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1.
Journal of Immunology ; 21:21, 2022.
Article in English | MEDLINE | ID: covidwho-2201457

ABSTRACT

Swine coronavirus-porcine epidemic diarrhea virus (PEDV) with specific susceptibility to pigs has existed for decades, and recurrent epidemics caused by mutant strains have swept the world again since 2010. In this study, single-cell RNA sequencing was used to perform for the first time, to our knowledge, a systematic analysis of pig jejunum infected with PEDV. Pig intestinal cell types were identified by representative markers and identified a new tuft cell marker, DNAH11. Excepting enterocyte cells, the goblet and tuft cells confirmed susceptibility to PEDV. Enrichment analyses showed that PEDV infection resulted in upregulation of cell apoptosis, junctions, and the MAPK signaling pathway and downregulation of oxidative phosphorylation in intestinal epithelial cell types. The T cell differentiation and IgA production were decreased in T and B cells, respectively. Cytokine gene analyses revealed that PEDV infection downregulated CXCL8, CXCL16, and IL34 in tuft cells and upregulated IL22 in Th17 cells. Further studies found that infection of goblet cells with PEDV decreased the expression of MUC2, as well as other mucin components. Moreover, the antimicrobial peptide REG3G was obviously upregulated through the IL33-STAT3 signaling pathway in enterocyte cells in the PEDV-infected group, and REG3G inhibited the PEDV replication. Finally, enterocyte cells expressed almost all coronavirus entry factors, and PEDV infection caused significant upregulation of the coronavirus receptor ACE2 in enterocyte cells. In summary, this study systematically investigated the responses of different cell types in the jejunum of piglets after PEDV infection, which deepened the understanding of viral pathogenesis.

2.
Chung-Hua Yu Fang i Hsueh Tsa Chih [Chinese Journal of Preventive Medicine] ; 57(1):8-14, 2023.
Article in Chinese | MEDLINE | ID: covidwho-2201076

ABSTRACT

Objective: To evaluate the household secondary attack rates of the SARS-CoV-2 Delta variant and the associated factors.

3.
Int J Environ Res Public Health ; 20(1), 2022.
Article in English | PubMed | ID: covidwho-2200060

ABSTRACT

While personal protective equipment (PPE) protects healthcare workers from viruses, it also increases the risk of heat stress. In this study, the effects of environmental heat stress, the insulation of the PPE inner-garment layer, and the personal cooling strategy on the physiological and perceptual responses of PPE-clad young college students were evaluated. Three levels of wet bulb globe temperatures (WBGT = 15 °C, 28 °C, and 32 °C) and two types of inner garments (0.37 clo and 0.75 clo) were chosen for this study. In an uncompensable heat stress environment (WBGT = 32 °C), the effects of two commercially available personal cooling systems, including a ventilation cooling system (VCS) and an ice pack cooling system (ICS) on the heat strain mitigation of PPE-clad participants were also assessed. At WBGT = 15 °C with 0.75 clo inner garments, mean skin temperatures were stabilized at 31.2 °C, H(skin) was 60-65%, and HR was about 75.5 bpm, indicating that the working scenario was on the cooler side. At WBGT = 28 °C, T(skin) plateaued at approximately 34.7 °C, and the participants reported "hot" thermal sensations. The insulation reduction in inner garments from 0.75 clo to 0.37 clo did not significantly improve the physiological thermal comfort of the participants. At WBGT = 32 °C, T(skin) was maintained at 35.2-35.7 °C, H(skin) was nearly 90% RH, T(core) exceeded 37.1 °C, and the mean HR was 91.9 bpm. These conditions indicated that such a working scenario was uncompensable, and personal cooling to mitigate heat stress was required. Relative to that in NCS (no cooling), the mean skin temperatures in ICS and VCS were reduced by 0.61 °C and 0.22 °C, respectively, and the heart rates were decreased by 10.7 and 8.5 bpm, respectively. Perceptual responses in ICS and VCS improved significantly throughout the entire field trials, with VCS outperforming ICS in the individual cooling effect.

4.
Frontiers in Psychology ; 13, 2022.
Article in English | Web of Science | ID: covidwho-2199234

ABSTRACT

Music enjoyment is considered to predict music-related academic performance and career choice. Although relevant research in non-music fields has demonstrated the association between teachers' autonomy support and students' academic enjoyment, it remains unknown whether this association is valid in the music discipline. In addition, in the post-COVID-19 era, online education has become a common way of teaching and learning for music undergraduates. In the form of online learning, the mechanisms mediating teachers' music autonomy support and students' music academic enjoyment are also unknown. This study draws on Pekrun's theory of achievement emotions and control values to explore the mediating role of attributions and values in the association between autonomous support and academic achievement. In this study, 270 undergraduates majoring in music eventually completed the online surveys. Results from structural equation modeling indicated that autonomy support positively predicted music enjoyment and that attributions (i.e., internal attribution and external attribution) and values (i.e., intrinsic value, attainment value, utility value) mediated the association between autonomy support and music enjoyment. The findings also provide insights into possible avenue for promoting music enjoyment emotion during online teaching in the post-COVID-19 era. Implications and limitations are discussed in the study.

5.
Frontiers in Cellular & Infection Microbiology ; 12:1079297, 2022.
Article in English | MEDLINE | ID: covidwho-2198725

ABSTRACT

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is an enveloped, positive single-stranded RNA virus belonging to Coronaviridae family, Orthocoronavirinae subfamily, Alphacoronavirus genus. As one of the main causes of swine diarrhea, SADS-CoV has brought huge losses to the pig industry. Although we have a basic understanding of SADS-CoV, the research on the pathogenicity and interactions between host and virus are still limited, especially the metabolic changes induced by SADS-CoV infection. Here, we utilized a combination of untargeted metabolomics and lipomics to analyze the metabolic alteration in SADS-CoV infected cells. Significant changes were observed in 1257 of 2225 metabolites identified in untargeted metabolomics, while the number of lipomics was 435 out of 868. Metabolic pathway enrichment analysis showed that amino acid metabolism, tricarboxylic acid (TCA) cycle and ferroptosis were disrupted during viral infection, suggesting that these metabolic pathways may partake in pathological processes related to SADS-CoV pathogenesis. Collectively, our findings gain insights into the cellular metabolic disorder during SADS-CoV infection, offer a valuable resource for further exploration of the relationship between virus and host metabolic activities, and provide potential targets for the development of antiviral drugs.

6.
PLoS ONE [Electronic Resource] ; 18(1):e0279879, 2023.
Article in English | MEDLINE | ID: covidwho-2197125

ABSTRACT

The current epidemiological status of the new coronary pneumonia epidemic in China is being explored to prevent and control the localized dissemination of aggregated outbreaks. This study analyzed the characteristics of new outbreaks of coronavirus disease 2019 (COVID-19) at three stages of aggregated outbreaks in Jilin Province, China, to provide a reference for the prevention and control of aggregated outbreaks. Case information were collected from all patients in Jilin Province from January 12, 2020 to the present. The epidemic was divided into three stages according to the time of onset. The first stage comprised 97 cases reported from January 12, 2020 to February 19, 2020, during which 17 aggregated outbreaks occurred. The second comprised 43 cases reported from April 25, 2020 and May 23, 2020, involving one aggregated outbreak. The third comprised 435 cases reported on January 10, 2021 and February 9, 2021, involving one aggregated outbreak. The relationship between aggregated and non-aggregated cases in the first phase of the outbreak and the difference between imported and local cases during the aggregated outbreak were assess using statistical analysis, and the differences in the baseline information between the three phases were analyzed. The incubation periods of the three phases were 10 days, 8 days, and 5 days. The number of aggregated epidemic events in Jilin Province tended to increase and then decrease over time. The clustered events in Jilin Province were divided into four categories: household contact (14 times, 51 cases);household contact and public places (one time, three cases);household contact, public places, and gatherings (one time, six cases);and household contact, public places, gatherings, and work (three times, 495 cases). Clustered events occurred mainly between January 22, 2020, and February 4, 2020. Among all cases in the first phase of the outbreak, the method of detection and the time from diagnosis to discharge were longer in aggregated cases than in non-aggregated cases, and that the source of infection and renewal cases were more frequent and more likely to be detected in the outpatient clinics during aggregated outbreaks than the imported cases. The second phase of the epidemic showed significant spatial variability (Moran's I<0, P<0.05). The third stage of the epidemic occurred in a higher proportion of individuals aged 50-90 years and within a shorter incubation period compared with the first two stages. The current focus of prevention and control of the COVID-19 epidemic in Jilin Province is to strictly implement the restrictions on gatherings and to perform timely screening and isolation of close contacts of infectious sources while strengthening the supervision of the inflow of people from outside the region. Simultaneously, more targeted prevention and control measures can be implemented for different age groups and occupations.

7.
PLoS ONE [Electronic Resource] ; 17(12):e0279711, 2022.
Article in English | MEDLINE | ID: covidwho-2197118

ABSTRACT

The COVID-19 pandemic has presented unprecedented challenges for university students, creating uncertainties for their academic careers, social lives, and mental health. Our study utilized a machine learning approach to examine the degree to which students' college adjustment and coping styles impacted their adjustment to COVID-19 disruptions. More specifically, we developed predictive models to distinguish between well-adjusted and not well-adjusted students in each of five psychological domains: academic adjustment, emotionality adjustment, social support adjustment, general COVID-19 regulations response, and discriminatory impact. The predictive features used for these models are students' individual characteristics in three psychological domains, i.e., Ways of Coping (WAYS), Adaptation to College (SACQ), and Perceived Stress Scale (PSS), assessed using established commercial and open-access questionnaires. We based our study on a proprietary survey dataset collected from 517 U.S. students during the initial peak of the pandemic. Our models achieved an average of 0.91 AUC score over the five domains. Using the SHAP method, we further identified the most relevant risk factors associated with each classification task. The findings reveal the relationship of students' general adaptation to college and coping in relation to their adjustment during COVID-19. Our results could help universities identify systemic and individualized strategies to support their students in coping with stress and to facilitate students' college adjustment in this era of challenges and uncertainties.

8.
BMC Infect Dis ; 23(1):25, 2023.
Article in English | PubMed | ID: covidwho-2196096

ABSTRACT

BACKGROUND: The ongoing coronavirus 2019 (COVID-19) pandemic has emerged and caused multiple pandemic waves in the following six countries: India, Indonesia, Nepal, Malaysia, Bangladesh and Myanmar. Some of the countries have been much less studied in this devastating pandemic. This study aims to assess the impact of the Omicron variant in these six countries and estimate the infection fatality rate (IFR) and the reproduction number [Formula: see text] in these six South Asia, Southeast Asia and Oceania countries. METHODS: We propose a Susceptible-Vaccinated-Exposed-Infectious-Hospitalized-Death-Recovered model with a time-varying transmission rate [Formula: see text] to fit the multiple waves of the COVID-19 pandemic and to estimate the IFR and [Formula: see text] in the aforementioned six countries. The level of immune evasion and the intrinsic transmissibility advantage of the Omicron variant are also considered in this model. RESULTS: We fit our model to the reported deaths well. We estimate the IFR (in the range of 0.016 to 0.136%) and the reproduction number [Formula: see text] (in the range of 0 to 9) in the six countries. Multiple pandemic waves in each country were observed in our simulation results. CONCLUSIONS: The invasion of the Omicron variant caused the new pandemic waves in the six countries. The higher [Formula: see text] suggests the intrinsic transmissibility advantage of the Omicron variant. Our model simulation forecast implies that the Omicron pandemic wave may be mitigated due to the increasing immunized population and vaccine coverage.

9.
Science Translational Medicine ; 15(677):eabo3332, 2023.
Article in English | MEDLINE | ID: covidwho-2193427

ABSTRACT

SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.

10.
IEEE Transactions on Mobile Computing ; : 1-14, 2022.
Article in English | Scopus | ID: covidwho-2192104

ABSTRACT

The outbreak of COVID-19 has greatly changed everyone's lifestyle all over the world. One of the best ways to prevent the spread of infections is by washing hands properly. Although a number of hand hygiene monitoring systems have been proposed, they either cannot achieve high accuracy in practice or work only in limited environments such as hospitals. Therefore, a ubiquitous, energy-efficient and highly accurate hand hygiene monitoring system is still lacking. In this paper, we present WashRing—the first smart ring-based handwashing monitoring system. In WashRing, we design a Partially Observable Markov Decision Process (POMDP) based adaptive sampling approach to achieve high energy efficiency. Then, we design an automatic feature extraction scheme based on wavelet scattering and a CNN-LSTM neural network to achieve fine-grained gesture recognition. Finally, we model the handwashing gesture classification as a few-shot learning problem to mitigate the burden of collecting extensive data from five fingers. We collect data from 25 subjects over 2 months and evaluate the system performance on both commercial OURA ring and customized ring. Evaluation results show that WashRing achieves 97.8%accuracy which is 10.2%–15.9%higher than state-of-the-arts. Our adaptive sampling approach reduces energy consumption by 64.2%compared to fixed duty cycle sampling strategies. IEEE

11.
Medicine ; 101(49):e32100, 2022.
Article in English | MEDLINE | ID: covidwho-2191103

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease (COVID-19), has been devastated by COVID-19 in an increasing number of countries and health care systems around the world since its announcement of a global pandemic on 11 March 2020. During the pandemic, emerging novel viral mutant variants have caused multiple outbreaks of COVID-19 around the world and are prone to genetic evolution, causing serious damage to human health. As confirmed cases of COVID-19 spread rapidly, there is evidence that SARS-CoV-2 infection involves the central nervous system (CNS) and peripheral nervous system (PNS), directly or indirectly damaging neurons and further leading to neurodegenerative diseases (ND), but the molecular mechanisms of ND and CVOID-19 are unknown. We employed transcriptomic profiling to detect several major diseases of ND: Alzheimer 's disease (AD), Parkinson' s disease (PD), and multiple sclerosis (MS) common pathways and molecular biomarkers in association with COVID-19, helping to understand the link between ND and COVID-19. There were 14, 30 and 19 differentially expressed genes (DEGs) between COVID-19 and Alzheimer 's disease (AD), Parkinson' s disease (PD) and multiple sclerosis (MS), respectively;enrichment analysis showed that MAPK, IL-17, PI3K-Akt and other signaling pathways were significantly expressed;the hub genes (HGs) of DEGs between ND and COVID-19 were CRH, SST, TAC1, SLC32A1, GAD2, GAD1, VIP and SYP. Analysis of transcriptome data suggests multiple co-morbid mechanisms between COVID-19 and AD, PD, and MS, providing new ideas and therapeutic strategies for clinical prevention and treatment of COVID-19 and ND.

12.
Briefings in Bioinformatics ; 24:24, 2022.
Article in English | MEDLINE | ID: covidwho-2188252

ABSTRACT

Underlying medical conditions, such as cancer, kidney disease and heart failure, are associated with a higher risk for severe COVID-19. Accurate classification of COVID-19 patients with underlying medical conditions is critical for personalized treatment decision and prognosis estimation. In this study, we propose an interpretable artificial intelligence model termed VDJMiner to mine the underlying medical conditions and predict the prognosis of COVID-19 patients according to their immune repertoires. In a cohort of more than 1400 COVID-19 patients, VDJMiner accurately identifies multiple underlying medical conditions, including cancers, chronic kidney disease, autoimmune disease, diabetes, congestive heart failure, coronary artery disease, asthma and chronic obstructive pulmonary disease, with an average area under the receiver operating characteristic curve (AUC) of 0.961. Meanwhile, in this same cohort, VDJMiner achieves an AUC of 0.922 in predicting severe COVID-19. Moreover, VDJMiner achieves an accuracy of 0.857 in predicting the response of COVID-19 patients to tocilizumab treatment on the leave-one-out test. Additionally, VDJMiner interpretively mines and scores V(D)J gene segments of the T-cell receptors that are associated with the disease. The identified associations between single-cell V(D)J gene segments and COVID-19 are highly consistent with previous studies. The source code of VDJMiner is publicly accessible at https://github.com/TencentAILabHealthcare/VDJMiner. The web server of VDJMiner is available at https://gene.ai.tencent.com/VDJMiner/.

13.
2nd International Conference on New Energy Technology and Industrial Development, NETID 2021 ; 292, 2021.
Article in English | Scopus | ID: covidwho-2186197

ABSTRACT

The COVID-19 epidemic has swept the world, causing serious impact and influence on economic development and residents' life in countries all over the world. This paper takes China as an example, further analyses the characteristics of China's hierarchical medical model based on the international hierarchical medical research planning, and proposes the application of "big data analysis + hierarchical medical" model for the new coronavirus epidemic and other public health emergencies based on the advantages of big data application to solve public health crises, in order to provide a reference for the planning of hierarchical medical system during the epidemic. It is expected to provide reference for the planning of hierarchical medical and health system during the epidemic, which is an innovative attempt of the medical industry. © The Authors, published by EDP Sciences.

14.
Nat Commun ; 14(1):223, 2023.
Article in English | PubMed | ID: covidwho-2185846

ABSTRACT

Consistent annotation transfer from reference dataset to query dataset is fundamental to the development and reproducibility of single-cell research. Compared with traditional annotation methods, deep learning based methods are faster and more automated. A series of useful single cell analysis tools based on autoencoder architecture have been developed but these struggle to strike a balance between depth and interpretability. Here, we present TOSICA, a multi-head self-attention deep learning model based on Transformer that enables interpretable cell type annotation using biologically understandable entities, such as pathways or regulons. We show that TOSICA achieves fast and accurate one-stop annotation and batch-insensitive integration while providing biologically interpretable insights for understanding cellular behavior during development and disease progressions. We demonstrate TOSICA's advantages by applying it to scRNA-seq data of tumor-infiltrating immune cells, and CD14+ monocytes in COVID-19 to reveal rare cell types, heterogeneity and dynamic trajectories associated with disease progression and severity.

15.
Cell Discov ; 9(1):3, 2023.
Article in English | PubMed | ID: covidwho-2185789

ABSTRACT

SARS-CoV-2 Omicron subvariants have demonstrated extensive evasion from monoclonal antibodies (mAbs) developed for clinical use, which raises an urgent need to develop new broad-spectrum mAbs. Here, we report the isolation and analysis of two anti-RBD neutralizing antibodies BA7208 and BA7125 from mice engineered to produce human antibodies. While BA7125 showed broadly neutralizing activity against all variants except the Omicron sublineages, BA7208 was potently neutralizing against all tested SARS-CoV-2 variants (including Omicron BA.1-BA.5) except Mu. By combining BA7208 and BA7125 through the knobs-into-holes technology, we generated a biparatopic antibody BA7208/7125 that was able to neutralize all tested circulating SARS-CoV-2 variants. Cryo-electron microscopy structure of these broad-spectrum antibodies in complex with trimeric Delta and Omicron spike indicated that the contact residues are highly conserved and had minimal interactions with mutational residues in RBD of current variants. In addition, we showed that administration of BA7208/7125 via the intraperitoneal, intranasal, or aerosol inhalation route showed potent therapeutic efficacy against Omicron BA.1 and BA.2 in hACE2-transgenic and wild-type mice and, separately, effective prophylaxis. BA7208/7125 thus has the potential to be an effective candidate as an intervention against COVID-19.

16.
Signal Transduction and Targeted Therapy ; 8(1):21, 2023.
Article in English | MEDLINE | ID: covidwho-2185774
17.
ACS Sensors ; 23:23, 2022.
Article in English | MEDLINE | ID: covidwho-2185540

ABSTRACT

A rapid and cost-effective method to detect the infection of SARS-CoV-2 is fundamental to mitigating the current COVID-19 pandemic. Herein, a surface-enhanced Raman spectroscopy (SERS) sensor with a deep learning algorithm has been developed for the rapid detection of SARS-CoV-2 RNA in human nasopharyngeal swab (HNS) specimens. The SERS sensor was prepared using a silver nanorod array (AgNR) substrate by assembling DNA probes to capture SARS-CoV-2 RNA. The SERS spectra of HNS specimens were collected after RNA hybridization, and the corresponding SERS peaks were identified. The RNA detection range was determined to be 103-109 copies/mL in saline sodium citrate buffer. A recurrent neural network (RNN)-based deep learning model was developed to classify 40 positive and 120 negative specimens with an overall accuracy of 98.9%. For the blind test of 72 specimens, the RNN model gave a 97.2% accuracy prediction for positive specimens and a 100% accuracy for negative specimens. All the detections were performed in 25 min. These results suggest that the DNA-functionalized AgNR array SERS sensor combined with a deep learning algorithm could serve as a potential rapid point-of-care COVID-19 diagnostic platform.

18.
Analytical Chemistry ; 28:28, 2022.
Article in English | MEDLINE | ID: covidwho-2185435

ABSTRACT

The COVID-19 pandemic has spread to every corner of the world and seriously affected our health and daily activities in the past three years;thereby, it is still urgent to develop various simple, quick, and accurate methods for early detection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Nanozymes, a kind of nanomaterial with intrinsic enzyme-mimicking activity, have emerged as a suitable alternative for both therapy and diagnosis of SARS-CoV-2. Here, ultrasensitive and ultrafast MIL-101(CuFe)-CD147 biosensors are established for the detection of SARS-CoV-2 by a simple colorimetric method. A MIL-101(CuFe) metal-organic framework has excellent peroxidase-like activity due to the synergistic effect of Fe and Cu atoms. In addition, the MIL-101(CuFe)-CD147 biosensor shows great potential to detect the various variants of SARS-CoV-2 due to the universal receptor of CD147. The enzyme-based biosensor for the detection of SARS-CoV-2 achieves a very low limit of detection (about 3 PFU/mL) within 30 min. Therefore, the present method provides a new generation of an alternative approach for highly sensitive and visual diagnosis of COVID-19.

19.
The Innovation ; 4(1), 2023.
Article in English | Scopus | ID: covidwho-2184481

ABSTRACT

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways;T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells;significant enhancement of cell-cell communications between innate and adaptive immunity;and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines. © 2022 The Authors

20.
Journal of Medical Virology ; 19:19, 2023.
Article in English | MEDLINE | ID: covidwho-2173251

ABSTRACT

OBJECTIVES: We investigated COVID-19 vaccine acceptance among people with chronic diseases and the factors correlating with their vaccination hesitancy.

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