The impact of crowd gatherings on the spread of COVID-19

Respiratory Viruses in Patients With Hematological Malignancy in Boreal Autumn/Winter 2023-2024: EPICOVIDEHA-EPIFLUEHA Report

Community-acquired respiratory viral infections (CARV) significantly impact patients with hematological malignancies (HM), leading to high morbidity and mortality. However, large-scale, real-world data on CARV in these patients is limited. This study analyzed data from the EPICOVIDEHA-EPIFLUEHA registry, focusing on patients with HM diagnosed with CARV during the 2023-2024 autumn-winter season. The study assessed epidemiology, clinical characteristics, risk factors, and outcomes. The study examined 1312 patients with HM diagnosed with CARV during the 2023-2024 autumn-winter season. Of these, 59.5% required hospitalization, with 13.5% needing ICU admission. The overall mortality rate was 10.6%, varying by virus: parainfluenza (21.3%), influenza (8.8%), metapneumovirus (7.1%), RSV (5.9%), or SARS-CoV-2 (5.0%). Poor outcomes were significantly associated with smoking history, severe lymphopenia, secondary bacterial infections, and ICU admission. This study highlights the severe risk CARV poses to patients with HM, especially those undergoing active treatment. The high rates of hospitalization and mortality stress the need for better prevention, early diagnosis, and targeted therapies. Given the severe outcomes with certain viruses like parainfluenza, tailored strategies are crucial to improving patient outcomes in future CARV seasons.

Role of Gut Microbiota in Long COVID: Impact on Immune Function and Organ System Health

SARS-CoV-2 infection has led to a range of long-lasting symptoms, collectively referred to as long COVID. Current research highlights the critical role of angiotensin-converting enzyme 2 (ACE2) in regulating gut microbiota diversity, vascular function, and homeostasis within the renin-angiotensin system (RAS). ACE2 is utilized by the SARS-CoV-2 virus to enter host cells, but its downregulation following infection contributes to gut microbiota dysbiosis and RAS disruption. These imbalances have been linked to a range of long COVID symptoms, including joint pain, chest pain, chronic cough, fatigue, brain fog, anxiety, depression, myalgia, peripheral neuropathy, memory difficulties, and impaired attention. This review investigates the dysregulation caused by SARS-CoV-2 infection and the long-term effects it has on various organ systems, including the musculoskeletal, neurological, renal, respiratory, and cardiovascular systems. We explored the bidirectional interactions between the gut microbiota, immune function, and these organ systems, focusing on how microbiota dysregulation contributes to the chronic inflammation and dysfunction observed in long COVID symptoms. Understanding these interactions is key for identifying effective therapeutic strategies and interventional targets aimed at mitigating the impact of long COVID on organ health and improving patient outcomes.

MobCovid: Confirmed Cases Dynamics Driven Time Series Prediction of Crowd in Urban Hotspot

Monitoring the crowd in urban hot spot has been an important research topic in the field of urban management and has high social impact. It can allow more flexible allocation of public resources such as public transportation schedule adjustment and arrangement of police force. After 2020, because of the epidemic of COVID-19 virus, the public mobility pattern is deeply affected by the situation of epidemic as the physical close contact is the dominant way of infection. In this study, we propose a confirmed case-driven time-series prediction of crowd in urban hot spot named MobCovid. The model is a deviation of Informer, a popular time-serial prediction model proposed in 2021. The model takes both the number of nighttime staying people in downtown and confirmed cases of COVID-19 as input and predicts both the targets. In the current period of COVID, many areas and countries have relaxed the lockdown measures on public mobility. The outdoor travel of public is based on individual decision. Report of large amount of confirmed cases would restrict the public visitation of crowded downtown. But, still, government would publish some policies to try to intervene in the public mobility and control the spread of virus. For example, in Japan, there are no compulsory measures to force people to stay at home, but measures to persuade people to stay away from downtown area. Therefore, we also merge the encoding of policies on measures of mobility restriction made by government in the model to improve the precision. We use historical data of nighttime staying people in crowded downtown and confirmed cases of Tokyo and Osaka area as study case. Multiple times of comparison with other baselines including the original Informer model prove the effectiveness of our proposed method. We believe our work can make contribution to the current knowledge on forecasting the number of crowd in urban downtown during the Covid epidemic.

Estimated relative potential for airborne SARS-CoV-2 transmission in a day care centre

We estimated the hourly probability of airborne severe acute respiratory coronavirus 2 (SARS-CoV-2) transmission and further the estimated number of persons at transmission risk in a day care centre by calculating the inhaled dose for airborne pathogens based on their concentration, exposure time and activity. Information about the occupancy and activity of the rooms was collected from day care centre personnel and building characteristics were obtained from the design values. The generation rate of pathogens was calculated as a product of viral load of the respiratory fluids and the emission of the exhaled airborne particles, considering the prevalence of the disease and the activity of the individuals. A well-mixed model was used in the estimation of the concentration of pathogens in the air. The Wells-Riley model was used for infection probability. The approach presented in this study was utilised in the identification of hot spots and critical events in the day care centre. Large variation in the infection probabilities and estimated number of persons at transmission risk was observed when modelling a normal day at the centre. The estimated hourly infection probabilities between the worst hour in the worst room and the best hour in the best room varied in the ratio of 100:1. Similarly, the number of persons at transmission risk between the worst and best cases varied in the ratio 1000:1. Although there are uncertainties in the input values affecting the absolute risk estimates the model proved to be useful in ranking and identifying the hot spots and events in the building and implementing effective control measures.

High-resolution short-term prediction of the COVID-19 epidemic based on spatial-temporal model modified by historical meteorological data

In the global challenge of Coronavirus disease 2019 (COVID-19) pandemic, accurate prediction of daily new cases is crucial for epidemic prevention and socioeconomic planning. In contrast to traditional local, one-dimensional time-series data-based infection models, the study introduces an innovative approach by formulating the short-term prediction problem of new cases in a region as multidimensional, gridded time series for both input and prediction targets. A spatial-temporal depth prediction model for COVID-19 (ConvLSTM) is presented, and further ConvLSTM by integrating historical meteorological factors (Meteor-ConvLSTM) is refined, considering the influence of meteorological factors on the propagation of COVID-19. The correlation between 10 meteorological factors and the dynamic progression of COVID-19 was evaluated, employing spatial analysis techniques (spatial autocorrelation analysis, trend surface analysis, etc.) to describe the spatial and temporal characteristics of the epidemic. Leveraging the original ConvLSTM, an artificial neural network layer is introduced to learn how meteorological factors impact the infection spread, providing a 5-day forecast at a 0.01° × 0.01° pixel resolution. Simulation results using real dataset from the 3.15 outbreak in Shanghai demonstrate the efficacy of Meteor-ConvLSTM, with reduced RMSE of 0.110 and increased R 2 of 0.125 (original ConvLSTM: RMSE = 0.702, R 2 = 0.567; Meteor-ConvLSTM: RMSE = 0.592, R 2 = 0.692), showcasing its utility for investigating the epidemiological characteristics, transmission dynamics, and epidemic development.

Drawing a parallel between the trend of confirmed COVID-19 deaths in the winters of 2022/2023 and 2023/2024 in Italy, with a prediction

We studied the weekly number and the growth/decline rates of COVID-19 deaths of the period from October 31, 2022, to February 9, 2023, in Italy. We found that the COVID-19 winter wave reached its peak during the three holiday weeks from December 16, 2022, to January 5, 2023, and it was definitely trending downward, returning to the same number of deaths as the end of October 2022, in the first week February 2023. During this period of 15 weeks, that wave caused a number of deaths as large as 8,526. Its average growth rate was +7.89% deaths per week (10 weeks), while the average weekly decline rate was -15.85% (5 weeks). At the time of writing of this paper, Italy has been experiencing a new COVID-19 wave, with the latest 7 weekly bulletins (October 26, 2023 - December 13, 2023) showing that deaths have climbed from 148 to 322. The weekly growth rate had risen by +14.08% deaths, on average. Hypothesizing that this 2023/2024 wave will have a total duration similar to that of 2022/2023, with comparable extensions of both the growth period and the decline period and similar growth/decline rates, we predict that the number of COVID-19 deaths of the period from the end of October 2023 to the beginning of February 2024 should be less than 4100. A preliminary assessment of this forecast, based on 11 of the 15 weeks of the period, has already confirmed the accuracy of this approach.

Geoepidemiological perspective on COVID-19 pandemic review, an insight into the global impact

The COVID-19 pandemic showed major impacts, on societies worldwide, challenging healthcare systems, economies, and daily life of people. Geoepidemiology, an emerging field that combines geography and epidemiology, has played a vital role in understanding and combatting the spread of the virus. This interdisciplinary approach has provided insights into the spatial patterns, risk factors, and transmission dynamics of the COVID-19 pandemic at different scales, from local communities to global populations. Spatial patterns have revealed variations in incidence rates, with urban-rural divides and regional hotspots playing significant roles. Cross-border transmission has highlighted the importance of travel restrictions and coordinated public health responses. Risk factors such as age, underlying health conditions, socioeconomic factors, occupation, demographics, and behavior have influenced vulnerability and outcomes. Geoepidemiology has also provided insights into the transmissibility and spread of COVID-19, emphasizing the importance of asymptomatic and pre-symptomatic transmission, super-spreading events, and the impact of variants. Geoepidemiology should be vital in understanding and responding to evolving new viral challenges of this and future pandemics.

From Immunogen to COVID-19 vaccines: Prospects for the post-pandemic era

The COVID-19 pandemic has affected millions of people and posed an unprecedented burden on healthcare systems and economies worldwide since the outbreak of the COVID-19. A considerable number of nations have investigated COVID-19 and proposed a series of prevention and treatment strategies thus far. The pandemic prevention strategies implemented in China have suggested that the spread of COVID-19 can be effectively reduced by restricting large-scale gathering, developing community-scale nucleic acid testing, and conducting epidemiological investigations, whereas sporadic cases have always been identified in numerous places. Currently, there is still no decisive therapy for COVID-19 or related complications. The development of COVID-19 vaccines has raised the hope for mitigating this pandemic based on the intercross immunity induced by COVID-19. Thus far, several types of COVID-19 vaccines have been developed and released to into financial markets. From the perspective of vaccine use in globe, COVID-19 vaccines are beneficial to mitigate the pandemic, whereas the relative adverse events have been reported progressively. This is a review about the development, challenges and prospects of COVID-19 vaccines, and it can provide more insights into all aspects of the vaccines.

Modeling vaccination and control strategies for outbreaks of monkeypox at gatherings

Background

The monkeypox outbreak in non-endemic countries in recent months has led the World Health Organization (WHO) to declare a public health emergency of international concern (PHEIC). It is thought that festivals, parties, and other gatherings may have contributed to the outbreak.

Methods

We considered a hypothetical metropolitan city and modeled the transmission of the monkeypox virus in humans in a high-risk group (HRG) and a low-risk group (LRG) using a Susceptible-Exposed-Infectious-Recovered (SEIR) model and incorporated gathering events. Model simulations assessed how the vaccination strategies combined with other public health measures can contribute to mitigating or halting outbreaks from mass gathering events.

Results

The risk of a monkeypox outbreak was high when mass gathering events occurred in the absence of public health control measures. However, the outbreaks were controlled by isolating cases and vaccinating their close contacts. Furthermore, contact tracing, vaccinating, and isolating close contacts, if they can be implemented, were more effective for the containment of monkeypox transmission during summer gatherings than a broad vaccination campaign among HRG, when accounting for the low vaccination coverage in the overall population, and the time needed for the development of the immune responses. Reducing the number of attendees and effective contacts during the gathering could also prevent a burgeoning outbreak, as could restricting attendance through vaccination requirements.

Conclusion

Monkeypox outbreaks following mass gatherings can be made less likely with some restrictions on either the number and density of attendees in the gathering or vaccination requirements. The ring vaccination strategy inoculating close contacts of confirmed cases may not be enough to prevent potential outbreaks; however, mass gatherings can be rendered less risky if that strategy is combined with public health measures, including identifying and isolating cases and contact tracing. Compliance with the community and promotion of awareness are also indispensable to containing the outbreak.

The environment, epidemics, and human health

In this editorial piece, the Editors of the Virtual Special Issue (VSI) "The environment, epidemics, and human health" comment on the papers accepted for publication, which were selected after peer-reviewing among all those manuscripts submitted to the Special Issue. In view of the title of the VSI, it is clear that its aim goes beyond the COVID-19 pandemic, trying to explore relations among environmental aspects, any kind of epidemics, and human health. However, COVID-19 is still hitting as a global and current main issue, causing that manuscripts dealing with this disease and the SARS-CoV-2 virus are of high relevance in the whole set of research papers published.

Effectiveness and safety of Tai Chi for anxiety disorder of COVID-19: A protocol of systematic review and meta-analysis

BACKGROUND

Anxiety disorders pose a significant threat to the clinical rehabilitation of patients with coronavirus disease 2019 (COVID-19). Tai Chi is a therapeutic exercise that can be used to treat anxiety disorders. We aim to conduct a systematic review and meta-analysis to evaluate the effectiveness and safety of Tai Chi for treating patients with anxiety disorders caused by COVID-19.

METHODS

The PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Chinese Biomedical Literature, Wan Fang, and Chinese Clinical Trial Registry databases will be searched for reports of randomized controlled trials on Tai Chi for the treatment of anxiety disorders caused by COVID-19, published from December 1, 2019, to August 22, 2022. Two researchers will screen the articles and extract the relevant information.

RESULTS

The results will provide a systematic overview of the current evidence on the use of Tai Chi to treat anxiety disorders caused by COVID-19 among patients.

CONCLUSION

The conclusions of this study will help clarify whether Tai Chi is effective and safe for treating anxiety disorders caused by COVID-19.

Exploring Sustainable Fashion Consumption Behavior in the Post-Pandemic Era: Changes in the Antecedents of Second-Hand Clothing-Sharing in China

Second-hand consumption of clothing plays a vital role in promoting the overall global trend of low-carbon transition; however, the COVID-19 outbreak put this consumption model into a development dilemma. Cultivating consumers’ sustainable behavior will be an effective way to promote the sustainable development of the apparel industry. Based on the unified theory of acceptance and use of technology (UTAUT), this study starts with fashion-sharing behavior and investigates the antecedents that influence consumers’ use of second-hand clothing-sharing platforms in the post-pandemic era. The research background involves the Chinese clothing-sharing market in the growing period. The findings revealed that the pandemic raised people’s awareness of health and hygiene protection. In addition, the cleaning problem of platform clothing has become the primary reason for curbing consumers’ choice of sharing. High-cost performance, high efficiency, and convenience can stimulate consumers to use shared services. Considering that the pandemic has driven consumer economic fluctuations, perceived economic risks could widen the gap between willingness and behavior. In conclusion, platforms must fully realize the transparency of the clothing cleaning and maintenance process, improve their own construction level such as ease of use, convenience, and safety, and incorporate functional clothing-sharing to refine people’s sustainable consumption habits.