Finite-time stability analysis and control of stochastic SIR epidemic model: A study of COVID-19

Finite-time stability analysis is a powerful tool for understanding the long-term behavior of epidemiological models and has been widely used to study the spread of infectious diseases such as COVID-19. In this paper, we present a finite-time stability analysis of a stochastic susceptible-infected-recovered (SIR) epidemic compartmental model with switching signals. The model includes a linear parameter variation (LPV) and switching system that represents the impact of external factors, such as changes in public health policies or seasonal variations, on the transmission rate of the disease. We use the Lyapunov stability theory to examine the long-term behavior of the model and determine conditions under which the disease is likely to die out or persist in the population. By taking advantage of the average dwell time method and Lyapunov functional (LF) method, and using novel inequality techniques the finite-time stability (FTS) criterion in linear matrix inequalities (LMIs) is developed. The finite-time stability of the resultant closed-loop system, with interval and linear parameter variation (LPV), is then guaranteed by state feedback controllers. By analyzing the modified SIR model with these interventions, we are able to examine the efficiency of different control measures and determine the most appropriate response to the COVID-19 pandemic and demonstrate the efficacy of the suggested strategy through simulation results.

The grief experience during the COVID-19 pandemic across different cultures

Grief is the physical or mental suffering experienced after a major loss, usually the death of a loved one. It is a universal experience, but sociocultural factors, such as cultural or ethnic identity and religious beliefs predict and shape the expression of grief. The circumstances under which people are experiencing grief during the coronavirus outbreak have adversely affected the grieving process. Unexpected deaths, social distancing rules and visitor restrictions in healthcare facilities have posed a heavier burden on the loss and have heightened the risk of grievers experiencing complicated or persistent grief. This concern led us, as early career psychiatrists (ECPs) from 14 different countries connected by the Early Career Psychiatrists Section of the World Psychiatric Association (WPA), to share our country-specific experiences on the mourning, grief tradition, and burial rites during the COVID-19 pandemic. In this paper, we discuss our experiences, similarities and differences with relation to the: 'Effect of the pandemic on mourning', 'Restrictions and Guideline on burial rites due to the pandemic', 'Effect of the pandemic on social support' and 'Role of media and telecommunication on mourning practices and burial rites'. We conclude that while telecommunication means have attempted to bridge the gap and provide some form of social connectedness, the total and global effect of the pandemic is yet to be fully seen and understood.

Associations of lockdown stringency and duration with Google searches for mental health terms during the COVID-19 pandemic: A nine-country study

OBJECTIVES

We examined the associations of lockdown stringency and duration with Google searches for four mental health concepts (i.e., "Anxiety," "Depression," "Suicide," "Mental Health") in nine countries (i.e., Hungary, India, Iran, Italy, Paraguay, Serbia, South Africa, Spain, Turkey) during the COVID-19 pandemic.

METHODS

We retrieved national-level data for each country from Google Trends and the Global Panel Database of Pandemic Policies. In our primary analysis, we used data from all countries to estimate a set of multilevel regression models examining associations of overall lockdown stringency and lockdown duration with relative search volumes for each mental health term. We repeated the models after replacing overall lockdown stringency with each of the lockdown stringency components.

RESULTS

A negative association was found between overall lockdown stringency and "Depression." Lockdown duration and the most stringent stay-at-home requirements were negatively associated with "Anxiety." Policies that recommended or required the cancelation of public events evidenced negative associations with "Depression," whereas associations between policies that required some or all levels of schooling to close and "Depression" were positive. Policies that recommended or required workplaces to close and those that enforced quarantines on non-citizens arriving from high-risk regions or closed borders entirely were negatively associated with "Suicide."

CONCLUSIONS

Lockdown duration and some lockdown policies during the COVID-19 pandemic were generally associated with significantly lower, rather than higher, Google searches for selected mental health terms. These findings could be used alongside other evidence to develop future lockdown strategies that are sensitive to mental health issues during public health crises.

Scaling Up Global Mental Health Services During the COVID-19 Pandemic and Beyond

Every health care system requires an adequate health care workforce, service delivery, financial support, and information technology. During the COVID-19 pandemic, global health systems were ill prepared to address the rising prevalence of mental health problems, especially in low- and middle-income countries (LMICs), thereby increasing treatment gaps. To close these gaps globally, task shifting and telepsychiatry should be made available and maximized, particularly in LMICs. Task shifting to nonspecialist health workers to improve essential mental health coverage and encourage efficient use of the available resources and technology has become the most viable strategy.

Design of robust reliable control for T-S fuzzy Markovian jumping delayed neutral type neural networks with probabilistic actuator faults and leakage delays: An event-triggered communication scheme

This study examines the problem of robust reliable control for Takagi-Sugeno (T-S) fuzzy Markovian jumping delayed neural networks with probabilistic actuator faults and leakage terms. An event-triggered communication scheme. First, the randomly occurring actuator faults and their failures rates are governed by two sets of unrelated random variables satisfying certain probabilistic failures of every actuator, new type of distribution based event triggered fault model is proposed, which utilize the effect of transmission delay. Second, Takagi-Sugeno (T-S) fuzzy model is adopted for the neural networks and the randomness of actuators failures is modeled in a Markov jump model framework. Third, to guarantee the considered closed-loop system is exponential mean square stable with a prescribed reliable control performance, a Markov jump event-triggered scheme is designed in this paper, which is the main purpose of our study. Fourth, by constructing appropriate Lyapunov-Krasovskii functional, employing Newton-Leibniz formulation and integral inequalities, several delay-dependent criteria for the solvability of the addressed problem are derived. The obtained stability criteria are stated in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones, among them one example was supported by real-life application of the benchmark problem.

Metabolic complications of schizophrenia and antipsychotic medications--an updated review

Metabolic syndrome is a cluster of risk factors comprising obesity, dyslipidaemias, glucose intolerance, insulin resistance (or hyperinsulinaemia), and hypertension, and is highly predictive of type 2 diabetes mellitus and cardiovascular disease. The life expectancy of people with schizophrenia is reduced by 20%, with 60% of the excess mortality due to physical illness. Schizophrenia itself may be a risk factor for metabolic syndrome and there is also increasing concern that antipsychotic drugs, particularly second-generation antipsychotics, have metabolic consequences that contribute to the risk. Various diagnostic guidelines, updated facts with regard to epidemiology, pathophysiology, risk factors, and complications of metabolic syndrome are discussed in this review. Moreover, the impact of various antipsychotics on metabolic syndrome and their possible mechanisms are comprehensively reviewed. The authors emphasise that, while many adults with schizophrenia receive little or no medical care, such care is important given the risk of metabolic abnormalities associated not only with antipsychotic medications, but also with schizophrenia in general.