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1.
Front Public Health ; 10: 865571, 2022.
Article in English | MEDLINE | ID: covidwho-1952801

ABSTRACT

Background: During the COVID-19 pandemic, vaccine hesitancy (VH) on COVID-19 vaccination still exists in different populations, which has a negative impact on epidemic prevention and control. The objectives were to explore college students' willingness to vaccinate, determine the factors influencing the vaccination behavior of students with COVID-19 vaccine hesitancy, and provide a basis for improving the compliance of college students with COVID-19 vaccination. Methods: The universities in Wuhan are categorized into three levels according to their comprehensive strength and randomly sampled at each level, of which ten universities were selected. A self-designed anonymous electronic questionnaire was distributed online from May 12 to 31, 2021 to investigate the hesitancy, vaccination status, and influencing factors of COVID-19 vaccination among college students in Wuhan. Results: Of the 1,617 participants (1,825 students received the electronic questionnaire) surveyed, 19.0% reported COVID-19 vaccine hesitancy. Among the vaccine-hesitant students, 40.1% were vaccinated against COVID-19. The binary logistic regression analysis shows that families' attitudes "Uncertain" (odds ratio (OR) = 0.258 [0.132-0.503]), vaccination risk psychology (OR = 0.242 [0.079-0.747]) and wait-and-see mentality (OR = 0.171 [0.068-0.468]) are negative factors for the vaccination behavior of hesitant students, while herd mentality (OR = 7.512 [2.718-20.767]) and uncertainty of free policy's impact on vaccine trust (OR = 3.412 [1.547-7.527]) are positive factors. Conclusion: The vaccine hesitancy among college students in Wuhan was relatively high. Family support, herd mentality and free vaccination strategies can help improve vaccination among hesitant students, while vaccination risk psychology and "wait-and-see" psychology reduce the possibility of vaccination. The vaccination strategy of college students should be strengthened from the perspective of social psychological construction.


Subject(s)
COVID-19 , Vaccines , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , China , Health Knowledge, Attitudes, Practice , Humans , Pandemics , Students , Surveys and Questionnaires , Vaccination
2.
Frontiers in public health ; 10, 2022.
Article in English | EuropePMC | ID: covidwho-1871967

ABSTRACT

Background During the COVID-19 pandemic, vaccine hesitancy (VH) on COVID-19 vaccination still exists in different populations, which has a negative impact on epidemic prevention and control. The objectives were to explore college students' willingness to vaccinate, determine the factors influencing the vaccination behavior of students with COVID-19 vaccine hesitancy, and provide a basis for improving the compliance of college students with COVID-19 vaccination. Methods The universities in Wuhan are categorized into three levels according to their comprehensive strength and randomly sampled at each level, of which ten universities were selected. A self-designed anonymous electronic questionnaire was distributed online from May 12 to 31, 2021 to investigate the hesitancy, vaccination status, and influencing factors of COVID-19 vaccination among college students in Wuhan. Results Of the 1,617 participants (1,825 students received the electronic questionnaire) surveyed, 19.0% reported COVID-19 vaccine hesitancy. Among the vaccine-hesitant students, 40.1% were vaccinated against COVID-19. The binary logistic regression analysis shows that families' attitudes “Uncertain” (odds ratio (OR) = 0.258 [0.132–0.503]), vaccination risk psychology (OR = 0.242 [0.079–0.747]) and wait-and-see mentality (OR = 0.171 [0.068–0.468]) are negative factors for the vaccination behavior of hesitant students, while herd mentality (OR = 7.512 [2.718–20.767]) and uncertainty of free policy's impact on vaccine trust (OR = 3.412 [1.547–7.527]) are positive factors. Conclusion The vaccine hesitancy among college students in Wuhan was relatively high. Family support, herd mentality and free vaccination strategies can help improve vaccination among hesitant students, while vaccination risk psychology and “wait-and-see” psychology reduce the possibility of vaccination. The vaccination strategy of college students should be strengthened from the perspective of social psychological construction.

3.
J Environ Manage ; 309: 114728, 2022 May 01.
Article in English | MEDLINE | ID: covidwho-1683294

ABSTRACT

Real-time evaluation of the fighting activities during a sudden unknown disaster like the COVID-19 pandemic is a critical challenge for control. This study demonstrates that the temporal variations of effluents from hospital sewage treatment facilities can be used as an effective indicator for such evaluation. Taking a typical infection-suffering city in China as an example, we found that there was an obvious decrease in effluent ammonia and COD concentrations in line with the start of city lockdown, and its temporal variations well indicated the major events happened during the pandemic control. Notably, the lagging period between the change point of effluent residual chlorine and the change points of COD and ammonia concentration coincided with a period in which there was a deficiency in local medical resources. In addition, the diurnal behavior of effluents from designated hospitals has varied significantly at different stages of the pandemic development. The effluent ammonia peaks shifted from daytime to nighttime after the outbreak of the COVID-19 pandemic, suggesting a high workload of the designated hospitals in fighting the rapidly emerging pandemic. This work well demonstrates the necessary for data integration at the wastewater-medical service nexus and highlights an unusual role of the effluents from hospital sewage treatment facilities in revealing the status of fighting the pandemic, which helps to control the pandemic.


Subject(s)
COVID-19 , Pandemics , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control , Hospitals , Humans , Pandemics/prevention & control , SARS-CoV-2 , Sewage
4.
PLoS One ; 15(10): e0241355, 2020.
Article in English | MEDLINE | ID: covidwho-928216

ABSTRACT

The response of netizens toward controversial events plays an important guiding role in the development of events. Based on the identification of such responses, this study aimed to determine the critical outbreak time window of events. The microblog texts related to an event were divided into seven emotional categories via multi-emotional analysis to capture the subtle emotions of netizens toward an event, i.e., public opinion. By detecting the characteristics of the text and regional coverage of emotions, an emotional coverage index that reflects the intensity of emotional impact was proposed to determine the mainstream emotion of netizens. By capturing the mutation characteristics of the impact intensity of mainstream emotions, the critical time window of the public opinion toward the event was obtained. The experimental results demonstrated that the proposed method can effectively identify the critical outbreak time window of controversial events, which can help authorities in preventing the further aggravation of events.


Subject(s)
Models, Theoretical , Public Opinion , Social Media , Humans
5.
Exp Ther Med ; 21(2): 129, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-993707

ABSTRACT

Coronavirus disease 2019 (COVID-19) has recently broken out in China. To describe the clinical and computed tomography (CT) characteristics in patients with COVID-19-induced pneumonia, the current study retrospectively analyzed the data of 152 patients with pneumonia between December 30, 2019 and February 29, 2020. Pharyngeal swabs for nucleic acid detection of respiratory secretions were used for all patients. A total of 65 cases were diagnosed as COVID-19, and 87 cases were non-COVID-19. When comparing the clinical and CT characteristics of the two groups of patients, only sex and history of exposure presented a statistically significant difference. The normal/low white blood cell count, low lymphocyte ratio and high C-reactive protein (CRP) exhibited a statistically significant difference between the two groups. A total of 62 patients in the COVID-19 group exhibited ground-glass opacity (GGO), which was higher than that in the non-COVID-19 group. In the COVID-19 group, 33 cases presented angiographic thickening in GGO, and 27 cases displayed a paving stone sign, which were higher than those in the non-COVID-19 group. Compared with the non-COVID-19 group, the lesions in the COVID-19 group were principally characterized by bilateral lungs, multifocal and subpleural distribution. The results of the present study revealed that when the male patients with contact history in the epidemic area exhibited fever and cough symptoms, the laboratory tests indicated normal/low white blood cell counts, low lymphocyte ratios and elevated CRP levels. CT scans were recommended for subsequent examination. GGO or GGO and consolidation with bilateral lungs were indicated to be primarily distributed in the multifocal subpleural area and were accompanied by angiographic thickening in GGO and paving stone sign. In conclusion, regardless of whether the viral nucleic acid test is positive, COVID-19 should be considered for medical treatment observation in isolation.

6.
Eur Radiol ; 30(12): 6828-6837, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-656333

ABSTRACT

OBJECTIVE: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression of COVID-19 using thick-section chest CT images. METHODS: In this retrospective study, an AI system was developed to automatically segment and quantify the COVID-19-infected lung regions on thick-section chest CT images. Five hundred thirty-one CT scans from 204 COVID-19 patients were collected from one appointed COVID-19 hospital. The automatically segmented lung abnormalities were compared with manual segmentation of two experienced radiologists using the Dice coefficient on a randomly selected subset (30 CT scans). Two imaging biomarkers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU), to assess disease severity and disease progression. The assessments were compared with patient status of diagnosis reports and key phrases extracted from radiology reports using the area under the receiver operating characteristic curve (AUC) and Cohen's kappa, respectively. RESULTS: The dice coefficient between the segmentation of the AI system and two experienced radiologists for the COVID-19-infected lung abnormalities was 0.74 ± 0.28 and 0.76 ± 0.29, respectively, which were close to the inter-observer agreement (0.79 ± 0.25). The computed two imaging biomarkers can distinguish between the severe and non-severe stages with an AUC of 0.97 (p value < 0.001). Very good agreement (κ = 0.8220) between the AI system and the radiologists was achieved on evaluating the changes in infection volumes. CONCLUSIONS: A deep learning-based AI system built on the thick-section CT imaging can accurately quantify the COVID-19-associated lung abnormalities and assess the disease severity and its progressions. KEY POINTS: • A deep learning-based AI system was able to accurately segment the infected lung regions by COVID-19 using the thick-section CT scans (Dice coefficient ≥ 0.74). • The computed imaging biomarkers were able to distinguish between the non-severe and severe COVID-19 stages (area under the receiver operating characteristic curve 0.97). • The infection volume changes computed by the AI system were able to assess the COVID-19 progression (Cohen's kappa 0.8220).


Subject(s)
Betacoronavirus , Community-Acquired Infections/diagnosis , Coronavirus Infections/diagnosis , Deep Learning , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , Pneumonia/diagnosis , Tomography, X-Ray Computed/methods , Artificial Intelligence , COVID-19 , China/epidemiology , Disease Progression , Female , Humans , Male , Middle Aged , Pandemics , ROC Curve , Retrospective Studies , SARS-CoV-2
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