Epi-DNNs: Epidemiological priors informed deep neural networks for modeling COVID-19 dynamics

Differential equations-based epidemic compartmental models and deep neural networks-based artificial intelligence (AI) models are powerful tools for analyzing and fighting the transmission of COVID-19. However, the capability of compartmental models is limited by the challenges of parameter estimation, while AI models fail to discover the evolutionary pattern of COVID-19 and lack explainability. This paper aims to provide a novel method (called Epi-DNNs) by integrating compartmental models and deep neural networks (DNNs) to model the complex dynamics of COVID-19. In the proposed Epi-DNNs method, the neural network is designed to express the unknown parameters in the compartmental model and the Runge–Kutta method is implemented to solve the ordinary differential equations (ODEs) so as to give the values of the ODEs at a given time. Specifically, the discrepancy between predictions and observations is incorporated into the loss function, then the defined loss is minimized and applied to identify the best-fitted parameters governing the compartmental model. Furthermore, we verify the performance of Epi-DNNs on the real-world reported COVID-19 data on the Omicron epidemic in Shanghai covering February 25 to May 27, 2022. The experimental findings on the synthesized data have revealed its effectiveness in COVID-19 transmission modeling. Moreover, the inferred parameters from the proposed Epi-DNNs method yield a predictive compartmental model, which can serve to forecast future dynamics.

Efficacy of SARS-CoV-2 vaccines and the dose-response relationship with three major antibodies: a systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: The efficacy of SARS-CoV-2 vaccines in preventing severe COVID-19 illness and death is uncertain due to the rarity of data in individual trials. How well the antibody concentrations can predict the efficacy is also uncertain. We aimed to assess the efficacy of these vaccines in preventing SARS-CoV-2 infections of different severities and the dose-response relationship between the antibody concentrations and efficacy. METHODS: We did a systematic review and meta-analysis of randomised controlled trials (RCTs). We searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, WHO, bioRxiv, and medRxiv for papers published between Jan 1, 2020 and Sep 12, 2022. RCTs on the efficacy of SARS-CoV-2 vaccines were eligible. Risk of bias was assessed using the Cochrane tool. A frequentist, random-effects model was used to combine efficacy for common outcomes (ie, symptomatic and asymptomatic infections) and a Bayesian random-effects model was used for rare outcomes (ie, hospital admission, severe infection, and death). Potential sources of heterogeneity were investigated. The dose-response relationships of neutralising, spike-specific IgG and receptor binding domain-specific IgG antibody titres with efficacy in preventing SARS-CoV-2 symptomatic and severe infections were examined by meta-regression. This systematic review is registered with PROSPERO, CRD42021287238. FINDINGS: 28 RCTs (n=286 915 in vaccination groups and n=233 236 in placebo groups; median follow-up 1-6 months after last vaccination) across 32 publications were included in this review. The combined efficacy of full vaccination was 44·5% (95% CI 27·8-57·4) for preventing asymptomatic infections, 76·5% (69·8-81·7) for preventing symptomatic infections, 95·4% (95% credible interval 88·0-98·7) for preventing hospitalisation, 90·8% (85·5-95·1) for preventing severe infection, and 85·8% (68·7-94·6) for preventing death. There was heterogeneity in the efficacy of SARS-CoV-2 vaccines against asymptomatic and symptomatic infections but insufficient evidence to suggest whether the efficacy could differ according to the type of vaccine, age of the vaccinated individual, and between-dose interval (p>0·05 for all). Vaccine efficacy against symptomatic infection waned over time after full vaccination, with an average decrease of 13·6% (95% CI 5·5-22·3; p=0·0007) per month but can be enhanced by a booster. We found a significant non-linear relationship between each type of antibody and efficacy against symptomatic and severe infections (p<0·0001 for all), but there remained considerable heterogeneity in the efficacy, which cannot be explained by antibody concentrations. The risk of bias was low in most studies. INTERPRETATION: The efficacy of SARS-CoV-2 vaccines is higher for preventing severe infection and death than for preventing milder infection. Vaccine efficacy wanes over time but can be enhanced by a booster. Higher antibody titres are associated with higher estimates of efficacy but precise predictions are difficult due to large unexplained heterogeneity. These findings provide an important knowledge base for interpretation and application of future studies on these issues. FUNDING: Shenzhen Science and Technology Programs.

Social identity loss and reverse culture shock: Experiences of international students in China during the COVID-19 pandemic.

Background: International students are often exposed to various challenges during life transitions. The 'mindsponge' mechanism suggests that individuals absorb and integrate new cultural values that are compatible with their core values while rejecting those of lesser importance. On the basis of this notion, this article explores the experiences of international students in China regarding their unplanned return to their home countries during the COVID-19 pandemic through the lens of the mindsponge mechanism. Aim: This article aims to highlight the experiences of international students in China who are going through life transitions due to the global pandemic. The study focuses on the experiences of two groups of international students: (1) Those who remained in China during the pandemic, and (2) those who had left China and were stranded in their home countries due to a ban on international travel amid COVID-19. Method: This qualitative study comprised of in-depth semi structured in-person and online interviews. Thematic Analysis was used to analyze the data in order to generate study themes. Results: The results revealed that students who remained in China experienced challenges which included anxiety, closure of campuses, lockdown, their parents' concern regarding health issues, and not being able to meet with friends. On the other hand, students who had left China during the pandemic were confined to their home countries. This group of students experienced more severe problems than the students who remained in China. Since the transition to home countries was "unplanned," they were not ready to readjust to their native culture and were vulnerable to severe reverse culture shock. Upon returning to their home countries, international students faced a number of challenges, including readjustment to their home countries and changes in their lives in host and home countries. In addition, they lost social and academic resources, such as the disruption of study environment, losing important group memberships, financial constraints, visa expiry, graduation delay, and academic suspension. Conclusion: This study concluded that the international students experienced cultural problems after unplanned transition to their home countries during the pandemic. They described effects of reverse culture shock as being more distressing. They perceived dissatisfaction due to loss of previously held social identities and sense of belonging to the traditional society they left behind. There is a need of future studies on the long-term effect of unplanned transition on psychological, social and professional experiences. The process of readjustment has proven to be a challenging endeavor.

COVID-19 Vaccine Hesitancy in China: An Analysis of Reasons through Mixed Methods.

This study aims to investigate the causes of COVID-19 vaccine hesitancy among the Chinese population. The LDA model and content analysis were used to analyze the content of COVID-19 vaccine hesitancy expressed by the Chinese on Weibo from 2020 to 2022, the leading causes of vaccine hesitancy, and the changes in the reasons for vaccine hesitancy over time. The study found that when the Chinese expressed vaccine hesitancy, it usually involved themes such as information access (18.59%), vaccination services (13.91%), and physical illness (13.24%), and topics such as vaccination process (6.83%), allergic diseases (6.59%), and international news (6.43%). Constraints (35.48%), confidence (17.94%), and calculation (15.99%) are the leading causes of vaccine hesitancy on Weibo. These findings provide a comprehensive picture of how the Chinese express vaccine hesitancy in social media and the reasons and changes for vaccine hesitancy, which can help inspire public health experts, health organizations, or governments in various countries to improve the phenomenon of vaccine hesitancy.

Epi-DNNs: Epidemiological priors informed deep neural networks for modeling COVID-19 dynamics.

Differential equations-based epidemic compartmental models and deep neural networks-based artificial intelligence (AI) models are powerful tools for analyzing and fighting the transmission of COVID-19. However, the capability of compartmental models is limited by the challenges of parameter estimation, while AI models fail to discover the evolutionary pattern of COVID-19 and lack explainability. This paper aims to provide a novel method (called Epi-DNNs) by integrating compartmental models and deep neural networks (DNNs) to model the complex dynamics of COVID-19. In the proposed Epi-DNNs method, the neural network is designed to express the unknown parameters in the compartmental model and the Runge-Kutta method is implemented to solve the ordinary differential equations (ODEs) so as to give the values of the ODEs at a given time. Specifically, the discrepancy between predictions and observations is incorporated into the loss function, then the defined loss is minimized and applied to identify the best-fitted parameters governing the compartmental model. Furthermore, we verify the performance of Epi-DNNs on the real-world reported COVID-19 data on the Omicron epidemic in Shanghai covering February 25 to May 27, 2022. The experimental findings on the synthesized data have revealed its effectiveness in COVID-19 transmission modeling. Moreover, the inferred parameters from the proposed Epi-DNNs method yield a predictive compartmental model, which can serve to forecast future dynamics.

Lessons learnt from the applying the Centers for Disease Control and Prevention (CDC) evaluation framework to the measles incident management system response, USA, 2020-2021.

The functionality and performance of public health programmes at all levels of government play a critical role in preventing, detecting, mitigating and responding to public health threats, including infectious disease outbreaks. Multiple and concurrent outbreaks in recent years, such as COVID-19, Ebola and Zika, have highlighted the importance of documenting lessons learnt from public health responses of national and global agencies. In February 2020, the US Centers for Disease Control and Prevention (CDC) Center for Global Health (CGH) activated the Measles Incident Management System (MIMS) to accelerate the ability to detect, mitigate and respond to measles outbreaks globally and advance progress towards regional measles elimination goals. The activation was triggered by a global resurgence in reported measles cases during 2018-2019 and supported emergency response activities conducted by partner organisations and countries. MIMS leadership decided early in the response to form an evaluation team to design and implement an evaluation approach for producing real-time data to document progress of response activities and inform timely decision-making. In this manuscript, we describe how establishing an evaluation unit within MIMS, and engaging MIMS leadership and subject matter experts in the evaluation activities, was critical to monitor progress and document lessons learnt to inform decision making. We also explain the CDC's Framework for Evaluation in Public Health Practice applied to evaluate the dynamic events throughout the MIMS response. Evaluators supporting emergency response should use a flexible framework that can be adaptable in dynamic contexts and document response activities in real-time.

The Relationship between the Transmission of Different SARS-CoV-2 Strains and Air Quality: A Case Study in China.

Coronavirus Disease 2019 (COVID-19) has been a global public health concern for almost three years, and the transmission characteristics vary among different virus variants. Previous studies have investigated the relationship between air pollutants and COVID-19 infection caused by the original strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, it is unclear whether individuals might be more susceptible to COVID-19 due to exposure to air pollutants, with the SARS-CoV-2 mutating faster and faster. This study aimed to explore the relationship between air pollutants and COVID-19 infection caused by three major SARS-CoV-2 strains (the original strain, Delta variant, and Omicron variant) in China. A generalized additive model was applied to investigate the associations of COVID-19 infection with six air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3). A positive correlation might be indicated between air pollutants (PM2.5, PM10, and NO2) and confirmed cases of COVID-19 caused by different SARS-CoV-2 strains. It also suggested that the mutant variants appear to be more closely associated with air pollutants than the original strain. This study could provide valuable insight into control strategies that limit the concentration of air pollutants at lower levels and would better control the spread of COVID-19 even as the virus continues to mutate.

Can Trust Bring Satisfaction to the Festival Under Pandemic?

In existing festival research, trust is often placed at the post-experience stage by scholars, and there is no research to explore the relationship between festivalscape, trust, and experience. In addition, the main function of trust is to reduce uncertainty and risk perception. Existing festival-related research scenarios do not have typical risks, which will limit the findings of the research. This research focuses on festivals under covid-19 pandemic, which is a typical risky scenario. Exploring the antecedent variables and the consequences of the trust of the festival participants in this context may therefore make up the deficiency of existing research. Several interesting findings have been made: the perception of the festivalscape during the pandemic has been significantly simplified. Epidemic prevention measures and staff may increase trust, but trust cannot have a direct and significant impact on festival satisfaction. While staff positively strengthen trust, they will have a significant negative impact on satisfaction.

Effects of COVID-19 on Vaccine-Preventable Disease Surveillance Systems in the World Health Organization African Region, 2020.

Global emergence of the COVID-19 pandemic in 2020 curtailed vaccine-preventable disease (VPD) surveillance activities, but little is known about which surveillance components were most affected. In May 2021, we surveyed 214 STOP (originally Stop Transmission of Polio) Program consultants to determine how VPD surveillance activities were affected by the COVID-19 pandemic throughout 2020, primarily in low- and middle-income countries, where program consultants are deployed. Our report highlights the responses from 154 (96%) of the 160 consultants deployed to the World Health Organization African Region, which comprises 75% (160/214) of all STOP Program consultants deployed globally in early 2021. Most survey respondents observed that VPD surveillance activities were somewhat or severely affected by the COVID-19 pandemic in 2020. Reprioritization of surveillance staff and changes in health-seeking behaviors were factors commonly perceived to decrease VPD surveillance activities. Our findings suggest the need for strategies to restore VPD surveillance to prepandemic levels.

Effects of Decreased Immunization Coverage for Hepatitis B Virus Caused by COVID-19 in World Health Organization Western Pacific and African Regions, 2020.

The World Health Organization-designated Western Pacific Region (WPR) and African Region (AFR) have the highest number of chronic hepatitis B virus (HBV) infections worldwide. The COVID-19 pandemic has disrupted childhood immunization, threatening progress toward elimination of hepatitis B by 2030. We used a published mathematical model to estimate the number of expected and excess HBV infections and related deaths after 10% and 20% decreases in hepatitis B birth dose or third-dose hepatitis B vaccination coverage of children born in 2020 compared with prepandemic 2019 levels. Decreased vaccination coverage resulted in additional chronic HBV infections that were 36,342-395,594 in the WPR and 9,793-502,047 in the AFR; excess HBV-related deaths were 7,150-80,302 in the WPR and 1,177-67,727 in the AFR. These findings support the urgent need to sustain immunization services, implement catch-up vaccinations, and mitigate disruptions in hepatitis B vaccinations in future birth cohorts.

Therapeutic Effect of Tocilizumab on Inhibiting Cytokine Release Syndrome in Severe Coronavirus Disease 2019 Patients

Background and Objectives: Older adults are more susceptible to coronavirus disease 2019 (COVID-19). Interleukin-6 (IL-6) is an important cytokine in the cytokine release syndrome (CRS), and tocilizumab blocks the IL-6 receptor. The objective is to analyze the effect of tocilizumab on CRS in older patients with severe COVID-19. Materials and Methods: Between February 10 and March 21, 2020, a total of 19 patients aged ≥60 years with severe or critical COVID-19 met the study inclusion criteria at the Tongji Hospital in Wuhan City, Hubei Province, China. The patients were divided into two groups: the tocilizumab group, with IL-6 levels, which exceeded the upper limit of normal by >10-fold and non-tocilizumab group. Results: Patients in the tocilizumab group were older (73.20 ± 4.44 vs. 66.21 ± 5.06 years, P = 0.014), had lower lymphocyte counts (0.71 ± 0.18 vs. 1.18 ± 0.59 × 109/L, P = 0.016), and higher high-sensitivity C-reactive protein (hsCRP) levels (94.04 ± 57.24 vs. 51.65 ± 45.37 mg/L, P = 0.035). Increases in ferritin (FER) and hsCRP levels in patients in the tocilizumab group were marked. Except for one patient who died, IL-6, FER, hsCRP levels, and the neutrophil/lymphocyte ratio in the remaining four patients decreased following treatment with tocilizumab. Tocilizumab did not cause any serious adverse reactions. There were no differences in mortality, days until lung computerized tomography improvement, or renal function between the two groups. The total mortality rate was 10.53%. Conclusions: Our results support the therapeutic efficacy and safety of tocilizumab in older patients with severe COVID-19.

Progress towards regional measles elimination - worldwide, 2000-2020

This report describes the progress towards WHA milestones and measles elimination objectives during 2000-2020 and updates a previous report. During 2000-2010, estimated MCV first dose (MCV1)coverage increased globally from 72% to 84%, peaked at 86% in 2019, and declined to 84% in 2020 during the COVID-19 pandemic. All countries conducted measlesurveillance, although fewer than one third achieved the sensitivity indicator target of 2 discarded cases per 100,000 population in 2020. From 2000 to 2016, annual reported measles incidence fell 88%, from 145 to 18 cases per 1 million population, before rebounding to 120 in 2019 and falling to 22 in 2020. During 2000-2020, the annual number of estimated measles deaths decreased by 94%, from 1,072,800 to 60,700, averting an estimated 31.7 million measles deaths. To reach regional measles eradication goals, more work needs to be done to make sure all children get two MCV doses, to have strong surveillance, and to find and close immunity gaps.

Night-Time Skyglow Dynamics during the COVID-19 Epidemic in Guangbutun Region of Wuhan City

The COVID-19 epidemic lockdown has a direct influence on urban socioeconomic activity, including night-time light (NTL) changes. Night-time skyglow, a form of light pollution caused by NTL, is also affected by public emergencies. Here we investigated the impact of the lockdown on the night-time skyglow in the Guangbutun region of Wuhan, China. We monitored the night-time sky from 1 November 2019 to 12 April 2020 and compared the intraday skyglow pattern and day-to-day variation of skyglow before and during the lockdown. We found that the detected earliest shutdown timing of lights (STL) was moved from 22:00 (before the lockdown) to 21:30 (after entering the lockdown), and the fluctuation of skyglow decreased significantly during the lockdown. Furthermore, we found the night-time skyglow at various time intervals generally decreased and then recovered during the lockdown. The most severe decrease in zenith sky brightness (ZSB) was observed at the 21:30–22:00 time interval, with a decrease ratio (DR) of 72.1% and a recovery ratio (RR) of only 22.6%. On the other hand, the skyglow near midnight was the least affected by the lockdown, and the RR (32.6% and 24.3%) was comparable to the DR (30.4% and 38.2%), which means the skyglow at this time basically recovered to the pre-epidemic level. We conclude that long-term monitoring of sky brightness using single-channel photometers, such as SQMs, can provide a multi-temporal microscopic perspective for studying the dynamics of skyglow caused by human activities.

Epidemiological and virological surveillance of influenza viruses in China during 2020-2021.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, seasonal influenza activity declined globally and remained below previous seasonal levels, but intensified in China since 2021. Preventive measures to COVID-19 accompanied by different epidemic characteristics of influenza in different regions of the world. To better respond to influenza outbreaks under the COVID-19 pandemic, we analyzed the epidemiology, antigenic and genetic characteristics, and antiviral susceptibility of influenza viruses in the mainland of China during 2020-2021. METHODS: Respiratory specimens from influenza like illness cases were collected by sentinel hospitals and sent to network laboratories in Chinese National Influenza Surveillance Network. Antigenic mutation analysis of influenza virus isolates was performed by hemagglutination inhibition assay. Next-generation sequencing was used for genetic analyses. We also conducted molecular characterization and phylogenetic analysis of circulating influenza viruses. Viruses were tested for resistance to antiviral medications using phenotypic and/or sequence-based methods. RESULTS: In the mainland of China, influenza activity recovered in 2021 compared with that in 2020 and intensified during the traditional influenza winter season, but it did not exceed the peak in previous years. Almost all viruses isolated during the study period were of the B/Victoria lineage and were characterized by genetic diversity, with the subgroup 1A.3a.2 viruses currently predominated. 37.8% viruses tested were antigenically similar to reference viruses representing the components of the vaccine for the 2020-2021 and 2021-2022 Northern Hemisphere influenza seasons. In addition, China has a unique subgroup of 1A.3a.1 viruses. All viruses tested were sensitive to neuraminidase inhibitors and endonuclease inhibitors, except two B/Victoria lineage viruses identified to have reduced sensitivity to neuraminidase inhibitors. CONCLUSIONS: Influenza activity increased in the mainland of China in 2021, and caused flu season in the winter of 2021-2022. Although the diversity of influenza (sub)type decreases, B/Victoria lineage viruses show increased genetic and antigenic diversity. The world needs to be fully prepared for the co-epidemic of influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus globally.

[Value of red blood cell distribution width in evaluating the severity of illness of novel coronavirus Delta variant].

OBJECTIVE: To explore the value of red blood cell distribution width (RDW) in evaluating the severity of patients infected with novel coronavirus Delta variant. METHODS: A total of 28 patients infected with novel coronavirus Delta variant in designated hospital treated by the First Affiliated Hospital of Xi'an Jiaotong University medical team from December 2021 to January 2022 were enrolled (23 cases of common type, 4 severe and 1 critical cases). The detailed clinical data of patients was collected. Then, Pearson's correlation analysis was used to identify the blood examination indexes which affected the arterial partial pressure of oxygen (PaO2) and arterial partial pressure of carbon dioxide (PaCO2). According to the median standard deviation of red blood cell distribution width (RDW-SD, 42.5 fL), 28 patients were divided into low RDW-SD group (≤ 42.5 fL, 16 cases) and high RDW-SD group (> 42.5 fL, 12 cases), and the immune related indexes of the two groups were compared. Receiver operator characteristic curve (ROC) was drawn to evaluate the predictive value of RDW-SD on the severity of illness of coronavirus disease 2019 (COVID-19). RESULTS: Correlation analysis showed that RDW-SD was the only index related to PaO2 and PaCO2 on the first day of admission, which was negative correlation with PaO2 (r = -0.379, P = 0.047) and positive correlation with PaCO2 (r = 0.509, P = 0.006). The results of effects of different clinical characteristics on RDW-SD level showed that there was no statistically significant difference in RDW-SD between groups with different clinical characteristics (including male/female, ≥ 65 years old/< 65 years old, having/without hypertension, having/without diabetes, smoking/not smoking, having/without hyperpyrexia, with/without fever for 3 days, with/without respiratory symptoms, with/without digestive symptoms). It was suggested that RDW-SD be relatively stable and not affected by the patient's baseline level. The percentage of B cells in low RDW-SD group was higher than that in high RDW-SD group (23.01±3.01 vs. 15.34±5.34, P < 0.05), immunoglobulin G (IgG) level in low RDW-SD group was lower than that in high RDW-SD group (g/L: 11.43±3.20 vs. 15.42±1.54, P < 0.05). The area under ROC curve (AUC) of RDW-SD in evaluating severe cases was 0.83 [95% confidence interval (95%CI) was 0.59-1.06], which was close to multilobularinltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hyper-tension and age (MuL BSTA score; AUC = 0.82, 95%CI was 0.51-1.12) and better than British Thoracic Society's modified pneumonia score (CURB-65 score; AUC = 0.70, 95%CI was 0.50-0.91). CONCLUSIONS: RDW-SD has significant evaluative effect on the severity of COVID-19 patients with Delta variants.

Appeal of word of mouth: Influences of public opinions and sentiment on ports in corporate choice of import and export trade in the post-COVID-19 era.

With the advent of the post-COVID-19 era, corporate managers of import and export trade are now more sensitive in their daily work, and their decisions are more likely to be influenced by the emotional bias of public opinions, especially regarding cooperation with trade ports of frequent circulation. Therefore, how to manage public opinion and sentiment in the post-COVID-19 era will be a new opportunity and challenge for the marketing management of ports. For the above considerations, through the same frequency verification between public opinions and sentiment on ports and corporate choice of import and export trade, and through analysis of the influence mechanism, the present study demonstrates the positive effects of public opinions and sentiment on ports in corporate choice of import and export trade in the post-COVID-19 era, verifies the significance of shaping word of mouth in port management, puts forward the great role of public opinions and sentiment in the cognitive and emotional empathy in the choice of import and export trade, and provides theoretical guidance for port managers' strategic choices in the post-COVID-19 era.

Development and Validation of a Predictive Nomogram with Age and Laboratory Findings for Severe COVID-19 in Hunan Province, China.

Purpose: To identify more objectively predictive factors of severe outcome among patients hospitalized for coronavirus disease 2019 (COVID-19). Patients and Methods: A retrospective cohort of 479 hospitalized patients diagnosed with COVID-19 in Hunan Province was selected. The prognostic effects of factors such as age and laboratory indicators were analyzed using the Kaplan-Meier method and Cox proportional hazards model. A prognostic nomogram model was established to predict the progression of patients with COVID-19. Results: A total of 524 patients in Hunan province with COVID-19 from December 2019 to October 2020 were retrospectively recruited. Among them, 479 eligible patients were randomly assigned into the training cohort (n = 383) and validation cohort (n = 96), at a ratio of 8:2. Sixty-eight (17.8%) and 15 (15.6%) patients developed severe COVID-19 after admission in the training cohort and validation cohort, respectively. The differences in baseline characteristics were not statistically significant between the two cohorts with regard to age, sex, and comorbidities (P > 0.05). Multivariable analyses included age, C-reactive protein, fibrinogen, lactic dehydrogenase, neutrophil-to-lymphocyte ratio, urea, albumin-to-globulin ratio, and eosinophil count as predictive factors for patients with progression to severe COVID-19. A nomogram was constructed with sufficient discriminatory power (C index = 0.81), and proper consistency between the prediction and observation, with an area under the ROC curve of 0.81 and 0.86 in the training and validation cohort, respectively. Conclusion: We proposed a simple nomogram for early detection of patients with non-severe COVID-19 but at high risk of progression to severe COVID-19, which could help optimize clinical care and personalized decision-making therapies.

Anti-Influenza Virus Study of Composite Material with MIL-101(Fe)-Adsorbed Favipiravir.

Nanomaterial technology has attracted much attention because of its antibacterial and drug delivery properties, among other applications. Metal-organic frameworks (MOFs) have advantages, such as their pore structure, large specific surface area, open metal sites, and chemical stability, over other nanomaterials, enabling better drug encapsulation and adsorption. In two examples, we used the common pathogenic bacterium Staphylococcus aureus and highly infectious influenza A virus. A novel complex MIL-101(Fe)-T705 was formed by synthesizing MOF material MIL-101(Fe) with the drug favipiravir (T-705), and a hot solvent synthesis method was applied to investigate the in vitro antibacterial and antiviral activities. The results showed that MIL-101(Fe)-T705 combined the advantages of nanomaterials and drugs and could inhibit the growth of Staphylococcus aureus at a concentration of 0.0032 g/mL. Regarding the inhibition of influenza A virus, MIL-101(Fe)-T705 showed good biosafety at 12, 24, 48, and 72 h in addition to a good antiviral effect at concentrations of 0.1, 0.2, 0.4, 0.8, 1.6, and 3 µg/mL, which were higher than MIL-101(Fe) and T-705.

Research on the Healing Potential of Rural Community Streets From the Perspective of Audiovisual Integration: A Case Study of Four Rural Communities in China.

Rural communities have become a hot topic in academic circles because of their graceful natural environment and great healing potential. However, existing research still lacks attention to the street space in rural communities and rarely considers its integrated visual and soundscape design in terms of their effect on public health. As a result, the healing potential of rural community streets cannot be fully used in design practice. Relevant audiovisual materials were collected from a field investigation in four rural communities in southwestern China. Based on these data, the subjective and objective healing index data of subjects under comprehensive audiovisual conditions were collected and analyzed through laboratory experiments. The results revealed that type of street space affects healing potential, and the artificial-natural enclosed and natural semi-enclosed streets are the street types with the best healing effect. When the total sound pressure level was 55dB(A), the sound combination with birdsong accounting for 70% had a significant positive effect on improving the healing effect of rural community streets. In contrast, the sound combination with birdsong accounting for 50% or less had no significant effect on improving healing. The subjective healing perception of street space in rural communities was significantly positively correlated with aesthetic preferences. There was also a significant correlation between subjective healing perception and physiological index data in the audiovisual combination. This research explored the impact of different types of street space and sound combinations on the healing effect of rural community streets in an integrated audiovisual environment and provided a scientific basis for the healing landscape design of rural community streets in an integrated audiovisual environment. It was expected to provide new ideas for the construction of rural community landscapes, including acoustic landscapes, to promote physical and mental healing.