The practice of drug emergency supply in China from a policy mix perspective (preprint)

Background This study aims to analyze relevant policy texts, explore and determine the focal points and inadequacies of the Chinese government in guaranteeing supplies of medicines, and provide advice on how to make better policies about drug supply when public health emergencies occur.Methods We selected 559 documents that guided the support of drug supply during emergencies issued by governments at both the national and provincial levels from December 1, 2019, to February 28, 2023. In addition, we developed a four-dimensional analysis framework of the issuing agency, issuing period, policy tools, and drug supply chain to analyze specific policy items, determine their basic characteristics, and quantitatively analyze them from a policy mix perspective.Results The analysis using policy tools showed that the national government tended to call on stakeholders in all aspects of drug supply to fulfil their responsibilities, and both national and provincial governments tended to use incentive tools, such as opening up urgent drug supply tracks and applying financial incentives to promote drug supply. However, managing stakeholders’ behaviors in drug supply and the capacity building to guarantee drug supply are still lacking and require improvement. From the perspective of the drug supply chain, the national government has paid much attention to the distribution of drugs, whereas attention to the supply of drug substances has been lacking. As various stages of the COVID-19 pandemic, the number of policies related to drug supply increased slowly after a surge at the beginning of the pandemic and then rapidly decreased. From the policy mix perspective, the analysis showed that incentives were lacking in drug research and development, and capacity building was not discussed much in the drug manufacturing process.Conclusions We suggest enhancing the complementarity and cohesion of the policy content issued by national and provincial governments, strengthening the coordination and connection between policymaking bodies, optimizing the internal structure of policy tools, improving the performance of various policy strategies, and using appropriate policy tools to create policies suited to various stages of emergencies and drug supply chains.

Risk factors associated with indoor transmission during home quarantine of COVID-19 patients.

Purpose: The study aimed to identify potential risk factors for family transmission and to provide precautionary guidelines for the general public during novel Coronavirus disease 2019 (COVID-19) waves. Methods: A retrospective cohort study with numerous COVID-19 patients recruited was conducted in Shanghai. Epidemiological data including transmission details, demographics, vaccination status, symptoms, comorbidities, antigen test, living environment, residential ventilation, disinfection and medical treatment of each participant were collected and risk factors for family transmission were determined. Results: A total of 2,334 COVID-19 patients participated. Compared with non-cohabitation infected patients, cohabitated ones were younger (p = 0.019), more commonly unvaccinated (p = 0.048) or exposed to infections (p < 0.001), and had higher rates of symptoms (p = 0.003) or shared living room (p < 0.001). Risk factors analysis showed that the 2019-nCov antigen positive (OR = 1.86, 95%CI 1.40-2.48, p < 0.001), symptoms development (OR = 1.86, 95%CI 1.34-2.58, p < 0.001), direct contact exposure (OR = 1.47, 95%CI 1.09-1.96, p = 0.010) were independent risk factors for the cohabitant transmission of COVID-19, and a separate room with a separate toilet could reduce the risk of family transmission (OR = 0.62, 95%CI 0.41-0.92, p = 0.018). Conclusion: Patients showing negative 2019-nCov antigen tests, being asymptomatic, living in a separate room with a separate toilet, or actively avoiding direct contact with cohabitants were at low risk of family transmission, and the study recommended that avoiding direct contact and residential disinfection could reduce the risk of all cohabitants within the same house being infected with COVID-19.

Research on the Integration of Cultural Tourism Industry Driven by Digital Economy in the Context of COVID-19-Based on the Data of 31 Chinese Provinces.

This article examines the impact of digital economy on the integration of China's cultural tourism industry in the context of COVID-19 by measuring the integration degree of cultural tourism industry as a substitute variable of cultural tourism integration. The empirical study found that the development of digital economy during the COVID-19 pandemic did promote the integration of China's cultural tourism industry, and compared with year 2019, the digital economy has strengthened the integration of cultural tourism industry. During the COVID-19 pandemic, the development of digital economy has promoted the integration of China's cultural tourism industry, and the positive effect of digital economy on the integration of China's cultural tourism industry has gradually strengthened compared to previous ones. The digital economy has played a mediating role in the impact of COVID-19 on the integration of China's cultural tourism industry. Therefore, China should formulate macropolicies and digital economy-related policies to strengthen the ability of digital economy to deal with risks and improve the digital system.

The occurrence and risk factors associated with post-traumatic stress disorder among discharged COVID-19 patients in Tianjin, China.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a serious mental health condition that is triggered by a terrifying event. We aimed to investigate the occurrence and risk factors of PTSD among discharged COVID-19 patients. METHODS: This study included 144 discharged COVID-19 patients. PTSD was assessed by using validated cut-offs of the impact of event scale-revised (IES-R, score ≥25). All patients completed a detailed questionnaire survey, and clinical parameters were routinely measured in the hospital. Binary logistic regression models were applied to identify factors associated with PTSD. RESULTS: Of the 144 participants with laboratory-confirmed COVID-19, the occurrence of PTSD was 16.0%. In multivariable analyses, age above 40 years (adjusted OR [95% CI], 5.19 [2.17-12.32]), female sex (adjusted OR [95% CI], 7.82 [3.18-18.21]), current smoker (adjusted OR [95% CI], 6.72 [3.23-15.26]), and ≥3 involved pulmonary lobes (adjusted OR [95% CI], 5.76 [1.19-15.71]) were significantly associated with a higher risk of PTSD. Conversely, history of hypertension and serum hemoglobin levels were significantly associated with a lower risk of PTSD with adjusted ORs (95% CI) of 0.37 (0.12-0.87) and 0.91 (0.82-0.96), respectively. CONCLUSION: Old age, gender (being female), current smoking, bacterial pneumonia, and ≥3 involved pulmonary lobes were associated with an increased occurrence of PTSD among discharged COVID-19 patients.

Generation and Characterization of a Nanobody Against SARS-CoV.

The sudden emergence of severe acute respiratory syndrome coronavirus (SARS-CoV) has caused global panic in 2003, and the risk of SARS-CoV outbreak still exists. However, no specific antiviral drug or vaccine is available; thus, the development of therapeutic antibodies against SARS-CoV is needed. In this study, a nanobody phage-displayed library was constructed from peripheral blood mononuclear cells of alpacas immunized with the recombinant receptor-binding domain (RBD) of SARS-CoV. Four positive clones were selected after four rounds of bio-panning and subjected to recombinant expression in E. coli. Further biological identification demonstrated that one of the nanobodies, S14, showed high affinity to SARS-CoV RBD and potent neutralization activity at the picomole level against SARS-CoV pseudovirus. A competitive inhibition assay showed that S14 blocked the binding of SARS-CoV RBD to either soluble or cell-expressed angiotensin-converting enzyme 2 (ACE2). In summary, we developed a novel nanobody targeting SARS-CoV RBD, which might be useful for the development of therapeutics against SARS.

Exploration of prognostic factors for critical COVID-19 patients using a nomogram model.

The study aimed to explore the influencing factors on critical coronavirus disease 2019 (COVID-19) patients' prognosis and to construct a nomogram model to predict the mortality risk. We retrospectively analyzed the demographic data and corresponding laboratory biomarkers of 102 critical COVID-19 patients with a residence time ≥ 24 h and divided patients into survival and death groups according to their prognosis. Multiple logistic regression analysis was performed to assess risk factors for critical COVID-19 patients and a nomogram was constructed based on the screened risk factors. Logistic regression analysis showed that advanced age, high peripheral white blood cell count (WBC), low lymphocyte count (L), low platelet count (PLT), and high-sensitivity C-reactive protein (hs-CRP) were associated with critical COVID-19 patients mortality risk (p < 0.05) and these were integrated into the nomogram model. Nomogram analysis showed that the total factor score ranged from 179 to 270 while the corresponding mortality risk ranged from 0.05 to 0.95. Findings from this study suggest advanced age, high WBC, high hs-CRP, low L, and low PLT are risk factors for death in critical COVID-19 patients. The Nomogram model is helpful for timely intervention to reduce mortality in critical COVID-19 patients.

Sleep quality and mental health of medical workers during the coronavirus disease 2019 pandemic.

The purpose of this study is to assess the sleep quality, mental health status, and associated factors among medical workers during the coronavirus disease 2019 (COVID-19) pandemic. A cross-sectional study was conducted and medical workers in Ningbo, China were recruited. Sleep quality was evaluated by Pittsburgh Sleep Quality Index (PSQI). Mental health status was evaluated by Symptom Checklist 90 (SCL-90). Logistic regression and generalized multi-factor dimensionality reduction (GMDR) analysis were utilized to explore the risk factors and their interactions on sleep quality and mental health status. 207 participants were surveyed, and 34.30% were found with poor sleep quality (total PSQI score > 10), mainly manifested as sleep disturbance (92.75%). 27.05% were found with mental symptoms (Global severity index > 1.50), mainly manifested as obsessive-compulsive (25.60%). Multivariate logistic analysis showed that male (OR 3.89, 95% CI 1.06-14.24, P = 0.04), working years > 15 years (OR 4.51, 95% CI 1.56-13.00, P = 0.01), nurse (OR 5.64, 95% CI 1.35-23.63, P = 0.02), more night shifts (OR 3.10, 95% CI 1.31-7.34, P = 0.01), and supporting Wuhan (OR 3.41, 95% CI 1.12-10.40, P = 0.03) were associated with poor sleep quality. GMDR analysis showed that there was a two-factor interaction between working years and working shifts (P = 0.01). No significant factors and interactions were found associated with mental symptoms. In conclusions, about one-third of medical workers suffered from sleep and mental problems during the COVID-19 pandemic in the current study. Interventions for sleep and mental problems among medical workers were needed based on related factors.