A Smartphone-based Zero-Effort Method for Mitigating Epidemic Propagation (preprint)

A large number of epidemics, including COVID-19 and SARS, spread through droplets, quickly swept the world and claimed the precious lives of large numbers of people. Building a low-cost and real-time epidemic early warning system to identify individuals who have been in contact with infected individuals and determine whether they need to be quarantined is an effective means to mitigate the spread of the epidemic. In this paper, we propose a smartphone-based zero-effort epidemic warning method for mitigating epidemic propagation. Firstly, we recognize epidemic-related voice activity relevant to epidemics spread by hierarchical attention mechanism and temporal convolutional network. The hierarchical attention mechanism is used to find local important information through global scanning, then enhances useful information and suppresses useless information. Subsequently, we estimate the social distance between users through sensors built-in smartphone. Furthermore, we combine Wi-Fi network logs and social distance to comprehensively judge whether there is spatiotemporal contact between users and determine the duration of contact. Finally, we estimate infection risk based on epidemic-related vocal activity, social distance, and contact time. We conduct a large number of well-designed experiments in typical scenarios to fully verify the proposed method. The proposed method does not rely on any additional infrastructure and historical training data, which is conducive to integration with epidemic prevention and control systems and large-scale applications.

Tracking disclosure change trajectories for financial fraud detection

The global economic disruption brought by COVID-19 crisis can set a stage for the prevalence of financial statement frauds, which jeopardize the efficient functioning of capital markets. In this paper, we propose a nuanced method to detect frauds by tracking granular changes in disclosures over time. Specifically, we first align paragraphs between consecutive disclosures by their similarities. This alignment can be solved as an optimization-based matching problem. Then we identify three types of changed contents: recurrent, newly added, and deleted contents. For each type, we measure the changes in terms of fraud-relevant linguistics features, such as sentiment and uncertainties. Further, we formulate a firm's Management Discussion and Analysis change trajectory over years as a multivariate time series composed of these granular metrics. We implement a deep learning model to predict frauds using the change trajectory as an input. Extensive experiments demonstrate that our model significantly outperforms benchmark models, and its performance increases with the length of the change trajectory. Moreover, we found specific types of changes are strongly associated with frauds, including weak modal or reward words in newly added or deleted contents. Our work provides an optimization-based method to define change trajectories and trace information mutation in narratives. Finally, our study contributes to the fraud detection literature with a new predictive signal-disclosure change trajectories with an effective deep learning architecture.

Data-driven analytics of COVID-19 ‘infodemic’

The rampant of COVID-19 infodemic has almost been simultaneous with the outbreak of the pandemic. Many concerted efforts are made to mitigate its negative effect to information credibility and data legitimacy. Existing work mainly focuses on fact-checking algorithms or multi-class labeling models that are less aware of the intrinsic characteristics of the language. Nor is it discussed how such representations can account for the common psycho-socio-behavior of the information consumers. This work takes a data-driven analytical approach to (1) describe the prominent lexical and grammatical features of COVID-19 misinformation;(2) interpret the underlying (psycho-)linguistic triggers in terms of sentiment, power and activity based on the affective control theory;(3) study the feature indexing for anti-infodemic modeling. The results show distinct language generalization patterns of misinformation of favoring evaluative terms and multimedia devices in delivering a negative sentiment. Such appeals are effective to arouse people’s sympathy toward the vulnerable community and foment their spreading behavior.

Comorbidity of hepatic cystic echinococcosis with HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma. (Theme Issue: New advances in the precise diagnosis and treatment of liver cancer.) [Chinese]

Objective: To investigate the comorbidity of hepatic cystic echinococcosis with HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma, and to lay a foundation for further research on the influence of hepatic cystic echinococcosis on HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma.

Insisting on Life Dignity: Advance Care Planning in Taiwan During COVID-19 Pandemic (preprint)

Background:The coronavirus disease 2019 (COVID-19) outbreak is a global public health crisis that has affected the implementation of advance care planning (ACP) in Taiwan. The purpose of this study is to (1) confirm that COVID-19 significantly reduced public participation in ACP, (2) identify factors influencing the implementation of ACP during the COVID-19 pandemic and how they differ from those before the COVID-19 outbreak.Methods: An observational study from retrospective review of medical chart and clinical information.This is a hospital-based study to examine the characteristics of ACP implementation in Taiwan during COVID-19. A total of 1,253 participants were recruited, including 916 people who had completed ACP from September through December 2019, and 337 people from January through April 2020.Results:This study representing an approximately 65% decrease in ACP participation after COVID-19 outbreak. The cancellation rate of ACP during COVID-19 is higher before outbreak. After COVID-19 outbreak, Participation rate of disadvantaged populations increased from 16.92% to 21.66%. The percentage of participants with caregiver experiences decreased from 31.66%to to 23.44% . Participants who did not wish for their families to bear decision-making responsibilities increased from 44.00% to 52.52%. The percentage of offspring participation increased from 86.57% to 90.80%. The percentage of individuals completing ACP after the outbreak without signing an advance directive increased from 5.57% to 9.20%. The COVID-19 pandemic significantly reduced participation in ACP. Conclusions: This study directly compared the ACP implementation before and after COVID-19, which is a tremendous global health crisis influencing the conceptions of life and death.COVID-19 has threatened the public’s health and has changed ACP in the healthcare system by increasing public awareness of the topic of death. After COVID-19, both medical staff and the public should clearly express their opinions on terminal care.Policy supports and active participation of medical team can encourage disadvantages to complete ACP.Healthcare workers should provide palliative and terminal care services in which patient comfort and dignity are the primary focus of care.Trial registration:This study was approved on 3 June 2020 by the Taipei City Hospital Institutional Review Board (Case No.: TCHIRB-10808008-E).

Global air quality change during the COVID-19 pandemic: Regionally different ozone pollution responses: COVID-19疫情期间全球空气质量变化:臭氧响应的区域间差异

The explosive spread of the 2019 novel coronavirus (COVID-19) provides a unique chance to rethink the relationship between human activity and air pollution. Though related studies have revealed substantial reductions in primary emissions, obvious differences do exist in the responses of secondary pollutants, like ozone (O3) pollution. However, the regional disparities of O3 responses and their causes have still not been fully investigated. To better elucidate the interrelationship between anthropogenic emissions, chemical production, and meteorological conditions, O3 responses caused by lockdowns over different regions were comprehensively explored at a global scale. Observational signals of air-quality change were derived from multi-year surface measurements and satellite retrievals. With similar substantial drops in nitrogen dioxide (NO2), ozone shows rising signals in most areas of both East Asia and Europe, even up to ∼14 ppb, while a non-negligible declining signal exists in North America, by about 2–4 ppb. Furthermore, the drivers behind the different O3 responses are discussed based on meteorological analysis and O3 sensitivity diagnosis. On the one hand, O3 responses to NO2 declines can be affected by the primary dependence on its precursors. On the other hand, it is also highly dependent on meteorological factors, especially temperature. Our study further highlights the great importance of taking into consideration both the regional disparities and synergistic effects of precursor reductions and meteorological influence for scientific mitigation of O3 pollution. 摘要: 疫情期间全球各地一次排放大幅削减, 而臭氧等二次污染的响应则存在着区域间差异.结合地面和卫星观测发现, 同在氮氧化物大幅下降的情况下,臭氧在东亚和欧洲呈现出可达14ppb的上升信号, 而北美则下降为主 (约2-4ppb) .我们结合气象分析和臭氧敏感性进一步讨论了臭氧响应差异性的原因, 一方面受臭氧与前体物间关系的影响;另一方面来自于气象, 尤其是温度.研究明晰了人为排放,化学和气象三者的内在关联, 强调了在臭氧控制过程中考虑前体物削减和气象条件协同的重要性.

Differential effects of Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers on COVID-19 (preprint)

BackgroundThe effect of angiotensin-converting enzyme inhibitor/angiotensin receptor blockers (ACEI/ARB) on the COVID-19 remains controversial from clinic evidence. MethodsThis is a retrospective, two-center case series of 198 consecutive COVID-19 patients with a history of hypertension. ResultsAmong 198 patients, 58 (29.3%) and 16 (8.1%) were on were on ARB and ACEI, respectively. Patients who were on ARB or ACEI/ARB had a significantly lower rate of severe illness and ARDS when compared with patients treated with ACEI alone or not receiving and RAAS blocker (P＜0.05). The Kaplan-Meier survival curve showed that patients with ARB in their antihypertensive regimen had a trend towards a higher survival rate when compared with individuals without ARB (adjusted hazard ratio, 0.27; 95% CI, 0.07-1.02; P = 0.054). The Cox-regression analysis to compared ACEI vs. ARB groups showed a significantly lower mortality rate in the ARB group (adjusted hazard ratio, 0.03; 95% CI, 0.00-0.58; P = 0.02). ConclusionsUsing of ARB was associated with a reduced rate of severe illness and ARDS, indicating their potential protective impact in COVID-19.

Retrospective analysis of the clinical features of outpatients with novel coronavirus in areas outside Wuhan, China (preprint)

Objective: The novel coronavirus pneumonia (COVID-19) has spread rapidly across the globe with the movement of people. How to diagnose COVID-19 quickly and accurately is a concern for all. We retrospectively assessed the clinical characteristics of patients with COVID-19 detected by outpatient screening in areas outside Wuhan, China, to guide early screening outside the epidemic area, to isolate and treat COVID-19-positive patients, and to control the spread of this virus in the region.Results: Among the 213 patients treated in the fever clinic of our hospital, 41 tested positive for novel coronavirus (2019-nCoV) and 172 were negative. Among the positive patients, 13 (31.7%) of the patients had been to Wuhan, while 28 (68.3%) had not been to Wuhan. There were 4 cases of clustering occurrence. The main symptoms exhibited by COVID-19-positive patients were fever (87.8%), cough (68.3%), and expectoration (34.1%). The C-reactive protein (CRP) levels were increased in 35 (85.3%) positive patients; the hydroxybutyrate dehydrogenase in the myocardial zymogram was increased in 22 positive patients (53.6%) and 38 negative patients (22.1%); computed tomography (CT) findings revealed lung lesions in all 41 positive patients (100%).Conclusion: We classified the patient population and analyzed the data to understand the early clinical performance of COVID-19. Our research illustrate that screening for COVID-19 outside Wuhan should focus on early symptoms such as fever and cough, in combination with lung CT findings, epidemiological history, and sputum pathogen detection to determine whether patients need further isolation.