Outcomes analysis of microsurgical physiologic lymphatic procedures for the upper extremity from the United States National Surgical Quality Improvement Program.

INTRODUCTION: Physiologic microsurgical procedures to treat lymphedema include vascularized lymph node transfer (VLNT) and lymphovenous bypass (LVB). The purpose of this study was to assess 30-day outcomes of VLNT and LVB using the National Surgical Quality Improvement Program (NSQIP) database. METHODS: NSQIP was queried (2012-2018) for lymphatic procedures for upper extremity lymphedema after mastectomy. Prophylactic lymphatic procedures and those for lower extremity lymphedema were excluded. Outcomes were assessed for three groups: LVB, VLNT, and patients who had procedures simultaneously (VLNA+LVB). Primary outcomes measured were operative time, 30-day morbidities, and hospital length of stay. RESULTS: The study included 199 patients who had LVB (n = 43), VLNT (n = 145), or VLNT+LVB (n = 11). There was no difference in co-morbidities between the groups (p = 0.26). 30-day complication rates including unplanned reoperation (6.9% VLNT vs. 2.3% LVB) and readmission (0.69% VLNT vs. none in LVB) were not statistically significant (p = 0.54). Surgical site infection, wound complications, deep vein thromboembolism, and cardiac arrest was also similar among the three groups. Postoperative length of stay for VLNT (2.5 days± 2.3), LVB (1.9 days± 1.9), and VLNT+LVB (2.8 days± 0.3) did not differ significantly (p = 0.20). Operative time for LVB (305.4 min ± 186.7), VLNT (254 min ± 164.4), and VLNT+LVB (295.3 min ± 43.2) was not significantly different (p = 0.21). CONCLUSIONS: Our analysis of the NSQIP data revealed that VLNT and LVB are procedures with no significant difference in perioperative morbidity. Our results support that choice of VLNT versus LVB can be justifiably made per the surgeon's preference and experience as the operations have similar complication rates.

An updated guide to the diagnosis and management of cesarean scar pregnancies.

PURPOSE OF REVIEW: To review the current literature on the diagnosis and management of cesarean scar pregnancies RECENT FINDINGS: The incidence of cesarean scar pregnancies (CSPs) is increasing as a result of the increasing cesarean section rate, improved diagnostic capabilities, and a growing awareness. CSPs are associated with significant morbidity and early diagnosis is key. Diagnosis is best achieved with transvaginal ultrasound. Sonographic diagnostic criteria have been developed over decades and recently endorsed by the Society for Maternal-Fetal Medicine and other professional societies. The current categorization system differentiates CSPs that are endogenic or 'on the scar' from those that are exogenic or 'in the niche'. Following diagnosis, the challenge remains in determining the optimal management as multiple modalities can be considered. Studies have demonstrated the favorable outcomes with combined local and systemic methotrexate, surgical excision through multiple routes, and adjunctive therapies, such as uterine artery embolization or uterine balloons. The current evidence is insufficient to identify a single best treatment course and a combined approach to treatment is often required. SUMMARY: Successful outcomes while minimizing complications can be achieved with a multidisciplinary, collaborative effort. Guidelines for cesarean scar pregnancies will continue to evolve as the published reports grow.

Bracketed radioactive seed localization vs bracketed wire-localization in breast surgery.

Multiple localizers placed in a bracketed fashion facilitates excision of radiographically extensive breast lesions. In this study, bracketed radioactive seed localization (bRSL) was compared to bracketed wire localization (bWL). We hypothesized that bRSL would achieve adequate margins and decrease re-operation rates with similar or less specimen volumes (SV) than bWL. Retrospective review identified patients who underwent bracketed breast procedures at an academic medical center. Data collected included patient demographics, tumor features, treatment variables, and surgical outcomes. Wilcoxon rank-sum test and chi-square test were used to compare continuous and categorical data, respectively. A multivariable logistic regression model was used to evaluate the association between re-excision and localization technique after adjusting for clinically relevant variables. Patients who underwent bWL were 3.9 times more likely to undergo re-excision compared to patients in bRSL group (OR=3.9, 95% CI: 2.0-7.4). Initial and total SV did not significantly differ between the two groups (P=.4). Patients were significantly more likely to undergo a mastectomy in the bWL group than in the bRSL group (24% vs 7%; P<.01). For patients undergoing excision of radiologically extensive breast lesions, bRSL serves as an alternative to bWL. In this retrospective study, bRSL was associated with a decreased re-excision rate with similar SV and a lower rate of mastectomy when compared to bWL.

COVID-19 Pandemic Risk Assessment: Systematic Review.

Background: The COVID-19 pandemic presents the possibility of future large-scale infectious disease outbreaks. In response, we conducted a systematic review of COVID-19 pandemic risk assessment to provide insights into countries' pandemic surveillance and preparedness for potential pandemic events in the post-COVID-19 era. Objective: We aim to systematically identify relevant articles and synthesize pandemic risk assessment findings to facilitate government officials and public health experts in crisis planning. Methods: This study followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and included over 620,000 records from the World Health Organization COVID-19 Research Database. Articles related to pandemic risk assessment were identified based on a set of inclusion and exclusion criteria. Relevant articles were characterized based on study location, variable types, data-visualization techniques, research objectives, and methodologies. Findings were presented using tables and charts. Results: Sixty-two articles satisfying both the inclusion and exclusion criteria were identified. Among the articles, 32.3% focused on local areas, while another 32.3% had a global coverage. Epidemic data were the most commonly used variables (74.2% of articles), with over half of them (51.6%) employing two or more variable types. The research objectives covered various aspects of the COVID-19 pandemic, with risk exposure assessment and identification of risk factors being the most common theme (35.5%). No dominant research methodology for risk assessment emerged from these articles. Conclusion: Our synthesized findings support proactive planning and development of prevention and control measures in anticipation of future public health threats.

Do Scholars Respond Faster Than Google Trends in Discussing COVID-19 Issues? An Approach to Textual Big Data.

Background: The COVID-19 pandemic has posed various difficulties for policymakers, such as the identification of health issues, establishment of policy priorities, formulation of regulations, and promotion of economic competitiveness. Evidence-based practices and data-driven decision-making have been recognized as valuable tools for improving the policymaking process. Nevertheless, due to the abundance of data, there is a need to develop sophisticated analytical techniques and tools to efficiently extract and analyze the data. Methods: Using Oxford COVID-19 Government Response Tracker, we categorize the policy responses into 6 different categories: (a) containment and closure, (b) health systems, (c) vaccines, (d) economic, (e) country, and (f) others. We proposed a novel research framework to compare the response times of the scholars and the general public. To achieve this, we analyzed more than 400,000 research abstracts published over the past 2.5 years, along with text information from Google Trends as a proxy for topics of public concern. We introduced an innovative text-mining method: coherent topic clustering to analyze the huge number of abstracts. Results: Our results show that the research abstracts not only discussed almost all of the COVID-19 issues earlier than Google Trends did, but they also provided more in-depth coverage. This should help policymakers identify core COVID-19 issues and act earlier. Besides, our clustering method can better reflect the main messages of the abstracts than a recent advanced deep learning-based topic modeling tool. Conclusion: Scholars generally have a faster response in discussing COVID-19 issues than Google Trends.

A fear conditioned cue orchestrates a suite of behaviors in rats.

Pavlovian fear conditioning has been extensively used to study the behavioral and neural basis of defensive systems. In a typical procedure, a cue is paired with foot shock, and subsequent cue presentation elicits freezing, a behavior theoretically linked to predator detection. Studies have since shown a fear conditioned cue can elicit locomotion, a behavior that - in addition to jumping, and rearing - is theoretically linked to imminent or occurring predation. A criticism of studies observing fear conditioned cue-elicited locomotion is that responding is non-associative. We gave rats Pavlovian fear discrimination over a baseline of reward seeking. TTL-triggered cameras captured 5 behavior frames/s around cue presentation. Experiment 1 examined the emergence of danger-specific behaviors over fear acquisition. Experiment 2 examined the expression of danger-specific behaviors in fear extinction. In total, we scored 112,000 frames for nine discrete behavior categories. Temporal ethograms show that during acquisition, a fear conditioned cue suppresses reward seeking and elicits freezing, but also elicits locomotion, jumping, and rearing - all of which are maximal when foot shock is imminent. During extinction, a fear conditioned cue most prominently suppresses reward seeking, and elicits locomotion that is timed to shock delivery. The independent expression of these behaviors in both experiments reveals a fear conditioned cue to orchestrate a temporally organized suite of behaviors.

Knowing that an animal is fearful is crucial for many psychology and neuroscience studies. For instance, this knowledge allows researchers to examine the brain pathways involved in processing and responding to fear. Typically, researchers consider that a rodent is experiencing fear if it 'freezes' ­ a response which, in the wild, helps to evade detection by predators. In Pavlovian fear conditioning experiments, for example, rats and mice freeze when exposed to a stimulus (often a specific sound) previously associated with unpleasant sensations. However, rodents can also respond more actively to threats, for instance by running or jumping away. It remains unclear whether the 'fearful stimuli' used in Pavlovian approaches specifically elicits only freezing, or other fear-related behaviors as well. To investigate this, Chu et al. used high-speed cameras to record rats' responses to a sound cue they had 'learned' to associate with a mild foot shock. In addition to freezing, the animals ran, jumped, stood on their hind legs and stopped their usual reward-seeking behavior in response to the cue. Crucially, these reactions were absent when the rats were exposed to sound cues not associated with pain. Overall, these experiments demonstrate that Pavlovian conditioning can elicit a full range of fear-related behaviors beyond freezing. Understanding the neural activity behind these diverse responses could lead to more targeted therapies and interventions addressing the various ways stress and anxiety manifest in people.

A moving-window bayesian network model for assessing systemic risk in financial markets.

Systemic risk refers to the uncertainty that arises due to the breakdown of a financial system. The concept of "too connected to fail" suggests that network connectedness plays an important role in measuring systemic risk. In this paper, we first recover a time series of Bayesian networks for stock returns, which allow the direction of links among stock returns to be formed with Markov properties in directed graphs. We rank the stocks in the time series of Bayesian networks based on the topological orders of the stocks in the learned Bayesian networks and develop an order distance, a new measure with which to assess the changes in the topological orders of the stocks. In an empirical study using stock data from the Hang Seng Index in Hong Kong and the Dow Jones Industrial Average, we use the order distance to predict the extreme absolute return, which is a proxy of extreme market risks, or a signal of systemic risks, using the LASSO regression model. Our results indicate that the network statistics of the time series of Bayesian networks and the order distance substantially improve the predictability of extreme absolute returns and provide insights into the assessment of systemic risk.

Interviewer bias when using multiple mini-interviews in selecting student nurses in a Chinese setting.

BACKGROUND: Interviewer effects may cause unfairness in assessments in multiple mini-interviews (MMIs). Due to cultural differences, the bias factors of interviewers may vary between the East and the West. MMIs are a relatively new type of assessment setting in China and few studies have been conducted to examine the interviewer effects of MMIs in this context. OBJECTIVES: We adopted a multi-faceted Rasch measurement (MFRM) to measure interviewer effects in assessments in Hong Kong. METHODS: Data were collected from a nursing school in Hong Kong. There were 431 candidates and 12 interviewers engaged in a six-station MMI setting. The scores collected from the interviews were analyzed in terms of 1) interviewer stringency/leniency, 2) candidate gender, 3) interview time, and 4) rating category in the station. The Student's t-statistic values were calculated to investigate the marking tendencies of individual interviewers. RESULTS: The research findings suggest that interviewers differ in their degree of stringency/leniency, but the number of candidates examined by each interviewer does not affect interviewer stringency/leniency in terms of the interviewer's assessment. There is not sufficient evidence indicating that candidate gender and interview time are bias factors affecting assessment score in this study. Among the six rating categories examined, honesty/integrity is the most stringent category, while self-awareness is the most lenient category. Interview bias from individuals was identified. When we consider the interview scores given by individual interviewers, it is evident that some interviewers may have been biased toward a certain gender or rating categories. CONCLUSIONS: MMIs are useful when selecting student nurses in a Chinese setting. However, interviewer bias may exist. We used an MFRM to better understand interviewer bias across various dimensions. The present study contributes to the development and use of MMIs in non-Western countries and can be used as a reference to extend this research to other locations.

Optogenetic inhibition of the caudal substantia nigra inflates behavioral responding to uncertain threat and safety.

Defensive responding is adaptive when it approximates current threat, but maladaptive when it exceeds current threat. Here we asked if the substantia nigra, a region consistently implicated in reward, is necessary to show appropriate levels of defensive responding in Pavlovian fear discrimination. Rats received bilateral transduction of the caudal substantia nigra with halorhodopsin or a control fluorophore, and bilateral ferrule implants. Rats then behaviorally discriminated cues predicting unique foot shock probabilities (danger, p =1; uncertainty, p =0.25; and safety, p =0). Green-light illumination (532 nm) during cue presentation inflated defensive responding of halorhodopsin rats - measured by suppression of reward seeking - to uncertainty and safety beyond control levels. Green-light illumination outside of cue presentation had no impact on halorhodopsin or control rat responding. The results reveal caudal substantia nigra cue activity is necessary to inhibit defensive responding to non-threatening and uncertain threat cues.

Optogenetic inhibition of the caudal substantia nigra inflates behavioral responding to uncertain threat and safety.

Defensive responding is adaptive when it approximates the current threat but maladaptive when it exceeds the current threat. Here we asked if the substantia nigra, a region consistently implicated in reward, is necessary to show appropriate levels of defensive responding in Pavlovian fear discrimination. Rats received bilateral transduction of the caudal substantia nigra with halorhodopsin or a control fluorophore and bilateral ferrule implants. Rats then behaviorally discriminated cues predicting unique foot shock probabilities (danger, p = 1; uncertainty, p = .25; and safety, p = 0). Green-light illumination (532 nm) during cue presentation inflated defensive responding of halorhodopsin rats-measured by suppression of reward seeking-to uncertainty and safety beyond control levels. Green-light illumination outside of cue presentation had no impact on halorhodopsin or control rat responding. The results reveal caudal substantia nigra cue activity is necessary to inhibit defensive responding to nonthreatening and uncertain threat cues. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Standardized local assortativity in networks and systemic risk in financial markets.

The study of assortativity allows us to understand the heterogeneity of networks and the implication of network resilience. While a global measure has been predominantly used to characterize this network feature, there has been little research to suggest a local coefficient to account for the presence of local (dis)assortative patterns in diversely mixed networks. We build on existing literature and extend the concept of assortativity with the proposal of a standardized scale-independent local coefficient to observe the assortative characteristics of each entity in networks that would otherwise be smoothed out with a global measure. This coefficient provides a lens through which the granular level of details can be observed, as well as capturing possible pattern (dis)formation in dynamic networks. We demonstrate how the standardized local assortative coefficient discovers the presence of (dis)assortative hubs in static networks on a granular level, and how it tracks systemic risk in dynamic financial networks.

Enhancing the Predictive Power of Google Trends Data Through Network Analysis: Infodemiology Study of COVID-19.

BACKGROUND: The COVID-19 outbreak has revealed a high demand for timely surveillance of pandemic developments. Google Trends (GT), which provides freely available search volume data, has been proven to be a reliable forecast and nowcast measure for public health issues. Previous studies have tended to use relative search volumes from GT directly to analyze associations and predict the progression of pandemic. However, GT's normalization of the search volumes data and data retrieval restrictions affect the data resolution in reflecting the actual search behaviors, thus limiting the potential for using GT data to predict disease outbreaks. OBJECTIVE: This study aimed to introduce a merged algorithm that helps recover the resolution and accuracy of the search volume data extracted from GT over long observation periods. In addition, this study also aimed to demonstrate the extended application of merged search volumes (MSVs) in combination of network analysis, via tracking the COVID-19 pandemic risk. METHODS: We collected relative search volumes from GT and transformed them into MSVs using our proposed merged algorithm. The MSVs of the selected coronavirus-related keywords were compiled using the rolling window method. The correlations between the MSVs were calculated to form a dynamic network. The network statistics, including network density and the global clustering coefficients between the MSVs, were also calculated. RESULTS: Our research findings suggested that although GT restricts the search data retrieval into weekly data points over a long period, our proposed approach could recover the daily search volume over the same investigation period to facilitate subsequent research analyses. In addition, the dynamic time warping diagrams show that the dynamic networks were capable of predicting the COVID-19 pandemic trends, in terms of the number of COVID-19 confirmed cases and severity risk scores. CONCLUSIONS: The innovative method for handling GT search data and the application of MSVs and network analysis to broaden the potential for GT data are useful for predicting the pandemic risk. Further investigation of the GT dynamic network can focus on noncommunicable diseases, health-related behaviors, and misinformation on the internet.

An automatic speech analytics program for digital assessment of stress burden and psychosocial health.

The stress burden generated from family caregiving makes caregivers particularly prone to developing psychosocial health issues; however, with early diagnosis and intervention, disease progression and long-term disability can be prevented. We developed an automatic speech analytics program (ASAP) for the detection of psychosocial health issues based on clients' speech. One hundred Cantonese-speaking family caregivers were recruited with the results suggesting that the ASAP can identify family caregivers with low or high stress burden levels with an accuracy rate of 72%. The findings indicate that digital health technology can be used to assist in the psychosocial health assessment. While the conventional method requires rigorous assessments by specialists with multiple rounds of questioning, the ASAP can provide a cost-effective and immediate initial assessment to identify high levels of stress among family caregivers so they can be referred to social workers and healthcare professionals for further assessments and treatments.

Isthmocele endometriosis: the relationship between cesarean section and endometriosis.

OBJECTIVE: To present a case of endometriosis within an isthmocele membrane and concomitant diffuse peritoneal endometriosis after cesarean sections. In addition, we describe a unique, color-contrasted surgical repair technique and propose a possible correlation between isthmocele formation and endometriosis. DESIGN: Narrated video article featuring the diagnosis, unique surgical management, and pathological findings of a case of isthmocele endometriosis. Informed consent was obtained from the patient, and all identifiers were removed. SETTING: University-affiliated hospital. PATIENT(S): A 44-year-old patient with three prior cesarean sections and a laparoscopic appendectomy, in none of which endometriosis was visualized. She presented with progressive pelvic pain, dysmenorrhea, dyspareunia, and secondary infertility with recurrent embryo transfer failures. The progressively debilitating symptoms started 14 years ago, shortly after her last cesarean section. Magnetic resonance imaging and ultrasound demonstrated a retroverted uterus and a prominent, thin, fluid-filled cesarean scar defect with a residual myometrial thickness of 1.1 mm. INTERVENTION(S): A combined hysteroscopic and laparoscopic approach was performed to allow for complete resection of the defect and reconstruction of the myometrium. The bladder was backfilled with indocyanine green dye to help identify its borders. Methylene blue was added to the hysteroscopy irrigation solution to create contrast and assist with the isthmocele identification. Wide excision of the isthmocele was performed, followed by a three-layer closure and excision of all apparent peritoneal lesions using the Aqua Blue Contrast Technique. MAIN OUTCOME MEASURE(S): Restoration of normal anatomy, resection of isthmocele, and resolution of the symptoms. RESULT(S): In the pathological assessment, multiple foci of endometriosis were identified within the isthmocele membrane, clearly differentiated from intrauterine endometrial tissue. Additionally, all seven excised peritoneal specimens contained peritoneal endometriosis. Two weeks after the procedure, a transvaginal sonographic scan confirmed a thick anterior uterine wall with a myometrial thickness of 9.2 mm, and the patient reported almost complete resolution of her symptoms. CONCLUSION(S): This case demonstrates endometriosis within the isthmocele membrane, with concomitant symptomatic peritoneal endometriosis. We propose a laparoscopic isthmocele excision technique and a three-layer reconstruction, followed by peritoneal endometriosis excision using methylene blue contrast. We suggest a possible link between isthmocele and endometriosis and emphasize the need for wide excision of the isthmocele margins and maintaining clean borders, given the possibility of endometriosis within the isthmocele, which may be a cause or a contributor to the tissue weakness and isthmocele formation.

Habit-Does It Matter? Bringing Habit and Emotion into the Development of Consumer's Food Waste Reduction Behavior with the Lens of the Theory of Interpersonal Behavior.

The immense food waste, generated by restaurants is not only a serious burden for the foodservice business but also a cause of anguish for the emerging nations in which eating out is becoming increasingly trendy. Consumers' food wastes account for a significant portion of restaurant food waste, indicating the need for a change in consumers' behavior to minimize food waste. To examine this problem, our study sought to identify the elements that influence restaurant consumers' behaviors on food waste reduction, reuse, and recycling. The influence of anticipated positive emotions, awareness of consequences, environmental knowledge, and social norms on waste reduction intentions were examined by using a quantitative technique in the investigation. Furthermore, the influence of habits, waste reduction intentions, and facilitating conditions on food waste reduction, reuse, and recycling behaviors have also been investigated. The study collected 1063 responses and employed the PLS-SEM approach to verify the hypotheses. The results suggested that anticipated positive emotions, awareness of consequences, environmental knowledge, and social norms all have substantial impacts on waste reduction intentions. In addition, habits, waste reduction intentions, and facilitating conditions have noteworthy influences on consumers' behaviors towards food waste reduction, reuse, and recycling in restaurants. Understanding these elements could help in correcting customers' waste behaviors in restaurants. The findings in this study are useful for managers, policymakers, and researchers who want to solve the problems of food waste. The implications, limits, and suggestions for further studies have also been discussed in our study.

Learning from work-from-home issues during the COVID-19 pandemic: Balance speaks louder than words.

During the 2019 novel coronavirus disease (COVID-19) pandemic, many employees have switched to working from home. Despite the findings of previous research that working from home can improve productivity, the scale, nature, and purpose of those studies are not the same as in the current situation with the COVID-19 pandemic. We studied the effects that three stress relievers of the work-from-home environment-company support, supervisor's trust in the subordinate, and work-life balance-had on employees' psychological well-being (stress and happiness), which in turn influenced productivity and engagement in non-work-related activities during working hours. In order to collect honest responses on sensitive questions or negative forms of behavior including stress and non-work-related activities, we adopted the randomized response technique in the survey design to minimize response bias. We collected a total of 500 valid responses and analyzed the results with structural equation modelling. We found that among the three stress relievers, work-life balance was the only significant construct that affected psychological well-being. Stress when working from home promoted non-work-related activities during working hours, whereas happiness improved productivity. Interestingly, non-work-related activities had no significant effect on productivity. The research findings provide evidence that management's maintenance of a healthy work-life balance for colleagues when they are working from home is important for supporting their psychosocial well-being and in turn upholding their work productivity.

Assessing systemic risk in financial markets using dynamic topic networks.

Systemic risk in financial markets refers to the breakdown of a financial system due to global events, catastrophes, or extreme incidents, leading to huge financial instability and losses. This study proposes a dynamic topic network (DTN) approach that combines topic modelling and network analysis to assess systemic risk in financial markets. We make use of Latent Dirichlet Allocation (LDA) to semantically analyse news articles, and the extracted topics then serve as input to construct topic similarity networks over time. Our results indicate how connected the topics are so that we can correlate any abnormal behaviours with volatility in the financial markets. With the 2015-2016 stock market selloff and COVID-19 as use cases, our results also suggest that the proposed DTN approach can provide an indication of (a) abnormal movement in the Dow Jones Industrial Average and (b) when the market would gradually begin to recover from such an event. From a practical risk management point of view, this analysis can be carried out on a daily basis when new data come in so that we can make use of the calculated metrics to predict real-time systemic risk in financial markets.

Predicting the burden of family caregivers from their individual characteristics.

This study examined the association between caregivers' burdens and their individual characteristics and identified characteristics that are useful for predicting the level of caregiver burden. We successfully surveyed 387 family caregivers, having them complete the caregiver burden inventory scale (CBI) and an individual characteristic questionnaire. When we compared the average CBI scores between groups with a particular individual characteristic (including caring for older adult(s), educational level, employment status, place of birth, marital status, financial status, need for family support, need for friend support, and need for nonprofit organizational support), we found a significant difference in the average scores. From a logistic regression model, with burden level as the outcome, we found that caring for older adult(s), educational level, employment status, place of birth, financial situation, and need for nonprofit organizational support were significant predictors of the burden level of caregivers. The research findings suggest that certain individual characteristics can be adopted for identifying and quantifying caregivers who may have a higher level of burden. The findings are useful to uncover caregivers who may need prompt support and social care.

On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics.

The spread of coronavirus disease 2019 (COVID-19) has caused more than 80 million confirmed infected cases and more than 1.8 million people died as of 31 December 2020. While it is essential to quantify risk and characterize transmission dynamics in closed populations using Susceptible-Infection-Recovered modeling, the investigation of the effect from worldwide pandemic cannot be neglected. This study proposes a network analysis to assess global pandemic risk by linking 164 countries in pandemic networks, where links between countries were specified by the level of 'co-movement' of newly confirmed COVID-19 cases. More countries showing increase in the COVID-19 cases simultaneously will signal the pandemic prevalent over the world. The network density, clustering coefficients, and assortativity in the pandemic networks provide early warning signals of the pandemic in late February 2020. We propose a preparedness pandemic risk score for prediction and a severity risk score for pandemic control. The preparedness risk score contributed by countries in Asia is between 25% and 50% most of the time after February and America contributes around 40% in July 2020. The high preparedness risk contribution implies the importance of travel restrictions between those countries. The severity risk score of America and Europe contribute around 90% in December 2020, signifying that the control of COVID-19 is still worrying in America and Europe. We can keep track of the pandemic situation in each country using an online dashboard to update the pandemic risk scores and contributions.

Dynamic Network Analysis of COVID-19 with a Latent Pandemic Space Model.

In this paper, we propose a latent pandemic space modeling approach for analyzing coronavirus disease 2019 (COVID-19) pandemic data. We developed a pandemic space concept that locates different regions so that their connections can be quantified according to the distances between them. A main feature of the pandemic space is to allow visualization of the pandemic status over time through the connectedness between regions. We applied the latent pandemic space model to dynamic pandemic networks constructed using data of confirmed cases of COVID-19 in 164 countries. We observed the ways in which pandemic risk evolves by tracing changes in the locations of countries within the pandemic space. Empirical results gained through this pandemic space analysis can be used to quantify the effectiveness of lockdowns, travel restrictions, and other measures in regard to reducing transmission risk across countries.