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 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.

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.

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.

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.

A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China.

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

Online Antenatal Care During the COVID-19 Pandemic: Opportunities and Challenges.

People across the world have been greatly affected by the ongoing coronavirus disease (COVID-19) pandemic. The high infection risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in hospitals is particularly problematic for recently delivered mothers and currently pregnant women who require professional antenatal care. Online antenatal care would be a preferable alternative for these women since it can provide pregnancy-related information and remote clinic consultations. In addition, online antenatal care may help to provide relatively economical medical services and diminish health care inequality due to its convenience and cost-effectiveness, especially in developing countries or regions. However, some pregnant women will doubt the reliability of such online information. Therefore, it is important to ensure the quality and safety of online services and establish a stable, mutual trust between the pregnant women, the obstetric care providers and the technology vis-a-vis the online programs. Here, we report how the COVID-19 pandemic brings not only opportunities for the development and popularization of online antenatal care programs but also challenges.

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach.

BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE: The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS: We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS: After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics' themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media's actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures.

BACKGROUND: A novel coronavirus disease (COVID-19) outbreak due to the severe respiratory syndrome coronavirus (SARS-CoV-2) infection occurred in China in late December 2019. Facemask wearing with proper hand hygiene is considered an effective measure to prevent SARS-CoV-2 transmission, but facemask wearing has become a social concern due to the global facemask shortage. China is the major facemask producer in the world, contributing to 50% of global production. However, a universal facemask wearing policy would put an enormous burden on the facemask supply. METHODS: We performed a policy review concerning facemasks using government websites and mathematical modelling shortage analyses based on data obtained from the National Health Commission (NHC), the Ministry of Industry and Information Technology (MIIT), the Centre for Disease Control and Prevention (CDC), and General Administration of Customs (GAC) of the People's Republic of China. Three scenarios with respect to wearing facemasks were considered: (1) a universal facemask wearing policy implementation in all regions of mainland China; (2) a universal facemask wearing policy implementation only in the epicentre (Hubei province, China); and (3) no implementation of a universal facemask wearing policy. FINDINGS: Regardless of different universal facemask wearing policy scenarios, facemask shortage would occur but eventually end during our prediction period (from 20 Jan 2020 to 30 Jun 2020). The duration of the facemask shortage described in the scenarios of a country-wide universal facemask wearing policy, a universal facemask wearing policy in the epicentre, and no universal facemask wearing policy were 132, seven, and four days, respectively. During the prediction period, the largest daily facemask shortages were predicted to be 589·5, 49·3, and 37·5 million in each of the three scenarios, respectively. In any scenario, an N95 mask shortage was predicted to occur on 24 January 2020 with a daily facemask shortage of 2·2 million. INTERPRETATION: Implementing a universal facemask wearing policy in the whole of China could lead to severe facemask shortage. Without effective public communication, a universal facemask wearing policy could result in societal panic and subsequently, increase the nationwide and worldwide demand for facemasks. These increased demands could cause a facemask shortage for healthcare workers and reduce the effectiveness of outbreak control in the affected regions, eventually leading to a pandemic. To fight novel infectious disease outbreaks, such as COVID-19, governments should monitor domestic facemask supplies and give priority to healthcare workers. The risk of asymptomatic transmission and facemask shortages should be carefully evaluated before introducing a universal facemask wearing policy in high-risk regions. Public health measures aimed at improving hand hygiene and effective public communication should be considered along with the facemask policy.