Factors Influencing Adoption and Use of Telemedicine Services in Rural Areas of China: Mixed Methods Study.

BACKGROUND: The shortage of medical resources in rural China reflects the health inequity in resource-limited settings, whereas telemedicine could provide opportunities to fill this gap. However, evidence of patient acceptance of telemedicine services from low- and middle-income countries is still lacking. OBJECTIVE: We aimed to understand the profile of patient end-user telemedicine use and identify factors influencing telemedicine service use in rural China. METHODS: Our study followed a mixed methods approach, with a quantitative cross-sectional survey followed by in-depth semistructured interviews to describe telemedicine use and its associated factors among rural residents in Guangdong Province, China. In the quantitative analysis, explanatory variables included environmental and context factors, household-level factors, individual sociodemographic factors, access to digital health care, and health needs and demand factors. We conducted univariate and multivariate analyses using Firth logistic regression to examine the correlations of telemedicine uptake. A thematic approach was used, guided by the Social Cognitive Theory for the qualitative analysis. RESULTS: A total of 2101 households were recruited for the quantitative survey. With a mean age of 61.4 (SD 14.41) years, >70% (1364/2101, 72.94%) of the household respondents were male. Less than 1% (14/2101, 0.67%) of the respondents reported experience of using telemedicine. The quantitative results supported that villagers living with family members who had a fever in the past 2 weeks (adjusted odds ratio 6.96, 95% CI 2.20-21.98; P=.001) or having smartphones or computers (adjusted odds ratio 3.71, 95% CI 0.64-21.32; P=.14) had marginally higher telemedicine uptake, whereas the qualitative results endorse these findings. The results of qualitative interviews (n=27) also supplemented the potential barriers to telemedicine use from the lack of knowledge, trust, demand, low self-efficacy, and sufficient physical and social support. CONCLUSIONS: This study found extremely low use of telemedicine in rural China and identified potential factors affecting telemedicine uptake. The main barriers to telemedicine adoption among rural residents were found, including lack of knowledge, trust, demand as well as low self-efficacy, and insufficient physical and social support. Our study also suggests strategies to facilitate telemedicine engagement in low-resource settings: improving digital literacy and self-efficacy, building trust, and strengthening telemedicine infrastructure support.

Effectiveness of a pay-it-forward intervention compared with user-paid vaccination to improve influenza vaccine uptake and community engagement among children and older adults in China: a quasi-experimental pragmatic trial.

BACKGROUND: China has low seasonal influenza vaccination rates among priority populations. In this study, we aimed to evaluate a pay-it-forward strategy to increase influenza vaccine uptake in rural, suburban, and urban settings in China. METHODS: We performed a quasi-experimental pragmatic trial to examine the effectiveness of a pay-it-forward intervention (a free influenza vaccine and an opportunity to donate financially to support vaccination of other individuals) to increase influenza vaccine uptake compared with standard-of-care user-paid vaccination among children (aged between 6 months and 8 years) and older people (≥60 years) in China. Recruitment took place in the standard-of-care group until the expected sample size was reached and then in the pay-it-forward group in primary care clinics from a rural site (Yangshan), a suburban site (Zengcheng), and an urban site (Tianhe). Participants were introduced to the influenza vaccine by project staff using a pamphlet about influenza vaccination and were either asked to pay out-of-pocket at the standard market price (US$8·5-23·2; standard-of-care group) or to donate any amount anonymously (pay-it-forward group). Participants had to be eligible to receive an influenza vaccine and to have not received an influenza vaccine in the past year. The primary outcome was vaccine uptake. Secondary outcomes were vaccine confidence and costs (from the health-care provider perspective). Regression methods compared influenza vaccine uptake and vaccine confidence between the two groups. This trial is registered with ChiCTR, ChiCTR2000040048. FINDINGS: From Sept 21, 2020, to March 3, 2021, 300 enrolees were recruited from patients visiting three primary care clinics. 55 (37%) of 150 people in the standard-of-care group (40 [53%] of 75 children and 15 [20%] of 75 older adults) and 111 (74%) of 150 in the pay-it-forward group (66 [88%] of 75 children and 45 [60%] of 75 older adults) received an influenza vaccine. People in the pay-it-forward group were more likely to receive an influenza vaccine compared with those in the standard-of-care group (adjusted odds ratio [aOR] 6·7 [95% CI 2·7-16·6] among children and 5·0 [2·3-10·8] among older adults). People in the pay-it-forward group had greater confidence in vaccine safety (aOR 2·2 [95% CI 1·2-3·9]), importance (3·1 [1·6-5·9]), and effectiveness (3·1 [1·7-5·7]). In the pay-it-forward group, 107 (96%) of 111 participants donated money for subsequent vaccinations. The pay-it-forward group had a lower economic cost (calculated as the cost without subtraction of donations) per person vaccinated (US$45·60) than did the standard-of-care group ($64·67). INTERPRETATION: The pay-it-forward intervention seemed to be effective in improving influenza vaccine uptake and community engagement. Our data have implications for prosocial interventions to enhance influenza vaccine uptake in countries where influenza vaccines are available for a fee. FUNDING: Bill & Melinda Gates Foundation and the UK National Institute for Health Research.

Changes in blood pressure and related risk factors among nurses working in a negative pressure isolation ward

Objective To observe changes in blood pressure (ΔBP) and explore potential risk factors for high ΔBP among nurses working in a negative pressure isolation ward (NPIW). Methods Data from the single-center prospective observational study were used. Based on a routine practice plan, female nurses working in NPIW were scheduled to work for 4 days/week in different shifts, with each day working continuously for either 5 or 6 h. BP was measured when they entered and left NPIW. Multivariable logistic regression was used to assess potential risk factors in relation to ΔBP ≥ 5 mm Hg. Results A total of 84 nurses were included in the analysis. The ΔBP was found to fluctuate on different working days;no significant difference in ΔBP was observed between the schedules of 5 and 6 h/day. The standardized score from the self-rating anxiety scale (SAS) was significantly associated with an increased risk of ΔBP ≥ 5 mm Hg (odds ratio [OR] = 1.12, 95% CI: 1.00–1.24). Working 6 h/day (vs. 5 h/day) in NPIW was non-significantly related to decreased risk of ΔBP (OR = 0.70), while ≥ 2 consecutive working days (vs. 1 working day) was non-significantly associated with increased risk of ΔBP (OR = 1.50). Conclusion This study revealed no significant trend for ΔBP by working days or working time. Anxiety was found to be significantly associated with increased ΔBP, while no <2 consecutive working days were non-significantly related to ΔBP. These findings may provide some preliminary evidence for BP control in nurses who are working in NPIW for Coronavirus Disease 2019 (COVID-19).

Building the hospital intelligent twins for all-scenario intelligence health care.

The COVID-19 pandemic has accelerated a long-term trend of smart hospital development. However, there is no consistent conceptualization of what a smart hospital entails. Few hospitals have genuinely reached being "smart," primarily failing to bring systems together and consider implications from all perspectives. Hospital Intelligent Twins, a new technology integration powered by IoT, AI, cloud computing, and 5G application to create all-scenario intelligence for health care and hospital management. This communication presented a smart hospital for all-scenario intelligence by creating the hospital Intelligent Twins. Intelligent Twins is widely involved in medical activities. However, solving the medical ethics, protecting patient privacy, and reducing security risks involved are significant challenges for all-scenario intelligence applications. This exploration of creating hospital Intelligent Twins that can be a worthwhile endeavor to assess how to inform evidence-based decision-making better and enhance patient satisfaction and outcomes.

2019 Novel Coronavirus-Infected Pneumonia on CT: A Feasibility Study of Few-Shot Learning for Computerized Diagnosis of Emergency Diseases.

COVID-19 is an emerging disease with transmissibility and severity. So far, there are no effective therapeutic drugs or vaccines for COVID-19. The most serious complication of COVID-19 is a type of pneumonia called 2019 novel coronavirus-infected pneumonia (NCIP) with about 4.3% mortality rate. Comparing to chest Digital Radiography (DR), it is recently reported that chest Computed Tomography (CT) is more useful to serve as the early screening and diagnosis tool for NCIP. In this study, aimed to help physicians make the diagnostic decision, we develop a machine learning (ML) approach for automated diagnosis of NCIP on chest CT. Different from most ML approaches which often require training on thousands or millions of samples, we design a few-shot learning approach, in which we combine few-shot learning with weakly supervised model training, for computerized NCIP diagnosis. A total of 824 patients are retrospectively collected from two Hospitals with IRB approval. We first use 9 patients with clinically confirmed NCIP and 20 patients without known lung diseases for training a location detector which is a multitask deep convolutional neural network (DCNN) designed to output a probability of NCIP and the segmentation of targeted lesion area. An experienced radiologist manually localizes the potential locations of NCIPs on chest CTs of 9 COVID-19 patients and interactively segments the area of the NCIP lesions as the reference standard. Then, the multitask DCNN is furtherly fine-tuned by a weakly supervised learning scheme with 291 case-level labeled samples without lesion labels. A test set of 293 patients is independently collected for evaluation. With our NCIP-Net, the test AUC is 0.91. Our system has potential to serve as the NCIP screening and diagnosis tools for the fight of COVID-19's endemic and pandemic.

The Smart Safeguard System for COVID-19 to prevent cluster-infection in workplaces.

The ongoing Coronavirus Disease 2019 (COVID-19) broke out in China since December 2019, and rapidly spread worldwide. To contain the disease, unessential businesses had been shut down in several countries to a varying extent. Nowadays, the enterprises are resuming productions and businesses. While the resumption of production is crucial to social development, it elevates the risk of cluster-infections at the workplaces. Guangdong Second Provincial General Hospital therefore set up the Smart Safeguard System for COVID-19, aiming to provide rapid screening and consistent protection to assist the local enterprises with resumption. The system has received positive feedback as being helpful and practical. It has the potential to be widely used to prevent the cluster-infection of COVID-19 at workplaces during the pandemic.

Development and application of a new framework for infectious disease management at the early stage of new epidemics: Taking COVID-19 outbreak in China as an example.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) rapidly spread across worldwide, posing a significant challenge to public health. Several shortcomings in the existing infectious disease management system were exposed during the pandemic, which hindered the control of the disease globally. To cope with this issue, we propose a window-period framework to reveal the general rule of the progression of management of infectious diseases and to help with decision making at the early stage of epidemics with a focus on healthcare provisions. METHODS: The framework has two significant periods (dark-window period and bright-window period). Outbreak of COVID-19 in China was used as an example for the application of the framework. RESULTS: The framework could reflect the progression of the epidemic objectively. The spread increased slowly in the dark-window period, but rocketed up in the bright-window period. The beginning of the bright-window period was the time when healthcare personnel were exposed to a substantially high risk of nosocomial infection. Additionally, proper and prompt preventive actions during the dark-window and bright-window periods were substantially important to reduce the future spreading of the disease. CONCLUSIONS: It was recommended that when possible healthcare provisions should upgrade to the highest level of alert for the control of an unknown epidemic in the dark-window period, while countermeasures in the bright-window period could be accordingly adjusted with full exploration and considerations. The framework may provide some insights into how to accelerate the control of future epidemics promptly and effectively.

Correlation between CT findings and outcomes in 46 patients with coronavirus disease 2019.

The aim of this study was to analyze initial chest computed tomography (CT) findings in COVID-19 pneumonia and identify features associated with poor prognosis. Patients with RT-PCR-confirmed COVID-19 infection were assigned to recovery group if they made a full recovery and to death group if they died within 2 months of hospitalization. Chest CT examinations for ground-glass opacity, crazy-paving pattern, consolidation, and fibrosis were scored by two reviewers. The total CT score comprised the sum of lung involvement (5 lobes, scores 1-5 for each lobe, range; 0, none; 25, maximum). 40 patients who recovered from COVID-19 and six patients who died were enrolled. The initial chest CTs showed 27 (58.7%) patients had ground-glass opacity, 19 (41.3%) had ground glass and consolidation, and 35 (76.1%) patients had crazy-paving pattern. None of the patients who died had fibrosis in contrast to six (15%) patients who recovered from COVID-19. Most patients had subpleural lesions (89.0%) as well as bilateral (87.0%) and lower (93.0%) lung lobe involvement. Diffuse lesions were present in four (67%) patients who succumbed to coronavirus but only one (2.5%) patient who recovered (p < 0.001). In the death group of patients, the total CT score was higher than that of the recovery group (p = 0.005). Patients in the death group had lower lymphocyte count and higher C-reactive protein than those in the recovery group (p = 0.011 and p = 0.041, respectively). A high CT score and diffuse distribution of lung lesions in COVID-19 are indicative of disease severity and short-term mortality.

The kinetics of viral load and antibodies to SARS-CoV-2.

OBJECTIVES: The aim was to understand persistence of the virus in body fluids the and immune response of an infected host to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), an agent of coronavirus disease 2019 (COVID-19). METHODS: We determined the kinetics of viral load in several body fluids through real time reverse transcription polymerase chain reaction, serum antibodies of IgA, IgG and IgM by enzyme-linked immunosorbent assay and neutralizing antibodies by microneutralization assay in 35 COVID-19 cases from two hospitals in Guangdong, China. RESULTS: We found higher viral loads and prolonged shedding of virus RNA in severe cases of COVID-19 in nasopharyngeal (1.3 × 106 vs 6.4 × 104, p < 0.05; 7∼8 weeks) and throat (6.9 × 106 vs 2.9 × 105, p < 0.05; 4∼5 weeks), but similar in sputum samples (5.5 × 106 vs 0.9 × 106, p < 0.05; 4∼5 weeks). Viraemia was rarely detected (2.8%, n = 1/35). We detected early seroconversion of IgA and IgG at the first week after illness onset (day 5, 5.7%, n = 2/35). Neutralizing antibodies were produced in the second week, and observed in all 35 included cases after the third week illness onset. The levels of neutralizing antibodies correlated with IgG (rs = 0.85, p < 0.05; kappa = 0.85) and IgA (rs = 0.64, p < 0.05; kappa = 0.61) in severe, but not mild cases (IgG, rs = 0.42, kappa = 0.33; IgA, rs = 0.32, kappa = 0.22). No correlation with IgM in either severe (rs = 0.17, kappa = 0.06) or mild cases (rs = 0.27, kappa = 0.15) was found. DISCUSSION: We revealed a prolonged shedding of virus RNA in the upper respiratory tract, and evaluated the consistency of production of IgG, IgA, IgM and neutralizing antibodies in COVID-19 cases.

Digital Health Technologies Respond to the COVID-19 Pandemic In a Tertiary Hospital in China: Development and Usability Study.

BACKGROUND: The outbreak of COVID-19 has caused a continuing global pandemic. Hospitals are integral to the control and prevention of COVID-19; however, they are facing numerous challenges during the epidemic. OBJECTIVE: Our study aimed to introduce the practical experience of the design and implementation of a web-based COVID-19 service platform at a tertiary hospital in China as well as the preliminary results of the implementation. METHODS: The web-based COVID-19 service platform was deployed within the health care system of the Guangdong Second Provincial General Hospital and Internet Hospital; the function of the platform was to provide web-based medical services for both members of the public and lay health care workers. The focal functions of this system included automated COVID-19 screening, related symptom monitoring, web-based consultation, and psychological support; it also served as a COVID-19 knowledge hub. The design and process of each function are introduced. The usage data for the platform service were collected and are represented by three periods: the pre-epidemic period (December 22, 2019, to January 22, 2020, 32 days), the controlled period (January 23 to March 31, 2020, 69 days), and the postepidemic period (April 1 to June 30, 2020, 91 days). RESULTS: By the end of June 2020, 96,642 people had used the automated COVID-19 screening and symptom monitoring systems 161,884 and 7,795,194 times, respectively. The number of general web-based consultation services per day increased from 30 visits in the pre-epidemic period to 122 visits during the controlled period, then dropped to 73 visits in the postepidemic period. The psychological counseling program served 636 clients during the epidemic period. For people who used the automated COVID-19 screening service, 160,916 (99.40%) of the total users were classified in the no risk category. 464 (0.29%) of the people were categorized as medium to high risk, and 12 people (0.01%) were recommended for further COVID-19 testing and treatment. Among the 96,642 individuals who used the COVID-19 related symptoms monitoring service, 6696 (6.93%) were symptomatic at some point during the monitoring period. Fever was the most frequently reported symptom, with 2684/6696 symptomatic people (40.1%) having had this symptom. Cough and sore throat were also relatively frequently reported by the 6696 symptomatic users (1657 people, 24.7%, and 1622 people, 24.2%, respectively). CONCLUSIONS: The web-based COVID-19 service platform implemented at a tertiary hospital in China is exhibited to be a role model for using digital health technologies to respond to the COVID-19 pandemic. The digital solutions of automated COVID-19 screening, daily symptom monitoring, web-based care, and knowledge propagation have plausible acceptability and feasibility for complementing offline hospital services and facilitating disease control and prevention.

Prolonged Persistence of SARS-CoV-2 RNA in Body Fluids.

We prospectively assessed 49 coronavirus disease cases in Guangdong, China, to estimate the frequency and duration of detectable severe acute respiratory syndrome coronavirus 2 RNA in human body fluids. The prolonged persistence of virus RNA in various body fluids may guide the clinical diagnosis and prevention of onward virus transmission.

Challenges of SARS-CoV-2 and lessons learnt from SARS in Guangdong Province, China.

With lessons learnt from the SARS outbreak in 2003, Guangdong Province is taking the lead in bringing COVID-19 under control by multiple strict regulations in combination with effective healthcare provision.