Inactivated Vaccine Dosage and Serum IgG Levels Correlate with Persistent COVID-19 Infection in Hematologic Malignancy Patients During the Omicron Surge in China (preprint)

In hematologic malignancies (HM) patients, COVID-19 infections carry a significant risk of mortality due to disease status, treatment, and other factors.The risk factors of the severity and persistence of COVID-19 infections remains unclear. A study observed adults with HM diagnosed with COVID-19 from November 2022 to February 2023. Patient blood samples yielded biochemical data, with COVID-19 confirmed via RNA or antigen testing. In the examined cohort, 133 individuals diagnosed with HM and concomitantly infected with COVID-19 were scrutinized. Using advanced multivariate logistic regression, high C-reactive protein levels (≥100mg/L) significantly increased the risk of severe/critical conditions in HM patients with COVID-19 (OR: 3.415, 95% CI: 1.294-9.012; p=0.013). Patients enduring Omicron infection beyond 30 days were deemed persistent, in contrast to those achieving infection control within this duration. The research indicated that taking ＜2 vaccine doses (OR: 0.202, 95% CI: 0.048-0.857; p=0.030), having low IgG levels (＜1000 mg/dl) (OR: 0.129, 95% CI: 0.027-0.607; p=0.010), and increased interleukin-6 levels (≥12pg/ml) (OR: 5.098, 95% CI: 1.118-23.243; p=0.035) were key indicators of ongoing infection. A significant difference in survival rates was observed between patients with persistent and non-persistent infections, with the latter showing better survival outcomes (P<0.001). In conclusion, increased C-reactive protein levels had a higher likelihood of severe health outcomes for HM patients with COVID-19 infection. Persistent infections tended to be more prevalent in those with lower vaccine dosages, diminished IgG levels, and escalated interleukin-6 levels.

Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China.

BACKGROUND: The transmission of 2019 novel coronavirus (COVID-19) has caused global panic in the past three years. Countries have learned an important lesson in the practice of responding to COVID-19 pandemic: timely and accurate diagnosis is critical. As an important technology of virus diagnosis, nucleic acid testing (NAT) is also widely used in the identification of other infectious diseases. However, geographic factors often constrain the provision of public health services such as NAT services, and the spatial nature of their resource allocation is a significant problem. METHODS: We used OLS, OLS-SAR, GWR, GWR-SAR, MGWR, and MGWR-SAR models to identify the determinants of spatial difference and spatial heterogeneity affecting NAT institutions in China. RESULTS: Firstly, we identify that the distribution of NAT institutions in China shows a clear spatial agglomeration, with an overall trend of increasing distribution from west to east. There is significant spatial heterogeneity in Chinese NAT institutions. Secondly, the MGWR-SAR model results show that city level, population density, number of tertiary hospitals and number of public health emergency outbreaks are important factors influencing the spatial heterogeneity of NAT institutions in China. CONCLUSIONS: Therefore, the government should allocate health resources rationally, optimise the spatial layout of testing facilities, and improve the ability to respond to public health emergencies. Meanwhile, third-party testing facilities need to focus on their role in the public health emergency response system as a market force to alleviate the inequitable allocation of health resources between regions. By taking these measures to prepare adequately for possible future public health emergencies.

Decay of enveloped SARS-CoV-2 and non-enveloped PMMoV RNA in raw sewage from university dormitories.

Introduction: Although severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA has been frequently detected in sewage from many university dormitories to inform public health decisions during the COVID-19 pandemic, a clear understanding of SARS-CoV-2 RNA persistence in site-specific raw sewage is still lacking. To investigate the SARS-CoV-2 RNA persistence, a field trial was conducted in the University of Tennessee dormitories raw sewage, similar to municipal wastewater. Methods: The decay of enveloped SARS-CoV-2 RNA and non-enveloped Pepper mild mottle virus (PMMoV) RNA was investigated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in raw sewage at 4°C and 20°C. Results: Temperature, followed by the concentration level of SARS-CoV-2 RNA, was the most significant factors that influenced the first-order decay rate constants (k) of SARS-CoV-2 RNA. The mean k values of SARS-CoV-2 RNA were 0.094 day-1 at 4°C and 0.261 day-1 at 20°C. At high-, medium-, and low-concentration levels of SARS-CoV-2 RNA, the mean k values were 0.367, 0.169, and 0.091 day-1, respectively. Furthermore, there was a statistical difference between the decay of enveloped SARS-CoV-2 and non-enveloped PMMoV RNA at different temperature conditions. Discussion: The first decay rates for both temperatures were statistically comparable for SARS-CoV-2 RNA, which showed sensitivity to elevated temperatures but not for PMMoV RNA. This study provides evidence for the persistence of viral RNA in site-specific raw sewage at different temperature conditions and concentration levels.

Fatigue as a Cause of Professional Dissatisfaction Among Chinese Nurses in Intensive Care Unit During COVID-19 Pandemic.

Aim: To clarify the mediating role of burnout and the moderating role of turnover intention in the association between fatigue and job satisfaction among Chinese nurses in intensive care units (ICU) during the COVID-19 pandemic. Methods: A cross-sectional survey of fifteen provinces in China was conducted, using an online questionnaire, from December 2020 to January 2021, during the COVID-19 pandemic. A total of 374 ICU nurses (effective response rate: 71.37%) provided sufficient responses. Sociodemographic factors, job demographic factors, fatigue, burnout, job satisfaction, and turnover intention were assessed using questionnaires. General linear modeling (GLM), hierarchical linear regression (HLR) analysis, and generalized additive modeling (GAM) were performed to examine all the considered research hypotheses. Results: Fatigue was found to be negatively and significantly associated with job satisfaction. Moreover, burnout played a partial mediating role and turnover intention played a moderating role in the relationship between fatigue and job satisfaction. Conclusion: Over time, a state of physical and mental exhaustion and work weariness among Chinese ICU nurses potentially results in job burnout and consequently promotes the level of job dissatisfaction. The results also found that turnover intention played a moderating role in the relationship between burnout and job satisfaction. Specific policies could be considered to eliminate nurses' fatigue and negative attitudes during times of public health emergencies.

Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis.

Objective: Over the past decade, scarlet fever has caused a relatively high economic burden in various regions of China. Non-pharmaceutical interventions (NPIs) are necessary because of the absence of vaccines and specific drugs. This study aimed to characterize the demographics of patients with scarlet fever, describe its spatiotemporal distribution, and explore the impact of NPIs on the disease in the era of coronavirus disease 2019 (COVID-19) in China. Methods: Using monthly scarlet fever data from January 2011 to December 2019, seasonal autoregressive integrated moving average (SARIMA), advanced innovation state-space modeling framework that combines Box-Cox transformations, Fourier series with time-varying coefficients, and autoregressive moving average error correction method (TBATS) models were developed to select the best model for comparing between the expected and actual incidence of scarlet fever in 2020. Interrupted time series analysis (ITSA) was used to explore whether NPIs have an effect on scarlet fever incidence, while the intervention effects of specific NPIs were explored using correlation analysis and ridge regression methods. Results: From 2011 to 2017, the total number of scarlet fever cases was 400,691, with children aged 0-9 years being the main group affected. There were two annual incidence peaks (May to June and November to December). According to the best prediction model TBATS (0.002, {0, 0}, 0.801, {<12, 5>}), the number of scarlet fever cases was 72,148 and dual seasonality was no longer prominent. ITSA showed a significant effect of NPIs of a reduction in the number of scarlet fever episodes (ß2 = -61526, P < 0.005), and the effect of canceling public events (c3) was the most significant (P = 0.0447). Conclusions: The incidence of scarlet fever during COVID-19 was lower than expected, and the total incidence decreased by 80.74% in 2020. The results of this study indicate that strict NPIs may be of potential benefit in preventing scarlet fever occurrence, especially that related to public event cancellation. However, it is still important that vaccines and drugs are available in the future.

External quality assessment of nucleic acid testing in provincial or municipal CDC laboratories in the COVID-19 surveillance network in China

Objective: To understand the RNA detection performance of SARS-CoV-2 Variants of Concern (VOCs) in 32 provincial or municipal CDC laboratories in COVID-19 surveillance network in China through an external quality assessment (EQA), and evaluate the clinical performance of the current SARS-CoV-2 nucleic acids detection kits used and provided by the participating laboratories.

Spatial effects of air pollution on the economic burden of disease: implications of health and environment crisis in a post-COVID-19 world.

BACKGROUND: Air pollution has been identified as related to the diseases of susceptible population, but the spatial heterogeneity of its economic burden and its determinants are rarely investigated. The issue is of great policy significance, especially after the epidemic of COVID-19, when human are facing the joint crisis of health and environment, and some areas is prone to falling into poverty. METHODS: The geographical detector was adopted to study the spatial distribution characteristics of the incidence of catastrophic health expenditure (ICHE) for older adults in 100 rural areas in China at the prefecture-city level. The health factors, sociological factors, policy factors and environmental factors and their interactions are identified. RESULTS: First, most health service factors had strong explanatory power for ICHE whether it interacts with air pollution. Second, 50 single-factor high-risk areas of ICHE were found in the study, but at the same time, there were 21 areas dominated by multiple factors. CONCLUSION: The different contributions and synergy among the factors constitute the complex mechanism of factors and catastrophic health expenditure. Moreover, during this process, air pollution aggravates the contribution of health service factors toward ICHE. In addition, the leading factors of ICHE are different among regions. At the end, this paper also puts forward some policy suggestions from the perspective of health and environment crisis in the post-COVID-19 world: environmental protection policies should be combined with the prevention of infectious diseases; advanced health investment is the most cost-effective policy for the inverse health sequences of air pollution and infectious diseases such as coronavirus disease 2019 (COVID-19); integrating environmental protection policy into healthy development policy, different regions take targeted measures to cope with the intertwined crisis.

Impacts of the COVID-19 on all aircraft emissions of international routes in South America.

The COVID-19 pandemic has had a significant impact on South America's economic development, as well as its international civil aviation industry. This paper seeks to calculate the emissions of six pollutions (CO2, CO, HC, NOx, SO2, and PM2.5) from the international routes in South America during 2019-2021 and discusses the impacts of COVID-19 on the emission change. The modified BFFM2-FOA-FPM method is proposed to unify the CO2 and non-CO2 calculations. The calculated results' average error rate is about 5.12%. The results showed that COVID-19 affected all emissions, including the number of routes, average flight distance, aircraft configuration, the proportion of CCD phase emissions, average emissions, etc. In addition, some airlines increased the number of flights and aircraft types during the pandemic, increasing emissions. The results give a reasonable data basis for the aviation industry in South America to formulate emission reduction policies.

The relations between different components of intolerance of uncertainty and symptoms of depression during the COVID-19 pandemic: A network analysis.

Background: The relations between depression and intolerance of uncertainty (IU) have been extensively investigated during the COVID-19 pandemic. However, there is a lack of understanding on how each component of IU may differentially affect depression symptoms and vice versa. The current study used a network approach to reveal the component-to-symptom interplay between IU and depression and identify intervention targets for depression during the COVID-19 pandemic. Methods: A total of 624 college students participated in the current study. An IU-Depression network was estimated using items from the 12-item Intolerance of Uncertainty Scale and the Patient Health Questionnaire-9. We examined the network structure, node centrality, and node bridge centrality to identify component-to-symptom pathways, central nodes, and bridge nodes within the IU-Depression network. Results: Several distinct pathways (e.g., "Frustration when facing uncertainty" and "Feelings of worthlessness") emerged between IU and Depression. "Fatigue" and "Frustration when facing uncertainty" were identified as the central nodes in the estimated network. "Frustration when facing uncertainty," "Psychomotor agitation/retardation," and "Depressed or sad mood" were identified as bridging nodes between the IU and Depression communities. Conclusion: By delineating specific pathways between IU and depression and highlighting the influential role of "Frustration when facing uncertainty" in maintaining the IU-Depression co-occurrence, current findings may inform targeted prevention and interventions for depression during the COVID-19 pandemic.

Can resilience promote calling among Chinese nurses in intensive care units during the COVID-19 pandemic? The mediating role of thriving at work and moderating role of ethical leadership

Background Nurses working in the intensive care unit (ICU) clung tenaciously to their job during the COVID-19 pandemic in spite of enduring stressed psychological and physical effects as a result of providing nursing care for the infected patients, which indicates that they possessed a high degree of professionalism and career calling. The aim of this study was to explain the associations between resilience, thriving at work, and ethical leadership influencing the calling of ICU nurses. Methods From December 2020 to January 2021 during the COVID-19 pandemic, a cross-sectional survey of 15 provinces in China was conducted using an online questionnaire. A total of 340 ICU nurses (effective response rate: 64.89%) completed sufficient responses to be used in the study. Sociodemographic factors, job demographic factors, resilience, calling, thriving at work, and ethical leadership were assessed using the questionnaire. General linear modeling (GLM), hierarchical linear regression (HLR) analysis, and generalized additive model (GAM) were performed to examine all the considered research hypotheses. Results Resilience was positively and significantly associated with calling. Moreover, thriving at work partially mediated the relationship between resilience and calling. The indirect effect of resilience on calling was 0.204 (p < 0.0001), and the direct effect of resilience on calling through thriving at work was 0.215 (p < 0.0001). The total effect of resilience on calling was 0.419 (p < 0.0001). In addition, ethical leadership played a moderating role in the relationship between resilience and calling (β = 0.16, p < 0.05). Conclusion Greater resilience can positively predict increased calling among Chinese ICU nurses during the COVID-19 pandemic. Moreover, thriving at work is a mechanism that partly transmits the positive effects of resilience on calling. Overall, nurses possessing greater resilience tend to maintain thriving at work in the face of such adversity, further resulting in subsequently increased calling. Besides, findings suggest that there is stronger influence of resilience on calling among nurses working in an organization managed by an ethical leader. The current findings may offer two insights for nursing practitioners and policymakers in the postpandemic world. First, resilience training and intervention are necessary to foster nurses' sense of thriving at work in the nursing industry, further promoting career calling. Second, better training and effort on the development of ethical leadership for leaders in nursing practice are essential to encourage followers to engage in social learning of ethical behaviors and abiding by normatively appropriate conduct, further enacting prosocial values and expressing moral emotions.

The impact of uncertainty induced by the COVID-19 pandemic on intertemporal choice.

The coronavirus disease (COVID-19) pandemic has triggered a strong sense of uncertainty worldwide, which may lead to short-sighted behaviors. This study aimed to examine the impact of uncertainty induced by COVID-19 on intertemporal choice, as well as its underlying mechanisms, by conducting four experiments. Study 1a verified the causal relationship between uncertainty and intertemporal choice by showing that participants who feel more uncertain are more likely to choose smaller and sooner gains. Study 1b further confirmed this finding by conducting field experiments, which improved the ecological validity of the results. Study 2 not only replicated the results of Study 1 but also investigated the mediating role of future orientation between uncertainty and intertemporal choice. In Study 3, all participants experienced high uncertainty by recalling their own experiences related to COVID-19. The results showed that increasing future orientation reduced their preferences for smaller and sooner gains, further confirming the mediating role of future orientation. Overall, these findings indicate that uncertainty may lead to a present orientation, which in turn fosters preferences for immediate gains.

Identifying the changing age distribution of opioid-related mortality with high-frequency data.

BACKGROUND: Opioid-related mortality continues to rise across North America, and mortality rates have been further exacerbated by the COVID-19 pandemic. This study sought to provide an updated picture of trends of opioid-related mortality for Ontario, Canada between January 2003 and December 2020, in relation to age and sex. METHODS: Using mortality data from the Office of the Chief Coroner for Ontario, we applied Bayesian Poisson regression to model age/sex mortality per 100,000 person-years, including random walks to flexibly capture age and time effects. Models were also used to explore how trends might continue into 2022, considering both pre- and post-COVID-19 courses. RESULTS: From 2003 to 2020, there were 11,633 opioid-related deaths in Ontario. A shift in the age distribution of mortality was observed, with the greatest mortality rates now among younger individuals. In 2003, mortality rates reached maximums at 5.5 deaths per 100,000 person-years (95% credible interval: 4.0-7.6) for males around age 44 and 2.2 deaths per 100,000 person-years (95% CI: 1.5-3.2) for females around age 51. As of 2020, rates have reached maximums at 67.2 deaths per 100,000 person-years (95% CI: 55.3-81.5) for males around age 35 and 16.8 deaths per 100,000 person-years (95% CI: 12.8-22.0) for females around age 37. Our models estimate that opioid-related mortality among the younger population will continue to grow, and that current conditions could lead to male mortality rates that are more than quadruple those of pre-pandemic estimations. CONCLUSIONS: This analysis may inform a refocusing of public health strategy for reducing rising rates of opioid-related mortality, including effectively reaching both older and younger males, as well as young females, with health and social supports such as treatment and harm reduction measures.

An Imported Case of COVID-19 Delta Variant B.1.617.2---Guangxi Zhuang Autonomous Region, China, June 8, 2021 (preprint)

A male passenger arriving at Nanning Wuxu Airport in Guangxi on an international flight from Jakarta, Indonesia, was found to be positive for SARS-CoV-2 nucleic acid on a routine test at the airport on June 8 2021. The passenger was sent to Fourth People’s Hospital of Nanning immediately for further isolation and observation. On the day of admission, the test for SARS-CoV-2 nucleic acid of nasopharyngeal swabs, pharyngeal swabs and sputum specimens were positive (CT values of N gene and ORF1ab gene were between 20 and 30). After 8 weeks of hospitalization, the patient’s test for SARS-CoV-2 nucleic acid of all specimens turned to negative. We isolated a SARS-CoV-2 variant strain from the nasal swab of the patient, and then we found that the genome sequence of the variant strain had 13 base deletions and 38 nucleotide mutations compared with that of the Novel Coronavirus Wuhan strain after sequencing, comparison and analysis. The deletions and mutations of the variant strain resulted in four amino acid deletions and 30 amino acid mutations. Furthermore, we found that the variant strain was similar to those from Indonesia, South Korea and The United Kingdom after conducting BLAST analysis on GISAID platform, among them, hCOV-19 /Indonesia/ Ji-ITD-43591N /2021 was the most similar, with 99.98% similarity and only 8 base differences. The maximum likelihood phylogenetic tree was constructed taking the Wuhan strain as the root and including most the reference sequence contained most of the epidemic strains. The result showed that the strains isolated in our laboratory belonged to Delta strain.

Three elderly asymptomatic SARS-CoV-2 infected patients in ICU.

Previous studies on asymptomatic COVID-19 carriers indicated that asymptomatic infections always occurred in people in community or patients in general wards, prone to be young and middle aged people. Limited data are available for asymptomatic infections in critically ill patients in intensive care unit or elderly people. Here we reported three elderly asymptomatic SARS-CoV-2 infected patients in intensive care unit. These three elderly patients had negative CT images and 14 consecutive negative RT-PCR test results, with dynamic changes in IgG-IgM antibody levels without any clinical symptoms, which might be related to their weakened immune responses due to elder age (over 85 years old) and the history of hypertension. Therefore, combining nucleic acid RT-PCR and the IgM-IgG antibody test can provide more accurate SARS-CoV-2 infection diagnosis, especially for elderly asymptomatic patients.

Real-Time RT-PCR Allelic Discrimination Assay for Detection of N501Y Mutation in the Spike Protein of SARS-CoV-2 Associated with B.1.1.7 Variant of Concern.

The N501Y amino acid mutation caused by a single point substitution A23063T in the spike gene of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is possessed by three variants of concern (VOCs), B.1.1.7, B.1.351, and P.1. A rapid screening tool using this mutation is important for surveillance during the coronavirus disease 2019 (COVID-19) pandemic. We developed and validated a single nucleotide polymorphism real-time reverse transcription PCR assay using allelic discrimination of the spike gene N501Y mutation to screen for potential variants of concern and differentiate them from SARS-CoV-2 lineages without the N501Y mutation. A total of 160 clinical specimens positive for SARS-CoV-2 were characterized as mutant (N501Y) or N501 wild type by Sanger sequencing and were subsequently tested with the N501Y single nucleotide polymorphism real-time reverse transcriptase PCR assay. Our assay, compared to Sanger sequencing for single nucleotide polymorphism detection, demonstrated positive percent agreement of 100% for all 57 specimens displaying the N501Y mutation, which were confirmed by Sanger sequencing to be typed as A23063T, including one specimen with mixed signal for wild type and mutant. Negative percent agreement was 100% in all 103 specimens typed as N501 wild type, with A23063 identified as wild type by Sanger sequencing. The identification of circulating SARS-CoV-2 lineages carrying an N501Y mutation is critical for surveillance purposes. Current identification methods rely primarily on Sanger sequencing or whole-genome sequencing, which are time consuming, labor intensive, and costly. The assay described herein is an efficient tool for high-volume specimen screening for SARS-CoV-2 VOCs and for selecting specimens for confirmatory Sanger or whole-genome sequencing. IMPORTANCE During the coronavirus disease 2019 (COVID-19) pandemic, several variants of concern (VOCs) have been detected, for example, B.1.1.7, B.1.351, P.1, and B.1.617.2. The VOCs pose a threat to public health efforts to control the spread of the virus. As such, surveillance and monitoring of these VOCs is of the utmost importance. Our real-time RT-PCR assay helps with surveillance by providing an easy method to quickly survey SARS-CoV-2 specimens for VOCs carrying the N501Y single nucleotide polymorphism (SNP). Samples that test positive for the N501Y mutation in the spike gene with our assay can be sequenced to identify the lineage. Thus, our assay helps to focus surveillance efforts and decrease turnaround times.

Self-compassion and resilience mediate the relationship between childhood exposure to domestic violence and posttraumatic growth/stress disorder during COVID-19 pandemic.

BACKGROUND: Studies have indicated that childhood exposure to domestic violence is a common factor in posttraumatic growth (PTG) and posttraumatic stress disorder (PTSD), but it is unclear whether PTG and PTSD share a common/different underlying mechanism. AIM: To explore the common/different underlying mechanism of PTG and PTSD. METHODS: Between February 12 and 17, 2020, a nationwide cross-sectional online survey was conducted in China among 2038 university students, and a self-administered questionnaire was used for the data collection. The data included demographic characteristics, such as age, gender, and subjective social economic status, and childhood exposure to domestic violence scale that was selected from the Chinese version of revised Adverse Childhood Experiences Question, Self-compassion Scale, Connor-Davidson Resilience Scale, Posttraumatic Growth Inventory, and the Abbreviated PTSD Checklist-Civilian version. A structural equation model was used to test the hypotheses. RESULTS: Exposure to domestic violence was significantly associated with PTG and PTSD via a 1-step indirect path of self-compassion (PTG: ß = -0.023, 95%CI: -0.44 to -0.007; PTSD: ß = 0.008, 95%CI: 0.002, 0.014) and via a 2-step indirect path from self-compassion to resilience (PTG: ß = -0.008, 95%CI: -0.018 to -0.002; PTSD: ß = 0.013, 95%CI: 0.004-0.024). However, resilience did not mediate the relationship between exposure to domestic violence and PTG and PTSD. CONCLUSION: PTG and PTSD are common results of childhood exposure to domestic violence, which may be influenced by self-compassion and resilience.

Exploring the effect of COVID-19 on airline environmental efficiency through an interval epsilon-based measure model.

COVID-19 has dealt an unprecedented blow to the aviation industry since 2020. This paper applies the interval epsilon-based measure (IEBM) model to evaluate the optimal quarterly environmental efficiency of 14 global airlines of passenger and cargo subsystems during 2018-2020. Then, the time series prediction method is applied to forecast the interval data of inputs and outputs from 2021 to 2022. Finally, we can calculate the quarterly efficiency. Thus, the future development trends of airlines can be predicted. The results show that (1) COVID-19 has hit the passenger subsystem harder, while the freight subsystem has become more efficient; (2) the efficiency of the freight subsystem has inevitably declined in the post-epidemic era; and (3) therefore, the airlines will have a "√" shaped recovery curve in the next few years.

Focus, Fusion, and Rectify: Context-Aware Learning for COVID-19 Lung Infection Segmentation.

The coronavirus disease 2019 (COVID-19) pandemic is spreading worldwide. Considering the limited clinicians and resources and the evidence that computed tomography (CT) analysis can achieve comparable sensitivity, specificity, and accuracy with reverse-transcription polymerase chain reaction, the automatic segmentation of lung infection from CT scans supplies a rapid and effective strategy for COVID-19 diagnosis, treatment, and follow-up. It is challenging because the infection appearance has high intraclass variation and interclass indistinction in CT slices. Therefore, a new context-aware neural network is proposed for lung infection segmentation. Specifically, the autofocus and panorama modules are designed for extracting fine details and semantic knowledge and capturing the long-range dependencies of the context from both peer level and cross level. Also, a novel structure consistency rectification is proposed for calibration by depicting the structural relationship between foreground and background. Experimental results on multiclass and single-class COVID-19 CT images demonstrate the effectiveness of our work. In particular, our method obtains the mean intersection over union (mIoU) score of 64.8%, 65.2%, and 73.8% on three benchmark datasets for COVID-19 infection segmentation.

Comparison of ARIMA, ES, GRNN and ARIMA–GRNN hybrid models to forecast the second wave of COVID-19 in India and the United States

As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.