Characteristics of viral shedding in people infected with SARS-CoV-2 during difference stages

Viral shedding of SARS-CoV-2 is a continuous dynamic process, which can be divided into latent stage, initial stage, peak stage and decreasing stage according to the characteristics of viral shedding. After being infected with SARS-CoV-2, the infected person generally stays in the latent period for 1-3 days, which is characterized by continuous negative nucleic acid test results and no infectiousness, and the risk of infection for close contacts is very low. At the initial stage of viral shedding is characterized by a rapid decline in the Ct value of nucleic acid tests in a short time, and clinical symptoms gradually appear. The infectiousness of the infected person gradually increases during this period, and the risk of infection for close contacts also gradually increases, but it is still in the early stage of infection, the possibility of viral shedding is low, and the risk of infection of secondary close contacts is low. The peak of viral shedding is characterized by low Ct value in nucleic acid test and obvious clinical symptoms;during this period, the infected person is the most infectious, and the risk of infection of the contact is the highest, so the scope of close contacts should be expanded appropriately. The decreasing period is characterized by the gradual increase of Ct value of nucleic acid test and the gradual disappearance of clinical symptoms;during this period, the infectiousness of the infected person gradually decreases to disappear. In an outbreak, an infected person in the decreasing phase is more likely to be an early infected person in the transmission chain. If infected individuals in the decreasing phase are found in an area without a SARS-CoV-2 epidemic, it suggests that the local outbreak epidemic has been spreading for some time and may be larger in scale. According to the characteristics of viral shedding, risk personnel can be determined more scientifically and accurately, so as to minimize the risk and reduce the waste of epidemic prevention resources.

Monitoring and responding to emerging infectious diseases in a university setting: A case study using COVID-19.

Emerging infection diseases (EIDs) are an increasing threat to global public health, especially when the disease is newly emerging. Institutions of higher education (IHEs) are particularly vulnerable to EIDs because student populations frequently share high-density residences and strongly mix with local and distant populations. In fall 2020, IHEs responded to a novel EID, COVID-19. Here, we describe Quinnipiac University's response to SARS-CoV-2 and evaluate its effectiveness through empirical data and model results. Using an agent-based model to approximate disease dynamics in the student body, the University established a policy of dedensification, universal masking, surveillance testing via a targeted sampling design, and app-based symptom monitoring. After an extended period of low incidence, the infection rate grew through October, likely due to growing incidence rates in the surrounding community. A super-spreader event at the end of October caused a spike in cases in November. Student violations of the University's policies contributed to this event, but lax adherence to state health laws in the community may have also contributed. The model results further suggest that the infection rate was sensitive to the rate of imported infections and was disproportionately impacted by non-residential students, a result supported by the observed data. Collectively, this suggests that campus-community interactions play a major role in campus disease dynamics. Further model results suggest that app-based symptom monitoring may have been an important regulator of the University's incidence, likely because it quarantined infectious students without necessitating test results. Targeted sampling had no substantial advantages over simple random sampling when the model incorporated contact tracing and app-based symptom monitoring but reduced the upper boundary on 90% prediction intervals for cumulative infections when either was removed. Thus, targeted sampling designs for surveillance testing may mitigate worst-case outcomes when other interventions are less effective. The results' implications for future EIDs are discussed.

Stability of SARS-CoV-2 on inanimate surfaces: A review.

The stability of SARS-CoV-2 for varying periods on a wide range of inanimate surfaces has raised concerns about surface transmission; however, there is still no evidence to confirm this route. In the present review, three variables affecting virus stability, namely temperature, relative humidity (RH), and initial virus titer, were considered from different experimental studies. The stability of SARS-CoV-2 on the surfaces of six different contact materials, namely plastic, metal, glass, protective equipment, paper, and fabric, and the factors affecting half-life period was systematically reviewed. The results showed that the half-life of SARS-CoV-2 on different contact materials was generally 2-10 h, up to 5 d, and as short as 30 min at 22 °C, whereas the half-life of SARS-CoV-2 on non-porous surfaces was generally 5-9 h d, up to 3 d, and as short as 4 min at 22 â„ƒ. The half-life on porous surfaces was generally 1-5 h, up to 2 d, and as short as 13 min at 22 °C. Therefore, the half-life period of SARS-CoV-2 on non-porous surfaces is longer than that on porous surfaces, and thehalf-life of the virus decreases with increasing temperature, whereas RH produces a stable negative inhibitory effect only in a specific humidity range. Various disinfection precautions can be implemented in daily life depending on the stability of SARS-CoV-2 on different surfaces to interrupt virus transmission, prevent COVID-19 infections, and avoid over-disinfection. Owing to the more stringent control of conditions in laboratory studies and the lack of evidence of transmission through surfaces in the real world, it is difficult to provide strong evidence for the efficiency of transmission of the contaminant from the surface to the human body. Therefore, we suggest that future research should focus on exploring the systematic study of the entire transmission process of the virus, which will provide a theoretical basis for optimizing global outbreak prevention and control measures.

Simultaneous detection and phylogenetic analysis of porcine epidemic diarrhea virus and porcine circovirus 4 in Henan province, China.

Porcine circovirus 4 (PCV4) is a recently discovered circovirus that was first reported in 2019 in several pigs in Hunan province of China and has also been identified in pigs infected with porcine epidemic diarrhea virus (PEDV). To further investigate the coinfection and genetic diversity of these two viruses, 65 clinical samples (including feces and intestinal tissues) were collected from diseased piglets on 19 large-scale pig farms in Henan province of China, and a duplex SYBR Green I-based quantitative real-time polymerase chain reaction (qPCR) assay was developed for detecting PEDV and PCV4 simultaneously. The results showed that the limit of detection was 55.2 copies/µL and 44.1 copies/µL for PEDV and PCV4, respectively. The detection rate for PEDV and PCV4 was 40% (26/65) and 38% (25/65), respectively, and the coinfection rate for the two viruses was 34% (22/65). Subsequently, the full-length spike (S) gene of eight PEDV strains and a portion of the genome containing the capsid (Cap) gene of three PCV4 strains were sequenced and analyzed. Phylogenetic analysis showed that all of the PEDV strains from the present study clustered in the G2a subgroup and were closely related to most of the PEDV reference strains from China from 2011 to 2021, but they differed genetically from a vaccine strain (CV777), a Korean strain (virulent DR1), and two Chinese strains (SD-M and LZC). It is noteworthy that two PEDV strains (HEXX-24 and HNXX-24XIA) were identified in one sample, and the HNXX-24XIA strain had a large deletion at amino acids 31-229 of the S protein. Moreover, a recombination event was observed in strain HEXX-24. Phylogenetic analysis based on the amino acid sequence of the PCV4 Cap protein revealed that PCV4 strains were divided into three genotypes: PCV4a1, PCV4a2, and PCV4b. Three strains in the present study belonged to PCV4a1, and they had a high degree of sequence similarity (>98% identity) to other PCV4 reference strains. This study not only provides technical support for field investigation of PEDV and PCV4 coinfection but also provides data for their prevention and control.

Different weathering conditions affect the release of microplastics by masks.

A generation of microplastics caused by improper disposal of disposable masks has become a non-negligible environmental concern. In order to investigate the degradation mechanisms of masks and the release of microplastics under different environmental conditions, the masks are placed in 4 common environments. After 30 days of weathering, the total amount and release kinetics of microplastics released from different layers of the mask were studied. The chemical and mechanical properties of the mask were also discussed. The results showed that the mask released 25141±3543 particles/mask into the soil, which is much more than the sea and river water. The release kinetics of microplastics fit the Elovich model better. All samples correspond to the release rate of microplastics from fast to slow. Experiments show that the middle layer of the mask is released more than the other layers, and the amount of release was highest in the soil. And the tensile capacity of the mask is negatively correlated with its ability to release microplastics in the following order, which are soil > seawater > river > air > new masks. In addition, during the weathering process, the C-C/C-H bond of the mask was broken.

Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

The whole-of-society approach of mass COVID-19 vaccination in China: a qualitative study.

BACKGROUND: Many countries have an inefficient vaccination system, which hinders global exit from the COVID-19 pandemic. It is vital to summarize COVID-19 vaccination practices in countries with high vaccination coverage and provide implications for other countries. This study aimed to investigate China's COVID-19 vaccination system and to summarize its implementation experience from a health system perspective. METHODS: We conducted key informant interviews in five representative cities of China in late 2021. Guided by the health systems framework proposed by WHO, we developed our interview guidelines which included seven building blocks-leadership and governance, health workforce, vaccination service delivery, vaccination mobilization and communication, financing, access to vaccines, and information systems. Semi-structured interviews and COVID-19 vaccination policy documents were collected and coded using a thematic analysis approach. RESULTS: A total of 61 participants (nine vaccination programme directors of the local Center for Disease Control and Prevention, four government staff and 48 vaccination service workers) were interviewed. We found that China adopted a whole-of-society approach with adequate government engagement and linked health and non-health sectors to promote COVID-19 vaccination. Key measures included the collaboration of multiple systems and departments from a governance perspective, allocating sufficient health workers and resources, large-scale vaccination mobilization and communication, expansion of vaccine financing channels, localized production and digital information systems. With the vaccination system strengthening, the two-doses vaccination coverage reached 89.5% for the total population but relatively lower coverage for older adults as of July 2022. CONCLUSIONS: Our study highlights the importance of a government-led whole-of-society approach to promote mass vaccination. The low vaccination coverage among older adults should be paid the greatest attention to. The experiences and lessons from China may serve as a reference for other countries.

User review analysis of dating apps based on text mining.

With the continuous development of information technology, more and more people have become to use online dating apps, and the trend has been exacerbated by the COVID-19 pandemic in these years. However, there is a phenomenon that most of user reviews of mainstream dating apps are negative. To study this phenomenon, we have used topic model to mine negative reviews of mainstream dating apps, and constructed a two-stage machine learning model using data dimensionality reduction and text classification to classify user reviews of dating apps. The research results show that: firstly, the reasons for the current negative reviews of dating apps are mainly concentrated in the charging mechanism, fake accounts, subscription and advertising push mechanism and matching mechanism in the apps, proposed corresponding improvement suggestions are proposed by us; secondly, using principal component analysis to reduce the dimensionality of the text vector, and then using XGBoost model to learn the low-dimensional data after oversampling, a better classification accuracy of user reviews can be obtained. We hope These findings can help dating apps operators to improve services and achieve sustainable business operations of their apps.

Identifying the determinants of face mask disposal behavior and policy implications: An application of the extended theory of planned behavior.

A study in Nigeria examined the psychological factors affecting face mask disposal behavior (DB) during the COVID-19 pandemic. The Theory of Planned Behavior (TPB) was used, with awareness of consequences and institutional barriers added. 1183 respondents completed an online survey, and structural equation modeling was used to analyze the data. The original TPB model revealed that attitudes, perceived behavioral control, and subjective norms explained 65% of the variance in respondents' behavior. Behavioral intention and perceived behavioral control accounted for 59.3% of the variance in DB. The extended TPB model, which included awareness of consequences and perceived institutional barriers, improved the model's explanatory power by 12.8%. Both TPB models adequately predicted face mask (FM) disposal behavior, with implications for policymakers and waste management authorities to design interventions to promote proper FM disposal behavior.

SARS-CoV-2 Infection Causes Hyperglycemia in Cats.

Isolated reports of new-onset diabetes in patients with coronavirus disease 2019 (COVID-19) have led researchers to hypothesize that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human exocrine and endocrine pancreatic cells ex vivo and in vivo. However, existing research lacks experimental evidence indicating that SARS-CoV-2 can infect pancreatic tissue. Here, we found that cats infected with a high dose of SARS-CoV-2 exhibited hyperglycemia. We also detected SARS-CoV-2 RNA in pancreatic tissues of these cats, and immunohistochemical staining revealed the presence of SARS-CoV-2 nucleocapsid protein (NP) in islet cells. SARS-CoV-2 NP and spike proteins were primarily detected in glucagon-positive cells, and most glucagon-positive cells expressed ACE2. Additionally, immune protection experiments conducted on cats showed that blood glucose levels of immunized cats did not increase postchallenge. Our data indicate cat pancreas as a SARS-CoV-2 target and suggest that the infection of glucagon-positive cells could contribute to the metabolic dysregulation observed in SARS-CoV-2-infected cats.

Detection and genetic analysis of porcine circovirus-like virus in pigs with diarrhea between 2016 and 2021 in Henan and Shanxi provinces of China.

Porcine circovirus-like virus (PCLV) is a recently discovered virus that may be associated with diarrhea in pigs. To investigate the epidemic profile and genetic characteristics of this virus, 175 clinical samples (141 intestinal samples, 17 blood samples, and 17 fecal samples) were collected from diseased piglets during outbreaks of diarrhea from 33 pig farms in 19 cities of Henan and Shanxi provinces of China between 2016 and 2021 and were screened by PCR for the presence of PCLV. The results showed that the positive rate for PCLV was 32% (56/175) at the sample level, 60.6% (20/33) at the farm level, and 57.9% (11/19) at the city level, which varied from 5.88% to 44.12% between 2016 and 2021. It was also found that PCLV occurred in coinfections with porcine circovirus type 2 (PCV2), PCV3, PCV4, porcine epidemic diarrhea virus, and porcine reproductive and respiratory syndrome virus, but no nucleic acids were detected for transmissible gastroenteritis virus, porcine deltacoronavirus, or porcine rotavirus in piglets with diarrhea. Notably, PCLV was detected in 13 diarrheal piglets from four different farms that were negative for the other porcine viruses. These findings suggest that PCLV may be associated with porcine diarrhea and that it has been circulating in piglets in Henan and Shanxi provinces of China. In addition, the complete genomes of 13 PCLV strains were sequenced and found to share 35.4%-91.0% nucleotide sequence identity with sequences available in the GenBank database. Phylogenetic analysis based on Rep amino acid sequences revealed that the 13 PCLV strains from this study clustered in group 1 and were closely related to eight Chinese PCLV strains, Bo-Circo-like virus CH, American strains 21 and 22, and Hungarian strains 288_4 and 302_4, but they differed genetically from seven other foreign PCLV strains. The whole genome and rep gene of 13 PCLV strains in this study were 72.2%-82% and 83.8%-89.7% identical, respectively, to those of Bo-Circo-like virus strain CH, indicating that PCLV is a novel virus in pigs that may be involved in cross-species transmission. Evidence of a recombination event was found in the rep region of the 13 PCLV strains sequenced. This study enriches the epidemiological data on PCLV infection in pigs in China and lays a foundation for further study on the pathogenesis of PCLV.

Moderating Role of Peer Pressure and Positive Learning Environment Between Career Calling and Academic Procrastination in Chinese Medical Students During Controlled COVID-19 Pandemic: A Cross-Sectional Study.

Purpose: The COVID-19 pandemic sets specific circumstances that may accelerate academic procrastination behavior of medical students. Career calling is a protective factor that fights against academic procrastination and may further improve medical students' mental health and academic achievement. This study aims to determine the status of Chinese medical students' academic procrastination during controlled COVID-19 pandemic. Moreover, the study investigates the relationships and mechanisms among career calling, peer pressure, a positive learning environment, and academic procrastination. Patients and Methods: Data were collected from several Chinese medical universities through an anonymous cross-sectional survey of 3614 respondents (effective response rate = 60.0%). Using online questionnaires to collect the data and IBM SPSS Statistics 22.0 for statistical analysis. Results: The average score of academic procrastination of Chinese medical students was 2.62±0.86. This study proved the usage of peer pressure and positive learning environment as moderating roles of relationship between career calling and academic procrastination. Career calling was negatively correlated with academic procrastination (r = -0.232, p < 0.01), while it was positively correlated with peer pressure (r = 0.390, p < 0.01) and a positive learning environment (r = 0.339, p < 0.01). Moreover, academic procrastination was negatively correlated with peer pressure (r = -0.279, p < 0.01) and a positive learning environment (r = -0.242, p < 0.01). Peer pressure was positively correlated with a positive learning environment (r = 0.637, p < 0.01). Conclusion: The findings emphasize the importance of constructive peer pressure and a positive learning environment that discourages academic procrastination. Educators should highlight medical career calling education by offering related courses to fight against academic procrastination.

Rapid response nursing triage outcomes for COVID-19: factors associated with patient's participation in triage recommendations.

BACKGROUND: COVID-19 is an ongoing global health crisis with prevention and treatment recommendations rapidly changing. Rapid response telephone triage and advice services are critical in providing timely care during pandemics. Understanding patient participation with triage recommendations and factors associated with patient participation can assist in developing sensitive and timely interventions for receiving the treatment to prevent adverse health effects of COVID-19. METHODS: This cohort study aimed to assess patient participation (percentage of patients who followed nursing triage suggestions from the COVID hotline) and identify factors associated with patient participation in four quarterly electronic health records from March 2020 to March 2021 (Phase 1: 14 March 2020-6 June 2020; Phase 2: 17 June 2020-16 September 2020; Phase 3: 17 September 2020-16 December 2020; Phase 4: 17 December 2020-16 March 2021). All callers who provided their symptoms (including asymptomatic with exposure to COVID) and received nursing triage were included in the study. Factors associated with patient participation were identified using multivariable logistic regression analyses, including demographic variables, comorbidity variables, health behaviors, and COVID-19-related symptoms. RESULTS: The aggregated data included 9849 encounters/calls from 9021 unique participants. Results indicated: (1) 72.5% of patient participation rate; (2) participants advised to seek emergency department care had the lowest patient participation rate (43.4%); (3) patient participation was associated with older age, a lower comorbidity index, a lack of unexplained muscle aches, and respiratory symptoms. The absence of respiratory symptoms was the only factor significantly associated with patient participation in all four phases (OR = 0.75, 0.60, 0.64, 0.52, respectively). Older age was associated with higher patient participation in three out of four phases (OR = 1.01-1.02), and a lower Charlson comorbidity index was associated with higher patient participation in phase 3 and phase 4 (OR = 0.83, 0.88). CONCLUSION: Public participation in nursing triage during the COVID pandemic requires attention. This study supports using a nurse-led telehealth intervention and reveals crucial factors associated with patient participation. It highlighted the importance of timely follow-up in high-risk groups and the benefit of a telehealth intervention led by nurses serving as healthcare navigators during the COVID-19 pandemic.