Modelling the effects of Wuhan's lockdown during COVID-19, China

Innovative public strategies in response to COVID-19: A review of practices from China

The COVID-19 pandemic presented unparalleled challenges to prompt and adaptive responses from nations worldwide. This review examines China's multifaceted approach to the crisis, focusing on five key areas of response: infrastructure and system design, medical care and treatment, disease prevention and control, economic and social resilience, and China's engagement in global health. This review demonstrates the effectiveness of a top-down command system at the national level, intersectoral coordination, a legal framework, and public social governance. This study also examines medical care and treatment strategies, highlighting the importance of rapid emergency response, evidence-based treatment, and well-planned vaccination rollout. Further discussion on disease prevention and control measures emphasizes the importance of adaptive measures, timely infection control, transmission interruption, population herd immunity, and technology applications. Socioeconomic impact was also assessed, detailing strategies for disease prevention, material supply, livelihood preservation, and social economy revival. Lastly, we examine China's contributions to the global health community, with a focus on knowledge-sharing, information exchange, and multilateral assistance. While it is true that each nation's response must be tailored to its own context, there are universal lessons to be drawn from China's approach. These insights are pivotal for enhancing global health security, especially as the world navigates evolving health crises.

High connectivity and human movement limits the impact of travel time on infectious disease transmission

The speed of spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 2019 (COVID-19) pandemic highlights the importance of understanding how infections are transmitted in a highly connected world. Prior to vaccination, changes in human mobility patterns were used as non-pharmaceutical interventions to eliminate or suppress viral transmission. The rapid spread of respiratory viruses, various intervention approaches, and the global dissemination of SARS-CoV-2 underscore the necessity for epidemiological models that incorporate mobility to comprehend the spread of the virus. Here, we introduce a metapopulation susceptible-exposed-infectious-recovered model parametrized with human movement data from 340 cities in China. Our model replicates the early-case trajectory in the COVID-19 pandemic. We then use machine learning algorithms to determine which network properties best predict spread between cities and find travel time to be most important, followed by the human movement-weighted personalized PageRank. However, we show that travel time is most influential locally, after which the high connectivity between cities reduces the impact of travel time between individual cities on transmission speed. Additionally, we demonstrate that only significantly reduced movement substantially impacts infection spread times throughout the network.

Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings

Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.

Does mobility restriction significantly control infectious disease transmission? Accounting for non-stationarity in the impact of COVID-19 based on Bayesian spatially varying coefficient models

COVID-19 is the most severe health crisis of the 21st century. COVID-19 presents a threat to almost all countries worldwide. The restriction of human mobility is one of the strategies used to control the transmission of COVID-19. However, it has yet to be determined how effective this restriction is in controlling the rise in COVID-19 cases, particularly in small areas. Using Facebook's mobility data, our study explores the impact of restricting human mobility on COVID-19 cases in several small districts in Jakarta, Indonesia. Our main contribution is showing how the restriction of human mobility data can give important information about how COVID-19 spreads in different small areas. We proposed modifying a global regression model into a local regression model by accounting for the spatial and temporal interdependence of COVID-19 transmission across space and time. We applied Bayesian hierarchical Poisson spatiotemporal models with spatially varying regression coefficients to account for non-stationarity in human mobility. We estimated the regression parameters using an Integrated Nested Laplace Approximation. We found that the local regression model with spatially varying regression coefficients outperforms the global regression model based on DIC, WAIC, MPL, and R2 criteria for model selection. In Jakarta's 44 districts, the impact of human mobility varies significantly. The impacts of human mobility on the log relative risk of COVID-19 range from -4.445 to 2.353. The prevention strategy involving the restriction of human mobility may be beneficial in some districts but ineffective in others. Therefore, a cost-effective strategy had to be adopted.

Evaluating the Impact of COVID-19 on Hospital Profit Compensation Activities: A Difference-in-Differences Event Study Analysis in China

The impact of the 2019 coronavirus disease (COVID-19) pandemic is still being revealed, and little is known about the effect of COVID-19-induced outpatient and inpatient losses on hospital operations in many counties. Hence, we aimed to explore whether hospitals adopted profit compensation activities after the 2020 first-wave outbreak of COVID-19 in China. A total of 2,616,589 hospitalization records from 2018, 2019, and 2020 were extracted from 36 tertiary hospitals in a western province in China; we applied a difference-in-differences event study design to estimate the dynamic effect of COVID-19 on hospitalized patients' total expenses before and after the last confirmed case. We found that average total expenses for each patient increased by 8.7% to 16.7% in the first 25 weeks after the city reopened and hospital admissions returned to normal. Our findings emphasize that the increase in total inpatient expenses was mainly covered by claiming expenses from health insurance and was largely driven by an increase in the expenses for laboratory tests and medical consumables. Our study documents that there were profit compensation activities in hospitals after the 2020 first-wave outbreak of COVID-19 in China, which was driven by the loss of hospitalization admissions during this wave outbreak.

Patriotism, nationalism, and evaluations of the government's handling of the coronavirus crisis

Introduction

The COVID-19 pandemic has been accompanied by a global rise of nationalism, and many countries' responses to the pandemic have further intensified nationalist sentiments. The public is polarized over government policies toward the pandemic. Hence, this study examined the associations of patriotism and nationalism with the support for lockdown policies and evaluations of governmental performance.

Methods

We recruited 180 participants from one Chinese university.

Results

Patriotism and nationalism had a direct effect on evaluations of governmental performance. Patriotism also had indirect effects on favorable evaluations of governmental performance through the support of lockdown policies. In addition, this study examined the relationship of threat perception and evaluations of governmental performance in the pandemic.

Discussion

This relationship was found to be insignificant; however, the interaction effects between threat perception and patriotism on evaluations of governmental performance were significant. The implications of the study results are discussed.

Use of Bluetooth contact tracing technology to model COVID-19 quarantine policies in high-risk closed populations

Containment measures in high-risk closed settings, like migrant worker (MW) dormitories, are critical for mitigating emerging infectious disease outbreaks and protecting potentially vulnerable populations in outbreaks such as coronavirus disease 2019 (COVID-19). The direct impact of social distancing measures can be assessed through wearable contact tracing devices. Here, we developed an individual-based model using data collected through a Bluetooth wearable device that collected 33.6M and 52.8M contact events in two dormitories in Singapore, one apartment style and the other a barrack style, to assess the impact of measures to reduce the social contact of cases and their contacts. The simulation of highly detailed contact networks accounts for different infrastructural levels, including room, floor, block, and dormitory, and intensity in terms of being regular or transient. Via a branching process model, we then simulated outbreaks that matched the prevalence during the COVID-19 outbreak in the two dormitories and explored alternative scenarios for control. We found that strict isolation of all cases and quarantine of all contacts would lead to very low prevalence but that quarantining only regular contacts would lead to only marginally higher prevalence but substantially fewer total man-hours lost in quarantine. Reducing the density of contacts by 30% through the construction of additional dormitories was modelled to reduce the prevalence by 14 and 9% under smaller and larger outbreaks, respectively. Wearable contact tracing devices may be used not just for contact tracing efforts but also to inform alternative containment measures in high-risk closed settings.

A propensity score matching study: The prevalence of mental health problems among pregnant women at first antenatal care increased in Chongqing during the first wave of the COVID-19 pandemic

Background

The 2019 coronavirus disease (COVID-19) pandemic increased the risks of mental health challenges, especially anxiety and depression. However, the impact of COVID-19 on mental health during pregnancy has not been fully established. Therefore, we investigated the impact of the COVID-19 pandemic on maternal mental health.

Methods

Two cohorts of pregnant women at their first antenatal care in the First Affiliated Hospital of Chongqing Medical University were enrolled in this study. One cohort was enrolled before the COVID-19 outbreak, from 1 June to 31 December 2019 (n = 5,728, pre-COVID-19 group), while the other was enrolled during the COVID-19 pandemic, from 24 January to 23 March 2020 (n = 739, COVID-19 pandemic group). Symptoms of depression, anxiety, and somatization disorders were assessed by the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-15 (PHQ-15), with a cutoff point of 10 for moderate-to-severe depression, anxiety, and somatoform symptoms. The propensity score matching method (1:1) was used to balance differences in demographic characteristics between groups. A chi-square analysis was performed to compare differences in demographic characteristics between the groups.

Results

Prevalence of moderate-to-severe depression, anxiety, and somatoform symptoms among pregnant women at their first antenatal care visit during the COVID-19 pandemic (9.5, 2.2, and 20.8%, respectively) was significantly lower than those before the pandemic (16.3, 4.4, and 25.7%, respectively) (p < 0.05). Compared with the same period before the pandemic, during the pandemic, the number of women newly registered for antenatal care decreased by nearly 50%. There were significant differences in the distributions of demographic characteristics between the groups (p < 0.05). After matching the demographic characteristics, differences in the prevalence of maternal mental health disorders between the groups reversed dramatically. Prevalence of moderate-to-severe depression, anxiety, and somatoform symptoms during the COVID-19 pandemic in this population (2.3, 9.6, and 20.8%, respectively) was significantly higher than those before the pandemic (0.3, 3.9, and 10%, respectively) (p < 0.05).

Conclusion

The COVID-19 pandemic increased mental health risks among pregnant women. As a large proportion of pregnant women with mental health challenges delay their prenatal care or change healthcare facilities after the outbreak of public health emergencies, there is a need to establish a balanced healthcare system in medical institutions at all levels.

The Impact of COVID-19 Pandemic on Ischemic Stroke Patients in a Comprehensive Hospital

PURPOSE

This study aimed to investigate the impact of characteristic ischemic stroke and outcomes during the first COVID-19 pandemic lockdown.

PATIENTS AND METHODS

A retrospective, observational cohort study of a comprehensive tertiary stroke center was conducted. Patients with ischemic stroke were divided into pre-COVID-19 lockdown (11/1/2019 to 1/30/2020) and COVID-19 lockdown (1/31/2020 to 4/30/2020) period groups. Patient data on stroke admission, thrombolysis, endovascular treatment, and 3-month routine follow-up were recorded. Data analysis was performed using SPSS according to values following a Gaussian distribution.

RESULTS

The pre-COVID-19 lockdown period group comprised 230 patients compared to 215 patients in the COVID-19 lockdown period group. Atrial fibrillation was more predominant in the COVID-19 lockdown period group (11.68% vs 5.65%, p=0.02) alongside patients who were currently smoking (38.8% vs 28.7%, p=0.02) and drinking alcohol (30.37% vs 20.00%, p=0.012) compared with that of the pre-COVID-19 lockdown period group. For patients receiving thrombolysis, the median door-to-CT time was longer in the COVID-19 lockdown period group (17.0 min (13.0, 24.0) vs 12.0 min (8.0, 17.3), p=0.012), median door to needle time was 48.0 minutes (35.5, 73.0) vs 43.5 minutes (38.0, 53.3), p=0.50, compared with that of the pre-COVID-19 lockdown period group. There were no differences for patients receiving mechanical thrombectomy. The median length of hospitalization (IQR) was no different. Discharge mRS scores (IQR) were higher in the COVID-19 lockdown period group (1.0 (1.0, 3.0) vs 1.0 (1.0, 2.0), p=0.022). Compared with the pre-COVID-19 lockdown period, hospitalization cost (Chinese Yuan) in the COVID-19 period group was higher (13,445.7 (11,009.7, 20,030.5) vs 10,799.2 (8692.4, 16,381.7), p=0.000). There was no difference observed in 3-month mRS scores.

CONCLUSION

Patients presenting with ischemic stroke during the COVID-19 pandemic lockdown period had longer median door-to-CT time and higher hospitalization costs. There were no significant differences in 3-month outcomes. Multidisciplinary collaboration and continuous workflow optimization may maintain stroke care during the COVID-19 pandemic lockdown.

COVID-19 exit strategy during vaccine implementation: a balance between social distancing and herd immunity

Currently, health authorities around the world are struggling to limit the spread of COVID-19. Since the beginning of the pandemic, social distancing has been the most important strategy used by most countries to control disease spread by flattening and elongating the epidemic curve. Another strategy, herd immunity, was also applied by some countries through relaxed control measures that allow the free spread of natural infection to build up solid immunity within the population. In 2021, COVID-19 vaccination was introduced with tremendous effort as a promising strategy for limiting the spread of disease. Therefore, in this review, we present the current knowledge about social distancing, herd immunity strategies, and aspects of their implementation to control the COVID-19 pandemic in the presence of the newly developed vaccines. Finally, we suggest a short-term option for controlling the pandemic during vaccine application.

Respiratory pandemics, urban planning and design: A multidisciplinary rapid review of the literature

COVID-19 is the most recent respiratory pandemic to necessitate better knowledge about city planning and design. The complex connections between cities and pandemics, however challenge traditional approaches to reviewing literature. In this article we adopted a rapid review methodology. We review the historical literature on respiratory pandemics and their documented connections to urban planning and design (both broadly defined as being concerned with cities as complex systems). Our systematic search across multidisciplinary databases returned a total of 1323 sources, with 92 articles included in the final review. Findings showed that the literature represents the multi-scalar nature of cities and pandemics - pandemics are global phenomena spread through an interconnected world, but require regional, city, local and individual responses. We characterise the literature under ten themes: scale (global to local); built environment; governance; modelling; non-pharmaceutical interventions; socioeconomic factors; system preparedness; system responses; underserved and vulnerable populations; and future-proofing urban planning and design. We conclude that the historical literature captures how city planning and design intersects with a public health response to respiratory pandemics. Our thematic framework provides parameters for future research and policy responses to the varied connections between cities and respiratory pandemics.

How Policy Mix Choices Affect the COVID-19 Pandemic Response Outcomes in Chinese Cities: An Empirical Analysis

Since January 2020, the COVID-19 pandemic has caused millions of deaths and has posed a major public health threat worldwide. Such a massive and complex crisis requires quick and comprehensive policy responses. We developed an empirical dataset of policy mixes that included 4915 policies across 36 Chinese cities and investigated the relationships between the policy design choices and the COVID-19 pandemic response outcomes of a city. Using topic modeling and ordinary least squares regression analysis, we found considerable variation among cities in the compositions and design features of their policy mixes. Our analysis revealed that restriction measures did not significantly influence limiting the spread of the pandemic, but they were negatively correlated with the economic growth rate. By contrast, health protection measures greatly contributed to controlling viral spread. Intensive socioeconomic support reduced the occurrence of secondary disasters. The most effective policy strategy to deal with the COVID-19 pandemic appears to be a comprehensive policy design with a mix of restrictions, health protection measures, and socioeconomic support policies accompanied by a timely lockdown. Our empirical findings can help to improve pandemic policy design and contribute to generating broader lessons for how local governments should deal with similar crises in the future.

Application of genetic algorithm combined with improved SEIR model in predicting the epidemic trend of COVID-19, China

Since the outbreak of the 2019 Coronavirus disease (COVID-19) at the end of 2019, it has caused great adverse effects on the whole world, and it has been hindering the global economy. It is ergent to establish an infectious disease model for the current COVID-19 epidemic to predict the trend of the epidemic. Based on the SEIR model, the improved SEIR models were established with considering the incubation period, the isolated population, and genetic algorithm (GA) parameter optimization method. The improved SEIR models can predict the trend of the epidemic situation better and obtain the more accurate epidemic-related parameters. Comparing some key parameters, it is capable to evaluate the impact of different epidemic prevention measures and the implementation of different epidemic prevention levels on the COVID-19, which has significant guidance for further epidemic prevention measures.

The Variation of b-Value of Earthquakes During COVID-19 Lockdowns: Case Studies from the Cascadia Subduction Zone and New Zealand

During the COVID-19 outbreak that took place in early 2020, restrictions on human activities were imposed by government-mandated lockdowns and stay-at-home orders. In this study, we analyse the impact of reduced anthropogenic activities on the detection of seismic events. We hypothesise and show that with reduced background noise levels due to the COVID-19 lockdowns, low-magnitude earthquakes are more easily detectable. We investigate the magnitudes of earthquakes recorded at the seismometers before and after COVID-19 lockdowns for two regions — Cascadia Subduction Zone and New Zealand. Gutenberg–Richter law, which gives a relationship between the number of earthquakes and their magnitudes (b-value), was applied in these two areas. Our results point to an increase in detection of smaller-magnitude earthquakes, as observed by an increased b-value during the COVID-19 period compared to those obtained in the pre-COVID time periods. Previous studies have shown that changes in b-value of an area over a sustained period of time affect the short-time probabilistic risk assessment. The variability of b-value also gives useful insights into the prevailing stress state of the region, crustal heterogeneity, pore pressure and tectonic setting of the area.

COVID-19 in Malaysia: Descriptive Epidemiologic Characteristics of the First Wave

This study aimed to describe the characteristics of COVID-19 cases and close contacts during the first wave of COVID-19 in Malaysia (23 January 2020 to 26 February 2020), and to analyse the reasons why the outbreak did not continue to spread and lessons that can be learnt from this experience. Characteristics of the cases and close contacts, spatial spread, epidemiological link, and timeline of the cases were examined. An extended SEIR model was developed using several parameters such as the average number of contacts per day per case, the proportion of close contact traced per day and the mean daily rate at which infectious cases are isolated to determine the basic reproduction number (R₀) and trajectory of cases. During the first wave, a total of 22 cases with 368 close contacts were traced, identified, tested, quarantine and isolated. Due to the effective and robust outbreak control measures put in place such as early case detection, active screening, extensive contact tracing, testing and prompt isolation/quarantine, the outbreak was successfully contained and controlled. The SEIR model estimated the R₀ at 0.9 which further supports the decreasing disease dynamics and early termination of the outbreak. As a result, there was a 11-day gap (free of cases) between the first and second wave which indicates that the first wave was not linked to the second wave.

Epidemiology of COVID-19 and effect of public health interventions, Chennai, India, March-October 2020: an analysis of COVID-19 surveillance system

OBJECTIVES

To describe the public health strategies and their effect in controlling the COVID-19 pandemic from March to October 2020 in Chennai, India.

SETTING

Chennai, a densely populated metropolitan city in Southern India, was one of the five cities which contributed to more than half of the COVID-19 cases in India from March to May 2020. A comprehensive community-centric public health strategy was implemented for controlling COVID-19, including surveillance, testing, contact tracing, isolation and quarantine. In addition, there were different levels of restrictions between March and October 2020.

PARTICIPANTS

We collected the deidentified line list of all the 192 450 COVID-19 cases reported from 17 March to 31 October 2020 in Chennai and their contacts for the analysis. We defined a COVID-19 case based on the real-time reverse transcriptase-PCR (RT-PCR) positive test conducted in one of the government-approved labs.

OUTCOME MEASURES

The primary outcomes of interest were incidence of COVID-19 per million population, case fatality ratio (CFR), deaths per million, and the effective reproduction number (R_t). We also analysed the surveillance, testing, contact tracing and isolation indicators.

RESULTS

Of the 192 450 RT-PCR confirmed COVID-19 cases reported in Chennai from 17 March to 31 October 2020, 114 889 (60%) were males. The highest incidence was 41 064 per million population among those 61-80 years. The incidence peaked during June 2020 at 5239 per million and declined to 3627 per million in October 2020. The city reported 3543 deaths, with a case fatality ratio of 1.8%. In March, R_t was 4.2, dropped below one in July and remained so until October, even with the relaxation of restrictions.

CONCLUSION

The combination of public health strategies might have contributed to controlling the COVID-19 epidemic in a large, densely populated city in India. We recommend continuing the test-trace-isolate strategy and appropriate restrictions to prevent resurgence.

Global cities, hypermobility, and Covid-19

The relationship between cities, globalization and mobility has produced recurring urban challenges over time. This article examines how mobility networks can turn global cities into Pandemic Gateways. Our hypothesis is that global cities became the gateway by which COVID-19 was introduced to many countries through the hypermobility of infected international travelers. To assess this transmission mechanism, we assembled data about the population and COVID-19 cases in global cities and their associated countries, comparing their infection rates on a fixed date. We demonstrate that most global cities followed a common pattern in the pace and intensity of COVID-19's spread during the first wave of the pandemic. Among our global cities sample, 75% served as the gateway through which COVID-19 was diffused within their respective countries. This trend reached 90% in a subset based upon the urban hierarchy among global cities. Hypermobility, which we demonstrate contributed to the mechanism by which global cities diffused COVID-19 initially, is also correlated with the global cities hierarchy, as supported by air travel data. Our findings suggest the need to appreciate why global cities can serve as gateways of pandemic diffusion, while also seeking to understand why some did not function in this way.

COVID-19 Lockdown and Exposure of Households to Food Insecurity in Uganda: Insights from a National High Frequency Phone Survey

We estimate the impact of COVID-19 lockdown induced income shocks on household food insecurity outcomes in Uganda using five rounds of a nationally representative High Frequency Phone Survey. Relative to the baseline survey conducted just before the pandemic, there was a significant decrease in households' participation in wage work, agricultural production, and non-farm business which in turn increased their income losses. Consequently, we find that lockdown induced income losses significantly increased incidences of food insecurity within households. With incidences of food insecurity increasing especially in rural areas, it is likely that COVID-19 reversed some of the gains recorded in recent years in lifting millions of rural smallholder farming households out of poverty. These results suggest that to assure the food security of poorer segments of the population especially in anticipation of future shocks, the government needs to invest more in social protection i.e., income and consumption support.

Discussion on China's anti‐epidemic response based on the Protocol on Prevention and Control of Coronavirus Disease 2019 from Chinese Authority

Eight versions of the Protocol on Prevention and Control of Coronavirus Disease 2019 (COVID‐19) (the Protocol) were issued successively by the Chinese authority to guide the local responses since the first COVID‐19 case appeared in Wuhan, China. This study aimed to investigate the evolution of the overall strategy and specific measures in these Protocols, and several recommendations were provided after analysing China's response to the epidemic resurgence. As a result, we found a gradual expanding trend in case surveillance, early screening, and epidemiological investigation, as well as a progressively rigorous tendency in isolation measures and close contact management. With the Protocol's guidance, China had achieved success in several recent fights against domestic COVID‐19 resurgences. The city lockdown and multiple city‐wide nucleic acid tests adopted were deemed necessary in COVID‐19 resurgence's battle. Besides, the large‐scale distance centralised quarantine, which is, quarantine in a purpose‐built isolation station away from communities where people under quarantine lived, was promoted in rural areas. China's anti‐epidemic achievements provide ideas for the global battle against COVID‐19.

All versions of Protocol on Prevention and Control of Coronavirus Disease 2019 (COVID‐19) were analysed

City lockdown and city‐wide nucleic acid tests were deemed necessary

The large‐scale distance centralised quarantine was proposed in rural areas

China's resurgence fight achievements provide ideas for global battle

Estimating the Economic Effects of the Early Covid-19 Emergency Response in Cities Using Intracity Travel Intensity Data

In the early days of the Covid-19 pandemic, China implemented the most stringent and serious emergency response. To understand the effect of such an emergency response strategy on the economic system, this study proposed a simultaneous overall estimation method using intracity travel intensity data. The overall effect is represented by the difference between intracity travel intensity with and without the emergency response. Using historical data and time series analysis, we compared intracity travel intensity post China’s implementation of the emergency response with predicted intracity travel intensity without such a response. The loss rates, defined by the proportion of intracity travel intensity loss, were calculated for 360 cities within 33 provincial-level regions in China based on data availability. We found that 30 days after the emergency response, 21% of the cities saw over 80% recovery and 10% of the cities showed more than 90% recovery; 45 days after the emergency response, more than 83% of the 360 cities witnessed 80% recovery. The correlation between gross domestic production loss rate and travel intensity loss rate was studied quantitatively to demonstrate the representativeness of the intracity travel intensity loss rate. This indicator was also used to analyze the spatial and temporal patterns of the effects on the economy. The results of this study can help us understand the economic effects caused by the early Covid-19 emergency response and the method can be a reference for fast and real-time economic loss estimation to support emergency response decision making under pandemic conditions.

"I am chatbot, your virtual mental health adviser." What drives citizens' satisfaction and continuance intention toward mental health chatbots during the COVID-19 pandemic? An empirical study in China

Introduction

In order to address the psychological problems during the COVID-19 pandemic, mental health chatbots have been extensively used by public sectors. According to Theory of Consumption Values, this paper proposed an analytical framework to investigate the determinants behind users’ satisfaction and continuance intention toward mental health chatbots.

Methods

The empirical study was conducted through an online survey, facilitated by the use of questionnaire posted on the WeChat platform. Seven-point Likert scale and closed-ended questions were employed. Totally 371 valid samples were collected. The research data was tested via the partial least squares structural equation modeling. Gender, age, and income were included as control variables.

Results

Analysis of samples collected from 371 Chinese users suggested that personalization (functional value), enjoyment (emotional value), learning (epistemic value), and the condition of the COVID-19 pandemic (conditional value) have positive influences on user satisfaction and continuance intention, but such effects were weak. The findings also revealed that user satisfaction has weakly positive impact on continuance intention. However, voice interaction (functional value) was an insignificant predictor of user satisfaction and continuance intention.

Discussion

This study developed a critical perspective on the role of Theory of Consumption Values in the context of mental health chatbot usage, while Theory of Consumption Value has been increasingly employed to explain the use of AI-based public services. Thus, this research devotes to the enhancement of theoretical frameworks regarding the usage of mental health chatbots.

A systematic review and meta-analysis of longitudinal cohort studies comparing mental health before versus during the COVID-19 pandemic in 2020

BACKGROUND

Increases in mental health problems have been observed during the COVID-19 pandemic. The objectives were to examine the extent to which mental health symptoms changed during the pandemic in 2020, whether changes were persistent or short lived, and if changes were symptom specific.

METHODS

Systematic review and meta-analysis of longitudinal cohort studies examining changes in mental health among the same group of participants before vs. during the pandemic in 2020.

RESULTS

Sixty-five studies were included. Compared to pre-pandemic outbreak, there was an overall increase in mental health symptoms observed during March-April 2020 (SMC = .102 [95% CI: .026 to .192]) that significantly declined over time and became non-significant (May-July SMC = .067 [95% CI: -.022 to .157]. Compared to measures of anxiety (SMC = 0.13, p = 0.02) and general mental health (SMC = -.03, p = 0.65), increases in depression and mood disorder symptoms tended to be larger and remained significantly elevated in May-July [0.20, 95% CI: .099 to .302]. In primary analyses increases were most pronounced among samples with physical health conditions and there was no evidence of any change in symptoms among samples with a pre-existing mental health condition.

LIMITATIONS

There was a high degree of unexplained heterogeneity observed (I2s > 90%), indicating that change in mental health was highly variable across samples.

CONCLUSIONS

There was a small increase in mental health symptoms soon after the outbreak of the COVID-19 pandemic that decreased and was comparable to pre-pandemic levels by mid-2020 among most population sub-groups and symptom types.

Analysis of social media data for public emotion on the Wuhan lockdown event during the COVID-19 pandemic

BACKGROUND

With outbreaks of COVID-19 around the world, lockdown restrictions are routinely imposed to limit the spread of the virus. During periods of lockdown, social media has become the main channel for citizens to exchange information with others. Public emotions are being generated and shared rapidly online with citizens using internet platforms to reduce anxiety and stress, and stay connected while isolated.

OBJECTIVES

This study aims to explore the regularity of emotional evolution by examining public emotions expressed in online discussions about the Wuhan lockdown event in January 2020.

METHODS

Data related to the Wuhan lockdown was collected from Sina Weibo by web crawler. In this study, the Ortony, Clore, and Collins (OCC) model, Word2Vec, and Bi-directional Long Short-Term Memory model were employed to determine emotional types, train vectorization of words, and identify each text emotion for the training set. Latent Dirichlet Allocation models were also employed to mine the various topic categories, while topic emotional evolution was visualized.

RESULTS

Seven types of emotions and four phases were categorized to describe emotional evolution on the Wuhan lockdown event. The study found that negative emotions such as blame and fear dominated in the early days, and public attitudes towards the lockdown gradually alleviated and reached a balance as the situation improved. Emotional expression about Wuhan lockdown event were significantly related to users' gender, location, and whether or not their account was verified. There were statistically significant correlations between different emotions within the subtle emotional categories. In addition, the evolution of emotions presented a different path due to different topics.

CONCLUSIONS

Multiple emotional categories were determined in our study, providing a detailed and explainable emotion analysis to explored emotional appeal of citizen. The public emotions were gradually easing related to the Wuhan lockdown event, there yet exists regional discrimination and post-traumatic stress disorder in this process, which would lead us to pay continuous attention to citizens lives and psychological status post-pandemic. In addition, this study provided an appropriate method and reference case for the government's public opinion control and emotional appeasement.

Evaluation of sleep quality, psychological states and subsequent self-medication practice among the Bangladeshi population during Covid-19 pandemic

Introduction

Due to the extended lockdown imposed for SARS-CoV-2 pandemic, many people have experienced problematic sleep patterns and associated health issues worldwide. This study was conducted to assess the sleep quality and psychological states of the Bangladeshi population during the COVID-19 pandemic, respondent's behavioral traits as well as psychological or sleep-related problems induced self-medication practice among the respondents, along with the probability of development of drug dependency.

Methods

The survey was conducted among 2941 respondents from 25th November 2020 to 4th December 2020 where the responses were analyzed by SPSS V22.

Results

10–29.5% experienced a significant degree of sleep problems whereas some experienced severe anxiety and depression. The associations between the behavioral traits and parameters concerning sleep quality, anxiety and depression showed 5% level of significance in all cases. Self-medication practice of sleep aids during this pandemic was reported by 7.14% of the respondents, with a greater percentage belonging to the female or senior age group. Tendency to repeatedly self-medication was observed in 18.86% of this self-medicating populace, and a greater number of male (10.26%) respondents displayed such tendency as opposed to their female (8.6%) equivalents. However, 48.10% of the respondents reported perceptions of improved physical and/or psychological health following self-medication, and this trait was predominant in men (52.14%).

Conclusion

Results showed a significant number of Bangladeshi populaces were suffering from psychological issues during this COVID-19 which also influenced a certain number of people towards self-medication practice where signs of drug dependency were observed in a significant number of respondents.

Comparing COVID-19 physical distancing policies: results from a physical distancing intensity coding framework for Botswana, India, Jamaica, Mozambique, Namibia, Ukraine, and the United States

BACKGROUND

Understanding the differences in timing and composition of physical distancing policies is important to evaluate the early global response to COVID-19. A physical distancing intensity monitoring framework comprising 16 domains was recently published to compare physical distancing approaches across 12 U.S. States. We applied this framework to a diverse set of low and middle-income countries (LMICs) (Botswana, India, Jamaica, Mozambique, Namibia, and Ukraine) to test the appropriateness of this framework in the global context and to compare the policy responses in these LMICs with a sample of U.S. States during the first 100-days of the pandemic.

RESULTS

The LMICs in our sample adopted wide ranging physical distancing policies. The highest peak daily physical distancing intensity during this period was: Botswana (4.60); India (4.40); Ukraine (4.40); Namibia (4.20); Mozambique (3.87), and Jamaica (3.80). The number of days each country stayed at peak policy intensity ranged from 12-days (Jamaica) to more than 67-days (Mozambique). We found some key similarities and differences, including substantial differences in whether and how countries expressly required certain groups to stay at home. Despite the much higher number of cases in the US, the physical distancing responses in our LMIC sample were generally more intense than in the U.S. States, but results vary depending on the U.S. State. The peak policy intensity for the U.S. 12-state average was 3.84, which would place it lower than every LMIC in this sample except Jamaica. The LMIC sample countries also reached peak physical distancing intensity earlier in outbreak progression compared to the U.S. states sample. The easing of physical distancing policies in the LMIC sample did not discernably correlate with change in COVID-19 incidence.

CONCLUSIONS

This physical distancing intensity framework was appropriate for the LMIC context with only minor adaptations. This framework may be useful for ongoing monitoring of physical distancing policy approaches and for use in effectiveness analyses. This analysis helps to highlight the differing paths taken by the countries in this sample and may provide lessons to other countries regarding options for structuring physical distancing policies in response to COVID-19 and future outbreaks.

Economic impact of COVID-19 pandemic on healthcare facilities and systems: International perspectives

International hospitals and healthcare facilities are facing catastrophic financial challenges related to the COVID-19 pandemic. The American Hospital Association estimates a financial impact of $202.6 billion in lost revenue for America's hospitals and healthcare systems, or an average of $50.7 billion per month. Furthermore, it could cost low- and middle-income countries ~ US$52 billion (equivalent to US$8.60 per person) each four weeks to provide an effective healthcare response to COVID-19. In the setting of the largest daily COVID-19 new cases in the US, this burden will influence patient care, surgeries, and surgical outcomes. From a global economic standpoint, The World Bank projects that global growth is projected to shrink by almost 8% with poorer countries feeling most of the impact, and the United Nations projects that it will cost the global economy around 2 trillion dollars this year. Overall, a lack of preparedness was a major contributor to the struggles experienced by healthcare facilities around the world. Items such as personal protective equipment (PPE) for healthcare workers, hospital equipment, sanitizing supplies, toilet paper, and water were in short supply. These deficiencies were exposed by COVID-19 and have prompted healthcare organizations around the world to invent new essential plans for pandemic preparedness. In this paper, we will discuss the economic impact of COVID-19 on US and international hospitals, healthcare facilities, surgery, and surgical outcomes. In the future, the US and countries around the world will benefit from preparing a plan of action to use as a guide in the event of a disaster or pandemic.

Regional COVID-19 Dynamics: Surrogate Synchrony in Case Infection Rates

As many jurisdictions consider in-person learning strategies (including at Institutions of Higher Education, IHE), implementing travel restrictions or quarantines, and/or establishing interstate pacts to reduce COVID-19 spread, this study explores the degree to which COVID-19 case infection rates in a group of neighboring, Southern and Midwestern U.S. states (namely, Arkansas and its contiguous neighbors) are patterned in a non-random way known as synchrony. Utilizing surrogate synchrony (SUSY) to estimate the dyadic coupling between the COVID-19 case infection rate processes in this region from March to December 2020, results indicate that significant synchrony is present between Arkansas and three of its neighbors. The highest level of instantaneous synchrony occurs between Arkansas and Tennessee, with the next highest level occurring between Arkansas and Missouri. There is evidence of directionality in the synchrony, indicating that Arkansas case infection rates lead Mississippi while rates in Missouri and Tennessee lead Arkansas. The lagged cross-correlations suggest the greatest synchrony to occur between 3 and 6 days. To explore the effect of IHE reopening on COVID-19, synchrony is compared between pre- and post-reopening windows. Results suggested that, following reopening, there are gains in detectable synchrony and that COVID-19 is in-flowing to Arkansas from all of its neighboring states. Taken together, results suggest that there is spatiality to COVID-19 with neighboring states having case infection rates that are significantly synchronous at a lag time that would be expected based on symptom onset. This synchrony is potentially strengthened by the in-flow and cross-border movement of IHE students.

Business Innovations in the New Mobility Market during the COVID-19 with the Possibility of Open Business Model Innovation

The current difficult situation in the world caused by the spread of the COVID-19 virus has led to the development of problems in many branches of the economy. However, it has significantly affected transport, which on the one hand, is the bloodstream of the economy and, on the other hand, creates a threat for virus infection. Thus, in various countries, different mobility-related restrictions during pandemic policies around the world have been introduced. What is more, plans for initiatives after lockdown have also started to appear. Moreover, not have only cities introduced appropriate management policies, but companies have also started providing logistics services, especially those offering new mobility solutions. We found a literature and research gap indicating the recording or combination of the different types of business practices and innovations used worldwide in new mobility companies in the case of a pandemic situation. Therefore, this article is dedicated to the business innovations that appear in the new mobility industry during the COVID-19 pandemic in connection to post-pandemic transportation plans in Asia, Europe, and America. In this work, we conducted two-level research based on the desk research and expert research methodologies. From the business point of view, the results show that car-sharing systems (most organizational practices) and ride-sharing services (most safety practices) have most adapted their business models to pandemic changes. In turn, bike-sharing services have implemented the fewest business practices and innovations. From the urban transport systems point of view, the results show that European authorities have proposed the most plans and practice projects for new mobility after the pandemic compared to Asia and America. The obtained results indicate, however, that business practices do not coincide with the authorities’ plans for transport after the pandemic. Moreover, the results show a lack of complementarity between the developed practices and a reluctance to create open innovations in the new mobility industry. The article supports the management of new mobility systems in times of pandemic and in post-COVID reality.

Exploration of spatial-temporal varying impacts on COVID-19 cumulative case in Texas using geographically weighted regression (GWR)

Since COVID-19 is extremely threatening to human health, it is significant to determine its impact factors to curb the virus spread. To tackle the complexity of COVID-19 expansion on a spatial-temporal scale, this research appropriately analyzed the spatial-temporal heterogeneity at the county-level in Texas. First, the impact factors of COVID-19 are captured on social, economic, and environmental multiple facets, and the communality is extracted through principal component analysis (PCA). Second, this research uses COVID-19 cumulative case as the dependent variable and the common factors as the independent variables. According to the virus prevalence hierarchy, the spatial-temporal disparity is categorized into four quarters in the GWR analysis model. The findings exhibited that GWR models provide higher fitness and more geodata-oriented information than OLS models. In El Paso, Odessa, Midland, Randall, and Potter County areas in Texas, population, hospitalization, and age structures are presented as static, positive influences on COVID-19 cumulative cases, indicating that they should adopt stringent strategies in curbing COVID-19. Winter is the most sensitive season for the virus spread, implying that the last quarter should be paid more attention to preventing the virus and taking precautions. This research is expected to provide references for the prevention and control of COVID-19 and related infectious diseases and evidence for disease surveillance and response systems to facilitate the appropriate uptake and reuse of geographical data.

How Transportation Restriction Shapes the Relationship Between Ambient Nitrogen Dioxide and COVID-19 Transmissibility: An Exploratory Analysis

Background: Several recent studies reported a positive (statistical) association between ambient nitrogen dioxide (NO₂) and COVID-19 transmissibility. However, considering the intensive transportation restriction due to lockdown measures that would lead to declines in both ambient NO₂ concentration and COVID-19 spread, the crude or insufficiently adjusted associations between NO₂ and COVID-19 transmissibility might be confounded. This study aimed to investigate whether transportation restriction confounded, mediated, or modified the association between ambient NO₂ and COVID-19 transmissibility.

Methods: The time-varying reproduction number (R_t) was calculated to quantify the instantaneous COVID-19 transmissibility in 31 Chinese cities from January 1, 2020, to February 29, 2020. For each city, we evaluated the relationships between ambient NO₂, transportation restriction, and COVID-19 transmission under three scenarios, including simple linear regression, mediation analysis, and adjusting transportation restriction as a confounder. The statistical significance (p-value < 0.05) of the three scenarios in 31 cities was summarized.

Results: We repeated the crude correlational analysis, and also found the significantly positive association between NO₂ and COVID-19 transmissibility. We found that little evidence supported NO₂ as a mediator between transportation restriction and COVID-19 transmissibility. The association between NO₂ and COVID-19 transmissibility appears less likely after adjusting the effects of transportation restriction.

Conclusions: Our findings suggest that the crude association between NO₂ and COVID-19 transmissibility is likely confounded by the transportation restriction in the early COVID-19 outbreak. After adjusting the confounders, the association between NO₂ and COVID-19 transmissibility appears unlikely. Further studies are warranted to validate the findings in other regions.

Impacts of the COVID-19 epidemic on the department of stomatology in a tertiary hospital: A case study in the General Hospital of the Central Theater Command, Wuhan, China

Objective

The impact of the worldwide COVID‐19 pandemic on the dental community is evident. Dental education programmes and academic activities have suffered from the ramifications of the pandemic. This study aimed to depict the impacts of the COVID‐19 epidemic on the clinical services and academic activities in the department of stomatology of a tertiary hospital in Wuhan, China.

Methods

We obtained historical data of the Department of Stomatology from the Health Information System of the General Hospital of Central Theater Command, Wuhan, China between January 2018 and June 2020. Mean, standard deviation and median with interquartile range were used to summarize the variables. Line plots were used to illustrate the temporal trend. The Kruskal‐Wallis equality‐of‐populations rank test was used to compare the difference between groups.

Results

A significant decrease was noted in the monthly average number of patients seeking outpatient services for the year 2020, which were decreased by two‐thirds from 2018 to 2020. The number of emergency cases also decreased significantly by 57.6% in 2020. The monthly number of teaching hours decreased from 3.8 ± 1.5 in 2018 and 4.7 ± 1.4 in 2019 to 1.7 ± 1.9 in 2020. The number of interns also decreased by more than 77.0% in 2020.

Conclusions

The impacts of COVID‐19 in the stomatology clinic were significant with notable decreases in clinical services and education offered to the stomatology students. There is a need to find solutions to keep as many dental professionals as needed remaining on the frontline of oral health care.

Risk Assessment of Importation and Local Transmission of COVID-19 in South Korea: Statistical Modeling Approach

Background

Despite recent achievements in vaccines, antiviral drugs, and medical infrastructure, the emergence of COVID-19 has posed a serious threat to humans worldwide. Most countries are well connected on a global scale, making it nearly impossible to implement perfect and prompt mitigation strategies for infectious disease outbreaks. In particular, due to the explosive growth of international travel, the complex network of human mobility enabled the rapid spread of COVID-19 globally.

Objective

South Korea was one of the earliest countries to be affected by COVID-19. In the absence of vaccines and treatments, South Korea has implemented and maintained stringent interventions, such as large-scale epidemiological investigations, rapid diagnosis, social distancing, and prompt clinical classification of severely ill patients with appropriate medical measures. In particular, South Korea has implemented effective airport screenings and quarantine measures. In this study, we aimed to assess the country-specific importation risk of COVID-19 and investigate its impact on the local transmission of COVID-19.

Methods

The country-specific importation risk of COVID-19 in South Korea was assessed. We investigated the relationships between country-specific imported cases, passenger numbers, and the severity of country-specific COVID-19 prevalence from January to October 2020. We assessed the country-specific risk by incorporating country-specific information. A renewal mathematical model was employed, considering both imported and local cases of COVID-19 in South Korea. Furthermore, we estimated the basic and effective reproduction numbers.

Results

The risk of importation from China was highest between January and February 2020, while that from North America (the United States and Canada) was high from April to October 2020. The R₀ was estimated at 1.87 (95% CI 1.47-2.34), using the rate of α=0.07 for secondary transmission caused by imported cases. The R_t was estimated in South Korea and in both Seoul and Gyeonggi.

Conclusions

A statistical model accounting for imported and locally transmitted cases was employed to estimate R₀ and R_t. Our results indicated that the prompt implementation of airport screening measures (contact tracing with case isolation and quarantine) successfully reduced local transmission caused by imported cases despite passengers arriving from high-risk countries throughout the year. Moreover, various mitigation interventions, including social distancing and travel restrictions within South Korea, have been effectively implemented to reduce the spread of local cases in South Korea.

Electric Shared Mobility Services during the Pandemic: Modeling Aspects of Transportation

The global spread of the COVID-19 virus has led to difficulties in many branches of the economy, including significant effects on the urban transport industry. Thus, countries around the world have introduced different mobility policies during the pandemic. Due to government restrictions and the changed behaviors of transport users, companies providing modern urban mobility solutions were forced to introduce new business practices to their services. These practices are also apparent in the context of the electric shared mobility industry. Although many aspects and problems of electric shared mobility have been addressed in scientific research, pandemic scenarios have not been taken into account. Noticing this research gap, we aimed to update a previously developed model of factors that influence the operation of electric shared mobility by incorporating aspects related to the COVID-19 pandemic and its impact on this industry. This article aims to identify the main factors influencing the electric shared mobility industry during the COVID-19 and post-lockdown periods, together with their operation areas and the involved stakeholders. The research was carried out on the basis of expert interviews, social network analysis (SNA), and the use of the R environment. The article also presents sustainable transport management recommendations for cities and transport service operators, which can be implemented after a lockdown caused by an epidemic. The results in this paper can be used to support transport modeling and the creation of new policies, business models, and sustainable development recommendations. The contents will also be helpful to researchers worldwide in preparing literature reviews for articles related to sustainable management in the COVID-19 pandemic reality.

Does lock-down of Wuhan effectively restrict early geographic spread of novel coronavirus epidemic during chunyun in China? A spatial model study

BACKGROUND

Prior to Wuhan lock-down in 2020, chunyun, the largest population mobility on this planet, had begun. We quantified impact of Wuhan lock-down on COVID-19 spread during chunyun across the nation.

METHODS

During the period of January 1 to February 9, 2020, a total of 40,278 confirmed COVID-19 cases from 319 municipalities in mainland China were considered in this study. The cross-coupled meta-population methods were employed using between-city Baidu migration index. We modelled four scenarios of geographic spread of COVID-19 including the presence of both chunyun and lock-down (baseline); lock-down without chunyun (scenario 1); chunyun without lock-down (scenario 2); and the absence of both chunyun and lock-down (scenario 3).

RESULTS

Compared with the baseline, scenario 1 resulted in 3.84% less cases by February 9 while scenario 2 and 3 resulted in 20.22 and 32.46% more cases by February 9. The geographic distribution of cases revealed that chunyun facilitated the COVID-19 spread in the majority but not all cities, and the effectiveness of Wuhan lock-down was offset by chunyun. Impacts of Wuhan lock-down during chunyun on the COVID-19 spread demonstrated heterogenetic geographic patterns.

CONCLUSION

Our results strongly supported the travel restriction as one of the effective responses and highlighted the importance of developing area-specific rather than universal countermeasures.

Factors associated with psychological distress among patients with breast cancer during the COVID-19 pandemic: a cross-sectional study in Wuhan, China

PURPOSE

This study aimed to examine the prevalence of psychological distress and the corresponding risk factors among patients with breast cancer affected by the outbreak of coronavirus disease 2019 (COVID-19).

METHODS

This cross-sectional, survey-based, region-stratified study was conducted from March 14 to March 21, 2020. An online survey was used to collect the basic characteristics of patients with breast cancer. The degree of depression, anxiety, and insomnia symptoms were assessed using the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder (GAD-7), and the Insomnia Severity Index (ISI) questionnaires, respectively. Multivariate logistic analysis was performed to identify factors associated with psychological distress outcomes.

RESULTS

Among the 834 patients with breast cancer included in the study, the prevalence of depression, anxiety, and insomnia was 21.6%, 15.5%, and 14.7%, respectively. No statistically significant difference in the prevalence of these symptoms was observed between patients in Wuhan and those outside Wuhan. Multivariate logistic regression analyses revealed that comorbidity, living alone, deterioration of breast cancer, and affected treatment plan were risk factors for psychological distress including depression, anxiety, and insomnia. When stratified by location, living alone was associated with depression and insomnia only among patients in Wuhan, but not those outside Wuhan.

CONCLUSIONS

This study shows an elevated prevalence of depression, anxiety, and insomnia among patients with breast cancer during part of the COVID-19 pandemic. Patients with comorbidity, living alone, deterioration of breast cancer, and whose treatment plan was affected should be paid more attention to prevent mental disorders.

Technical supplement - COVID-19 Australia: Epidemiology reporting Last updated 19 January 2021

Summary

This supplement to the series of regular Australian coronavirus disease 2019 (COVID-19) epidemiological reports describes the technical background to the surveillance data reported through Communicable Diseases Network Australia (CDNA) as part of the nationally-coordinated response to COVID-19.

Background

Coronavirus disease 19 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in humans in Wuhan, China, in December 2019. The disease subsequently spread rapidly, leading to a global pandemic.1 The predominant modes of transmission for COVID-19 are through direct or close contact with an infected person via respiratory droplets, or indirectly via contact with contaminated fomites.2 The median incubation period of COVID-19 is 5-6 days, ranging from 1 to 14 days.3,4 The infectious period remains uncertain; however, it is estimated to be from 48 hours before symptoms develop until two weeks after symptom onset.3,5 The predominant symptoms reported in COVID-19 cases are cough, sore throat, fatigue, runny nose and fever.6 The majority of cases recover from the disease without clinical intervention; however, approximately 20% of global cases result in more severe outcomes, such as shortness of breath and pneumonia, necessitating hospitalisation and the requirement of additional oxygen or ventilation.7,8 Severe or fatal outcomes are generally more common among elderly cases or those with comorbid conditions.8 A visual depiction of the severity spectrum of COVID-19, and of the data sources that we use in this report to measure aspects of severity, is provided in Figure 1.

Technical supplement: COVID-19 Australia: Epidemiology reporting. Last updated 19 January 2021

This supplement to the series of regular Australian coronavirus disease 2019 (COVID-19) epidemiological reports describes the technical background to the surveillance data reported through Communicable Diseases Network Australia (CDNA) as part of the nationally-coordinated response to COVID-19.

Primary care perspectives on pandemic politics

While the COVID-19 pandemic now affects the entire world, countries have had diverse responses. Some responded faster than others, with considerable variations in strategy. After securing border control, primary health care approaches (public health and primary care) attempt to mitigate spread through public education to reduce person-to-person contact (hygiene and physical distancing measures, lockdown procedures), triaging of cases by severity, COVID-19 testing, and contact-tracing. An international survey of primary care experts' perspectives about their country's national responseswas conducted April to early May 2020. This mixed method paper reports on whether they perceived that their country's decision-making and pandemic response was primarily driven by medical facts, economic models, or political ideals; initially intended to develop herd immunity or flatten the curve, and the level of decision-making authority (federal, state, regional). Correlations with country-level death rates and implications of political forces and processes in shaping a country's pandemic response are presented and discussed, informed by our data and by the literature. The intersection of political decision-making, public health/primary care policies and economic strategies is analysed to explore implications of COVID-19's impact on countries with different levels of social and economic development.

Maternal Mental Health Status and Approaches for Accessing Antenatal Care Information During the COVID-19 Epidemic in China: Cross-Sectional Study

BACKGROUND

China was the first country in the world to experience a large-scale COVID-19 outbreak. The rapid spread of the disease and enforcement of public health measures has caused distress among vulnerable populations such as pregnant women. With a limited understanding of the novel, emerging infectious disease, pregnant women have sought ways to access timely and trusted health care information. The mental health status of pregnant women during this public health emergency, as well as how they responded to the situation and where and how they obtained antenatal care information, remain to be understood.

OBJECTIVE

This study aimed to evaluate the mental health status of pregnant women during the COVID-19 epidemic in China by measuring their perceived stress, anxiety, and depression levels; explore the approaches used by them to access antenatal health care information; and determine their associations with maternal mental health status.

METHODS

We conducted a web-based, cross-sectional survey to assess the mental health status of Chinese pregnant women by using the validated, Chinese version of Perceived Stress Scale, Self-Rating Anxiety Scale, and Edinburgh Depression Scale. We also collected information on the various approaches these women used to access antenatal care information during the early stage of the COVID-19 epidemic, from February 5 to 28, 2020.

RESULTS

A total of 1873 pregnant women from 22 provinces or regions of China participated in the survey. The prevalence of perceived stress, anxiety, and depression among these participants was 89.1% (1668/1873; 95% CI 87.6%, 90.4%), 18.1% (339/1873; 95% CI 16.4%, 19.9%), and 45.9% (859/1873; 95% CI 43.6%, 48.1%), respectively. Hospitals' official accounts on the Chinese social media platforms WeChat and Weibo were the most popular channels among these pregnant women to obtain antenatal care information during the COVID-19 outbreak. Access to antenatal care information via the hospitals' official social media accounts was found to be associated with a significantly lower risk of perceived stress (adjusted odds ratio [aOR] 0.46, 95% CI 0.30-0.72; P=.001), anxiety (aOR 0.53, 95% CI 0.41-0.68; P<.001), and depression (aOR 0.73, 95% CI 0.59-0.91; P=.005). Access to health care information via hospital hotlines or SMS was found to be significantly associated with a lower risk of anxiety only (OR 0.77, 95% CI 0.60-0.98; P=.04).

CONCLUSIONS

During the COVID-19 outbreak in China, pregnant women experienced high levels of perceived stress, anxiety, and depression. During such public health emergencies, mental health care services should be strengthened to reassure and support pregnant women. Specific information targeted at pregnant women, including information on how to cope in an emergency or major disease outbreak, developed and disseminated by health care institutions via social media platforms could be an effective way to mitigate mental health challenges and ensure epidemic preparedness and response in the future.

COVID-19 Australia: Epidemiology Report 32: Four-week reporting period ending 3 January 2021

This is the thirty-second epidemiological report for coronavirus disease 2019 (COVID-19), reported in Australia as at 23:59 Australian Eastern Daylight Time [AEDT] 3 January 2021. It includes data on COVID-19 cases diagnosed in Australia and the international situation.

Knowledge, Attitudes, and Practices Toward COVID-19 Among Construction Industry Practitioners in China

The COVID-19 pandemic has put labor-intensive industries at risk, among which the construction industry is a typical one. Practitioners in the construction industry are facing high probabilities of COVID-19 transmission, while their knowledge, attitudes, and practices (KAP) are critical to the prevention of virus spread. This study seeks to investigate the KAP of construction industry practitioners in China through an online questionnaire survey conducted from 15 to 30 June 2020. A total of 702 effective responses were received and analyzed. The results revealed that: (1) although an overwhelming percentage of respondents had the correct knowledge about COVID-19, there were significant respondents (15% of all) who were unsure or wrong about the human-to-human transmission of the virus; (2) practitioners generally showed an optimistic attitude about winning the battle against the COVID-19 pandemic and were satisfied with the governments' contingency measures; (3) practitioners tended to actively take preventive measures, although checking body temperature, wearing face masks, and keeping safe social distance still needs to be reinforced. This research is among the first to identify the KAP of construction industry practitioners toward the COVID-19 pandemic in China. Results presented here have implications for enhancing strategies to reduce and prevent COVID-19 spread in the construction industry.

COVID-19 Australia: Epidemiology Report 31: Fortnightly reporting period ending 6 December 2020

Nationally, COVID-19 notifications remained at low levels this fortnight. Testing rates also decreased during the surveillance period. The daily average number of cases was eight compared to an average of 11 cases for the previous fortnight. There were 109 cases of COVID-19 and no deaths this fortnight, bringing the cumulative case count to 28,049 and 908 deaths. New South Wales reported the highest proportion of cases again this fortnight (54%; 59/109), with the majority of these acquired overseas (97%; 57/59). Locally-acquired cases accounted for 5% (5/109) of all cases reported this fortnight, with one of these from an unknown source. FluTracking data indicated that 47% of people in the community with ‘fever and cough’ and 19% of those with ‘runny nose and sore throat’ were tested for SARS-CoV-2, which was a decrease from the previous reporting period. Testing rates decreased to 9.3 tests per 1,000 population per week during this reporting period, representing a 29% decrease in fortnightly tests conducted compared to the last reporting period. The overall positivity rate for the reporting period remains at 0.03%.

COVID-19 Australia: Epidemiology Report 28: Fortnightly reporting period ending 25 October 2020

Nationally, there was a continuing downward trend in notifications of COVID-19. The daily average number of cases for this reporting period was 13 compared to an average of 18 cases per day in the previous fortnight. There were 176 cases of COVID-19 and 7 deaths this fortnight, bringing the cumulative case count to 27,582 and 905 deaths. New South Wales reported the highest proportion of cases this fortnight (42%; 74/176), the majority of which were overseas acquired (52). Locally-acquired cases accounted for 31% (54/176) of all cases reported this fortnight. While the majority of these were reported from Victoria (33/54), there continues to be a decrease in new cases in this state resulting from public health interventions. Testing rates increased during the reporting period and remain high overall at 10.3 tests per week per 1,000 persons. There was variability in the testing rate by jurisdiction, with testing rates depending on the epidemic context. The overall positivity rate for the reporting period was 0.05%, with Western Australia reporting a positivity rate of 0.21% for this reporting period. In all other jurisdictions the positivity rate was ≤ 0.06%.

COVID-19 Australia: Epidemiology Report 28: Fortnightly reporting period ending 25 October 2020

Nationally, there was a continuing downward trend in notifications of COVID-19. The daily average number of cases for this reporting period was 13 compared to an average of 18 cases per day in the previous fortnight. There were 176 cases of COVID-19 and 7 deaths this fortnight, bringing the cumulative case count to 27,582 and 905 deaths. New South Wales reported the highest proportion of cases this fortnight (42%; 74/176), the majority of which were overseas acquired (52). Locally-acquired cases accounted for 31% (54/176) of all cases reported this fortnight. While the majority of these were reported from Victoria (33/54), there continues to be a decrease in new cases in this state resulting from public health interventions. Testing rates increased during the reporting period and remain high overall at 10.3 tests per week per 1,000 persons. There was variability in the testing rate by jurisdiction, with testing rates depending on the epidemic context. The overall positivity rate for the reporting period was 0.05%, with Western Australia reporting a positivity rate of 0.21% for this reporting period. In all other jurisdictions the positivity rate was ≤ 0.06%.

COVID-19 Australia: Epidemiology Report 30: Fortnightly reporting period ending 22 November 2020

Nationally, COVID-19 notifications remained at low levels this fortnight. The daily average number of cases for this reporting period was nine, which was similar to last fortnight’s average. There were 123 cases of COVID-19 and no deaths this fortnight, bringing the cumulative case count to 27,892 and 907 deaths. Hospitalisations for COVID-19 dropped further in the past two fortnights: there were just two cases admitted to FluCAN participating hospitals and there were no admissions to ICU in SPRINT-SARI sites during this four-week period. New South Wales reported the highest proportion of cases this fortnight (46%; 56/123), all of which were overseas acquired. Locally-acquired cases accounted for 15% (19/123) of all cases reported this fortnight all of which were attributed to a cluster of cases in South Australia. At the end of this reporting period, it had been 24 days since there was a locally-acquired case of unknown source. Testing rates increased to 12.0 tests per 1,000 population per week during this reporting period, driven by a significant increasing in testing in South Australia. The overall positivity rate for the reporting period was 0.03%, will all jurisdictions reporting a positivity rate ≤ 0.10%.

COVID-19 Australia: Epidemiology Report 27: Fortnightly reporting period ending 11 October 2020

Nationally, there was a continuing downward trend in notifications of COVID-19. The daily average number of cases for this reporting period was 14 compared to an average of 23 cases per day in the previous fortnight. There were 192 cases of COVID-19 and 23 deaths this fortnight, bringing the cumulative case count to 27,344 and 898 deaths. While the majority of cases in this reporting period were from Victoria (60%; 116/192), there continues to be a decrease in cases in this state resulting from public health interventions. During this fortnight, 66% (127/192) of all cases were reported as locally acquired, with the majority reported from Victoria (108/127). The highest proportion of overseas-acquired cases was reported in New South Wales (75%; 38/51), followed by Western Australia (22%; 11/51). Although testing rates declined, they remain high overall at 9.2 tests per week per 1,000 persons. There was variability in the testing rate by jurisdiction, with testing rates depending on the epidemic context. The overall positivity rate for the reporting period was 0.05%, with Victoria reporting a positivity rate of 0.08% for this reporting period. In all other jurisdictions the positivity rate was ≤ 0.06%.

COVID-19 Australia: Epidemiology Report 29: Fortnightly reporting period ending 8 November 2020

Nationally, there was a continuing downward trend in notifications of COVID-19. The daily average number of cases for this reporting period was nine, compared to an average of 14 cases per day in the previous fortnight. There were 123 cases of COVID-19 and two deaths this fortnight, bringing the cumulative case count to 27,743 and 904 deaths. New South Wales reported the highest proportion of cases this fortnight (56%; 69/123), the majority of which were overseas acquired (54). Locally-acquired cases accounted for 15% (18/123) of all cases reported this fortnight. Victoria has seen a continuing decline of cases: at the end of this reporting period, 10 days had passed since the last locally-acquired case was reported in this jurisdiction. Testing rates increased during the reporting period and remain high overall at 11.0 tests per week per 1,000 persons. There was variability in the testing rate by jurisdiction, with testing rates depending on the epidemic context. The overall positivity rate for the reporting period was 0.03%, with the Northern Territory reporting a positivity rate of 0.12% for this reporting period. In all other jurisdictions the positivity rate was ≤ 0.06%.

Risk factors for adolescents' mental health during the COVID-19 pandemic: a comparison between Wuhan and other urban areas in China

Background

The outbreak of Coronavirus Disease is causing considerable acute risk to public health and might also have an unanticipated impact on the mental health of children and adolescents in the long run. This study collected data during the national lockdown period in China and aims to understand whether there is a clinically significant difference in anxiety, depression, and parental rearing style when comparing adolescents from Wuhan and other cities in China. This study also intends to examine whether gender, grade in school, single child status, online learning participation, parents’ involvement in COVID-19 related work, and parents being quarantined or infected due to the disease would lead to clinically significant differences in anxiety and depression. Beyond that, this study explored the pathways among the different variables in order to better understand how these factors play a part in impacting adolescents’ mental health condition.

Results

Results showed that there was a statistically significant difference in anxiety symptoms between participants who were from Wuhan compared to other urban areas, but not in depressive symptoms. In addition, participants’ grade level, gender, relative being infected, and study online have direct positive predictive value for depressive and anxiety symptoms, whereas location and sibling status have indirect predictive value. Having relatives who participated in COVID-19 related work only had positive direct predictive value toward depression, but not anxiety.

Conclusions

This study discovered several risk factors for adolescents’ depression and anxiety during the pandemic. It also called for a greater awareness of Wuhan parents’ mental wellbeing and recommended a systematic approach for mental health prevention and intervention.