A real-world data validation of the value of early-stage SIR modelling to public health.

Performance of Susceptible-Infected-Recovered (SIR) model in the early stage of a novel epidemic may be hindered by data availability. Additionally, the traditional SIR model may oversimplify the disease progress, and knowledge about the virus and transmission is limited early in the epidemic, resulting in a greater uncertainty of such modelling. We aimed to investigate the impact of model inputs on the early-stage SIR projection using COVID-19 as an illustration to evaluate the application of early infection models. We constructed a modified SIR model using discrete-time Markov chain to simulate daily epidemic dynamics and estimate the number of beds needed in Wuhan in the early stage of COVID-19 epidemic. We compared eight scenarios of SIR projection to the real-world data (RWD) and used root mean square error (RMSE) to assess model performance. According to the National Health Commission, the number of beds occupied in isolation wards and ICUs due to COVID-19 in Wuhan peaked at 37,746. In our model, as the epidemic developed, we observed an increasing daily new case rate, and decreasing daily removal rate and ICU rate. This change in rates contributed to the growth in the needs of bed in both isolation wards and ICUs. Assuming a 50% diagnosis rate and 70% public health efficacy, the model based on parameters estimated using data from the day reaching 3200 to the day reaching 6400 cases returned a lowest RMSE. This model predicted 22,613 beds needed in isolation ward and ICU as on the day of RWD peak. Very early SIR model predictions based on early cumulative case data initially underestimated the number of beds needed, but the RMSEs tended to decline as more updated data were used. Very-early-stage SIR model, although simple but convenient and relatively accurate, is a useful tool to provide decisive information for the public health system and predict the trend of an epidemic of novel infectious disease in the very early stage, thus, avoiding the issue of delay-decision and extra deaths.

Understanding influencing attributes of COVID-19 vaccine preference and willingness-to-pay among Chinese and American middle-aged and elderly adults: A discrete choice experiment and propensity score matching study.

Background and objective: COVID-19 has imposed burdens on public health systems globally. Owing to the urgency of vaccination, this study aimed at comparing the differences in preference and willingness to pay of COVID-19 vaccine among Chinese and American middle-aged and elderly adults. Methods: A cross-sectional survey containing demographic questions, rating their acceptance of COVID-19 vaccination with and without recommendations from friends, family members or employers (the social cues referred to in our study), and a discrete choice experiment understanding COVID-19 vaccine preference and willingness to pay was conducted to collect data. Propensity score matching was utilized to adjust confounding factors of baseline characteristics and the relative importance of respondents' preference for each attribute and its level was estimated using a conditional logit model. Then, willingness to pay was calculated. Results: In total, 3,494 (2,311 and 1,183 from China and the United States, respectively) completed the questionnaire, among which 3,444 questionnaires were effective. After propensity score matching, 1,604 respondents with 802 from the US and 802 from China were included. Under the influence of the social cues, Chinese respondents' vaccine acceptance decreased from 71.70 to 70.70%, while American respondents' vaccine acceptance increased from 74.69 to 75.81%. The discrete choice experiment showed that American respondents regarded the efficacy of COVID-19 vaccine as the most important attribute, whereas Chinese respondents attached the highest importance to the cost of vaccination. But overall, the COVID-19 vaccine with the higher efficacy, the milder adverse effect, the lower cost, and the longer duration will promote the preference of the public in both countries. Additionally, the public were willing to spend the most money for a reduction in COVID-19 vaccine adverse effect from moderate to very mild (37.476USD for the United States, 140.503USD for China), followed by paying for the 1% improvement in its efficacy and paying for the one-month extension of its duration. Conclusion: Given the impact of social cues on vaccine acceptance, Chinese government should promote reasonable vaccine-related information to improve national vaccination acceptance. Meanwhile, considering the influence of COVID-19 attributes on public preference and willingness to pay, regulating the vaccine pricing, improving the efficacy of the vaccine, reducing its adverse effect, and prolonging the duration of the vaccine works will contribute to vaccine uptake.

COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures.

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

Megastudies: A New Approach to Reducing Vaccine Hesitation Worldwide.

Vaccine hesitancy is a considerable obstacle to achieving vaccine protection worldwide. There needs to be more evidence-based research for interventions for vaccine hesitancy. Existing effectiveness evaluations are limited to one particular hypothesis, and no studies have compared the effectiveness of different interventions. A megastudy takes a large-scale, multi-intervention, uniform participant and the same evaluation criteria approach to evaluate many interventions simultaneously and find the most effective ones. Therefore, megastudies can help us find the most effective interventions for vaccine hesitancy. Additionally, considering the complex causes of vaccine hesitancy, we design interventions that involve social factors in megastudies. Lastly, quality control and justice are critical issues for megastudies in the future.

Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries.

BACKGROUND: Due to the COVID-19 pandemic, health information related to COVID-19 has spread across news media worldwide. Google is among the most used internet search engines, and the Google Trends tool can reflect how the public seeks COVID-19-related health information during the pandemic. OBJECTIVE: The aim of this study was to understand health communication through Google Trends and news coverage and to explore their relationship with prevention and control of COVID-19 at the early epidemic stage. METHODS: To achieve the study objectives, we analyzed the public's information-seeking behaviors on Google and news media coverage on COVID-19. We collected data on COVID-19 news coverage and Google search queries from eight countries (ie, the United States, the United Kingdom, Canada, Singapore, Ireland, Australia, South Africa, and New Zealand) between January 1 and April 29, 2020. We depicted the characteristics of the COVID-19 news coverage trends over time, as well as the search query trends for the topics of COVID-19-related "diseases," "treatments and medical resources," "symptoms and signs," and "public measures." The search query trends provided the relative search volume (RSV) as an indicator to represent the popularity of a specific search term in a specific geographic area over time. Also, time-lag correlation analysis was used to further explore the relationship between search terms trends and the number of new daily cases, as well as the relationship between search terms trends and news coverage. RESULTS: Across all search trends in eight countries, almost all search peaks appeared between March and April 2020, and declined in April 2020. Regarding COVID-19-related "diseases," in most countries, the RSV of the term "coronavirus" increased earlier than that of "covid-19"; however, around April 2020, the search volume of the term "covid-19" surpassed that of "coronavirus." Regarding the topic "treatments and medical resources," the most and least searched terms were "mask" and "ventilator," respectively. Regarding the topic "symptoms and signs," "fever" and "cough" were the most searched terms. The RSV for the term "lockdown" was significantly higher than that for "social distancing" under the topic "public health measures." In addition, when combining search trends with news coverage, there were three main patterns: (1) the pattern for Singapore, (2) the pattern for the United States, and (3) the pattern for the other countries. In the time-lag correlation analysis between the RSV for the topic "treatments and medical resources" and the number of new daily cases, the RSV for all countries except Singapore was positively correlated with new daily cases, with a maximum correlation of 0.8 for the United States. In addition, in the time-lag correlation analysis between the overall RSV for the topic "diseases" and the number of daily news items, the overall RSV was positively correlated with the number of daily news items, the maximum correlation coefficient was more than 0.8, and the search behavior occurred 0 to 17 days earlier than the news coverage. CONCLUSIONS: Our findings revealed public interest in masks, disease control, and public measures, and revealed the potential value of Google Trends in the face of the emergence of new infectious diseases. Also, Google Trends combined with news media can achieve more efficient health communication. Therefore, both news media and Google Trends can contribute to the early prevention and control of epidemics.

Disparities in the unmet mental health needs between LGBTQ+ and non-LGBTQ+ populations during COVID-19 in the United States from 21 July 2021 to 9 May 2022.

Background: Evidence highlighted the likelihood of unmet mental health needs (UMHNs) among LGBTQ+ than non-LGBTQ+ populations during COVID-19. However, there lacks evidence to accurately answer to what extent the gap was in UMHN between LGBTQ+ and non-LGBTQ+ populations. We aim to evaluate the difference in UMHN between LGBTQ+ and non-LGBTQ+ during COVID-19. Methods: Cross-sectional data from Household Pulse Survey between 21 July 2021 and 9 May 2022 were analyzed. LGBTQ+ was defined based on self-reported sex at birth, gender, and sexual orientation identity. UMHN was assessed by a self-reported question. Multivariable logistic regressions generated adjusted odds ratios (AODs) of UMHN, both on overall and subgroups, controlling for a variety of socio-demographic and economic-affordability confounders. Findings: 81267 LGBTQ+ and 722638 non-LGBTQ+ were studied. The difference in UMHN between LGBTQ+ and non-LGBTQ+ (as reference) varied from 4.9% (95% CI 1.2-8.7%) in Hawaii to 16.0% (95% CI 12.2-19.7%) in Utah. In multivariable models, compared with non-LGBTQ+ populations, LGBTQ+ had a higher likelihood to report UMHN (AOR = 2.27, 95% CI 2.18-2.39), with the highest likelihood identified in transgender (AOR = 3.63, 95% CI 2.97-4.39); compared with LGBTQ+ aged 65+, LGBTQ+ aged 18-25 had a higher likelihood to report UMHN (AOR = 1.34, 95% CI 1.03-1.75); compared with White LGBTQ+ populations, Black and Hispanic LGBTQ+ had a lower likelihood to report UMHN (AOR = 0.72, 95% CI 0.63-0.82; AOR = 0.85, 95% CI 0.75-0.97, respectively). Interpretation: During the COVID-19, LGBTQ+ had a substantial additional risk of UMHN than non-LGBTQ+. Disparities among age groups, subtypes of LGBTQ+, and geographic variance were also identified.

Preferences for Attributes of Initial COVID-19 Diagnosis in the United States and China During the Pandemic: Discrete Choice Experiment With Propensity Score Matching.

BACKGROUND: China and the United States play critical leading roles in the global effort to contain the COVID-19 virus. Therefore, their population's preferences for initial diagnosis were compared to provide policy and clinical insights. OBJECTIVE: We aim to quantify and compare the public's preferences for medical management of fever and the attributes of initial diagnosis in the case of presenting symptoms during the COVID-19 pandemic in China and the United States. METHODS: We conducted a cross-sectional study from January to March 2021 in China and the United States using an online discrete choice experiment (DCE) questionnaire distributed through Amazon Mechanical Turk (MTurk; in the United States) and recruited volunteers (in China). Propensity score matching (PSM) was used to match the 2 groups of respondents from China and the United States to minimize confounding effects. In addition, the respondents' preferences for different diagnosis options were evaluated using a mixed logit model (MXL) and latent class models (LCMs). Moreover, demographic data were collected and compared using the chi-square test, Fisher test, and Mann-Whitney U test. RESULTS: A total of 9112 respondents (5411, 59.4%, from China and 3701, 40.6%, from the United States) who completed our survey were included in our analysis. After PSM, 1240 (22.9%) respondents from China and 1240 (33.5%) from the United States were matched for sex, age, educational level, occupation, and annual salary levels. The segmented sizes of 3 classes of respondents from China were 870 (70.2%), 270 (21.8%), and 100 (8.0%), respectively. Meanwhile, the US respondents' segmented sizes were 269 (21.7%), 139 (11.2%), and 832 (67.1%), respectively. Respondents from China attached the greatest importance to the type of medical institution (weighted importance=40.0%), while those from the United States valued the waiting time (weighted importance=31.5%) the most. Respondents from China preferred the emergency department (coefficient=0.973, reference level: online consultation) and fever clinic (a special clinic for the treatment of fever patients for the prevention and control of acute infectious diseases in China; coefficient=0.974, reference level: online consultation), while those from the United States preferred private clinics (general practices; coefficient=0.543, reference level: online consultation). Additionally, shorter waiting times, COVID-19 nucleic acid testing arrangements, higher reimbursement rates, and lower costs were always preferred. CONCLUSIONS: Improvements in the availability of COVID-19 testing and medical professional skills and increased designated health care facilities may help boost potential health care seeking during COVID-19 and prevent unrecognized community spreading of SARS-CoV-2 in China and the United States. Moreover, to better prevent future waves of pandemics, identify undiagnosed patients, and encourage those undiagnosed to seek health care services to curb the pandemic, the hierarchical diagnosis and treatment system needs improvement in China, and the United States should focus on reducing diagnosis costs and raising the reimbursement rate of medical insurance.

The Construct Structures of Psychological and Behavioral Responses to COVID-19 Pandemic in Pregnant Women

Aim The present study aimed to investigate the construct structure behind the psychosocial response, behavioral response, prenatal depression, and post-traumatic stress disorder (PTSD) in pregnant women during the COVID-19 pandemic in China. Method The validated Chinese version of the Edinburgh Postnatal Depression Scale (EPDS), PTSD CheckList (PCL)-6, and two newly established scales for COVID-19-related psychological and behavioral responses were used. Structural equation modeling (SEM) analysis was applied to evaluate the structural relationships of psychological and behavioral responses during the COVID-19 pandemic. Results Of the 1,908 mothers who completed the questionnaires, 1,099 met the criteria for perinatal depression, and 287 were positively screened for PTSD, where 264 women exceed the cut-off points for both. Pregnant women with full-time or part-time jobs tended to have the lowest scores of EPDS (10.07 ± 5.11, P < 0.001) and stress levels (23.85 ± 7.96, P = 0.004), yet they were more likely to change their behavior in accordance with the COVID-19 outbreak (13.35 ± 3.42, P = 0.025). The structural model fit the data (χ2 = 43.260, p < 0.001) and resulted in satisfactory fit indices (CFI = 0.984, TLI = 0.959, RMSEA = 0.072, and χ2/df = 10.815), all path loadings were significant (p < 0.05). The SEM indicates that the level of QoL was attributable to the occurrence of PND, leading to PTSD, and COVID-19 related behavioral and psychological responses. Conclusion The inter-relationships between the COVID-19-related psychosocial and behavioral responses have been assessed, indicating that the pandemic increased the burden of perinatal depression. Psychoeducation, as well as other psychological interventions, may be needed to alleviate the COVID-19-based anxiety and increase their engagement in protective behaviors.

Acceptance of and Preference for COVID-19 Vaccination in India, the United Kingdom, Germany, Italy, and Spain: An International Cross-Sectional Study.

Objective: India and Europe have large populations, a large number of Coronavirus disease 2019 (COVID-19) cases, and different healthcare systems. This study aims to investigate the differences between the hesitancy toward and preference for COVID-19 vaccines in India and four European countries, namely, the United Kingdom (UK), Germany, Italy, and Spain. Methodology: We conducted a cross-national survey for distribution in India, the UK, Germany, Italy, and Spain. More specifically, a discrete choice experiment (DCE) was conducted to evaluate vaccine preferences, and Likert scales were used to probe the underlying factors that contribute to vaccination acceptance. Propensity score matching (PSM) was performed to directly compare India and European countries. Results: A total of 2565 respondents (835 from India and 1730 from the specified countries in Europe) participated in the survey. After PSM, more than 82.5% of respondents from India positively accepted the COVID-19 vaccination, whereas 79.9% of respondents from Europe had a positive attitude; however, the proportion in Europe changed to 81.6% in cases in which the vaccine was recommended by friends, family, or employers. The DCE found that the COVID-19 vaccine efficacy was the most important factor for respondents in India and the four European nations (41.8% in India and 47.77% in Europe), followed by the vaccine cost (28.06% in India and 25.88% in Europe). Conclusion: Although most respondents in both regions showed high acceptance of COVID-19 vaccines, either due to general acceptance or acceptance as a result of social cues, the vaccination coverage rate shows apparent distinctions. Due to the differences in COVID-19 situations, public health systems, cultural backgrounds, and vaccine availability, the strategies for COVID-19 vaccine promotion should be nation-dependent.

Acceptance of and Preference for COVID-19 Vaccination in India, the United Kingdom, Germany, Italy, and Spain: An International Cross-Sectional Study

Objective: India and Europe have large populations, a large number of Coronavirus disease 2019 (COVID-19) cases, and different healthcare systems. This study aims to investigate the differences between the hesitancy toward and preference for COVID-19 vaccines in India and four European countries, namely, the United Kingdom (UK), Germany, Italy, and Spain. Methodology: We conducted a cross-national survey for distribution in India, the UK, Germany, Italy, and Spain. More specifically, a discrete choice experiment (DCE) was conducted to evaluate vaccine preferences, and Likert scales were used to probe the underlying factors that contribute to vaccination acceptance. Propensity score matching (PSM) was performed to directly compare India and European countries. Results: A total of 2565 respondents (835 from India and 1730 from the specified countries in Europe) participated in the survey. After PSM, more than 82.5% of respondents from India positively accepted the COVID-19 vaccination, whereas 79.9% of respondents from Europe had a positive attitude;however, the proportion in Europe changed to 81.6% in cases in which the vaccine was recommended by friends, family, or employers. The DCE found that the COVID-19 vaccine efficacy was the most important factor for respondents in India and the four European nations (41.8% in India and 47.77% in Europe), followed by the vaccine cost (28.06% in India and 25.88% in Europe). Conclusion: Although most respondents in both regions showed high acceptance of COVID-19 vaccines, either due to general acceptance or acceptance as a result of social cues, the vaccination coverage rate shows apparent distinctions. Due to the differences in COVID-19 situations, public health systems, cultural backgrounds, and vaccine availability, the strategies for COVID-19 vaccine promotion should be nation-dependent.

Patients' Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice Experiment.

BACKGROUND: Misdiagnosis, arbitrary charges, annoying queues, and clinic waiting times among others are long-standing phenomena in the medical industry across the world. These factors can contribute to patient anxiety about misdiagnosis by clinicians. However, with the increasing growth in use of big data in biomedical and health care communities, the performance of artificial intelligence (Al) techniques of diagnosis is improving and can help avoid medical practice errors, including under the current circumstance of COVID-19. OBJECTIVE: This study aims to visualize and measure patients' heterogeneous preferences from various angles of AI diagnosis versus clinicians in the context of the COVID-19 epidemic in China. We also aim to illustrate the different decision-making factors of the latent class of a discrete choice experiment (DCE) and prospects for the application of AI techniques in judgment and management during the pandemic of SARS-CoV-2 and in the future. METHODS: A DCE approach was the main analysis method applied in this paper. Attributes from different dimensions were hypothesized: diagnostic method, outpatient waiting time, diagnosis time, accuracy, follow-up after diagnosis, and diagnostic expense. After that, a questionnaire is formed. With collected data from the DCE questionnaire, we apply Sawtooth software to construct a generalized multinomial logit (GMNL) model, mixed logit model, and latent class model with the data sets. Moreover, we calculate the variables' coefficients, standard error, P value, and odds ratio (OR) and form a utility report to present the importance and weighted percentage of attributes. RESULTS: A total of 55.8% of the respondents (428 out of 767) opted for AI diagnosis regardless of the description of the clinicians. In the GMNL model, we found that people prefer the 100% accuracy level the most (OR 4.548, 95% CI 4.048-5.110, P<.001). For the latent class model, the most acceptable model consists of 3 latent classes of respondents. The attributes with the most substantial effects and highest percentage weights are the accuracy (39.29% in general) and expense of diagnosis (21.69% in general), especially the preferences for the diagnosis "accuracy" attribute, which is constant across classes. For class 1 and class 3, people prefer the AI + clinicians method (class 1: OR 1.247, 95% CI 1.036-1.463, P<.001; class 3: OR 1.958, 95% CI 1.769-2.167, P<.001). For class 2, people prefer the AI method (OR 1.546, 95% CI 0.883-2.707, P=.37). The OR of levels of attributes increases with the increase of accuracy across all classes. CONCLUSIONS: Latent class analysis was prominent and useful in quantifying preferences for attributes of diagnosis choice. People's preferences for the "accuracy" and "diagnostic expenses" attributes are palpable. AI will have a potential market. However, accuracy and diagnosis expenses need to be taken into consideration.

The Impact of Public Health Events on COVID-19 Vaccine Hesitancy on Chinese Social Media: National Infoveillance Study.

BACKGROUND: The ongoing COVID-19 pandemic has brought unprecedented challenges to every country worldwide. A call for global vaccination for COVID-19 plays a pivotal role in the fight against this virus. With the development of COVID-19 vaccines, public willingness to get vaccinated has become an important public health concern, considering the vaccine hesitancy observed worldwide. Social media is powerful in monitoring public attitudes and assess the dissemination, which would provide valuable information for policy makers. OBJECTIVE: This study aimed to investigate the responses of vaccine positivity on social media when major public events (major outbreaks) or major adverse events related to vaccination (COVID-19 or other similar vaccines) were reported. METHODS: A total of 340,783 vaccine-related posts were captured with the poster's information on Weibo, the largest social platform in China. After data cleaning, 156,223 posts were included in the subsequent analysis. Using pandas and SnowNLP Python libraries, posts were classified into 2 categories, positive and negative. After model training and sentiment analysis, the proportion of positive posts was computed to measure the public positivity toward the COVID-19 vaccine. RESULTS: The positivity toward COVID-19 vaccines in China tends to fluctuate over time in the range of 45.7% to 77.0% and is intuitively correlated with public health events. In terms of gender, males were more positive (70.0% of the time) than females. In terms of region, when regional epidemics arose, not only the region with the epidemic and surrounding regions but also the whole country showed more positive attitudes to varying degrees. When the epidemic subsided temporarily, positivity decreased with varying degrees in each region. CONCLUSIONS: In China, public positivity toward COVID-19 vaccines fluctuates over time and a regional epidemic or news on social media may cause significant variations in willingness to accept a vaccine. Furthermore, public attitudes toward COVID-19 vaccination vary from gender and region. It is crucial for policy makers to adjust their policies through the use of positive incentives with prompt responses to pandemic-related news to promote vaccination acceptance.

A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States.

OBJECTIVES: To investigate the differences in vaccine hesitancy and preference of the currently available COVID-19 vaccines between two countries, namely, China and the United States (U.S.). METHOD: A cross-national survey was conducted in both China and the United States, and discrete choice experiments, as well as Likert scales, were utilized to assess vaccine preference and the underlying factors contributing to vaccination acceptance. Propensity score matching (PSM) was performed to enable a direct comparison between the two countries. RESULTS: A total of 9077 (5375 and 3702 from China and the United States, respectively) respondents completed the survey. After propensity score matching, over 82.0% of respondents from China positively accepted the COVID-19 vaccination, while 72.2% of respondents from the United States positively accepted it. Specifically, only 31.9% of Chinese respondents were recommended by a doctor to have COVID-19 vaccination, while more than half of the U.S. respondents were recommended by a doctor (50.2%), local health board (59.4%), or friends and families (64.8%). The discrete choice experiments revealed that respondents from the United States attached the greatest importance to the efficacy of COVID-19 vaccines (44.41%), followed by the cost of vaccination (29.57%), whereas those from China held a different viewpoint, that the cost of vaccination covered the largest proportion in their trade-off (30.66%), and efficacy ranked as the second most important attribute (26.34%). Additionally, respondents from China tended to be much more concerned about the adverse effect of vaccination (19.68% vs. 6.12%) and have a lower perceived severity of being infected with COVID-19. CONCLUSION: Although the overall acceptance and hesitancy of COVID-19 vaccination in both countries are high, underpinned distinctions between these countries were observed. Owing to the differences in COVID-19 incidence rates, cultural backgrounds, and the availability of specific COVID-19 vaccines in the two countries, vaccine rollout strategies should be nation-dependent.

Factors Influencing Mental Health Among Chinese Medical and Non-medical Students in the Early Stage of the COVID-19 Pandemic.

Background: The 2019 coronavirus disease (COVID-19) pandemic is a public health emergency of international concern. This study aimed to assess the psychological outcomes and their influencing factors among medical and non-medical University students during the COVID-19 pandemic in China. Methods: A cross-sectional online survey using structured questionnaires was conducted from February 20 to March 20, 2020. Psychological outcomes were assessed according to the Depression, Anxiety, and Stress Scale (DASS-21). Influencing factors were assessed by COVID-19 knowledge, mindful coping scale, and sense of control scale. Results: Our sample is comprised of 563 University students (male = 172, mean age = 21.52). Among them, 382 are medical students. Among the participants, 12.26, 18.47, and 8.53% have moderate to severe levels of depression, anxiety, and stress symptoms, respectively. Compared with the non-medical students, the medical students had a higher knowledge level of COVID-19, a higher sense of awareness, and fewer mental health symptoms. After controlling the covariance, perceived constraints of sense of control were negatively associated with depression, anxiety, and stress among both medical and non-medical students. Prevention of negative emotions by mindful coping was negatively associated with depression and anxiety among non-medical students. Knowledge of COVID-19 is not associated with mental distress among medical and non-medical students. Conclusions: During the COVID-19 pandemic in China, the mental health of University students was affected. Our findings suggested that a sense of control is a protective factor for both medical and non-medical students, while mindful coping is a protective factor for only non-medical students.

Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study.

BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences for AI clinicians and traditional clinicians are worth exploring. OBJECTIVE: We aimed to quantify and compare people's preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people's preferences were affected by the pressure of pandemic. METHODS: We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people's preferences for different diagnosis methods. RESULTS: In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. CONCLUSIONS: Individuals' preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis.

BACKGROUND: The influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated. OBJECTIVE: This study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities. METHODS: Pearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. RESULTS: The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, P<.001), Shanghai (r=-0.47, P<.001), and Guangzhou (r=-0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model. CONCLUSIONS: The findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

Psychobehavioral Responses, Post-Traumatic Stress and Depression in Pregnancy During the Early Phase of COVID-19 Outbreak.

Objective: The novel coronavirus disease (COVID-19) outbreak has aroused a range of negative effects. Such considerable influence can be greater in vulnerable populations including pregnant women. This study aimed to assess the presence of prenatal depression (PND, as an important risk factor of postpartum depression) and post-traumatic stress disorder (PTSD) and to characterize infection-induced preventive behaviors and psychological responses in the early phase of COVID-19 outbreak. Methods: Based on a population-based sample of pregnant women from all regions in China, presence of probable PND and suspected PTSD were assessed using the Edinburgh Postnatal Depression Scale (≥13) and the PTSD Checklist (≥14), respectively. A web-based questionnaire was used to assess psychological and behavioral responses to COVID-19. Results: Among a total of 1908 questionnaires returned, 1901 women provided valid data (mean [SD] age, 28.9 [4.7] years). High prevalence of probable PND (34%) and suspected PTSD (40%) among pregnant women was observed. Those with suspected PTSD presented six times higher risk of probable PND than the non-suspected (OR=7.83, 95% CI: 6.29-9.75; p<0.001). Most women (91%-96%) reported anxiousness about infection of themselves and the members within their social network. Lack of security and loss of freedom were reported in approximately two-thirds of pregnant women. More frequent preventive behaviors, including handwashing, use of facemasks, and staying at home, were undertaken in more than 80% of the sample. Anxiousness of miscarriage and preterm birth were prevalent (>75%). Conclusions: High prevalence of PND and PTSD and high levels of anxiety suggest profound impacts of the present outbreak on mental health. This calls for special attention and support for vulnerable populations. Mental health care should become part of public health measures during the present outbreak and should continue to be intensified to empower the health system for post-outbreak periods.

Perceived Effectiveness, Safety, and Attitudes Toward the Use of Nucleic Tests of SARS-CoV-2 Among Clinicians and General Public in China.

Objective: To assess whether there is a knowledge gap about the use of test kits for residents and to explore the knowledge, attitudes, and practices of using test kits in China during the coronavirus disease 2019 (COVID-19) epidemic. Method: An online-based, nationwide, and cross-sectional study was conducted. A total of 1,167 respondents were recruited from June 19 to July 2, 2020. All participants completed a validated questionnaire written in Chinese. Electronic consent was obtained from all participants upon their agreement to commence the questionnaire. Perceived efficacy, safety, and their attitudes toward the use of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing kits were measured. Result: The majority of the study respondents were female [749 (64.2%)], aged 31-40 years old [372 (31.9%)], and located in mainland China [1,137 (97.4%)]. The majority of the respondents held a positive view toward the introduction of the fast-track approval policy for novel coronavirus testing products (6.16 ± 1.30) as well as toward putting more investment in scientific research and biomedicine to improve the detection accuracy of detection kits (5.94 ± 1.55) in China. The respondents valued the detection accuracy more as opposed to the detection time of the testing kits (4.66 ± 2.00), whereas few participants agreed that in the research and development process, detection accuracy could be sacrificed to speed up production and coverage capacity (3.02 ± 2.04). Conclusion: The majority of the participants have a basic knowledge of the detection methods of the SARS-CoV-2 virus and the types of test kits, as well as great confidence in China's domestic production of test kits and decisions. However, how basic knowledge, high compliance, and positive attitudes play a role in easing the tension of the pandemic still remains unknown.

The use of methylprednisolone in COVID-19 patients: A propensity score matched retrospective cohort study.

PURPOSE: To evaluate the efficacy and safety of methylprednisolone in treating the coronavirus disease 2019 (COVID-19) patients. METHODS: A retrospective cohort study was conducted, and all COVID-19 patients were recruited who were admitted to the Yichang Third People's Hospital from February 1st to March 31st, 2020. One-to-one propensity score matching (PSM) was used for minimizing confounding effects. The primary outcome was hospital mortality, with the secondary outcomes being the time needed for a positive SARS-CoV-2 nucleic acid test to turn negative and the length of hospital stay. RESULTS: Totaling 367 patients with COVID-19 hospitalized at the Yichang Third People's Hospital were identified, of whom 276 were mild or stable COVID-19, and 67 were serious or critically ill. Among them, 255 patients were treated using methylprednisolone, and 188 did not receive any corticosteroid-related treatment. After PSM, no statistically significant difference was found in the baseline characteristics between the two groups. Regarding the outcomes, there also were no statistically significant difference between the two groups. Patients without the use of methylprednisolone were more quickly to obtain negative results of their nasopharyngeal swab tests of SARS-CoV-2 nucleic acid after treatment, compared to those receiving methylprednisolone. CONCLUSION: Methylprednisolone could not improve the prognosis of patients with COVID-19, and the efficacy and safety of the use of methylprednisolone in patients with COVID-19 still remain uncertain, thus the use of corticosteroids clinically in patients with COVID-19 should be with cautions.