Comparison of Comorbidities between Adults and Children with Glycogen Storage Disease Type Ia (GSDIA)

Objectives: Glycogen Storage Disease Type Ia (GSDIa) is a rare inherited disorder resulting in acute hypoglycemia due to impaired release of glucose from glycogen. Despite dietary management practices to prevent hypoglycemia in patients with GSDIa, complications still occur in children and throughout adulthood. This retrospective cohort study compared the prevalence of complications in adults and children with GSDIa. Method(s): Using ICD-10 diagnosis codes, the IQVIA Pharmetrics Plus database was searched for patients with >=2 GSDI claims (E74.01) from January 2016 through February 2020, with >=12 months continuous enrollment beginning prior to March 2019 (for one year of follow-up before COVID-19), and no inflammatory bowel disease diagnoses (indicative of GSDIb). Complication prevalence in adults and children with GSDIa was summarized descriptively. Result(s): In total, 557 patients with GSDIa were identified (adults, 67%;male, 63%), including 372 adults (median age, 41 years) and 185 children (median age, 7 years). Complications occurring only in adults were atherosclerotic heart disease (8.6%), pulmonary hypertension (3.0%), primary liver cancer (1.9%), dialysis (0.8%), and focal segmental glomerulosclerosis (0.3%). Other complications with the greatest prevalence in adults/children included gout (11.8%/0.5%), insomnia (10.0%/1.1%), osteoarthritis (22.0%/2.7%), severe chronic kidney disease (4.3%/0.5%), malignant neoplasm (10.8%/1.6%), hypertension (49.7%/8.7%), acute kidney failure (15.3%/2.7%), pancreatitis (3.0%/0.5%), gallstones (7.8%/1.6%), benign neoplasm (37.4%/8.1%), hepatocellular adenoma (7.0%/1.6%), neoplasm (41.1%/9.7%), and hyperlipidemia (45.2%/10.8%). Complications with the greatest prevalence in children/adults included poor growth (22.2%/1.9%), gastrostomy (29.7%/3.2%), kidney hypertrophy (2.7%/0.8%), seizure (1.6%/0.5%), hypoglycemia (27.0%/11.3%), hepatomegaly (28.7%/15.9%), kidney transplant (1.6%/1.1%), diarrhea (26.5%/18.6%), nausea and/or vomiting (43.8%/35.8%), acidosis (20.0%/17.2%), and anemia due to enzyme disorders (43.8%/40.6%). Conclusion(s): GSDIa is associated with numerous, potentially serious complications. Compared with children, adults with GSDIa had a greater prevalence of chronic complications, potentially indicating the progressive nature of disease. Children with GSDIa had more acute complications related to suboptimal metabolic control.Copyright © 2023

Can internet concern about COVID-19 help predict stock markets: new evidence from high-concern and low-concern periods

The unprecedented outbreak of Corona Virus Disease 2019 (COVID-19) has resulted in extreme volatility in stock markets. This study mainly examines the predictive ability of the Internet concern about COVID-19 on stock index returns, based on the framework of GARCH type models. Instead of using the whole sample period, we divide the Internet concern about COVID-19 into high-concern and low-concern periods by breakpoint test method and then examine its predictive ability for stock returns in different periods, respectively. Using stock indexes of 10 countries and abnormal Google search volume of 'coronavirus' as study samples, the results reveal that (1) the Internet concern about COVID-19 has a negative impact on the stock index returns in the whole and high-concern periods, while its influence in the low-concern period is mixed;(2) the Internet concern about COVID-19 improves the prediction accuracy of stock index returns in the high-concern period, while seems to lose its powerful predictive ability in the whole and low-concern periods.

COVID-19 Pandemic as an Opportunity or Challenge: Applying Psychological Distance Theory and the Co-Benefit Frame to Promote Public Support for Climate Change Mitigation on Social Media

The current study employs psychological distance theory and the co-benefit frame to explore message framing strategies on social media to promote public support in climate change mitigation during the COVID-19 pandemic. This online 2 x 2 x 2 experiment recruited 708 Chinese college students to examine the effect of temporal distance (2025 vs. 2050), spatial distance (China vs. the global), and the co-benefit frame (present vs. absent) on behavioral intentions to mitigate climate change and policy support in climate change mitigation. Unexpectedly, the MANOVA results showed that the co-benefit frame of COVID-19 and climate change did not have main or interaction that affect behavioral intention and policy support. However, close temporal distance increases support for climate change mitigation. Meanwhile, temporal and spatial distance have an interaction on behavioral intention. Our results suggest that strategies to reduce psychological distance on social media are effective, especially on temporal distance, but bonding two events through psychological distance to promote support for climate change mitigation must be reconsidered.

Innovations in Ambulatory Stewardship

Ambulatory antibiotic use accounts for most of the global consumption of antibiotics leading to selection pressure, multidrug resistance, and significant healthcare costs (https://www.cdc.gov/antibiotic-use/community/pdfs/16_268900-A_CoreElementsOutpatient_508.pdf) The Centers for Disease Control and Prevention established the Core Elements of outpatient antimicrobial stewardship in 2016 as a framework to develop, expand, and evaluate ambulatory stewardship programs, which must address overuse in multiple settings (e.g., urgent care centers, adult and pediatric outpatient practices, dental practices, and retail clinics). As such, we present examples of innovative yet adaptable outpatient stewardship initiatives encompassing a variety of settings. We also address patterns of ambulatory antibiotic prescribing and novel stewardship initiatives implemented during the novel coronavirus disease 2019 (COVID-19) pandemic. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Artificial Bee Colony for Logic Mining in Credit Scoring

During the SARS-CoV-2 (Covid-19) pandemic, credit applications skyrocketed unimaginably. Thus, creditors or financial entities were burdened with information overload to ensure they provided the proper credit to the right person. The existing methods employed by financial entities were prone to overfitting and did not provide any information regarding the behavior of the creditor. However, the outcome did not consider the attribute of the creditor that led to the default outcome. In this paper, a swarm intelligence-based algorithm named Artificial Bee Colony has been implemented to optimize the learning phase of the Hopfield Neural Network with 2 Satisfiability-based Reverse Analysis Methods. The proposed hybrid model will be used to extract logical information in the credit data with more than 80% accuracy compared to the existing method. The effectiveness of the proposed hybrid model was evaluated and showed superior results compared to other models.

Towards a Model for Inclusive Healthcare Access post COVID-19

The devastation caused by the COVID-19 pandemic has exposed years of cyclic inequalities faced by disadvantaged and minority communities. Unequal access to healthcare and a lack of financial resources further exacerbates their suffering, especially during a pandemic. In such critical conditions, information technology-based healthcare services can be an efficient way of increasing access to healthcare for these communities. In this paper, we put forward a decision model for guiding the distribution of IT-based healthcare services for racial minorities. We augment the Health Belief Model by adding financial and technology beliefs. We posit that financial inclusion of minority populations increases their ability to access technology and, by extension, IT-based healthcare services. Financial inclusion and the use of secure private technologies like federated learning can indeed enable greater access to healthcare services for minorities. Therefore, we incorporate financial, health, and technology tools to develop a model for equitable delivery of healthcare services and test its applicability in different use-case scenarios. © 2022 IEEE Computer Society. All rights reserved.

Effects of Temperature and Water Types on the Decay of Coronavirus: A Review

The analysis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) gene copy numbers in wastewater samples can provide quantitative information on Coronavirus Disease-19 (COVID-19) cases within a sewer catchment. However, many wastewater-based epidemiology (WBE) studies have neglected virus decay during the wastewater transportation process in sewers while back-calculating COVID-19 prevalence. Among various sewer condition parameters, wastewater temperature and dilution by fresh/saltwater infiltration may result in a significant change to the virus decay, in terms of both infectivity and Ribonucleic Acid (RNA). This paper reviewed the literature to identify and discuss the effects of temperature and water types (i.e., wastewater, freshwater, and seawater) on coronavirus decay based on the decay rate constants that were collected from published papers. To evaluate the importance of virus decay, a sensitivity analysis was then conducted with decay rates of SARS-CoV-2 RNA based on a WBE back-calculation equation. Finally, the decay rates of coronavirus in wastewater were also compared with those of other viruses to further understand the difference among virus species. The decay of SARS-CoV-2 RNA was found to be less impacted by temperature variation than viable coronaviruses. Nevertheless, WBE back-calculation was still sensitive to the RNA decay rates increased by warm wastewater (i.e., over 26 °C), which could lead to a two-times higher relative variance in estimated COVID-19 prevalence, considering the wastewater temperature variation between 4 and 37 °C in a sewer catchment with a 12-h hydraulic retention time. Comparatively, the sensitivity of the WBE estimation to the enveloped SARS-CoV-2 was greater than nonenveloped enteric viruses, which were less easily degradable in wastewater. In addition, wastewater dilution by stormwater inflow and accompanied cold weather might alleviate the decay of coronavirus infectivity, thus increasing the potential risk of COVID-19 transmission through wastewater. Overall, this paper aims to better understand the impact of in-sewer processes on coronavirus decay and its potential implications for WBE. The outcome could quantitatively inform WBE and improve awareness of the increased risk of COVID-19 infection via wastewater during heavy rainfall events. Given the identified scarcity of data available for coronavirus decay in salt water or with chemical additions, future research on the fate of SARS-CoV-2 subjected to chemical dosing for sewer or wastewater treatment plant operations is recommended. © 2023 by the authors.

A Prompt-Based Topic-Modeling Method for Depression Detection on Low-Resource Data

Depression has a large impact on one’s personal life, especially during the COVID-19 pandemic. People have been trying to develop reliable methods for the depression detection task. Recently, methods based on deep learning have attracted much attention from the research community. However, they still face the challenge that data collection and annotation are difficult and expensive. In many real-world applications, only a small number of or even no training data are available. In this context, we propose a Prompt-based Topic-modeling method for Depression Detection (PTDD) on low-resource data, aiming to establish an effective way of depression detection under the above challenging situation. Instead of learning discriminating features from a small amount of labeled data, the proposed framework turns to leverage the generalization power of pretrained language models. Specifically, based on the question-and-answer routine during the interview, we first reorganize the text data according to the predefined topics for each interviewee. Via the prompt-based framework, we then predict whether the next-sentence prompt is emotionally positive or not. Finally, the depression detection task can be achieved based on the obtained topicwise predictions through a simple voting process. In the experiments, we validate the effectiveness of our model under several low-resource data settings. The results and analysis demonstrate that our PTDD achieves acceptable performance when only a few training samples or even no training samples are available. IEEE

[The predictive value of warning scores for intensive care unit admission in coronavirus disease 2019 patients].

To evaluate the predictive value of early warning scores for intensive care unit (ICU) admission in patients with coronavirus disease 2019 (COVID-19). For COVID-19 patients who were admitted to Shijiazhuang People's Hospital from January 2021 to February 2021, national early warning score (NEWS), national early warning score 2 (NEWS2), rapid emergency medicine score (REMS), quick sepsis-related organ failure (qSOFA), altered consciousness, blood urea nitrogen, respiratory rate, blood pressure, and age-65 (CURB-65) were used to evaluate the inpatient condition and the predictive value for ICU admission. A total of 368 patients were included, and 32 patients (8.7%) were transferred to the ICU. The median age was 49.0 (34.0,61.0) years. The scores of NEWS, NEWS2, REMS, and CURB-65 were 1 (0, 2), 1 (0, 2), 4 (2, 6) and 0 (0, 1), respectively. The receiver operating characteristic (ROC) cure (AUC) was used to evaluate the predictive value in detecting patients who are at risk of being transferred to the ICU. Area under the ROC AUC of NEWS was 0.756, sensitivity 65.6%, and specificity 71.3%. ROC AUC of NEWS2 was 0.732, sensitivity 62.5%, and specificity 61.3%. ROC AUC of REMS was 0.787, sensitivity 84.4%, and specificity 64.6%. ROC AUC of CURB-65 was 0.814, sensitivity 81.3%, and specificity 76.8%. The predictive value of NEWS and NEWS2 combined with age were significantly improved. The ROC AUC of NEWS combined with age was 0.885, sensitivity 85.1%, and specificity 75.0%. The ROC AUC of NEWS2 combined with age was 0.883, sensitivity 84.2%, and specificity 75.0%. NEWS and NEWS2 combined with age can be used as a predictive tool for whether COVID-19 patients will be admitted to the ICU.

Segmentation Algorithm for COVID-19 Infections using Joint Mix and Context Encoder

Automatic image segmentation is critical for medical image segmentation. For example, automatic segmentation of infection area of COVID-19 before and after diagnosis and treatment can help us automatically analyze the diagnosis and treatment effect. The existing algorithms do not solve the problems of insufficient data and insufficient feature extraction at the same time. In this paper, we propose a new data augmentation algorithm to handle the insufficient data problem, named Joint Mix;we utilize an improved U-Net with context encoder to enhance the feature extraction ability. Experiments in the segmentation of COVID-19 infection region using CT images demonstrate its effectiveness. © 2022 IEEE.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Buzzo or Eureka - Robot that Makes Remote Participants Feel More Presence in Hybrid Discussions

Teleconferencing technology has been widely used in the context of the covid-19 pandemic. However, local and remote participants always have a poorer experience of hybrid discussion for various reasons in the leaderless group discussions with mixed online and offline members. In this paper, this phenomenon is explored through an early pilot study. We found problems with the lack of presence of remote participants in hybrid discussion sessions, as well as unclear information about the status of members. To solve such problems, we've designed a social robot called SNOTBOX. The bot indicates the participation status (marginalized or not) of the remote participant using "Buzzo" and the remote participant's desire to be heard through a "Eureka". We used both representations to attract the attention of local participants as a way to enhance the presence of remote participants in the conference. SNOTBOX is easy to produce and allows for DIY customization, and also supports multi-participant online discussions. © 2023 IEEE Computer Society. All rights reserved.

The New Progress and Methods of Privacy Protection on Medical and Health Big Data*

In recent years, due to the emergence of COVID-19(Corona Virus Disease 2019), how to have a higher quality medical environment has become a troubling problem. The proposal of the Office of the State Council on promoting the development of 'Internet plus medical and health' has brought a lot of convenience to the public, but also brought about the problem of data leakage and other user privacy protection. In view of the problems of user's personal information storage and user's health data processing in the medical and health context, how to ensure that these data are not stolen, leaked or tampered with has become a major challenge faced by current researchers. Based on the privacy protection of users in the context of health care, this paper classifies the current privacy protection mechanisms, and introduces the latest progress of related technologies. Finally, according to the integrated information, the research direction of privacy protection technologies in the field of health care is prospected. © 2022 IEEE.

Fast In Situ Inactivation of Pathogens in Tubes by Plasma

During the COVID-19 pandemic, the prevailing method for inactivating samples used in nucleic acid detection is a time-consuming process that involves heating the samples in a thermostatic water bath at 56 <inline-formula> <tex-math notation="LaTeX">$

Is the global supply chain hard to reverse? Understanding manufacturing strategies of Chinese, Japanese, and South Korean Firms

As the Covid pandemic underscores global supply chain risks, there is a debate on whether to bring US manufacturing back from overseas. This paper provides insights into the heated debate on the global supply chain by examining the competitive manufacturing environments of China, Japan, and South Korea. More specifically, we conduct a cross-national survey and empirically investigate the manufacturing strategies employed by manufacturing managers in the top Asian players: China, Japan, and South Korea. We examine four dimensions of the manufacturing strategies: quality, inventory, flexibility, and top management involvement. Our findings indicate that Japanese manufacturers are more committed to the cumulative approach to quality management and see enhanced flexibility as a strategic priority. While Chinese managers are also committed to achieving quality, they are more delivery-driven and thus are more likely to occasionally accept slightly off-quality components from suppliers to "save” an order. However, in all three countries, managers with a high focus on quality also focus on just-in-time management and in turn, on flexibility. There is significantly less agreement among Chinese managers, compared to their Japanese and Korean counterparts, that the top management should be involved in operational planning, goal setting, and the provision of rewards. © 2022 Wiley Periodicals LLC.

Knowledge integration for resilience among multinational SMEs amid the COVID-19: from the view of global digital platforms

Purpose: Multinational small-to-medium-sized enterprises (SMEs) are increasingly participating in cross-border digital platforms – especially amid the COVID-19 pandemic. Accordingly, knowledge integration (KI) has become more and more important. In fact, it has been deemed by many as the key to organizational resilience. Given this burgeoning phenomenon, this study aims to explore a path for improving the resilience of multinational SMEs. Through this process, this study also finds a relationship between the KI processes associated with adopting global digital platforms and the resiliency of local–global businesses. Hence, in part, this paper also explores the effectiveness of all these mechanisms. Design/methodology/approach: This study used the stepwise regression method in Stata 16.0 to analyze the direct effects of both horizontal and vertical KI processes on the resilience of local–global businesses. Additionally, t-tests were also used to compare the differences in coefficients between the mechanisms. The sample analyzed comprised data on multinational manufacturing SMEs in the Yangtze River Delta region of China who are using global digital platforms. Findings: The KI processes of these firms, both horizontal and vertical, positively correlate to resilience. Horizontal KI processes more efficiently increase the resilience of global businesses, whereas vertical processes more efficiently increase the resilience of local businesses. Originality/value: First, this study provides insights into how multinational SMEs can improve their resilience in a crisis. In addition to adding to the knowledge of KI processes, this expands the KM literature on pandemics. Second, by creating two KI processes based on global digital platforms and discussing their influence on resilience, this research deepens the understanding of affordance in the KM literature. Third, focusing on the KI research stream, the results shed light on how KI processes might occur and how firms develop their KI processes. © 2022, Emerald Publishing Limited.

Assembly process based on supply chain management of prefabricated houses using BIM

The assembly of modular containers using building information modelling (BIM) technologies was studied. The purpose of this study was to analyse the literature on prefabricated (prefab) houses and explore the concept of creating a digital prototype of a building based on Huoshenshan hospital using Autodesk Revit software. This hospital was constructed to treat Covid-19 patients in early 2020. The article describes the methodology of installing modular containers and assembly structures using BIM technologies for rapid construction. The results of this study showed that building object implementation depends directly on a proper model with a step-by-step mechanism for installation. Due to the supply of prefab structures at the construction site, both initial project cost and project time can be reduced. Prefab house technology demonstrated the high efficiency of using BIM technology in the assembly of Huoshenshan hospital, which was constructed in 10 days. The need for information modelling data exchange with modern technology and systems, which allows the team to become acquainted with the project before installation work starts at the construction site, is investigated.

[Research progress of influenza vaccination, pneumococcal vaccination and COVID-19 vaccination among cancer patients].

This article reviews the relevant studies on the efficacy and safety of influenza, pneumococcal and COVID-19 vaccination among tumor patients worldwide in recent years. By combing and analyzing the retrieved literature, the results show that influenza and pneumococcal vaccination can significantly reduce the morbidity and hospitalization rate of infectious diseases in tumor patients, reduce the risk of cardiovascular events and death, and significantly improve survival prognosis. COVID-19 vaccination can also protect tumor patients, especially those who have completed full dose vaccination. Authoritative guidelines and consensuses worldwide all recommend that tumor patients receive influenza, pneumococcal and COVID-19 vaccines. We should carry out relevant researches, as well as take effective measures to strengthen patient education, so that tumor patients can fully experience the health protection brought by the vaccine to this specific group.