independent sample t-test, and variance analysis were carried out on the survey results using mathematical statistics methods and big data technology. The survey results show high reliability, and the Cronbach's α coefficients were all greater than 0.9. There was a positive correlation between physical exercise methods and mental health in general, and the difference in the degree of exercise is significantly different from the mental health of students (p < 0.05). With the increase of exercise intensity, the score of "symptom self-assessment scale" first decreased and then increased, and the exercise intensity of medium and high intensity showed the best psychological state. And the correlation dimension of depression was the highest. This indicated that the students who liked family physical exercise were less likely to suffer from depression. In addition, depression was the most relevant dimension with self demand physical exercise, and interpersonal sensitivity was the most relevant dimension with social expansion physical exercise. The conclusion shows that the more active the students participate in family physical exercise, the healthier their mental state is. Occupational therapy has obvious curative effect on depression, which can improve patients' negative symptoms, their living ability, and social function. Meanwhile, analyzing data through big data technology reduces human workload and improves data processing efficiency and accuracy. The scheme proposed here provides some ideas for the application of big data technology in occupational therapy.

Spatiotemporal disparities in regional public risk perception of COVID-19 using Bayesian Spatiotemporally Varying Coefficients (STVC) series models across Chinese cities.

Regional public attention has been critical during the COVID-19 pandemic, impacting the effectiveness of sub-national non-pharmaceutical interventions. While studies have focused on public attention at the national level, sub-national public attention has not been well investigated. Understanding sub-national public attention can aid local governments in designing regional scientific guidelines, especially in large countries with substantial spatiotemporal disparities in the spread of infections. Here, we evaluated the online public attention to the COVID-19 pandemic using internet search data and developed a regional public risk perception index (PRPI) that depicts heterogeneous associations between local pandemic risk and public attention across 366 Chinese cities. We used the Bayesian Spatiotemporally Varying Coefficients (STVC) model, a full-map local regression for estimating spatiotemporal heterogeneous relationships of variables, and improved it to the Bayesian Spatiotemporally Interacting Varying Coefficients (STIVC) model to incorporate space-time interaction non-stationarity at spatial or temporal stratified scales. COVID-19 daily cases (median contribution 82.6%) was the most critical factor affecting public attention, followed by urban socioeconomic conditions (16.7%) and daily population mobility (0.7%). After adjusting national and provincial impacts, city-level influence factors accounted for 89.4% and 58.6% in spatiotemporal variations of public attention. Spatiotemporal disparities were substantial among cities and provinces, suggesting that observing national-level public dynamics alone was insufficient. Multi-period PRPI maps revealed clusters and outlier cities with potential public panic and low health literacy. Bayesian STVC series models are systematically proposed and provide a multi-level spatiotemporal heterogeneous analytical framework for understanding collective human responses to major public health emergencies and disasters.

The Application of Awake-Prone Positioning Among Non-intubated Patients With COVID-19-Related ARDS: A Narrative Review

The coronavirus disease (COVID-19) pandemic has significantly increased the number of patients with acute respiratory distress syndrome (ARDS), necessitating respiratory support. This strain on intensive care unit (ICU) resources forces clinicians to limit the use of mechanical ventilation by seeking novel therapeutic strategies. Awake-prone positioning appears to be a safe and tolerable intervention for non-intubated patients with hypoxemic respiratory failure. Meanwhile, several observational studies and meta-analyses have reported the early use of prone positioning in awake patients with COVID-19-related ARDS (C-ARDS) for improving oxygenation levels and preventing ICU transfers. Indeed, some international guidelines have recommended the early application of awake-prone positioning in patients with hypoxemic respiratory failure attributable to C-ARDS. However, its effectiveness in reducing intubation rate, mortality, applied timing, and optimal duration is unclear. High-quality evidence of awake-prone positioning for hypoxemic patients with COVID-19 is still lacking. Therefore, this article provides an update on the current state of published literature about the physiological rationale, effect, timing, duration, and populations that might benefit from awake proning. Moreover, the risks and adverse effects of awake-prone positioning were also investigated. This work will guide future studies and aid clinicians in deciding on better treatment plans.

Driving factors of virtual water in international grain trade: A study for belt and road countries

Water resources are distributed in the form of virtual water through international trade, which influences the water supply and consumption of each country. Therefore, it is of significance to study the driving factors of grain virtual water trade to alleviate water stress and guarantee food security. In this paper, the virtual water volume of grain crops traded between China and countries along the Belt and Road (B&R) from 2000 to 2019 was calculated, and a gravity model using panel data was applied to explore the effect of natural and socioeconomic factors on virtual water trade. The virtual water export from B&R countries to China obviously increased in the twenty years and the contributions of various crops to virtual water were more balanced. The regression results indicate that GDP and exchange rate were positively correlated with virtual water inflow, while per capital water resources, arable land, geographic distance, and population were negative factors that hindered virtual water import. The most powerful driving force for grain virtual water trade is water endowment. GDP is an important driver on importing virtual water for countries without water shortage, and a large number of local water resources will not obviously inhibit the driving force of economic strength. By comparing the contribution of factors to virtual water in the past ten years, it can be found that the contribution rate of distance decreased due to the development of transportation industry which reduced the transportation cost of exporting products. The contribution rate of GDP and exchange rate increased, because economic globalization has promoted the effect of economic factors on grain trade. Therefore, the trade structure of agricultural products should be modified based on the characteristics of virtual water flow. For countries without high economic level but water shortage, export crops with high water consumption be reasonably controlled. [Display omitted] • A gravity model was applied to explore the effect of natural and socioeconomic factors on virtual water trade. • The most powerful driving force is water endowment, which were negative factor that hindered virtual water inflow. • Economic strength is an important driver on importing virtual water for countries without water shortage. • The contribution rate of distance decreased due to the development of transportation industry and economic globalization. [ FROM AUTHOR] Copyright of Agricultural Water Management is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Early Prediction of Disease Progression in Patients with Severe COVID-19 Using C-Reactive Protein to Albumin Ratio.

BACKGROUND: Early identification of patients with severe coronavirus disease (COVID-19) at an increased risk of progression may promote more individualized treatment schemes and optimize the use of medical resources. This study is aimed at investigating the utility of the C-reactive protein to albumin (CRP/Alb) ratio for early risk stratification of patients. METHODS: We retrospectively reviewed 557 patients with COVID-19 with confirmed outcomes (discharged or deceased) admitted to the West Court of Union Hospital, Wuhan, China, between January 29, 2020 and April 8, 2020. Patients with severe COVID-19 (n = 465) were divided into stable (n = 409) and progressive (n = 56) groups according to whether they progressed to critical illness or death during hospitalization. To predict disease progression, the CRP/Alb ratio was evaluated on admission. RESULTS: The levels of new biomarkers, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, CRP/Alb ratio, and systemic immune-inflammation index, were higher in patients with progressive disease than in those with stable disease. Correlation analysis showed that the CRP/Alb ratio had the strongest positive correlation with the sequential organ failure assessment score and length of hospital stay in survivors. Multivariate logistic regression analysis showed that percutaneous oxygen saturation (SpO2), D-dimer levels, and the CRP/Alb ratio were risk factors for disease progression. To predict clinical progression, the areas under the receiver operating characteristic curves of Alb, CRP, CRP/Alb ratio, SpO2, and D-dimer were 0.769, 0.838, 0.866, 0.107, and 0.748, respectively. Moreover, patients with a high CRP/Alb ratio (≥1.843) had a markedly higher rate of clinical deterioration (log - rank p < 0.001). A higher CRP/Alb ratio (≥1.843) was also closely associated with higher rates of hospital mortality, ICU admission, invasive mechanical ventilation, and a longer hospital stay. CONCLUSION: The CRP/Alb ratio can predict the risk of progression to critical disease or death early, providing a promising prognostic biomarker for risk stratification and clinical management of patients with severe COVID-19.

Clinical, laboratory, and imaging features of pediatric COVID-19: A systematic review and meta-analysis.

ABSTRACT: Pediatric cases of coronavirus disease 2019 (COVID-19) have been reported. This meta-analysis was aimed at describing the clinical, laboratory, and imaging characteristics of children with COVID-19 based on published data of pediatric COVID-19 cases.Search of PubMed, Embase, Web of Sciences, Science Direct, and Google Scholar for articles published until December 14, 2020, that described the clinical, laboratory, and imaging features of children with COVID-19. Data were extracted independently by 2 authors. Random-effects meta-analysis models were used to report pooled results.Clinical data from 2874 children with COVID-19 from 37 articles were finally included for quantitative analyses. Fever (48.5%, 95% CI: 41.4%-55.6%) and cough (40.6%, 95% CI: 33.9%-47.5%) were the most common symptoms; asymptomatic infection and severe cases, respectively, accounted for 27.7% (95% CI: 19.7%-36.4%) patients and 1.1% of the 1933 patients included. Laboratory tests showed 5.5% (95% CI: 2.8%-8.9%) of the patients had lymphopenia. The pooled prevalence of leukopenia was 7.3% (95% CI: 3.4%-12.2%), and the C-reactive protein level was high in 14.0% (95% CI: 6.8%-22.8%). Chest computed tomography showed unilateral and bilateral lesions, and ground-glass opacity in 29.4% (95% CI: 24.8%-34.3%) and 24.7% (95% CI: 18.2%-31.6%), and 32.9% (95% CI: 25.3%-40.9%), respectively, and normal in approximately 36.0% (95% CI: 27.7%-44.7%).We found that children with COVID-19 had relatively mild disease, with quite a lot of asymptomatic infections and low rate of severe illness. Data from more regions are needed to determine the prevention and treatment strategies for children with COVID-19.