Optimal adaptive nonpharmaceutical interventions to mitigate the outbreak of respiratory infections following the COVID-19 pandemic: a deep reinforcement learning study in Hong Kong, China.

Background: Long-lasting nonpharmaceutical interventions (NPIs) suppressed the infection of COVID-19 but came at a substantial economic cost and the elevated risk of the outbreak of respiratory infectious diseases (RIDs) following the pandemic. Policymakers need data-driven evidence to guide the relaxation with adaptive NPIs that consider the risk of both COVID-19 and other RIDs outbreaks, as well as the available healthcare resources.

Methods: Combining the COVID-19 data of the sixth wave in Hong Kong between May 31, 2022 and August 28, 2022, 6-year epidemic data of other RIDs (2014-2019), and the healthcare resources data, we constructed compartment models to predict the epidemic curves of RIDs after the COVID-19-targeted NPIs.

Future trajectory of respiratory infections following the COVID-19 pandemic in Hong Kong.

The accumulation of susceptible populations for respiratory infectious diseases (RIDs) when COVID-19-targeted non-pharmaceutical interventions (NPIs) were in place might pose a greater risk of future RID outbreaks. We examined the timing and magnitude of RID resurgence after lifting COVID-19-targeted NPIs and assessed the burdens on the health system. We proposed the Threshold-based Control Method (TCM) to identify data-driven solutions to maintain the resilience of the health system by re-introducing NPIs when the number of severe infections reaches a threshold.

Impacts of Export Restrictions on the Global Personal Protective Equipment Trade Network During COVID-19.

The COVID-19 pandemic has caused a dramatic surge in demand for personal protective equipment (PPE) worldwide. Many countries have imposed export restrictions on PPE to ensure the sufficient domestic supply. The surging demand and export restrictions cause shortage contagions on the global PPE trade network.

Adaptively Weighted k-Tuple Metric Network for Kinship Verification.

Facial image-based kinship verification is a rapidly growing field in computer vision and biometrics. The key to determining whether a pair of facial images has a kin relation is to train a model that can enlarge the margin between the faces that have no kin relation while reducing the distance between faces that have a kin relation. Most existing approaches primarily exploit duplet (i.

Correction: COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment-Based Topic Modeling.

[This corrects the article DOI: 10.2196/31726.].

Equitable access to COVID-19 vaccines makes a life-saving difference to all countries.

Despite broad agreement on the negative consequences of vaccine inequity, the distribution of COVID-19 vaccines is imbalanced. Access to vaccines in high-income countries (HICs) is far greater than in low- and middle-income countries (LMICs). As a result, there continue to be high rates of COVID-19 infections and deaths in LMICs.

Reconstruction of the Transmission Chain of COVID-19 Outbreak in Beijing's Xinfadi Market, China.

Objectives: The aim of the study was to reconstruct the complete transmission chain of the COVID-19 outbreak in Beijing's Xinfadi Market using data from epidemiological investigations, which contributes to reflecting transmission dynamics and transmission risk factors.

Methods: We set up a transmission model, and the model parameters are estimated from the survey data via Markov chain Monte Carlo sampling. Bayesian data augmentation approaches are used to account for uncertainty in the source of infection, unobserved onset, and infection dates.

Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis.

Background: Innovative surveillance methods are needed to assess adherence to COVID-19 recommendations, especially methods that can provide near real-time or highly geographically targeted data. Use of location-based social media image data (eg, Instagram images) is one possible approach that could be explored to address this problem.

Objective: We seek to evaluate whether publicly available near real-time social media images might be used to monitor COVID-19 health policy adherence.

COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment-Based Topic Modeling.

Background: COVID-19 vaccines are one of the most effective preventive strategies for containing the pandemic. Having a better understanding of the public's conceptions of COVID-19 vaccines may aid in the effort to promptly and thoroughly vaccinate the community. However, because no empirical research has yet fully explored the public's vaccine awareness through sentiment-based topic modeling, little is known about the evolution of public attitude since the rollout of COVID-19 vaccines.

Demand-driven spreading patterns of African swine fever in China.

African swine fever (ASF) is a highly contagious hemorrhagic viral disease of domestic and wild pigs. ASF has led to major economic losses and adverse impacts on livelihoods of stakeholders involved in the pork food system in many European and Asian countries. While the epidemiology of ASF virus (ASFV) is fairly well understood, there is neither any effective treatment nor vaccine.

Relationship between angiotensin-converting enzyme inhibitors or angiotensin receptor blockers and COVID-19 incidence or severe disease.

Background: Angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) may be associated with higher susceptibility of COVID-19 infection and adverse outcomes. We compared ACEI/ARB use and COVID-19 positivity in a case-control design, and severity in COVID-19 positive patients.

Methods: Consecutive patients who attended Hong Kong's public hospitals or outpatient clinics between 1 January and 28 July 2020 for COVID-19 real time-PCR (RT-PCR) tests were included.

Automated Generation of Personalized Shock Wave Lithotripsy Protocols: Treatment Planning Using Deep Learning.

Background: Though shock wave lithotripsy (SWL) has developed to be one of the most common treatment approaches for nephrolithiasis in recent decades, its treatment planning is often a trial-and-error process based on physicians' subjective judgement. Physicians' inexperience with this modality can lead to low-quality treatment and unnecessary risks to patients.

Objective: To improve the quality and consistency of shock wave lithotripsy treatment, we aimed to develop a deep learning model for generating the next treatment step by previous steps and preoperative patient characteristics and to produce personalized SWL treatment plans in a step-by-step protocol based on the deep learning model.

Development of a multivariable prediction model for severe COVID-19 disease: a population-based study from Hong Kong.

Recent studies have reported numerous predictors for adverse outcomes in COVID-19 disease. However, there have been few simple clinical risk scores available for prompt risk stratification. The objective is to develop a simple risk score for predicting severe COVID-19 disease using territory-wide data based on simple clinical and laboratory variables.

The impact of non-pharmaceutical interventions on the prevention and control of COVID-19 in New York City.

The emergence of coronavirus disease 2019 (COVID-19) has infected more than 62 million people worldwide. Control responses varied across countries with different outcomes in terms of epidemic size and social disruption. This study presents an age-specific susceptible-exposed-infected-recovery-death model that considers the unique characteristics of COVID-19 to examine the effectiveness of various non-pharmaceutical interventions (NPIs) in New York City (NYC).

The collective wisdom in the COVID-19 research: Comparison and synthesis of epidemiological parameter estimates in preprints and peer-reviewed articles.

Objectives: We aimed to explore the collective wisdom of preprints related to COVID-19 by comparing and synthesizing them with results of peer-reviewed publications.

Methods: PubMed, Google Scholar, medRxiv, bioRxiv, arXiv, and SSRN were searched for papers regarding the estimation of four epidemiological parameters of COVID-19: the basic reproduction number, incubation period, infectious period, and case-fatality-rate. Distributions of parameters and timeliness of preprints and peer-reviewed papers were compared.

Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission.

Motivated by the importance of individual differences in risk perception and behavior change in people's responses to infectious disease outbreaks (particularly the ongoing COVID-19 pandemic), we propose a heterogeneous disease-behavior-information transmission model, in which people's risk of getting infected is influenced by information diffusion, behavior change, and disease transmission. We use both a mean-field approximation and Monte Carlo simulations to analyze the dynamics of the model. Information diffusion influences behavior change by allowing people to be aware of the disease and adopt self-protection and subsequently affects disease transmission by changing the actual infection rate.

Characterizing Social Media Messages Related to Underage JUUL E-Cigarette Buying and Selling: Cross-Sectional Analysis of Reddit Subreddits.

Background: Stopping the epidemic of e-cigarette use among youth has become the common goal of both regulatory authorities and health departments. JUUL is currently the most popular e-cigarette brand on the market. Young people usually obtain and exchange information about JUUL with the help of social media platforms.

Public Reactions to the Cigarette Control Regulation on a Chinese Microblogging Platform: Empirical Analysis.

Background: On January 1, 2019, a new regulation on the control of smoking in public places was officially implemented in Hangzhou, China. On the day of the implementation, a large number of Chinese media reported the contents of the regulation on the microblog platform Weibo, causing a strong response from and heated discussion among netizens.

Objective: This study aimed to conduct a content and network analysis to examine topics and patterns in the social media response to the new regulation.

A Matter of Reevaluation: Incentivizing Users to Contribute Reviews in Online Platforms.

Content sharing platforms such as product review websites largely depend on reviewers' voluntary contributions. In order to motivate reviewers to contribute more, many platforms established incentive mechanisms, either reputation-based or financial. Yet most of the existing research has focused on reputations that are everlasting, such as badges and virtual points, or financial rewards where no evaluation exists about the users' contributed content, such as rebates.

Underage JUUL Use Patterns: Content Analysis of Reddit Messages.

Background: The popularity of JUUL (an e-cigarette brand) among youth has recently been reported in news media and academic papers, which has raised great public health concerns. Little research has been conducted on the age distribution, geographic distribution, approaches to buying JUUL, and flavor preferences pertaining to underage JUUL users.

Objective: The aim of this study was to analyze social media data related to demographics, methods of access, product characteristics, and use patterns of underage JUUL use.

Understanding Users' Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques.

Background: E-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids-much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications.

Objective: This study aimed to understand users' "vaping" experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production).