COVID-19 and healthcare system in China: challenges and progression for a sustainable future

Methylene blue for COVID-19 ARDS: insights from a randomized Clinical Trial

BACKGROUND

Around the world, the COVID-19 pandemic has presented many difficulties, and acute respiratory distress syndrome (ARDS) has become a major worry. The antiviral and anti-inflammatory characteristics of methylene blue (MB) have garnered interest for potential medicinal applications. The object of the current study is to assess the effect of orally administered MB on the treatment of ARDS associated with COVID-19.

METHOD

A randomized clinical study was carried out on 122 hospitalized patients who had ARDS related to COVID-19. Patients who met the eligibility requirements were randomized at random to either the control group (CG) (n = 60) or the intervention group (IG) (n = 62). Standard treatments were administered to both groups, with the addition of oral MB to the IG. Clinical outcomes, including SpO2 levels, CRP levels were assessed on the third and fifth days. Additionally, at the time of discharge, patients' assessments were made in terms of APACHE II scores, SOFA scores, LDH and CRP levels, SpO2, and respiratory rate in comparison to the day prior to the intervention. Patients were followed for mortality outcomes at one month and three months after the intervention.

RESULTS

Significant changes were observed in SpO2 levels over time (P < 0.001) and between groups (P = 0.022), with higher levels in the MB-treated group. The interaction between time and group (P = 0.019) indicated a stronger increase in SpO2 in the IG, with the IG's SpO2 level increasing by 6.42%. Furthermore, CRP levels showed significant changes over time (P < 0.001), but not between groups (P = 0.092). However, the interaction between group and CRP change over time (P = 0.019) suggested a distinct pattern of CRP decrease in the IG. Significant improvement in RR, SpO2, CRP, and APACHE II score were found according to discharge results. However, in terms of SpO2 and the APACHE II score, this improvement was noteworthy for IG. The length of hospitalization and mortality rates at one- and three-month follow-ups did not differ significantly.

CONCLUSION

Oral administration of MB demonstrated positive effects on improving SpO2 levels and reducing inflammatory markers in COVID-19-related ARDS patients. Despite no significant impact on survival rates or hospitalization length, the study supports the potential efficacy of MB as an alternative treatment for COVID-19 ARDS.

TRIAL REGISTRATION

This study was registered with the Iranian Registry of Clinical Trials ( http://www.irct.ir ) under the registration code IRCT20200409047007N2 on 11/29/2021.

Connecting efficiency and responsiveness in China: public sentiments and stakeholder perspectives towards COVID-19 crisis governance

The COVID-19 (coronavirus disease 2019) pandemic initiated debates on how crisis management affects democracy. In them, the balance between deploying control strategies that limit citizens' freedom and their democratic legitimation features prominently. Informed by theoretical debates about responsive crisis governance, this paper explores how Chinese citizens reacted by quantitatively and qualitatively analysing social media expressions and Chinese stakeholders' narratives. The quantitative analysis indicated that public sentiments towards pandemic control were complex and mostly related to the severe pandemic in Wuhan. Negative sentiments were mainly directed at local states; national states largely received respect. The qualitative analysis exhibited more nuances. Although Chinese crisis governance raised efficiency and trust, aggressive accountability efforts and improper information exchange caused justice deficits and public anxiety. Draconian social control misaligned public interests and a lack of specific partnership mechanisms frustrated social participation. Reconciling institutional efficiency with civic liberties on diverse governance levels is thus expected to increase the responsiveness of pandemic control to public demands.

Enhancing home delivery of emergency medicine and medical supplies through clustering and simulation techniques: A case study of COVID-19 home isolation in Bangkok

This study investigates the enhancement of the home delivery distribution network for COVID-19 Home Isolation (HI) kits during the Delta variant outbreak of the SARS-CoV-2 virus in Bangkok Metropolitan Area, Thailand. It addresses challenges related to limited resources and delays in delivering HI kits, which can exacerbate symptoms and increase mortality rates. A k-means clustering approach is utilized to optimize the assignment of service areas within the COVID-19 HI program, while discrete event simulation (DES) evaluates potential changes in the home delivery logistics network. Real-world data from the peak outbreak is used to determine the optimal allocation of resources and propose a new logistics network based on proximity to patients' residences. Experimental results demonstrate a significant 44.29 % improvement in overall performance and a substantial 40.80 % decrease in maximum service time. The findings offer theoretical and managerial implications for effective HI management, supporting practitioners and policymakers in mitigating the impact of future outbreaks.

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice

Artificial intelligence (AI) chatbots, such as ChatGPT, have widely invaded all domains of human life. They have the potential to transform healthcare future. However, their effective implementation hinges on healthcare workers' (HCWs) adoption and perceptions. This study aimed to evaluate HCWs usability of ChatGPT three months post-launch in Saudi Arabia using the System Usability Scale (SUS). A total of 194 HCWs participated in the survey. Forty-seven percent were satisfied with their usage, 57 % expressed moderate to high trust in its ability to generate medical decisions. 58 % expected ChatGPT would improve patients' outcomes, even though 84 % were optimistic of its potential to improve the future of healthcare practice. They expressed possible concerns like recommending harmful medical decisions and medicolegal implications. The overall mean SUS score was 64.52, equivalent to 50 % percentile rank, indicating high marginal acceptability of the system. The strongest positive predictors of high SUS scores were participants' belief in AI chatbot's benefits in medical research, self-rated familiarity with ChatGPT and self-rated computer skills proficiency. Participants' learnability and ease of use score correlated positively but weakly. On the other hand, medical students and interns had significantly high learnability scores compared to others, while ease of use scores correlated very strongly with participants' perception of positive impact of ChatGPT on the future of healthcare practice. Our findings highlight the HCWs' perceived marginal acceptance of ChatGPT at the current stage and their optimism of its potential in supporting them in future practice, especially in the research domain, in addition to humble ambition of its potential to improve patients' outcomes particularly in regard of medical decisions. On the other end, it underscores the need for ongoing efforts to build trust and address ethical and legal concerns of AI implications in healthcare. The study contributes to the growing body of literature on AI chatbots in healthcare, especially addressing its future improvement strategies and provides insights for policymakers and healthcare providers about the potential benefits and challenges of implementing them in their practice.

Innovative applications of artificial intelligence during the COVID-19 pandemic

The COVID-19 pandemic has created unprecedented challenges worldwide. Artificial intelligence (AI) technologies hold tremendous potential for tackling key aspects of pandemic management and response. In the present review, we discuss the tremendous possibilities of AI technology in addressing the global challenges posed by the COVID-19 pandemic. First, we outline the multiple impacts of the current pandemic on public health, the economy, and society. Next, we focus on the innovative applications of advanced AI technologies in key areas such as COVID-19 prediction, detection, control, and drug discovery for treatment. Specifically, AI-based predictive analytics models can use clinical, epidemiological, and omics data to forecast disease spread and patient outcomes. Additionally, deep neural networks enable rapid diagnosis through medical imaging. Intelligent systems can support risk assessment, decision-making, and social sensing, thereby improving epidemic control and public health policies. Furthermore, high-throughput virtual screening enables AI to accelerate the identification of therapeutic drug candidates and opportunities for drug repurposing. Finally, we discuss future research directions for AI technology in combating COVID-19, emphasizing the importance of interdisciplinary collaboration. Though promising, barriers related to model generalization, data quality, infrastructure readiness, and ethical risks must be addressed to fully translate these innovations into real-world impacts. Multidisciplinary collaboration engaging diverse expertise and stakeholders is imperative for developing robust, responsible, and human-centered AI solutions against COVID-19 and future public health emergencies.

Chinese model in global COVID-19 prevention and control: Successful experience, institutional advantages and optimal path

The prevention and control measures adopted by various countries have different effects in the face of COVID-19. The performance in some socialist countries and capitalist countries were compared from three aspects, including the proportion of confirmed cases and deaths to the national population, economic recovery and production and living, social satisfaction and international evaluation. The overall performance of listed socialist countries was better than that of capitalist countries. China's performance, forming a unique Chinese model of the epidemic prevention and control, was better than that of other socialist countries. The successful experience of Chinese model can be mainly reflected in four aspects, including resource allocation, social participation, speed and quality, system and mechanism optimization. The successful experience roots in the four institutional advantages of the leadership of the Communist Party of China (CPC), coordinated national response, basic economic system and traditional Chinese culture. In the future, Chinese government should adhere to the socialist system with Chinese characteristics and improve the public health and emergency management system. Chinese government should accelerate the construction of a community with a shared future for mankind and promote the modernization of the national governance system and governance capacity. These findings are of great significance in understanding China's prevention and control measures, the institutional advantages and subsequent optimization.

Impact de la Covid 19 sur la première ligne en Tunisie

INTRODUCTION

Public primary healthcare facilities, the cornerstone of the Tunisian health system, were impacted by the Covid 19 crisis as all health systems in the world.

AIM

This study aims to assess this impact of the pandemic.

METHODS

We analyzed the budgetary evolution of the basic healthcare group (BHG) of Medenine and Djerba between 2019 and 2020. Similarly, we examined the evolution of all the activities of BHG of Medenine. This analysis was also completed by a semi-structured questioning with a regional expert.

RESULTS

Our results showed an increase in expenditure, a decrease in revenue (12.4% for GSB of Medenine and 10.8% for BHG of Djerba), and an accumulation of outstanding payment. BHG's activities have been affected by the pandemic. We showed that stomatology and vaccine activities were well maintained during the pandemic. However, we noted a regression in the number of patients and some illnesses. Activity related to child health and health education has significantly decreased. This impact has had and will have repercussions on the epidemiological state of the population. Despite the intervention of the regional management in terms of organization, training and strengthening of equipment and human resources, the pandemic has generally impacted the operation process of these establishments, which are already facing several challenges.

CONCLUSION

We recommend above all to activate the already existing opportunities to replenish the financial resources of primary healthcare facilities, to improve work environment and continuous professional development and to computerize the data and its analysis according to a scientific approach.

Current challenges in the healthcare sector and respective response measures

OBJECTIVE

Aim: To improve the classification of current challenges in the healthcare sector and specify the areas of appropriate response measures.

PATIENTS AND METHODS

Materials and Methods: The work uses a systematic approach that enables the analysis of the study of individual challenges in the field of healthcare. The following scientific methods were used: analysis; dialectic; specification.

CONCLUSION

Conclusions: The classification of current challenges and mechanisms for responding to them in the field of healthcare has been improved according. Each of these areas of response to healthcare challenges is to some extent interrelated and therefore has a synergistic effect.

Systematic review and meta-analysis of knowledge, attitudes, and practices regarding COVID-19 among chronic disease patients: A global perspective

Background

Chronic health conditions were significantly correlated with an increased clinical severity of coronavirus 2019 (COVID-19) and a heightened risk of COVID-19 mortality. This study aims to determine global knowledge, attitudes, and practices (Knowledge Abuse Profile) of the patients with chronic diseases toward COVID-19.

Methods

The study was initiated in December 2019 and extended until April 2023, during which an extensive search for relevant English-language literature was conducted as part of this systematic review and meta-analysis. Google Scholar, Scopus, PubMed/MEDLINE, Science Direct, Web of Science, EMBASE, Springer, and ProQuest were utilized for the search. The quality of included studies was assessed using a quality rating checklist created by Joanna Briggs Institute for cross-sectional research. In the STATA software version 14, inverse variance and Cochran Q statistics were used for statistical analysis to assess heterogeneity among the studies. The Dersimonian and Liard random-effects models were applied in cases where heterogeneity existed.

Results

A total of 23 studies involving 14,587 patients contributed to this meta-analysis. These studies comprised 21 studies focused on knowledge, with 6864 participants, 12 studies on attitudes involving 3597 patients, and 12 on practices, encompassing 4126 patients. The pooled estimates for sufficient knowledge, positive attitudes, and COVID-19 preventive behaviors among chronic disease patients were determined as 48.2% (95% confidence interval [95% CI]: 33.9%-62.5%), 60.8% (95% CI: 46.8%-74.8%), and 58.3% (95% CI: 39.5%-77.0%), respectively. Over the years, there was a consistent decrease in adequate knowledge, positive attitudes, and COVID-19 preventive behaviors among the population. Specifically, regarding knowledge, the rates declined from 50.2% in 2020 to 49.7% in 2021 and dropped to 45.1%. Similarly, the percentage of individuals with a positive attitude fell, decreasing from 64.1% in 2020 to 60.3% in 2021 and dropping to 57.9% in 2022. Furthermore, COVID-19 preventive behaviors showed fluctuations, with the rates recorded at 63.7% in 2020, increasing to 75.4% in 2021, and then decreasing to 47% in 2022, in line with the publication dates of included studies.

Conclusion

The findings of meta-analysis show a significant decrease in the levels of knowledge, attitudes, and adherence to preventative interventions for COVID-19 among individuals with chronic diseases. The findings emphasize the need for targeted interventions, and ongoing education to address this trend.

Assessing airborne transmission risks in COVID-19 hospitals by systematically monitoring SARS-CoV-2 in the air

IMPORTANCE

Risk management and control of airborne transmission in hospitals is crucial in response to a respiratory virus pandemic. However, the formulation of these infection control measures is often based on epidemiological investigations, which are an indirect way of analyzing the transmission route of viruses. This can lead to careless omissions in infection prevention and control or excessively restrictive measures that increase the burden on healthcare workers. The study provides a starting point for standardizing transmission risk management in designated hospitals by systemically monitoring viruses in the air of typical spaces in COVID-19 hospitals. The negative results of 359 air samples in the clean and emergency zones demonstrated the existing measures to interrupt airborne transmission in a designated COVID-19 hospital. Some positive cases in the corridor of the contaminant zone during rounds and meal delivery highlighted the importance of monitoring airborne viruses for interrupting nosocomial infection.

Leveraging the E-commerce footprint for the surveillance of healthcare utilization

The utilization of healthcare services serves as a barometer for current and future health outcomes. Even in countries with modern healthcare IT infrastructure, however, fragmentation and interoperability issues hinder the (short-term) monitoring of utilization, forcing policymakers to rely on secondary data sources, such as surveys. This deficiency may be particularly problematic during public health crises, when ensuring proper and timely access to healthcare acquires special importance. We show that, in specific contexts, online pharmacies' digital footprint data may contain a strong signal of healthcare utilization. As such, online pharmacy data may enable utilization surveillance, i.e., the monitoring of short-term changes in utilization levels in the population. Our analysis takes advantage of the scenario created by the first wave of the Covid-19 pandemic in Mainland China, where the virus' spread lead to pervasive and deep reductions of healthcare service utilization. Relying on a large sample of online pharmacy transactions with full national coverage, we first detect variation that is strongly consistent with utilization reductions across geographies and over time. We then validate our claims by contrasting online pharmacy variation against credit-card transactions for medical services. Using machine learning methods, we show that incorporating online pharmacy data into the models significantly improves the accuracy of utilization surveillance estimates.

Dynamic zero-COVID policy and healthcare utilization patterns in China during the Shanghai COVID-19 Omicron outbreak

BACKGROUND

In April 2022, an outbreak of the SARS-CoV-2 virus Omicron variant in Shanghai precipitated an extensive lockdown. We assessed changes in healthcare utilization during this outbreak and investigated the relationship between the stringency of mitigation strategies and disruptions in healthcare utilization.

METHODS

Using provincial-level data from routine health information systems covering all hospitals across Mainland China, we conducted an interrupted time series analysis to examine changes in healthcare utilization during the Shanghai outbreak. Linear regression was used to evaluate the direction and magnitude of the association between the relative changes in the move-out movement index, a proxy for the stringency in population-level mitigation strategies, and the estimated relative changes in healthcare utilization.

RESULTS

Overall, there were 22.9 billion outpatient visits and 1.2 billion discharged inpatients during the study period from January 2016 to May 2022, including 9.1 billion (39.7%) and 0.46 billion (38.2%) in the post-COVID-19 period (January 2020-May 2022), respectively. From March through May 2022, the outbreak resulted in an accumulative loss of 23.5 million (47%) outpatient visits and 0.6 million (55%) discharged inpatients in Shanghai, and a loss of 150.3 million (14%) outpatient visits and 3.6 million (7%) discharged inpatients in other regions. We find that for every 10-percentage point reduction in the relative change of move-out index, a 2.7 (95% CI: 2.0-3.4) percentage point decline in the relative change of outpatient visits, and a 4.3 (95% CI: 3.5-5.2) percentage points decline in the relative change of inpatient discharges.

CONCLUSIONS

The Shanghai COVID-19 Omicron outbreak associates with a substantial reduction in outpatient visits and inpatient discharges within Shanghai and other regions in China. The stringency of the COVID-19 lockdown policies associates with more profound reductions in healthcare utilization.

"We felt so proud by the president calling us my heroes." An exploration of the nurse's experiences in the management of COVID-19 patients in Uganda

INTRODUCTION

Adequate and intensive nursing care was a key characteristic of recovery of the COVID-19 patients globally and in Uganda. However, there is limited literature on the experiences of nurses who participated in the care of COVID-19 patients in Uganda, East Africa, and Africa at large, yet imperative in designing approaches to increase the efficiency of the health systems' response to future pandemics. To address this gap, this study aimed to explore the experiences of the nurses who managed COVID-19 patients at Mulago National Referral Hospital in Uganda.

METHODS

This was an exploratory qualitative study that used purposive sampling to identify 21 nurses who treated COVID-19 patients at Mulago National Referral Hospital in Uganda. Focus Group Discussions were used to collect data. Thematic Analysis was used to analyze the data. Common codes were identified and grouped to create subthemes and major themes.

RESULTS

Six themes were identified: 1) Motivation to work on COVID-19 patients, 2 ) Roles performed by nurses, 3) High workload and professional role strain, 4) Challenges with maintaining personal health and relationships, 5) Institutional and government support, 6) Acquired professional knowledge and skills to manage critical patients and epidemics. Most of the nurses faced work burnout, social isolation, stress, and psychological trauma. However, interprofessional collaboration, financial incentives, government recognition, and provision of personal protective equipment, were key motivators for the nurses. The majority reported to have gained new knowledge and skills in the management of pandemics and highly infectious diseases.

CONCLUSION

The nurses experienced negative scenarios like work burnout due to high workload, social isolation, and psychological stress. Therefore, there is a need for health systems to develop approaches and policies that support nurses' well-being. Nevertheless, key attributes like resilience, adaptability, and diligence to serve enabled them to persevere despite the hardships faced.

Preventing and developmental factors of sustainability in healthcare organisations from the perspective of decision makers: an exploratory factor analysis

BACKGROUND

UN Sustainable Development Goals are part of the political agenda of most developed countries. Being a developing country, Albania has only recently adhered to this trend. Prior research at national level has sporadically focused on environmental sustainability, neglecting a holistic view of the phenomenon. To fill this gap, this study aims to explore preventing and developmental factors of sustainability in healthcare organisations from the perspective of decision makers by relying to a Triple Bottom Line approach.

METHODS

Data were collected through a questionnaire administered to healthcare facilities and analysed through the Exploratory Factor Analysis. Findings revealed that the factors influencing the sustainability of the national healthcare system were five: Barriers of Organisational Sustainability; Stakeholders Pressure (regarding sustainable issues); Awareness (knowledge and measures taken for sustainability); Institutional Engagement; and Personal Interest and Involvement. The underlying factors included 19 items suitable for this sample, representing 64.371% of the total variance.

RESULTS

The findings show the existence of 4 factors: Barriers of Organisational Sustainability, Stakeholders Pressure regarding Sustainable issues, Awareness/knowledge and measures taken for sustainability, Personal Interest and Involvement.

CONCLUSIONS

It is evident that national health organisations should continuously improve its strategies to be consistent with the sustainable development goals of international organisations, so that their initiatives could reflect the integration of sustainability approaches at the organisational level.

Assessing the Knowledge, Attitudes, and Vaccination Practices Towards COVID-19 Vaccination Among Mainland Chinese Nursing Students and Interns: A Multicenter Cross-Sectional Study

Objective

This study investigated factors influencing the knowledge, attitudes, practice profiles, and vaccination intentions among Chinese nursing students and nursing interns toward the coronavirus disease (COVID-19) vaccination.

Materials and Methods

The multicenter cross-sectional study was based on a self-reported questionnaire collecting information among nursing students and nursing interns from three major geographic regions of China, and the sample was selected by consecutive sampling. The questionnaire was developed by knowledge, attitudes, and practice (KAP) theory. Univariate and multivariate logistic regression were used for statistical analysis.

Results

A total of 3180 nursing students and interns (effective rate: 99.8%) from six Chinese provinces were polled. The vaccine hesitation rate was 9.65% (307/3180), 2230 participants (70.1%) had gotten at least one dose of the vaccine, and 643 participants (67.7%) had indicated a readiness to be vaccinated. The results showed that older age, higher academic background, perfect vaccine management, others' recommendations, influenza vaccination history, epidemic under control, knowledge of vaccines or intervals, and vaccine knowledge training were associated with higher vaccination rates. Conversely, vaccine hesitancy was caused by a perceived lack of physical need, uncertainty about vaccination requirements, and fear of vaccination.

Conclusion

This study provided population-based estimates of COVID-19 vaccine uptake intention among mainland Chinese nursing students and interns. Factors such as age, education, vaccine knowledge, and attitudes influence COVID-19 vaccine behaviour. Relevant authorities should understand the barriers to COVID-19 vaccination from knowledge, attitude and practice, which is significant for formulating effective response strategies in future global public health crises.

Associations between laboratory variables and clinical features in patients hospitalized with COVID-19 after non-mRNA vaccination in China: A cross-sectional study

Objectives

Based on the data during the outbreak of COVID-19 in Wuxi city in China, we explored the relationship between laboratory variables and clinical features in patients hospitalized with COVID-19 after non-mRNA vaccination, and attempted to identify the significant impact of vaccination and COVID-19 infection on humans.

Methods

A retrospective observational cohort study was carried out. Patients who received non-mRNA COVID-19 vaccines and were hospitalized with COVID-19 between June 28, 2022, and July 24, 2022 were included. The correlation between different vaccine statuses, the time to negative PCR test, and biochemical parameters were investigated.

Results

All patients had a mild COVID-19 disease. The number of vaccine doses exerted no effects on the time to negative PCR test (P = 0.559). No differences were evident among inactivated, adenoviral-vectored, and recombinant subunit vaccines in the time to negative PCR test.Patients who just received one dose had significantly lower blood glucose levels than those who received three doses (P = 0.024), whereas two doses had no effect on blood glucose levels (one dose vs. two doses, P = 0.223; two doses vs. three doses, P = 0.457).Body temperature (β = 0.168, P = 0.011) and the percentage of lymphocytes (β = -0.219, P = 0.001) were substantially correlated with the time to COVID-19 negative PCR test. The prolonged stay was linked to a rise in GOT that fell within the usual range (P = 0.025).The percentage of lymphocytes (P = 0.007) and serum potassium (P = 0.004) were concordant with the marked change in body temperature.

Conclusions

The dose and type of vaccination had no effect on the time to COVID-19 negative PCR test in patients with mild COVID-19. Comparing the first dose with the booster dose, the blood glucose levels increased within the normal range. The period at which the COVID-19 nucleic acid turned negative correlated with body temperature, the proportion of lymphocytes, GOT, and serum potassium.

Vlogging Pregnancy and Laboring During the Pandemic on YouTube

Since early 2020, the world has been dealing with the COVID-19 pandemic. The rapid changing situation led to unforeseeable challenges and questions for many people, including pregnant women. Through a textual analysis of personal narratives told via pregnancy and/or laboring vlogs during COVID-19, this present study aims to understand how women from China who live in another country during pregnancy have utilized YouTube vlogs to share their experiences. Through this analysis, we identify various challenges that these women experienced during their pregnancy. The COVID-19 pandemic exaggerated the normal difficulties of these issues and also created additional problems for these women, including regular pregnancy tests, choice of birthing locations, and the support and caring that were normal during this time period.

Performance analysis of hospitals before and during the COVID-19 in Iran: A cross-sectional study

BACKGROUND AND OBJECTIVE

The COVID-19 pandemic placed considerable pressure on the health care systems and caused many disruptions to the care hospital system around the globe. This study aimed to analyze the performance of hospitals affiliated with the University of Medical Sciences and Health Services of South Khorasan Province before and during COVID-19.

METHOD

This cross-sectional study tracked the financial performance (FP) and service performance (SP) of 12 hospitals affiliated with South Khorasan University of Medical Sciences and Health Services using the Farabar system and Hospital Information System (HIS). Our study covered two time periods: from February 2018 to February 2020 (pre-COVID-19) and from February 2020 to February 2021 (during COVID-19). SP analysis of hospitals was performed by examining the trend of monthly changes before and during the COVID-19 pandemic and analyzed using SPSS software version 22 and Paired Sample T-Test. FP of hospitals was analyzed through relevant ratios and analyzed using Microsoft Office Excel.

RESULTS

Most SP indicators decreased considerably in all hospitals during COVID-19. FP ratios (e.g., activity and leverage ratios) increased during either or both pre-COVID or COVID periods. Compared to before COVID-19, the operating margin ratio and operating expenses coverage from operating income increased from -0.50 and 66.55 to -1.42 and 41.32, respectively, during COVID-19. Moreover, the net profit margin ratio and Return On Assets (ROA) ratio were increased during COVID-19.

CONCLUSION

COVID-19 has decreased the FP and SP of hospitals due to limitations in providing services to patients since the beginning of COVID-19. Measures such as providing various financing resources and improving the financial resilience of hospitals are essential. Funds should be disbursed to offset hospitals' losses due to reduced elective and outpatient revenue. Policymakers should come up with holistic policies to tackle the adverse impact of such crises in the future, support hospitals financially, and consider allocating additional funding to them during emergencies.

Langya virus outbreak: current challenges and lesson learned from previous henipavirus outbreaks in China, Australia, and Southeast Asia

Background and aims

A new novel virus, Langya virus (LayV), was detected in China in August 2022, 3 years after the COVID-19 pandemic. LayV is similar to the previously discovered Mojiang henipavirus. Other zoonotic henipaviruses include the Hendra and Nipah viruses. The emergence of the zoonotic Langya virus is attributed to climate change and wildlife encroachment, as LayV is detected in shrews. Those who are infected in China showed various symptoms, but no deaths have been recorded yet. This review aims to shed light on the current state of Langya virus outbreak, its infection control efforts, and the remaining challenges that need to be addressed to curb the outbreak.

Methods

We utilized online publication databases such as PubMed, Google Scholar, and Scopus in writing this review article.

Results

A surveillance study on thirty-five febrile patients in Eastern China identified the Langya virus outbreak. The current efforts from the Chinese government and health authorities to reduce the transmission and spread of Langya virus such as isolation and characterization of LayV, challenges associated with the increase in cases of LayV, and trackable recommendations such as strengthening the healthcare system in China, sensitization of people about risks associated with Langya virus outbreaks, creating an intensive surveillance system network, etc. were discussed.

Conclusion

It is germane and pertinent that the Chinese government and health authorities continue to intensify efforts against Langya virus and address the challenges to effectively reduce transmission.

A data-driven optimization model to response to COVID-19 pandemic: a case study

COVID-19 is a highly prevalent disease that has led to numerous predicaments for healthcare systems worldwide. Owing to the significant influx of patients and limited resources of health services, there have been several limitations associated with patients' hospitalization. These limitations can cause an increment in the COVID-19-related mortality due to the lack of appropriate medical services. They can also elevate the risk of infection in the rest of the population. The present study aims to investigate a two-phase approach to designing a supply chain network for hospitalizing patients in the existing and temporary hospitals, efficiently distributing medications and medical items needed by patients, and managing the waste created in hospitals. Since the number of future patients is uncertain, in the first phase, trained Artificial Neural Networks with historical data forecast the number of patients in future periods and generate scenarios. Through the use of the K-Means method, these scenarios are reduced. In the second phase, a multi-objective, multi-period, data-driven two-stage stochastic programming is developed using the acquired scenarios in the previous phase concerning the uncertainty and disruption in facilities. The objectives of the proposed model include maximizing the minimum allocation-to-demand ratio, minimizing the total risk of disease spread, and minimizing the total transportation time. Furthermore, a real case study is investigated in Tehran, the capital of Iran. The results showed that the areas with the highest population density and no facilities near them have been selected for the location of temporary facilities. Among temporary facilities, temporary hospitals can allocate up to 2.6% of the total demand, which puts pressure on the existing hospitals to be removed. Furthermore, the results indicated that the allocation-to-demand ratio can remain at an ideal level when disruptions occur by considering temporary facilities. Our analyses focus on: (1) Examining demand forecasting error and generated scenarios in the first phase, (2) exploring the impact of demand parameters on the allocation-to-demand ratio, total time and total risk, (3) investigating the strategy of utilizing temporary hospitals to address sudden changes in demand, (4) evaluating the effect of disruption to facilities on the supply chain network.

Professional identity, job satisfaction, and intention to stay among clinical nurses during the prolonged COVID-19 pandemic: A mediation analysis

AIM

This study aims to examine the relationship between professional identity and job satisfaction and their impact on intention to stay among clinical nurses in China during the prolonged COVID-19 pandemic.

METHODS

A cross-sectional survey was conducted from April 30 to May 25, 2021, in China. Data were collected using professional identity, job satisfaction, and intention to stay questionnaires from 1425 clinical nurses. A single mediation analysis was utilized to test the interrelationship among the variables, and the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) checklist as a reporting guide.

RESULTS

Nurses indicated a medium level of professional identity, job satisfaction, and intention to stay, with mean scores of 3.85, 3.25, and 3.47, respectively. The professional identity displayed positive indirect effect on nurses' intention to stay through job satisfaction (indirect effect = 0.498, 95% CI [0.439, 0.558]).

CONCLUSION

Cultivating professional identity among nurses can increase their job satisfaction and ultimately enhance the intention to stay in the nursing profession. However, this study also suggests paying more attention to job satisfaction to keep nursing retention. These may be helpful to retain the nursing workforce.

Quality of care in the course of subcutaneous versus intravenous trastuzumab administration in patients with breast cancer: an integrated time-motion study with mixed-methods research

OBJECTIVES

This study aimed to compare the time required and concerns raised by various perspectives of participants regarding administering subcutaneous and intravenous trastuzumab for patients with breast cancer (BC).

DESIGN

This observational time-motion study design with mixed-methods research (cross-sectional surveys and semistructured interviews) was conducted. The time spent on preparing or administering trastuzumab by different healthcare professionals (HCPs) was recorded. The data were analysed by descriptive/inferential statistical analyses, followed by thematic analyses.

SETTING

Outpatient and inpatient administration units of a single medical centre in Taiwan.

PARTICIPANTS

The study included patients with early-stage BC who received subcutaneous or intravenous trastuzumab (n=93), and HCPs including two attending physicians, a nurse practitioner, two pharmacists and two nurses.

RESULT

Based on the perspectives of patients and HCPs, the subcutaneous form of trastuzumab was more efficient, less expensive and produced less discomfort in outpatient units than inpatient units. More participants preferred the subcutaneous form over the intravenous form in both outpatient and inpatient units. Pharmacists and nurse practitioners spent threefold more time on patients when preparing and administering the intravenous form in both outpatient and inpatient units. The concerns raised by patients and HCPs varied in certain aspects, including the injection skills, speed, mental distress (eg, needle phobia) and pain associated with the subcutaneous form. Almost all patients preferred receiving the subcutaneous form in outpatient units after the initial COVID-19 outbreak.

CONCLUSION

Patients with early-stage BC preferred receiving subcutaneous trastuzumab in outpatient units rather than inpatient units or the intravenous form before and after the COVID-19 outbreak. Such findings may serve as real-world evidence to facilitate better quality of care regarding administration of subcutaneous or intravenous trastuzumab in medical settings, and its feasible resolutions to balance the quality, concerns and efficiency of anticancer administration during the COVID-19 pandemic.

Designing Digital COVID-19 Screening: Insights and Deliberations

Due to the global COVID-19 pandemic, public health control and screening measures have been introduced at healthcare facilities, including those housing our most vulnerable populations. These warning measures situated at hospital entrances are presently labour-intensive, requiring additional staff to conduct manual temperature checks and risk-assessment questionnaires of every individual entering the premises. To make this process more efficient, we present eGate, a digital COVID-19 health-screening smart Internet of Things system deployed at multiple entry points around a children's hospital. This paper reports on design insights based on the experiences of concierge screening staff stationed alongside the eGate system. Our work contributes towards social-technical deliberations on how to improve design and deploy of digital health-screening systems in hospitals. It specifically outlines a series of design recommendations for future health screening interventions, key considerations relevant to digital screening control systems and their implementation, and the plausible effects on the staff who work alongside them.

Understanding Use Intention of mHealth Applications Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) Model in China

The COVID-19 pandemic has significantly impacted the healthcare industry, especially public health resources and resource allocation. With the change in people's lifestyles and increased demand for medical and health care in the post-pandemic era, the Internet and home healthcare have rapidly developed. As an essential part of Internet healthcare, mobile health (mHealth) applications help to fundamentally address the lack of medical resources and meet people's healthcare needs. In this mixed-method study, we conducted in-depth interviews with 20 users in China (mean age = 26.13, SD = 2.80, all born in China) during the pandemic, based on the unified theory of acceptance and use of technology 2 (UTAUT-2) mode, and identified four dimensions of user needs in mHealth scenarios: convenience, control, trust, and emotionality. Based on the interview results, we adjusted the independent variables, deleted the hedonic motivation and the habit, and added the perceived trust and perceived risk as the variables. Using a structural equation model (SEM), we designed the questionnaire according to the qualitative results and collected data from 371 participants (above 18 years old, 43.9% male) online to examine the interrelationships these variables. The results show that performance expectancy (β = 0.40, p < 0.001), effort expectancy (β = 0.40, p < 0.001), social influence (β = 0.14, p < 0.05), facilitating condition (β = 0.15, p < 0.001), and perceived trust (β = 0.31, p < 0.001) had positive effects on use intention. Perceived risk (β = -0.31, p < 0.001) harmed use intention, and price value (β = 0.10, p > 0.5) had no significant effects on use intention. Finally, we discussed design and development guidelines that can enhance user experience of mHealth applications. This research combines the actual needs and the main factors affecting the use intention of users, solves the problems of low satisfaction of user experience, and provides better strategic suggestions for developing mHealth applications in the future.

Application of big data and artificial intelligence in epidemic surveillance and containment

Faced with the current time-sensitive COVID-19 pandemic, the overburdened healthcare systems have resulted in a strong demand to develop newer methods to control the spread of the pandemic. Big data and artificial intelligence (AI) have been leveraged amid the COVID-19 pandemic; however, little is known about their use for supporting public health efforts. In epidemic surveillance and containment, efforts are needed to treat critical patients, track and manage the health status of residents, isolate suspected cases, and develop vaccines and antiviral drugs. The applications of emerging practices of artificial intelligence and big data have become powerful "weapons" to fight against the pandemic and provide strong support in pandemic prevention and control, such as early warning, analysis and judgment, interruption and intervention of epidemic, to achieve goals of early detection, early report, early diagnosis, early isolation and early treatment. These are the decisive factors to control the spread of the epidemic and reduce the mortality. This paper systematically summarized the application of big data and AI in epidemic, and describes practical cases and challenges with emphasis on epidemic prevention and control. The included studies showed that big data and AI have the potential strength to fight against COVID-19. However, many of the proposed methods are not yet widely accepted. Thus, the most rewarding research would be on methods that promise value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for practice.

Validation of the RIM Score-COVID in the Spanish SEMI-COVID-19 Registry

The significant impact of COVID-19 worldwide has made it necessary to develop tools to identify patients at high risk of severe disease and death. This work aims to validate the RIM Score-COVID in the SEMI-COVID-19 Registry. The RIM Score-COVID is a simple nomogram with high predictive capacity for in-hospital death due to COVID-19 designed using clinical and analytical parameters of patients diagnosed in the first wave of the pandemic. The nomogram uses five variables measured on arrival to the emergency department (ED): age, sex, oxygen saturation, C-reactive protein level, and neutrophil-to-platelet ratio. Validation was performed in the Spanish SEMI-COVID-19 Registry, which included consecutive patients hospitalized with confirmed COVID-19 in Spain. The cohort was divided into three time periods: T1 from February 1 to June 10, 2020 (first wave), T2 from June 11 to December 31, 2020 (second wave, pre-vaccination period), and T3 from January 1 to December 5, 2021 (vaccination period). The model's accuracy in predicting in-hospital COVID-19 mortality was assessed using the area under the receiver operating characteristics curve (AUROC). Clinical and laboratory data from 22,566 patients were analyzed: 15,976 (70.7%) from T1, 4,233 (18.7%) from T2, and 2,357 from T3 (10.4%). AUROC of the RIM Score-COVID in the entire SEMI-COVID-19 Registry was 0.823 (95%CI 0.819-0.827) and was 0.834 (95%CI 0.830-0.839) in T1, 0.792 (95%CI 0.781-0.803) in T2, and 0.799 (95%CI 0.785-0.813) in T3. The RIM Score-COVID is a simple, easy-to-use method for predicting in-hospital COVID-19 mortality that uses parameters measured in most EDs. This tool showed good predictive ability in successive disease waves.

Counseling for Health: How Psychological Distance Influences Continuance Intention towards Mobile Medical Consultation

As mobile healthcare services entered the public sight with high frequency during the COVID-19 pandemic, patients are increasingly recognizing the effectiveness of mobile medical consultation (MMC). Earlier studies have investigated what influences continuance intention (CI) towards MMC, but few studies have scrutinized it from the perspective of patients' psychological distance. We formulated a framework to examine the psychological factors influencing CI towards MMC by integrating the information systems continuance model and psychological distance theory. The framework was validated using the partial least squares structural equation modeling (PLS-SEM) approach and data from 475 MMC users in China. The empirical results revealed that immediacy, telepresence, intimacy, and substitutability were significant predictors of CI, while satisfaction mediated these pathways. Pandemic-induced anxiety positively moderated the effect of immediacy on satisfaction and the effect of satisfaction on CI. Practical implementations for MMC healthcare practitioners, designers, and marketers are drawn.

Global law, policy, and governance for effective prevention and control of COVID-19: A comparative analysis of the law and policy of Pakistan, China, and Russia

Global health governance is a developing system in this complex institutional regime. The local and regional health policies sometimes challenge global health governance due to diverse discourse in various countries. In the wake of COVID-19, global health governance was reaffirmed as indifferent modules to control and eliminate the pandemic; however, the global agencies later dissected their own opinion and said that "countries must learn to live with a pandemic." Given the controversial statement, this research focuses on the strong and effective policies of the Russian Federation, Pakistan, and China. The research uses the law and governance results and newly developed policies of the three countries formed under the global health policies. The conclusion is based on the statement that in order to live with the pandemic, strong health measures are required at each level.

Knowledge, attitude, and practices on COVID-19 prevention and diagnosis among medical workers in the radiology department: A multicenter cross-sectional study in China

Objective

The aim of this study was to investigate the knowledge, attitude, and practice (KAP) of medical workers in the radiology department toward the prevention and diagnosis of COVID-19.

Methods

This multicenter cross-sectional study was conducted among medical workers in the radiology department of 17 hospitals between March and June 2022.

Results

A total of 324 medical workers were enrolled. The mean knowledge scores were 15.3 ± 3.4 (out of 23), attitude scores were 31.1 ± 5.6 (range 8-40), and practice scores were 35.1 ± 4.4 (range 8-40). Positive attitudes (OR = 1.235, 95% CI: 1.162-1.311, P < 0.001) and aged 41-50 years were independently associated with higher practice scores. Those with the better practice were more likely to be older (OR = 2.603, 95% CI: 1.242-5.452, P = 0.011), nurses (OR = 2.274, 95% CI: 1.210-4.272, P = 0.011) and with junior/intermediary/vice-senior title (OR = 2.326, 95% CI: 1.030-5.255, P = 0.042; OR = 2.847, 95% CI: 1.226-6.606, P = 0.015; OR = 4.547, 95% CI: 1.806-11.452, P = 0.001, respectively). Subgroup analysis revealed significant differences in knowledge between technicians and physicians and nurses and between staff working in tertiary hospitals and non-tertiary hospitals. Knowledge is positively correlated with attitude (β = 0.54, P < 0.001), and attitude is positively correlated with practice (β = 0.37, P < 0.001). Attitudes significantly mediated the association between knowledge and practice (β = 0.119, P < 0.001).

Conclusion

The radiology medical workers showed moderate knowledge but good attitudes and practices of prevention and diagnosis of COVID-19. Attitudes were found to be positively associated with better practices of prevention and diagnosis of COVID-19. Attitudes significantly mediated the association between knowledge and practice.

Using machine learning to explore the determinants of service satisfaction with online healthcare platforms during the COVID-19 pandemic

This study investigates the determinants of service satisfaction with online healthcare platforms using machine learning (ML) algorithms. By training and testing eleven ML models based on data mined from a leading online healthcare platform in China, we obtained the best-performing ML algorithm for service satisfaction prediction, namely, Light Gradient Boosting Machine. Furthermore, our empirical results indicate that gifts, patient votes, popularity, fee-based consultation volume, gender, and thank-you letters positively impact service satisfaction, while the impacts of consultation volume, free consultation volume, views, waiting time, articles, physician title, and hospital level are negative. We discuss the theoretical and managerial implications.

Logistics Trends and Innovations in Response to COVID-19 Pandemic: An Analysis Using Text Mining

The disruptions caused by the COVID-19 pandemic have forced many companies in the logistics sector to innovate, or even transform their business and underlying processes. Closing borders, limited supply and manpower, and continuous changes in regulations challenged many logistics firms to innovate. This study analyzes 5098 abstracts of logistics articles using text mining to identify and to quantify the changes in logistics trends and innovations before and during the COVID-19 pandemic, and if these trends and innovations were accelerated by the COVID-19 pandemic. Results indicate that (1) resiliency is an ongoing trend in logistics and has shown increasing importance during the COVID-19 pandemic; (2) there appears to be acceleration in digitalization trend in logistics based on emerging focus on blockchain, Internet of Things, data, drones, robots, and unmanned vehicles during COVID-19 pandemic, and (3) there seems to be no evidence of acceleration in sustainability due to COVID-19 despite an observed shift in sustainability trends in terms of bioenergy and biofuel before COVID-19 pandemic to low-carbon, hydrogen and electric vehicles during COVID-19 pandemic. This paper recommends logistics firms, especially Small and Medium Enterprises (SMEs), to analyze their readiness to adopt digitalization in terms of data, resources, and technology via, e.g., the use of a maturity scan, to contribute to sustainable and resilient logistics and to make sure that they remain competitive and future-proof. Policy makers can provide support to these SMEs by providing information, funding, and template solutions.

The 4Rs approach to COVID-19 emergency management during the post-pandemic period: What lessons can be learned from Shenzhen, China?

The Omicron variant of SARS-CoV-2 (or Omicron) is extremely contagious and has swept the world in a short period. Shenzhen-a new international city in China with a permanent population of 17.56 million and covering nearly 2000 square kilometers-was attacked by Omicron in 2022. However, the pandemic was controlled in a very short time as a result of prompt government reaction that prevented the variant's further spread. The total number of cases in this wave of the pandemic was more than 2600. Shenzhen's successful experience in tackling the Omicron wave deserves in-depth discussion. Proposed by American scholar Robert Heath, the 4Rs model aims to reduce the harm from a crisis through the measures of reduction, readiness, response, and recovery. This article presents the successful experience of Shenzhen's local government and the Third People's Hospital of Shenzhen, the only hospital in Shenzhen designated to use the 4Rs emergency management model for the treatment of COVID-19 during the 2022 Omicron wave of the pandemic.

High prevalence and risk factors of dropout intention among Chinese medical postgraduates

BACKGROUND

A high attrition rate in medical students has exacerbated the physician shortage in China. However, few studies have explored the risk factors of dropout intention in medical postgraduates. This study compared the prevalence of dropout intention and mental distress between medical and non-medical postgraduates in China and investigated risk factors for dropout intention. This study also explored the impact of medical postgraduates' perception of the Chinese healthcare environment on their mental status and dropout intention.

METHODS

This cross-sectional study was conducted using online questionnaires from October 2020 to April 2021. Convenience sampling was used to recruit postgraduates in different majors. Outcomes included dropout intention and potential risk factors, including mental distress, quality of life, and fatigue. Medical postgraduates were additionally assessed for healthcare environment satisfaction, burnout, career choice regret, and experiences of workplace violence. A logistic regression model was constructed to evaluate the association between dissatisfaction, mental distress, and turnover intention.

RESULTS

A total of 740 medical and 670 non-medical postgraduates participated in the survey. The rates of depression symptoms (33.8% vs. 39.0%, p < 0.001), anxiety symptoms (22.2% vs. 32.4%, p < 0.001), and somatic symptoms (34.7% vs. 42.4%, p = 0.004) were lower in medical postgraduates, while more medical postgraduates (58.4% vs. 48.4%, p < 0.001) reported dropout intention. Dissatisfaction with the healthcare environment (odds ratio [OR]: 1.65; 95% confidence interval [CI]: 1.17-2.34, p = 0.005), career choice regret (OR: 6.23; 95% CI: 4.42-8.78, p < 0.001), and high perceived stress (OR: 2.74; 95%CI: 1.90-3.94, p < 0.001) remained independently associated with turnover intention.

CONCLUSIONS

Mental distress is common among postgraduates, calling for timely interventions. Medical postgraduates reported higher turnover intention. Healthcare environment perception also affected the mental health and dropout intentions of medical students. A decent future income, reduced workload, shorter duration medical training, and better doctor-patient relationships are urgently needed.

COVID-induced 3 weeks' treatment delay may exacerbate breast cancer patient's psychological symptoms

The delayed access to cancer treatment due to the outbreak of COVID-19 pandemic posed a unique challenge to breast cancer patients and caused a significant level of mental distress among them. In the current research, we examined the psychological impacts of COVID on a subpopulation of breast cancer patients from a hospital in Shaanxi province of China using Symptom Checklist-90-R (SCL-90-R). Participants were 195 breast cancer patients at the outpatient clinic of Xijing hospital, Xi'an, Shaanxi Province, China. We found that a treatment delay of more than 3 weeks may exacerbate breast cancer patients' psychological symptoms, such as somatization, obsessive-compulsive disorder, interpersonal sensitivity, depression, hostility, phobic anxiety, paranoid ideation, and psychoticism, whereas a short-term delay of less than 3 weeks is less likely to have a significant effect on one's mental well-being. Additionally, breast cancer survivors, especially those at more advance stages, tend to experience more elevated psychological symptoms with longer treatment delay, and whose treatments continues to be delayed reported stronger psychological symptoms than individuals whose treatment are resumed, regardless of treatment type.

Changes of working conditions and job-related challenges due to the SARS-CoV-2 pandemic for medical assistants in general practices in Germany: a qualitative study

Background

In Germany, general practices are usually contacted first by patients with health complaints, including symptoms characteristic of SARS-CoV-2. Within general practices, medical assistants (MAs) are the first contact person for patients and perform various tasks in close physical patient contact. Working conditions of MAs have been characterized as challenging, e.g., due to low salaries, a high workload, time pressure and frequent interruptions. The potential changes of working conditions and job-related challenges experienced by MAs due to the SARS-CoV-2 pandemic have not been fully explored. We aimed to address this knowledge gap among MAs working in general practices in Germany.

Methods

Semi-structured telephone interviews were conducted between March and April 2021 with 24 MAs. Medical assistants of legal age, who worked in general practices in Germany, and who were continuously employed and without change of employer in 2020 were eligible for participation. Interview recordings were transcribed verbatim and content-analyzed using MAXQDA, using deductive and inductive coding.

Results

The SARS-CoV-2 pandemic posed great challenges for MAs, including a dramatic increase in workload, changes in occupational tasks, increased hygiene measures, rearrangements of work organization, childcare issues, and structural and personnel challenges within their practice. Participants described both improved but also worsened collaboration with their employers and colleagues due to the pandemic. Many MAs complained about issues regarding SARS-CoV-2-related billing processes and an increase in unpleasant patient behavior, including disregard of practice rules or frequent verbal insults. Many also did not feel adequately appreciated by politics, media, or society for their efforts during the pandemic. Positive changes were perceived to be the expansion of digital communication channels and a growing social cohesiveness of practice teams.

Conclusions

Our study suggests that the SARS-CoV-2 pandemic posed great challenges for MAs. The pandemic seems to have worsened MAs’ working conditions, which had been described as challenging already prior to the pandemic. In order to improve job satisfaction and to prevent loss of healthcare personnel, measures must be taken to improve working conditions of MAs in general practices.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01880-y.

User acceptance of smart home voice assistant: a comparison among younger, middle-aged, and older adults

Voice assistants are widely used in smart home environments. This study aimed to investigate user acceptance of a smart home voice assistant. A questionnaire was designed, and 471 Chinese adults were recruited to complete the questionnaire. The data were analyzed using exploratory factor analysis and regression analysis. The results revealed that user requirements of adults were composed of six factors: hedonic motivation and trust (β = .41, p < .001), social influence (β = .22, p < .001), performance expectancy (β = .15, p < .001), effort expectancy (β = .08, p = .018), product features (β = .15, p = .009), and facilitating conditions (β = .06, p = .049). Among these six factors, hedonic motivation and trust are considered the most important. Younger, middle-aged, and older adults differed significantly in their requirements and acceptance of a smart home voice assistant. These findings have implications for the design of smart home voice assistants so that they are more acceptable to younger and older adults.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10209-022-00936-1.

A long waiting time from diagnosis to treatment decreases the survival of non-small cell lung cancer patients with stage IA1: A retrospective study

Objective

The prognostic effect of delayed treatment on stage IA1 non-small cell lung cancer (NSCLC) patients is still unclear. This study aimed to explore the association between the waiting time before treatment and the prognosis in stage IA1 NSCLC patients.

Methods

Eligible patients diagnosed with pathological stage IA1 NSCLC were included in this study. The clinical endpoints were overall survival (OS) and cancer-specific survival (CSS). The Kaplan-Meier method, the Log-rank test, univariable, and multivariable Cox regression analyses were used in this study. Propensity score matching was used to reduce the bias of data distribution.

Results

There were eligible 957 patients in the study. The length of waiting time before treatment stratified the survival in patients [&lt;3 months vs. ≥3-months, unadjusted hazard ratio (HR) = 0.481, P = 0.007; &lt;2 months vs. ≥2-months, unadjusted HR = 0.564, P = 0.006; &lt;1 month vs. ≥1-month, unadjusted HR = 0.537, P = 0.001]. The 5-year CSS rates were 95.0% and 77.0% in patients of waiting time within 3 months and over 3 months, respectively. After adjusting for other confounders, the waiting time was identified as an independent prognostic factor.

Conclusions

A long waiting time before treatment may decrease the survival of stage IA1 NSCLC patients. We propose that the waiting time for those patients preferably is less than one month and should not exceed two months.

Analysis of the Elderly’s Preferences for Choosing Medical Service Facilities from the Perspective of Accessibility: A Case Study of Tertiary General Hospitals in Hefei, China

The accessibility of medical service facilities is a vital influence on elderly people choosing medical treatment. Encouraging residents to seek nearby medical treatment can facilitate the rational layout and diversion of urban medical facilities and reduce health resource waste. However, due to accessibility factors, elderly people may not choose the nearest hospital. In order to investigate such factors, we conducted a questionnaire survey among the elderly from 10 tertiary general hospitals in Hefei, China. On the basis of the origin-destination (OD) cost matrix analysis and statistical analysis of 830 valid questionnaires, this paper analyzed the elders’ selection rules when choosing medical facilities and the factors considered when making a choice. The study found that although 85% of elderly participants valued a short distance to tertiary hospitals, only 31% of them attended the closest hospitals in reality, which correlated with regularity according to their education level, travel activity status, and place of residence. The elderly highlighted road congestion, convenience of public transport stations, and number of transfers as critical in determining whether they sought nearby medical treatment. According to the results, effective ways to encourage the elderly to attend their nearest hospital, from the perspective of accessibility, include easing road congestion, improving the layout of public transport stations, and optimizing urban public transport routes. In particular, when planning future medical facilities, attention should be paid to the elderly with primary school education or below, who cannot travel independently, and those who live far from the city center.

The Coupling Coordination Evolutionary Analysis of Tourism-Ecological Environment-Public Service for the Yellow River Basin of China

In the context of the global pandemic, the development of tourism in the Yellow River Basin is constrained by the dual mechanisms of the decline in the quality of public service and the deterioration of the ecological environment. In order to promote the high-quality development of the ecological environment in the Yellow River Basin, this paper studies the coordinated development of tourism, the ecological environment and public service in the Yellow River Basin by treating tourism, the ecological environment and public service as a whole. Based on the coupling coordination function GM (1,1) grey prediction method and PVAR model, we discuss the characteristics of spatio-temporal differences, evolutionary trends and the interaction mechanism of the coupling coordination degree (CCD) of tourism-ecological environment-public service in nine provinces along the Yellow River Basin in China from 2008 to 2019. The results show that tourism and public service in the Yellow River Basin are closely related, and the protection of the ecological environment and tourism development are not contradictory. In terms of time, the overall trend is stable and upward from the perspective of the CCD of the three systems; in terms of space, Henan, Shandong, and Sichuan provinces have a relatively high level of CCD. While Qinghai, Gansu, Ningxia, Inner Mongolia, Shaanxi and Shanxi provinces have a lower level of CCD, which shows an upward trend from upstream to downstream in the space. The evolutionary trend of the CCD of the three systems in the basin will be upward in all provinces except for the Shandong province in the next five years. Tourism can promote both the ecological environment and public service from the perspective of the mutual influence mechanism.

The Impact of Scarcity on Consumers' Impulse Buying Based on the S-O-R Theory

Purpose

The global COVID-19 pandemic impacted the healthcare systems of every nation. The scarcity of medical protective equipment led to impulse buying at the early stages of the COVID-19 outbreak in China which resulted in stockpiling and the increase of prices by retailers and insufficiencies among frontline workers. This situation impacted epidemic control work and market order and is the context from which this paper identifies how the scarcity of medical protective equipment affected Chinese consumers’ impulse buying based on the theories of S-O-R model and bandwagon effect. The research provides insight into the mechanism of mediation (fear of missing out) and moderation (bandwagon) in the relationship between scarcity and impulse buying.

Design/Methodology/Approach

This study uses convenience sampling, surveying 488 Chinese consumers through an online questionnaire. Smart-PLS was used to test the hypotheses.

Findings

The empirical findings demonstrate that scarcity makes consumers fear missing the chance of getting protective medical equipment, leading ultimately to impulse buying. Besides, the scarcity effect on consumers’ impulse buying was found to depend on other consumers’ follow up behaviour in such emergency situations.

Research Limitations/Implications

The findings provide managerial and theoretical insight and a point of reference for businesses in the implementation of a scarcity strategy. The findings will also prove useful to the Chinese Risk Response Department as it continuously improves its responses to the risk of consumers’ impulse buying during a pandemic.

Originality/Value

This study consolidates and takes research forward in the areas of impulse buying and consumer behaviour, confirming the mediating effect of fear of missing out and the moderating effect of the bandwagon in the relationship between scarcity and impulse buying.

Study on infection behavior and characteristics of poplar wood dyed by Lasiodiplodia theobromae

The technology of dyeing wood by microorganisms is a kind of pollution-free and sustainable wood dyeing technology. To achieve fast and rich dyeing of Lasiodiplodia theobromae on the surface of poplar wood, tyrosinase and tricyclazole were used as induction factors in this experiment. The results showed that L. theobromae had a better induction effect in the cross-section of poplar wood and induced with tricyclazole. The surface color of poplar ranged from light yellow dyeing to gray and brown, the chromatic aberration of the cross-section of wood was above 44.5 NBS, and the infected area was over 50%, while the dyed parts of radial and tangential sections of wood were only on the surface of the wood after 30 days of infection. The induced infection of L. theobromae on poplar wood had little effect on the chemical components of poplar and had good colorfastness to washing and light. Therefore, microbial dyeing of wood showed a beneficial application prospect in the field of wood dyeing.

The Coordinated Development and Regulation Research on Public Health, Ecological Environment and Economic Development: Evidence from the Yellow River Basin of China

The dual problems of the public crisis from the global epidemic and the deterioration of the ecological environment constrain the economic development in the Yellow River Basin. To promote the sustainable and balanced development in the Yellow River Basin, this paper takes public health, ecological environment, and economic development, as a whole, to study the coordinated development of the Yellow River Basin. Based on coupling coordinated theory, we use the SMI-P method to evaluate the coordinated development index of public health, the ecological environment, and economic development in the Yellow River Basin. Moreover, we use the coordinated regulation and obstacle factor diagnosis to identify the main influencing factors and design regulation methods to optimize the coordinated development index. The results found that (1), during the research period, there is spatiotemporal heterogeneity in the coordinated development level in the Yellow River Basin. From 2009 to 2019, the overall development index increased steadily, while the regional disparity in the coordinated development level was obvious. (2) The ecological environment indicators contribute more to the relevance and obstacle factors, such as the average concentration of fine particulate matter, per capita arable land area, afforestation area, etc. (3) After regulating the overall development level of the Yellow River Basin, we prove that Path 4, which comprehensively considers the relevance and obstacle factors, performs better.

Optimization of Site Selection for Emergency Medical Facilities considering the SEIR Model

Since the outbreak of COVID-19, the rapid construction and operation of Wuhan Vulcan Mountain Hospital and Raytheon Hospital have attracted positive responses from local and international observers. At the same time, it has also highlighted the urgency for the construction of emergency medical facilities for public health emergencies. Before construction, the practical location of medical facilities is the basis for improving the city's emergency management ability. Based on the classic susceptible, exposed, infected, and recovered (SEIR) epidemic model and epidemic data in Guangzhou, we established a multi-stage time-delay SEIR epidemic model that is suitable for epidemic research in Guangzhou. According to the results of the model, the five areas with the highest number of infected patients were identified, which included Baiyun District, Panyu District, Haizhu District, Tianhe District, and Zengcheng District. We then centralized infected individuals at five demand points. Based on the distribution of these points and by combining the characteristics of the emergency medical facilities, we built and solved the set covering location decision model, and considered the economy, society, and environment as the starting points to optimize the site location. Finally, based on simulations, we concluded that appropriate site selection can increase the time required to reach the maximum number of patients and reduce the proportion of infected and exposed people by 11.3% and 1.11%, respectively. This is indicative of the effectiveness of the site selection model and the rational selection of facility points in this study. It solves the optimization problem of the location decision of emergency medical facilities for public health emergencies in China, and also provides some valuable references for site selection decisions of emergency medical facilities in other areas.

Cost-Effectiveness of Mobile Health-Based Integrated Care for Atrial Fibrillation: Model Development and Data Analysis

BACKGROUND

Mobile health (mHealth) technology is increasingly used in disease management. Using mHealth tools to integrate and streamline care has improved clinical outcomes of patients with atrial fibrillation (AF).

OBJECTIVE

The aim of this study was to investigate the potential clinical and health economic outcomes of mHealth-based integrated care for AF from the perspective of a public health care provider in China.

METHODS

A Markov model was designed to compare outcomes of mHealth-based care and usual care in a hypothetical cohort of patients with AF in China. The time horizon was 30 years with monthly cycles. Model outcomes measured were direct medical cost, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratio (ICER). Sensitivity analyses were performed to examine the robustness of the base-case results.

RESULTS

In the base-case analysis, mHealth-based care gained higher QALYs of 0.0730 with an incurred cost of US $1090. Using US $33,438 per QALY (three times the gross domestic product) as the willingness-to-pay threshold, mHealth-based care was cost-effective, with an ICER of US $14,936 per QALY. In one-way sensitivity analysis, no influential factor with a threshold value was identified. In probabilistic sensitivity analysis, mHealth-based care was accepted as cost-effective in 92.33% of 10,000 iterations.

CONCLUSIONS

This study assessed the expected cost-effectiveness of applying mHealth-based integrated care for AF according to a model-based health economic evaluation. The exploration suggested the potential cost-effective use of mHealth apps in streamlining and integrating care via the Atrial fibrillation Better Care (ABC) pathway for AF in China. Future economic evaluation alongside randomized clinical trials is highly warranted to verify the suggestion and investigate affecting factors such as geographical variations in patient characteristics, identification of subgroups, and constraints on local implementation.

A mathematical-adapted model to analyze the characteristics for the mortality of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, has led to the rapid development of Coronavirus disease 2019 (COVID-19) pandemic. COVID-19 represents a fatal disease with a great global public health importance. This study aims to develop a three-parameter Weibull mathematical model using continuous functions to represent discrete COVID-19 data. Subsequently, the model was applied to quantitatively analyze the characteristics for the mortality of COVID-19, including the age, sex, the length of symptom time to hospitalization time (SH), hospitalization date to death time (HD) and symptom time to death time time (SD) and others. A three-parameter mathematical model was developed by combining the reported cases in the Data Repository from the Center for Systems Science and Engineering at Johns Hopkins University and applied to estimate and analyze the characteristics for mortality of COVID-19. We found that the scale parameters of males and females were 5.85 and 5.45, respectively. Probability density functions in both males and females were negative skewness. 5% of male patients died under the age of 43.28 (44.37 for females), 50% died under 69.55 (73.25 for females), and 95% died under 86.59 (92.78 for females). The peak age of male death was 67.45 years, while that of female death was 71.10 years. The peak and median values of SH, HD and SD in male death were correspondingly 1.17, 5.18 and 10.30 days, and 4.29, 11.36 and 16.33 days, while those in female death were 1.19, 5.80 and 12.08 days, and 4.60, 12.44 and 17.67 days, respectively. The peak age of probability density in male and female deaths was 69.55 and 73.25 years, while the high point age of their mortality risk was 77.51 and 81.73 years, respectively. The mathematical model can fit and simulate the impact of various factors on IFR. From the simulation results of the model, we can intuitively find the IFR, peak age, average age and other information of each age. In terms of time factors, the mortality rate of the most susceptible population is not the highest, and the distribution of male patients is different from the distribution of females. This means that Self-protection and self-recovery in females against SARS-CoV-2 virus might be better than those of males. Males were more likely to be infected, more likely to be admitted to the ICU and more likely to die of COVID-19. Moreover, the infection fatality ration (IFR) of COVID-19 population was intrinsically linked to the infection age. Public health measures to protect vulnerable sex and age groups might be a simple and effective way to reduce IFR.

Impact of the COVID-19 pandemic on career intention amongst undergraduate medical students: a single-centre cross-sectional study conducted in Hubei Province

BACKGROUND

Undergraduate medical (UM) students faced the difficulties inherent in medical careers due to the coronavirus (COVID-19) outbreak. Thus, imperative containment measures might affect UM students' career intentions. Information on the factors that may be associated with these students' career change intentions is limited.

METHODS

We conducted a cross-sectional survey in August 2020 to investigate the impact of the COVID-19 pandemic on career intention and the associated factors in UM students. Univariate analyses and logistic regression analysis were performed to identify said factors.

RESULTS

A total of 2040 medical students from the Hubei University of Medicine were surveyed. Univariate analyses showed that grade, attitude towards healthcare, and the degree of the COVID-19 pandemic's impact on the students' lives were associated with changes in career choice (P<0.05). Logistic regression analysis showed that Grade 2, Grade 5, attitude towards a medical career, and having relatives with a medical background were associated with changes in career choice. The degree of the COVID-19 pandemic's impact was a common and significant factor associated with career preference, career perspective, and ideal workplace.

CONCLUSIONS

Changes in career intentions were particularly influenced by grade, attitude towards being a health worker, and the degree of COVID-19's impact on the participants' lives. Treating large-scale public health emergencies rationally, setting up correct views of occupation choice, and building reasonable career planning may reduce the loss of medical talent.

Workload of Healthcare Workers During the COVID-19 Outbreak in Korea: A Nationwide Survey

BACKGROUND

As the coronavirus disease 2019 (COVID-19) pandemic is ongoing, heavy workload of healthcare workers (HCWs) is a concern. This study investigated the workload of HCWs responding to the COVID-19 outbreak in South Korea.

METHODS

A nationwide cross-sectional survey was conducted from September 16 to October 15, 2020, involving 16 healthcare facilities (4 public medical centers, 12 tertiary-care hospitals) that provide treatment for COVID-19 patients.

RESULTS

Public medical centers provided the majority (69.4%) of total hospital beds for COVID-19 patients (n = 611), on the other hand, tertiary care hospitals provided the majority (78.9%) of critical care beds (n = 57). The number of beds per doctor (median [IQR]) in public medical centers was higher than in tertiary care hospitals (20.2 [13.0, 29.4] versus 3.0 [1.3, 6.6], P = 0.006). Infectious Diseases physicians are mostly (80%) involved among attending physicians. The number of nurses per patient (median [interquartile range, IQR]) in tertiary-care hospitals was higher than in public medical centers (4.6 [3.4-5] vs. 1.1 [0.8-2.1], P = 0.089). The median number of nurses per patient for COVID-19 patients was higher than the highest national standard in South Korea (3.8 vs. 2 for critical care). All participating healthcare facilities were also operating screening centers, for which a median of 2 doctors, 5 nurses, and 2 administrating staff were necessary.

CONCLUSION

As the severity of COVID-19 patients increases, the number of HCWs required increases. Because the workload of HCWs responding to the COVID-19 outbreak is much greater than other situations, a workforce management plan regarding this perspective is required to prevent burnout of HCWs.

The effects of super spreading events and movement control measures on the COVID-19 pandemic in Malaysia

This paper aims to develop an automated web application to generate validated daily effective reproduction numbers (Rt) which can be used to examine the effects of super-spreading events due to mass gatherings and the effectiveness of the various Movement Control Order (MCO) stringency levels on the outbreak progression of COVID-19 in Malaysia. The effective reproduction number, Rt, was estimated by adopting and modifying an Rt estimation algorithm using a validated distribution mean of 3.96 and standard deviation of 4.75 with a seven-day sliding window. The Rt values generated were validated using thea moving window SEIR model with a negative binomial likelihood fitted using methods from the Bayesian inferential framework. A Pearson’s correlation between the Rt values estimated by the algorithm and the SEIR model was r = 0.70, p < 0.001 and r = 0.81, p < 0.001 during the validation period The Rt increased to reach the highest values at 3.40 (95% CI 1.47, 6.14) and 1.72 (95% CI 1.54, 1.90) due to the Sri Petaling and Sabah electoral process during the second and third waves of COVID-19 respectively. The MCOs was able to reduce the Rt values by 63.2 to 77.1% and 37.0 to 47.0% during the second and third waves of COVID-19, respectively. Mass gathering events were one of the important drivers of the COVID-19 outbreak in Malaysia. However, COVID-19 transmission can be fuelled by noncompliance to Standard Operating Procedure, population mobility, ventilation and environmental factors.