COVID-19 and New-Onset Psychosis: A Comprehensive Review.

Psychosis is a multifactorial condition that typically involves delusions, hallucinations, and disorganized thought, speech or behavior. The observation of an association between infectious epidemics and acute psychosis dates back to the last century. Recently, concerns have been expressed regarding COVID-19 and the risk for the development of new-onset psychosis. This article reviewed the current evidence of a possible link between SARS-CoV-2 and risk of psychosis as an acute or post-infectious manifestation of COVID-19. We here discuss potential neurobiological and environmental factors as well as a number of challenges in ascribing a causal pathogenic relationship between SARS-CoV-2 infection and new-onset psychosis.

1000 Days: The "WeCare Generation" Program-The Ultimate Model for Improving Human Mental Health and Economics: The Study Protocol.

INTRODUCTION: The COVID-19 pandemic stressed the necessity of a new resilience of the human population and health system. The "WeCare Generation" program is a new proposal of territorial intervention, with a new paradigm, on the diseases of the human body and mind. BACKGROUND: In recent decades, the independent strands of investigation on brain plasticity and early trauma consequences have demonstrated that traumatic experiences in the period from pregnancy to the age of 3 years have an enormous impact on an individual's future development, and both physical and mental health. Research shows that adverse child experiences (ACEs) are associated with a strong risk of conditions such as: harmful alcohol use, smoking, illicit drug use, high body-mass index, depression, anxiety, interpersonal violence, cancer, type 2 diabetes, cardiovascular diseases, stroke respiratory diseases and, as a consequence, to a high financial cost in Italy and also across Europe (1-9% GDP) and the USA (total annual costs estimated to be USD 581 billion in Europe and USD 748 billion in North America). All this suggests that an early intervention on that traumatized-slice of population leads to multiplied savings. METHODS: A multi-center, randomized, controlled trial was designed. The parents of the future neonatal population (from pregnancy to delivery) with trauma will be enrolled, and randomized to treatment, or control arm. The article describes in detail how the primary outpoint (cost to the national health system), and some secondary outpoints, will be collected. DISCUSSION: An overall rate of return on investment (ROI) statistically significant 13.0% per annum with an associated benefit/cost ratio (BCR) of 6.3 is expected as the primary outcome of the "WeCare Generation" program. Our proposed model predicts a new medical paradigm aiming to empower new generations, with a strong return on economy and health.

A Treatment Model for Young Adults with Severe Mental Disorders in a Community Mental Health Center: The Crisalide Project and the Potential Space.

In line with priorities set by the Italian Ministry of Health and international literature, the "Crisalide project" provides specific care pathways aimed at young adults (YA) with severe mental disorders (SMD). As described in Materials and Methods, it consists of three lines of activity: transition to adult mental health services (TSMREE/CSM 17-19); Diagnostic, Therapeutic, and Assistance Pathways for Young Adults (PDTA-YA); high-intensity treatment center for young adults "Argolab2 Potential Space". The aim of the study is to assess the results relating to the first three years of implementation of this clinical-organizational model (2018/2020) according to the process indicators identified by the ministry. Among the population aged 18-30 under treatment, results show increased prevalence (30%) and incidence (26%); 0% treatment conclusions due to the expiration of the conventional time limit; 0% involuntary hospitalizations (TSO); 0% STPIT hospitalizations; 0% repeated hospitalizations; 0% hospitalizations in the common mental disorders diagnostic group. Among the population of Argolab2 Potential Space, 45.4% have resumed studies; 40.9% have had a first work experience; 22.7% have obtained educational or training qualifications, and 18.2% live in independent houses. At a time when the academic literature underlines the terrible impact of the COVID-19 pandemic on this population, the present study confirms that specific treatment processes for young populations are a protective factor.

Exploring a COVID-19 Endemic Scenario: High-Resolution Agent-Based Modeling of Multiple Variants.

Our efforts as a society to combat the ongoing COVID-19 pandemic are continuously challenged by the emergence of new variants. These variants can be more infectious than existing strains and many of them are also more resistant to available vaccines. The appearance of these new variants cause new surges of infections, exacerbated by infrastructural difficulties, such as shortages of medical personnel or test kits. In this work, a high-resolution computational framework for modeling the simultaneous spread of two COVID-19 variants: a widely spread base variant and a new one, is established. The computational framework consists of a detailed database of a representative U.S. town and a high-resolution agent-based model that uses the Omicron variant as the base variant and offers flexibility in the incorporation of new variants. The results suggest that the spread of new variants can be contained with highly efficacious tests and mild loss of vaccine protection. However, the aggressiveness of the ongoing Omicron variant and the current waning vaccine immunity point to an endemic phase of COVID-19, in which multiple variants will coexist and residents continue to suffer from infections.

Activity-driven network modeling and control of the spread of two concurrent epidemic strains.

The emergency generated by the current COVID-19 pandemic has claimed millions of lives worldwide. There have been multiple waves across the globe that emerged as a result of new variants, due to arising from unavoidable mutations. The existing network toolbox to study epidemic spreading cannot be readily adapted to the study of multiple, coexisting strains. In this context, particularly lacking are models that could elucidate re-infection with the same strain or a different strain-phenomena that we are seeing experiencing more and more with COVID-19. Here, we establish a novel mathematical model to study the simultaneous spreading of two strains over a class of temporal networks. We build on the classical susceptible-exposed-infectious-removed model, by incorporating additional states that account for infections and re-infections with multiple strains. The temporal network is based on the activity-driven network paradigm, which has emerged as a model of choice to study dynamic processes that unfold at a time scale comparable to the network evolution. We draw analytical insight from the dynamics of the stochastic network systems through a mean-field approach, which allows for characterizing the onset of different behavioral phenotypes (non-epidemic, epidemic, and endemic). To demonstrate the practical use of the model, we examine an intermittent stay-at-home containment strategy, in which a fraction of the population is randomly required to isolate for a fixed period of time.

Concerns and Challenges Related to Sputnik V Vaccination Against the Novel COVID-19 Infection in the Russian Federation: The Role of Mental Health, and Personal and Social Issues as Targets for Future Psychosocial Interventions.

Background: Vaccine hesitancy causes serious difficulties in vaccination campaigns in many countries. The study of the population's attitude toward vaccination and detection of the predictive important individual psychological and social factors defining the vaccination necessity perception will allow elaborating promoting vaccination adherence measures. Objectives: The aim of this research was to study COVID-19 threat appraisal, fear of COVID-19, trust in COVID-19 information sources, COVID-19 conspiracy beliefs, and the relationship of sociodemographic variables to COVID-19 preventive behavior. Methods: We carried out a cohort cross-sectional study of the population's attitude toward vaccination against the novel COVID-19 coronavirus infection, using a specially designed questionnaire for an online survey. Totally, there were 4,977 respondents, ranging in age from 18 to 81 years. Statistical assessment was carried out using the SPSS-11 program. Results: There were different attitudes toward vaccination. Among respondents, 34.2% considered vaccination to be useful, 31.1% doubted its effectiveness, and 9.9% considered vaccination unnecessary. The survey indicated that 7.4% of respondents were indifferent to the vaccine, while 12.2% deemed it to be dangerous. Nearly one-third (32.3%) of respondents indicated that they did not plan to be vaccinated, while another third (34.0%) would postpone their decision until more comprehensive data on the results and effectiveness of vaccination were available. Only 11.6% of the respondents were vaccinated at the time of the study. Young people were less focused on vaccination compared to middle-aged and elderly people. Receiving information concerning COVID-19 vaccination from healthcare workers and scientific experts was associated with greater vaccination acceptance. Conclusion: The study results showed that vaccination attitudes interacted with individuals' mental health and various sociodemographic factors. Insofar as reports of physicians and experts are essential for shaping attitudes to vaccination, the study results inform the selection of target groups in need of particular psychosocial interventions to overcome their vaccine hesitancy.

Trazodone Prolonged-Release Monotherapy in Cannabis Dependent Patients during Lockdown Due to COVID-19 Pandemic: A Case Series.

(1) Background: During the SARS-CoV-2 (COVID-19) pandemic, cannabis use increased relative to pre-pandemic levels, while forced home confinement frequently caused sleep/wake cycle disruptions, psychological distress, and maladaptive coping strategies with the consequent appearance of anxiety symptoms and their potential impact on substance use problems. (2) Aim: Long-acting trazodone (150 mg or 300 mg daily) has a potential benefit as monotherapy in patients with cannabis use disorder. The present work aims to investigate the effectiveness of trazodone in optimizing the condition of people with cannabis dependence under pandemic conditions. (3) Methods: All cases with cannabis use disorder were uniformly treated with long-acting trazodone 150 mg or 300 mg/day; their craving and clinical status were monitored through appropriate psychometric scales. Side effects were recorded as they were reported by patients. We described the cases of three young patients-one man and two women-who were affected by chronic cannabis use disorder and who experienced lockdown-related psychological distress and sought psychiatric help. (4) Results: The described cases highlight that the once-a-day formulation of trazodone seems to have a therapeutic role in patients with cannabis use disorder and to guarantee tolerability and efficacy over time. No significant side effects emerged. (5) Conclusions: The use of long-acting trazodone (150 mg or 300 mg daily) has a potential benefit as monotherapy in patients with cannabis use disorder. Trazodone deserves to be studied in terms of its efficacy for cannabis use disorder.

Predicting the Effects of Waning Vaccine Immunity Against COVID-19 through High-Resolution Agent-Based Modeling (Adv. Theory Simul. 6/2022)

Predicting the Effects of Waning Vaccine Immunity Against COVID-19 through High-Resolution Agent-Based Modeling Mathematical models have proven to be indispensable in our fight against COVID-19. In article 2100521, Agnieszka Truszkowska, Maurizio Porfiri, and co-workers expand on a high-resolution agent-based model published previously in this journal to study the effectiveness of the booster shot campaign in preventing new COVID-19 waves in the town of New Rochelle, NY. Image by Anna Sawulska and Maurizio Porfiri.

Urban Determinants of COVID-19 Spread: a Comparative Study across Three Cities in New York State.

The ongoing pandemic is laying bare dramatic differences in the spread of COVID-19 across seemingly similar urban environments. Identifying the urban determinants that underlie these differences is an open research question, which can contribute to more epidemiologically resilient cities, optimized testing and detection strategies, and effective immunization efforts. Here, we perform a computational analysis of COVID-19 spread in three cities of similar size in New York State (Colonie, New Rochelle, and Utica) aiming to isolate urban determinants of infections and deaths. We develop detailed digital representations of the cities and simulate COVID-19 spread using a complex agent-based model, taking into account differences in spatial layout, mobility, demographics, and occupational structure of the population. By critically comparing pandemic outcomes across the three cities under equivalent initial conditions, we provide compelling evidence in favor of the central role of hospitals. Specifically, with highly efficacious testing and detection, the number and capacity of hospitals, as well as the extent of vaccination of hospital employees are key determinants of COVID-19 spread. The modulating role of these determinants is reduced at lower efficacy of testing and detection, so that the pandemic outcome becomes equivalent across the three cities.

Predicting the Effects of Waning Vaccine Immunity Against COVID‐19 through High‐Resolution Agent‐Based Modeling

The potential waning of the vaccination immunity to COVID‐19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near‐complete restoration of normalcy. Should also testing be relaxed, a resurgent COVID‐19 wave in winter 2021/2022 might be witnessed. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. A projected study with an outlook of 6 months explores the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent‐based model tuned on a medium‐sized US town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid‐spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to the continuously evolving nature of the pandemic. This study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed. Mathematical models have been proven to be indispensable in our fight against COVID‐19. This paper expands on a high‐resolution agent‐based model published previously in this journal to study the effectiveness of the booster shot campaign in preventing a new wave in the town of New Rochelle, NY during this fall and the coming spring.

Smart Charging Management for Autonomous Vehicles: A Smart Solution for Smart Cities & Societies: COVID 19 Predicting the Effects of Waning Vaccine Immunity Against COVID-19 through High-Resolution Agent-Based Modeling

Summary Smart Cities have a high quality of life determined by several variables with renewable transport networks, protection and health, open space connectivity, and other critical facilities. The key elements of smart city classification are transportation, traffic management, and parking. Among those elements, the intelligent transportation system plays a vital role. Big data analytics can create smart cities to achieve a smart transport system, autonomous vehicles, and crowdsourcing. The coronavirus disease (COVID-19) has spread quickly through China since December 2019 and later globally. As this article was written, the disease was reported to globally infect 100 countries. Evening transmission from person to person is a practical approach for controlling and preventing the epidemic. Specific everyday tasks, such as logistics that move goods in our daily lives, ultimately require interaction between men. Using an automated logistic vehicle has been the preferred option for achieving the contactless transportation of goods. This chapter describes Hercules, an autonomous logistic vehicle used to move goods without touch during the outbreak of COVID-19. The vehicle shall be equipped for autonomous navigation capability. The research introduces the mechanism for smart charging of shared autonomous electric vehicles. Researchers include information on the hardware and software and the algorithms for achieving autonomous navigation, including vision, planning, and control. Autonomous vehicles (AVs) are believed to provide many profits for individuals and society, with increased road safety, reduced traffic congestion, and an improved ecological footprint. However, many barriers still hinder the widespread acceptance of autonomous driving. During this pandemic situation, decision-making towards adopting autonomous driving imposes a more accessible and reliable way to deliver things, such as food and medical supplies, in an emergency than policymakers and automakers have devoted in recent years. Innovative AVs emerge as potential energy savers in the transportation system. There is a cumulative emphasis on AVs together in terms of rapid technological advances and evaluating these technologies and their significant effects on society and transportation systems during COVID-19 around the world. The potential waning of the vaccination immunity to COVID-19 could pose threats to public health, as it is tenable that the timing of such waning would synchronize with the near-complete restoration of normalcy. Should also testing be relaxed, a resurgent COVID-19 wave in winter 2021/2022 might be witnessed. In response to this risk, an additional vaccine dose, the booster shot, is being administered worldwide. A projected study with an outlook of 6 months explores the interplay between the rate at which boosters are distributed and the extent to which testing practices are implemented, using a highly granular agent-based model tuned on a medium-sized US town. Theoretical projections indicate that the administration of boosters at the rate at which the vaccine is currently administered could yield a severe resurgence of the pandemic. Projections suggest that the peak levels of mid-spring 2021 in the vaccination rate may prevent such a scenario to occur, although exact agreement between observations and projections should not be expected due to the continuously evolving nature of the pandemic. This study highlights the importance of testing, especially to detect asymptomatic individuals in the near future, as the release of the booster reaches full speed.

Will Nothing Be the Same Again?: Changes in Lifestyle during COVID-19 Pandemic and Consequences on Mental Health.

Social isolation caused by the COVID-19 pandemic has drastically affected lifestyles: from sedentary behaviors to reduced physical activity, from disrupted sleep patterns to altered dietary habits. As a consequence, serious mental and emotional responses have been registered. There was a significant decline in physical and other meaningful activities of daily living, leisure, social activity, and education. In children, collateral effects of the pandemic include inadequate nutrition with a risk of both overweight and underweight, addiction to screens, lack of schooling, and psychosocial difficulties. Older adults are frequently unable to adapt to lockdown measures and suffer from depression and cognitive complaints. Recent studies focusing on changes in lifestyle during the Covid-19 pandemic and consequences on mental health have been identified in PubMed/Medline, Scopus, Embase, and ScienceDirect. All the available literature has been retrospectively reviewed. The results of the present narrative review suggest that mental distress caused by social isolation seems to be linked not only to personality characteristics but also to several lifestyle components (sleep disruption, altered eating habits, reduced physical activity). This review aims to explore major changes in the lifestyle and quality of life and the impact of these changes on mental health, and to inform clinicians and policymakers about elements that may reduce the negative psychological effects of the quarantine period imposed during this worldwide crisis. There is an urgent need for tailored preventive, diagnostic, and therapeutic mental health interventions for the general population and for higher risk groups.

Designing the Safe Reopening of US Towns Through High-Resolution Agent-Based Modeling.

As COVID-19 vaccine is being rolled out in the US, public health authorities are gradually reopening the economy. To date, there is no consensus on a common approach among local authorities. Here, a high-resolution agent-based model is proposed to examine the interplay between the increased immunity afforded by the vaccine roll-out and the transmission risks associated with reopening efforts. The model faithfully reproduces the demographics, spatial layout, and mobility patterns of the town of New Rochelle, NY - representative of the urban fabric of the US. Model predictions warrant caution in the reopening under the current rate at which people are being vaccinated, whereby increasing access to social gatherings in leisure locations and households at a 1% daily rate can lead to a 28% increase in the fatality rate within the next three months. The vaccine roll-out plays a crucial role on the safety of reopening: doubling the current vaccination rate is predicted to be sufficient for safe, rapid reopening.

Psychiatric disorders among hospitalized patients deceased with COVID-19 in Italy.

BACKGROUND: there is concern about the increased risk for SARS-CoV-2 infection, COVID-19 severe outcomes and disparity of care among patients with a psychiatric disorder (PD). Based on the Italian COVID-19 death surveillance, which collects data from all the hospitals throughout the country, we aimed to describe clinical features and care pathway of patients dying with COVID-19 and a preceding diagnosis of a PD. METHODS: in this cross-sectional study, the characteristics of a representative sample of patients, who have died with COVID-19 in Italian hospitals between February 21st and August 3rd 2020, were drawn from medical charts, described and analysed by multinomial logistic regression according to the recorded psychiatric diagnosis: no PD, severe PD (SPD) (i.e. schizophrenia and other psychotic disorders, bipolar and related disorders), common mental disorder (CMD) (i.e. depression without psychotic features, anxiety disorders). FINDINGS: the 4020 COVID-19 deaths included in the study took place in 365 hospitals across Italy. Out of the 4020 deceased patients, 84 (2•1%) had a previous SPD, 177 (4.4%) a CMD. The mean age at death was 78.0 (95%CI 77.6-78.3) years among patients without a PD, 71.8 (95%CI 69.3-72.0) among those with an SPD, 79.5 (95%CI 78.0-81.1) in individuals with a CMD. 2253 (61.2%) patients without a PD, 62 (73.8%) with an SPD, and 136 (78.2%) with a CMD were diagnosed with three or more non-psychiatric comorbidities.When we adjusted for clinically relevant variables, including hospital of death, we found that SPD patients died at a younger age than those without a PD (adjusted OR per 1 year increment 0.96; 95% CI 0.94-0.98). Women were significantly more represented among CMD patients compared to patients without previous psychiatric history (aOR 1.56; 95% CI 1.05-2.32). Hospital admission from long-term care facilities (LTCFs) was strongly associated with having an SPD (aOR 9.02; 95% CI 4.99-16.3) or a CMD (aOR 2.09; 95% CI 1.19-3.66). Comorbidity burden, fever, admission to intensive care and time from symptoms' onset to nasopharyngeal swab did not result significantly associated with an SPD or with a CMD in comparison to those without any PD. INTERPRETATION: even where equal treatment is in place, the vulnerability of patients with a PD may reduce their chance of recovering from COVID-19. The promotion of personalised therapeutic projects aimed at including people with PD in the community rather than in non-psychiatric LTCFs should be prioritised.

COVID-19 Modeling: High-Resolution Agent-Based Modeling of COVID-19 Spreading in a Small Town (Adv. Theory Simul. 3/2021).

Since 2020, COVID-19 has wreaked havoc across the planet, taking the lives of more than one million people. The uncertainty and novelty of the current conditions call for the development of theory and simulation tools that can support effective policy-making. In article number 2000277, Agnieszka Truszkowska, Maurizio Porfiri, and co-workers report a high-resolution, agent-based modeling platform to simulate the spreading of COVID-19 in the city of New Rochelle, NY-one of the first outbreaks registered in the United States. Image by Anna Sawulska, Agnieszka Truszkowska, Beata Truszkowska, and Maurizio Porfiri.

High-Resolution Agent-Based Modeling of COVID-19 Spreading in a Small Town.

Amid the ongoing COVID-19 pandemic, public health authorities and the general population are striving to achieve a balance between safety and normalcy. Ever changing conditions call for the development of theory and simulation tools to finely describe multiple strata of society while supporting the evaluation of "what-if" scenarios. Particularly important is to assess the effectiveness of potential testing approaches and vaccination strategies. Here, an agent-based modeling platform is proposed to simulate the spreading of COVID-19 in small towns and cities, with a single-individual resolution. The platform is validated on real data from New Rochelle, NY-one of the first outbreaks registered in the United States. Supported by expert knowledge and informed by reported data, the model incorporates detailed elements of the spreading within a statistically realistic population. Along with pertinent functionality such as testing, treatment, and vaccination options, the model accounts for the burden of other illnesses with symptoms similar to COVID-19. Unique to the model is the possibility to explore different testing approaches-in hospitals or drive-through facilities-and vaccination strategies that could prioritize vulnerable groups. Decision-making by public authorities could benefit from the model, for its fine-grain resolution, open-source nature, and wide range of features.

Reduced Hedonic Tone and Emotion Dysregulation Predict Depressive Symptoms Severity during the COVID-19 Outbreak: An Observational Study on the Italian General Population.

The COVID-19 pandemic has spiked stress-related symptoms worldwide. This study aims to assess depressive symptoms related to the early phase of the COVID-19 outbreak among the Italian general population and to analyze anhedonia and emotion dysregulation as potential predictors of depression severity. Through an online questionnaire, we collected sociodemographic and lockdown-related information; depressive symptoms, hedonic tone, and emotion dysregulation were assessed through the Beck Depression Inventory II, the Snaith-Hamilton Pleasure Scale, and the Difficulties in Emotion Regulation Scale, respectively. In our sample (n = 500), 122 individuals (24.4%) reported depressive symptoms during the COVID-19 outbreak. Individuals with and without depression differed in gender (X2 = 4.77, df = 1, p = 0.02) and age (X2 = 15.7, df = 4, p = 0.003). Among individuals presenting with depressive symptoms, those reporting close contact with confirmed cases of COVID-19 were at higher risk for severe depression (p = 0.026). Reduced hedonic tone (p = 0.014) and emotion dysregulation (p < 0.001) also predicted depression severity. To the best of our knowledge, these are among the earliest data that focus on the risk for depression among a sizeable sample of the Italian general population during the COVID-19 outbreak. Our results indicate emotion dysregulation and reduced hedonic tone as potential factors predicting COVID-19-related depression severity and provide insight into developing targeted intervention policies.