Global Adaptive Histogram Feature Network for Automatic Segmentation of Infection Regions in CT Images (preprint)

We applied deep learning techniques in lung CT image diagnosis of COVID-19 for accurate segmentation of disease diagnosis. We propose a new deep learning framework, GAHFNet, specifically designed for automatic segmentation of COVID-19 lung CT images. GAHFNet outperforms other traditional and the state-of-the-art methods in various evaluation metrics, demonstrating the effectiveness and the efficiency of the proposed method in this task. This article discusses the limitations of current diagnostic methods, such as RT-PCR, and highlights the advantages of deep learning, including its ability to automatically learn features and handle complex lesion morphology and texture. Furthermore, the proposed method addresses the challenges in lung CT image segmentation, such as the complex image structure and difficulties of distinguishing COVID-19 pneumonia lesions from other pathologies. We provide the detailed description of the proposed GAHFNet. Finally, comprehensive experiments are carried out to evaluate the performance of GAHFNet, demonstrating that GAHFNet is able to facilitate the application of artificial intelligence in COVID-19 diagnosis and achieve accurate automatic segmentation of infected areas in COVID-19 lung CT images.

Cost-Effectiveness of Convalescent Plasma for COVID-19: A Cost-effectiveness Analysis of the CONCOR-1 Randomized Trial (preprint)

Background The CONvalescent Plasma for Hospitalized Adults With COVID-19 Respiratory Illness (CONCOR-1) trial was a multicenter randomized controlled trial assessing convalescent plasma in hospitalized COVID-19 patients. Though stopped early due to the lack of treatment benefit, the cost-effectiveness of convalescent plasma provides insight into its potential as an alternative treatment option in resource constrained settings.Methods Individual patient data on health outcomes and healthcare resource utilization from the CONCOR-1 trial were used to conduct the analysis from the Canadian public payer’s perspective with a time horizon of 30 days post-randomization. Baseline and 30-day EQ-5D-5L was measured to calculate quality-adjusted survival. All costs are presented in 2021 Canadian dollars. The base case assessed the EQ-5D-5L scores of patients reporting at both timepoints, and a utility score of 0 was assigned for patients who died within 30 days. Costs for all patients enrolled in the study were used. The sensitivity analysis utilizes EQ-5D-5L scores from the same population but only uses the costs from this population.Results 940 patients were randomized: 627 received CCP and 313 received standard care. The total costs were $28,716 (standard deviation, $25,380) and $24,258 ($22,939) for the convalescent plasma and standard care arms respectively. EQ-5D-5L scores were 0.61 both arms (p = 0.85) at baseline. At 30 days, EQ-5D-5L scores were 0.63 and 0.64 for patients in the convalescent plasma and standard care arms respectively (p = 0.46). The incremental cost was $4,458 and incremental quality-adjusted life day was − 0.078.Conclusion These results indicate that convalescent plasma was less effective and more costly than standard care in treating hospitalized patients with COVID-19. The sensitivity analysis yielded similar results to the base case analysis.

Improving modelling for epidemic responses: reflections from members of the UK infectious disease modelling community on their experiences during the COVID-19 pandemic (preprint)

The COVID-19 pandemic both relied and placed significant burdens on the experts involved from research and public health sectors. The sustained high pressure of a pandemic on responders, such as healthcare workers, can lead to lasting psychological impacts including acute stress disorder, post-traumatic stress disorder, burnout, and moral injury, which can impact individual wellbeing and productivity. As members of the infectious disease modelling community, we convened a reflective workshop to understand the professional and personal impacts of response work on our community and to propose recommendations for future epidemic responses. The attendees represented a range of career stages, institutions, and disciplines. This piece was collectively produced by those present at the session based on our collective experiences. Key issues we identified at the workshop were lack of institutional support, insecure contracts, unequal credit and recognition, and mental health impacts. Our recommendations include rewarding impactful work, fostering academia-public health collaboration, decreasing dependence on key individuals by developing teams, increasing transparency in decision-making, and implementing sustainable work practices. Despite limitations in representation, this workshop provided valuable insights into the UK COVID-19 modelling experience and guidance for future public health crises. Recognising and addressing the issues highlighted here is crucial, in our view, for ensuring the effectiveness of epidemic response work in the future.

Mediating effect of resilience and fear of COVID-19 on the relationship between social support and post-traumatic stress disorder among campus-quarantined nursing students: a cross-sectional study.

BACKGROUND: The emergency of Omicron variants, spreading in China and worldwide, has sparked a new wave of the coronavirus disease 2019 (COVID-19) pandemic. The high infectivity and persistence of the pandemic may trigger some degrees of post-traumatic stress disorder (PTSD) for nursing students experiencing indirect trauma exposure to the epidemic, which hinders the role transition from students to qualified nurses and exacerbates the health workforce shortage. Thus, it's well worth an exploration to understand PTSD and its underlying mechanism. Specifically, PTSD, social support, resilience, and fear of COVID-19 were selected after widely literature review. This study aimed to investigate the relationship between social support and PTSD among nursing students during COVID-19, to address the mediating role of resilience and fear of COVID-19 between social support and PTSD, and to provide practical guidance for nursing students' psychological intervention. METHODS: From April 26 to April 30, 2022, 966 nursing students from Wannan Medical College were selected by the multistage sampling method to fill the Primary Care PTSD Screen for the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), Brief Resilience Scale, Fear of COVID-19 Scale, and Oslo 3 Items Social Support Scale. Data were analyzed by descriptive statistics, spearman's correlation analysis, regression analysis, and path analysis. RESULTS: 15.42% of nursing students had PTSD. There were significant correlations between social support, resilience, fear of COVID-19, and PTSD (r =-0.291 ~ 0.353, P <0.001). Social support had a direct negative effect on PTSD (ß =-0.216; 95% confidence interval, CI: -0.309~-0.117), accounting for 72.48% of the total effect. Analysis of mediating effects revealed that social support influenced PTSD through three indirect pathways: the mediated effect of resilience was statistically significant (ß =-0.053; 95% CI: -0.077~-0.031), accounting for 17.79% of the total effect; the mediated effect of fear of COVID-19 was statistically significant (ß =-0.016; 95% CI: -0.031~-0.003), accounting for 5.37% of the total effect; the chain mediating effect of resilience and fear of COVID-19 was statistically significant (ß =-0.013; 95% CI: -0.022~-0.006), accounting for 4.36% of the total effect. CONCLUSION: The social support of nursing students not only directly affects PTSD, but also indirectly affects PTSD through the separate and chain mediating effect of resilience and fear of COVID-19. The compound strategies targeted at boosting perceived social support, fostering resilience, and controlling fear of COVID-19 are warranted for reducing PTSD.

Work as a Frontline Volunteer During the COVID-19 Outbreak in Hubei, China: A Qualitative Inquiry of Male Nurses.

BACKGROUND: During the coronavirus (COVID-19) outbreak in 2019, an increased large number of male nurses volunteered for frontline assignment. Their excellent performance suggests that male nurses have several advantages over female nurses. However, research into the activities of Chinese male nurses engaged in frontline work during the COVID-19 pandemic remains limited. PURPOSE: This study was designed to summarize the reflections of male nurses on their experiences while volunteering for frontline COVID-19 duty in Hubei, China. METHODS: An interpretative qualitative descriptive study was conducted from May to July 2020 on male nurses who had volunteered for frontline COVID-19 duty in Hubei. Twelve male nurses were selected using a purposive sampling method. Data were collected using semistructured interviews, transcribed verbatim, and analyzed using thematic analysis. RESULTS: Four main themes and 11 subthemes were identified, including (a) changing the way of thinking at work (four subthemes), (b) clarity regarding career development (three subthemes), (c) change in life philosophy (two subthemes), and (d) personal growth (two subthemes). CONCLUSIONS: The experience of volunteering during the COVID-19 public health emergency influenced the male nurses positively in terms of improved organizational, management, and decision-making skills as well as improved performance. The beneficial attributes of male nurses should be taken into consideration when developing management policies related to nursing personnel.

Evaluating the Impact of COVID-19 on Hospital Profit Compensation Activities: A Difference-in-Differences Event Study Analysis in China.

The impact of the 2019 coronavirus disease (COVID-19) pandemic is still being revealed, and little is known about the effect of COVID-19-induced outpatient and inpatient losses on hospital operations in many counties. Hence, we aimed to explore whether hospitals adopted profit compensation activities after the 2020 first-wave outbreak of COVID-19 in China. A total of 2,616,589 hospitalization records from 2018, 2019, and 2020 were extracted from 36 tertiary hospitals in a western province in China; we applied a difference-in-differences event study design to estimate the dynamic effect of COVID-19 on hospitalized patients' total expenses before and after the last confirmed case. We found that average total expenses for each patient increased by 8.7% to 16.7% in the first 25 weeks after the city reopened and hospital admissions returned to normal. Our findings emphasize that the increase in total inpatient expenses was mainly covered by claiming expenses from health insurance and was largely driven by an increase in the expenses for laboratory tests and medical consumables. Our study documents that there were profit compensation activities in hospitals after the 2020 first-wave outbreak of COVID-19 in China, which was driven by the loss of hospitalization admissions during this wave outbreak.

Porcine Epidemic Diarrhea Virus Replication in Human Intestinal Cells Reveals Potential Susceptibility to Cross-Species Infection.

Various coronaviruses have emerged as a result of cross-species transmission among humans and domestic animals. Porcine epidemic diarrhea virus (PEDV; family Coronaviridae, genus Alphacoronavirus) causes acute diarrhea, vomiting, dehydration, and high mortality in neonatal piglets. Porcine small intestinal epithelial cells (IPEC-J2 cells) can be used as target cells for PEDV infection. However, the origin of PEDV in pigs, the host range, and cross-species infection of PEDV remain unclear. To determine whether PEDV has the ability to infect human cells in vitro, human small intestinal epithelial cells (FHs 74 Int cells) were inoculated with PEDV LJX and PEDV CV777 strains. The results indicated that PEDV LJX, but not PEDV CV777, could infect FHs 74 Int cells. Furthermore, we observed M gene mRNA transcripts and N protein expression in infected FHs 74 Int cells. A one-step growth curve showed that the highest viral titer of PEDV occurred at 12 h post infection. Viral particles in vacuoles were observed in FHs 74 Int cells at 24 h post infection. The results proved that human small intestinal epithelial cells are susceptible to PEDV infection, suggesting the possibility of cross-species transmission of PEDV.

Pathway of Cell Death and Its Role in Virus Infection.

The global pandemic of SARS-CoV-2 in the past 2 years has aroused great attention to infectious diseases, and emerging virus outbreaks have brought huge challenges to the global health system. Viruses are specific pathogens that completely rely on host cells for their own survival and disease transmission. At present, a growing number of studies have proved that inducing the death of virus-infected cells can prevent the spread of virus and promote disease recovery. Therefore, many ways to induce the death of infected cells are considered to be beneficial to host immunity. Cell death is a basic biological phenomenon. Programmed cell death (PCD), as an important part of the host's innate immune response, provides effective protection against virus transmission. Pyroptosis, apoptosis, and necroptosis are the most commonly studied pathways of PCD. Recent studies have found that three pathways of cell death can be activated during virus infection. More and more studies have shown the existence of extensive connections between PCDs, and this complex relationship is defined as PANoptosis, an inflammatory PCD pathway regulated by the PANoptosome complex, whose characteristics cannot be explained by any of the three PCD pathways. During viral infection, PANoptosis can promote inflammatory response by inducing the production of inflammatory cytokines and cell death to exert an antiviral mechanism. This article reviews the various effects of cell death pathways during viral infection and provides new ideas for clinical antiviral therapy and related immunotherapy.

Open problems in causal structure learning: A case study of COVID-19 in the UK (preprint)

Causal machine learning (ML) algorithms recover graphical structures that tell us something about cause-and-effect relationships. The causal representation praovided by these algorithms enables transparency and explainability, which is necessary for decision making in critical real-world problems. Yet, causal ML has had limited impact in practice compared to associational ML. This paper investigates the challenges of causal ML with application to COVID-19 UK pandemic data. We collate data from various public sources and investigate what the various structure learning algorithms learn from these data. We explore the impact of different data formats on algorithms spanning different classes of learning, and assess the results produced by each algorithm, and groups of algorithms, in terms of graphical structure, model dimensionality, sensitivity analysis, confounding variables, predictive and interventional inference. We use these results to highlight open problems in causal structure learning and directions for future research. To facilitate future work, we make all graphs, models, data sets, and source code publicly available online.

COVID-19 and Obesity: Epidemiology, Pathogenesis and Treatment.

The growing prevalence of overweight and obesity has been a worldwide public health issue. During the COVID-19 pandemic, obesity is associated with a higher risk of severity and a worse clinical outcome of SARS-COV-2 infection. This may be because of the chronic low-grade inflammation, impaired immune response and metabolic disorders in obese patients. In this narrative review, we have summarized the association between obesity and COVID-19 and discussed the potential pathogenesis and treatment in these patients. This work may provide practical suggestions on the clinical management of obese COVID-19 patients.

A new polysaccharide platform constructs self-adjuvant nanovaccines to enhance immune responses.

BACKGROUND: Nanovaccines have shown the promising potential in controlling and eradicating the threat of infectious diseases worldwide. There has been a great need in developing a versatile strategy to conveniently construct diverse types of nanovaccines and induce potent immune responses. To that end, it is critical for obtaining a potent self-adjuvant platform to assemble with different types of antigens into nanovaccines. RESULTS: In this study, we identified a new natural polysaccharide from the rhizomes of Bletilla striata (PRBS), and used this polysaccharide as a platform to construct diverse types of nanovaccines with potent self-adjuvant property. In the construction process of SARS-CoV-2 nanovaccine, PRBS molecules and RBD protein antigens were assembled into ~ 300 nm nanoparticles by hydrogen bond. For HIV nanovaccine, hydrophobic effect dominantly drove the co-assembly between PRBS molecules and Env expression plasmid into ~ 350 nm nanospheres. Importantly, PRBS can potently activate the behaviors and functions of multiple immune cells such as macrophages, B cells and dendritic cells. Depending on PRBS-mediated immune activation, these self-adjuvant nanovaccines can elicit significantly stronger antigen-specific antibody and cellular responses in vivo, in comparison with their corresponding traditional vaccine forms. Moreover, we also revealed the construction models of PRBS-based nanovaccines by analyzing multiple assembly parameters such as bond energy, bond length and interaction sites. CONCLUSIONS: PRBS, a newly-identified natural polysaccharide which can co-assemble with different types of antigens and activate multiple critical immune cells, has presented a great potential as a versatile platform to develop potent self-adjuvant nanovaccines.

Work: A Social Determinant of Health Worth Capturing.

Work is a recognized social determinant of health. This became most apparent during the COVID-19 pandemic. Workers, particularly those in certain industries and occupations, were at risk due to interaction with the public and close proximity to co-workers. The purpose of this study was to assess how states collected work and employment data on COVID-19 cases, characterizing the need for systematic collection of case-based specific work and employment data, including industry and occupation, of COVID-19 cases. A survey was distributed among state occupational health contacts and epidemiologists in all 50 states to assess current practices in state public health surveillance systems. Twenty-seven states collected some kind of work and employment information from COVID-19 cases. Most states (93%) collected industry and/or occupation information. More than half used text-only fields, a predefined reference or dropdown list, or both. Use of work and employment data included identifying high risk populations, prioritizing vaccination efforts, and assisting with reopening plans. Reported barriers to collecting industry and occupation data were lack of staffing, technology issues, and funding. Scientific understanding of work-related COVID-19 risk requires the systematic, case-based collection of specific work and employment data, including industry and occupation. While this alone does not necessarily indicate a clear workplace exposure, collection of these data elements can help to determine and further prevent workplace outbreaks, thereby ensuring the viability of the nation's critical infrastructure.

Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.

The COVID-19 pandemic highlighted the need for decision-support tools to help cities become more resilient to infectious diseases. Through urban design and planning, non-pharmaceutical interventions can be enabled, nudging behaviour change and facilitating lower risk buildings and public spaces. Computational tools, including computer simulation, statistical models, and artificial intelligence, were used to support responses in the current pandemic as well as to the previous infectious diseases. Our multidisciplinary research group systematically reviewed state-of-the-art literature to propose a toolkit that employs computational modelling for various interventions and urban design processes. From 8,737 records returned from databases, 109 records were selected and analysed based on the pathogen type, transmission mode and phase, design intervention and process, as well as modelling methodology (method, goal, motivation, focus, and indication to urban design). We also explored the relationship between infectious disease and urban design as well as computational modelling supports, including specific models and parameters. The proposed toolkit will help designers, planners, and computer modellers to select relevant approaches to evaluate and consider design decisions depending on the disease, geographic context, design stages, and spatial and temporal scales. The findings herein can be regarded as stand-alone tools, particularly for COVID-19 or be incorporated into broader frameworks to help cities become more resilient to future disasters.

The third inactivated vaccine booster dramatically enhanced SARS-CoV-2 antibody responses and did not influence the profile of prothrombotic antibody.

OBJECTIVE: The purpose of this study is to investigate the production of both SARS-CoV-2-specific antibodies and autoantibodies in serum following the third booster vaccination of the inactivated COVID-19 vaccine, and to study the effect of B cell subsets with CD27 and CD38 phenotypes in peripheral blood on antibody production. METHODS: Routine blood indexes, SARS-CoV-2 antibodies, platelet factor 4 and seven antiphospholipid antibodies were detected both before and 2 months after vaccination in the medical staff of the Zhongnan Hospital of Wuhan University. Peripheral blood B cell subtypes were detected prior to vaccination. RESULTS: Following immunization, the positive rate of anti-N-S1 IgG had increased from 24.8% to 91.3% and the average antibody concentration had increased by 11 times. The positive rate of NAb had increased from 24.8% to 91.3%, the average antibody concentration had increased by 12 times, and the primary increased anti-S1 IgG subtype was that of IgG1. Peripheral blood CD27+CD38+ B cells were positively correlated with antibody levels after vaccination and were a predictor of the antibody response. In addition, although some indicators showed slight absolute changes, the blood parameters and antiphospholipid antibodies of most volunteers were normal both before and after COVID-19 inactivated vaccine inoculation, and there was no statistical difference in abnormal rates either before or after inoculation. CONCLUSION: Antibodies in vivo were increased after vaccination with the inactivated vaccine, and IgG1 was the main subtype involved in response to the vaccine. Vaccination with the inactivated COVID-19 vaccine did not appear to affect thrombus-related autoantibodies. This article is protected by copyright. All rights reserved.

Anxiety, depression and post-traumatic stress disorder and related factors among Chinese population during the COVID-19 pandemic: A cross-sectional study

The sudden outbreak of coronavirus disease 2019 (COVID-19) has deep and wide negative mental impacts on the public, and studies on the impact of COVID-19 on social and mental well-being are necessary. This study aimed to evaluate mental distress, including anxiety, depression, and post-traumatic stress disorder (PTSD), and its related risk factors in Chinese adults in the early stages of the COVID-19 pandemic. This study used a large-scale cross-sectional design. A total of 2067 adult participants completed the online survey via REDcap from 1st to 15th of March 2020 during the COVID-19 outbreak in China. Anxiety, depression, PTSD, and related risk factors, including self-efficacy, coping style, and social support, were measured using valid and reliable instruments. The data were analyzed using multiple linear regression. We found that 201 (9.7%) participants reported moderate-to-severe anxiety, 669 (33.8%) reported depression, and 368 (17.8%) reported symptoms of PTSD. Self-efficacy, coping style, and social support significantly affected anxiety, depression, and PTSD symptoms. Participants' sociodemographic characteristics, COVID-19 pandemic-related factors, low self-efficacy, low social support, and negative coping were predictors of mental distress during the COVID-19 pandemic. Our study will help healthcare professionals carry out early predictions and identification of high-risk groups and provide appropriate interventions to target groups during public health emergencies that plague the world.

Redistribution and activation of CD16brightCD56dim NK cell subset to fight against Omicron subvariant BA.2 after COVID-19 vaccination (preprint)

With the alarming surge in COVID-19 cases globally, vaccination must be prioritised to achieve herd immunity. Immune dysfunction is detected in the majority of patients with COVID-19; however, it remains unclear whether the immune responses elicited by COVID-19 vaccination function against the Omicron subvariant BA.2. Of the 508 Omicron BA.2-infected patients enrolled, 102 were unvaccinated controls and 406 were vaccinated. Despite the presence of clinical symptoms in both groups, vaccination led to a significant decline in nausea or vomiting, abdominal pain, headache, pulmonary infection, overall clinical symptoms, and a moderate rise in body temperature. Omicron BA.2-infected individuals were also characterised by a mild increase in both serum pro- and anti-inflammatory cytokine levels after vaccination. There were no significant differences or trend changes between T and B lymphocyte subsets; however, a significant expansion of NK lymphocytes in COVID-19-vaccinated patients was observed. Moreover, the most effective CD16brightCD56dim subsets of NK cells showed increased functional capacities, as evidenced by a significantly greater IFN-{gamma} secretion and stronger cytotoxic potential in Omicron BA.2-infected patients after vaccination. Collectively, these results suggest that COVID-19 vaccination interventions promote the redistribution and activation of CD16brightCD56dim NK cell subsets against viral infections, and could facilitate the clinical management of Omicron BA.2-infected patients.

Identification of highly effective inhibitors against SARS-CoV-2 main protease: From virtual screening to in vitro study

Background and Objective: The public’s safety has been significantly jeopardized by the pandemic of COVID-19, which is brought on by the highly virulent and contagious SARS-CoV-2 virus. Finding novel antiviral drugs is currently of utmost importance for the treatment of patients with COVID-19. Main protease (3CLpro) of SARS-CoV-2 is involved in replication of virus, so it is considered as a promising target. Using small molecules to inhibit SARS-CoV-2-3CLpro activity may be an effective way to prevent viral replication to fight COVID-19. Despite the fact that some SARS-CoV-2-3CLpro inhibitors have been described, only few of them have high levels of inhibition at nanomolar concentrations. In this study, we aimed to screen out effective SARS-CoV-2-3CLpro inhibitors. Methods: To identify highly effective SARS-CoV-2-3CLpro inhibitors, a pharmacophore mapping and multiple-conformation docking were efficiently applied to find novel hit compounds from a database. Then, the stability of the 3CLpro-hit complexes was validated by using molecular dynamics simulation. Finally, biological assay was used to assess the inhibition effects of hit compounds on SARS-CoV-2-3CLpro. Results: Four hit compounds were identified by using computer-assisted strategy. Molecular dynamics simulation suggested that these hits bound stably to the 3CLpro-active pocket. Bioassay showed that all the hits had potent inhibition against SARS-CoV-2-3CLpro with IC50 values in the range of 0.017–0.83 μM. Particularly, hit one was the best 3CLpro inhibitor and its inhibition effect of SARS-CoV-2-3CLpro (IC50 = 0.017 ± 0.003 µM) was about 236 times stronger than that of ML300 (IC50 = 4.01 ± 0.66 µM). Conclusion: These data indicate that hit one could be regarded as an anti-SARS-CoV-2 candidate worth exploring further for the treatment of COVID-19.

China-Europe freight transportation under the first wave of COVID-19 pandemic and government restriction measures

International freight transportation experienced significant disruptions during the COVID-19 pandemic. The impact of the pandemic and related government restriction measures on international freight transportation is worth analysing for the development of transportation policies and practices in the post-pandemic period, but has received limited attention. To fill the gap, this study applies structural equation models to analyze the impact of the COVID-19 pandemic on the international transportation market and the relationships among the pandemic, government restriction measures, and international transportation market. The impact is also differentiated for different modes of transportation. Results confirm that both demand and supply of international transportation services have been negatively affected by the first wave of the pandemic, with sea transportation being more affected by the reduction of demand and air transportation more by the supply volatility. The government restriction measures are found to play a mediation role, in the way that the impact of the pandemic on the supply of transportation service is suppressed through the government restriction measures. Our findings provide important guidance for transportation industry players and governments in their decision-making process facing with global market shocks such as a pandemic.

Recursive Zero-COVID model and quantitation of control efforts of the Omicron epidemic in Jilin province.

Since the beginning of March 2022, the epidemic due to the Omicron variant has developed rapidly in Jilin Province. To figure out the key controlling factors and validate the model to show the success of the Zero-COVID policy in the province, we constructed a Recursive Zero-COVID Model quantifying the strength of the control measures, and defined the control reproduction number as an index for describing the intensity of interventions. Parameter estimation and sensitivity analysis were employed to estimate and validate the impact of changes in the strength of different measures on the intensity of public health preventions qualitatively and quantitatively. The recursive Zero-COVID model predicted that the dates of elimination of cases at the community level of Changchun and Jilin Cities to be on April 8 and April 17, respectively, which are consistent with the real situation. Our results showed that the strict implementation of control measures and adherence of the public are crucial for controlling the epidemic. It is also essential to strengthen the control intensity even at the final stage to avoid the rebound of the epidemic. In addition, the control reproduction number we defined in the paper is a novel index to measure the intensity of the prevention and control measures of public health.

Effect of GS-441524 in combination with the 3C-like protease inhibitor GC376 on the treatment of naturally transmitted feline infectious peritonitis.

Objectives: The main objectives of this study were to investigate the efficacy of the nucleotide analog GS-441524 in combination with the 3C-like protease inhibitor GC376 for the treatment of naturally aquired feline infectious peritonitis (FIP) and to test whether their combination shortens the dosing period and improves the cure rate. Methods: In total, 46 FIP-affected cats were enrolled in this experiment, including 36 with wet FIP (29 with abdominal effusion, six with thoracic effusion, and one with thoracic+abdominal effusion), and 10 with dry FIP. The cats were aged from 3 to 96 months. Thoracic+abdominal effusion, lymph-node puncture fluid and perirenal puncture fluid was collected from the affected cats for qPCR testing, and all 46 cats were positive for feline coronavirus (FCoV). The cats divided into different dose groups, all treated for 4 weeks: group 1 (GS-441524, 5 mg/kg.sc.q.24 h; GC376, 20 mg/kg.sc.q.12 h), group 2 (GS-441524, 2.5 mg/kg.sc.q.24 h; GC376, 20 mg/kg.sc.q.12 h), group 3 (GS-441524, 2.5 mg/kg.sc.q.24 h; GC376, 10 mg/kg.sc.q.12 h), and group 4 (GS-441524, 5 mg/kg.sc.q.24 h; GC376, 10 mg/kg.sc.q.12 h). Results: After the 4-week combination treatment, 45 of the 46 (97.8%) cats survived, and 43 of those became clinically normal. Two cats required longer (7 to 12 weeks) treatment to achieve full recovery. As of writing (10 months after completion of the trial), all 45 cats were alive and no relapse was observed. Conclusions and relevance: GS-441524 combined with GC376 can be safely and effectively used to treat FIP and reduces the treatment period to 4 weeks, with an excellent cure rate.