A memory effect model to predict COVID-19: analysis and simulation

Background: Due to quarantine, mental health problems particularly depression and anxiety worsen in the general population. The psychological impact of COVID-19 on university students is more due to exaggerated stress levels and anxiety-related evidence as a result of transformed delivery and doubtfulness of university education, technological concerns of online courses of instruction, being far away from home, social separation and financial losses. Objective: To determine the post-COVID-19 psychological complications among university students in Islamabad. Methods: The study was carried out in various educational universities in Islamabad from March to August 2021. A questionnaire was distributed to obtain data about demographic characteristics and psychological complications during quarantine periods after the Covid-19 outbreak in Pakistan. The questionnaire used to collect data was DASS 21 questionnaire. The association between quarantine due to COVID-19 and students' psychological health was estimated through SPSS 23 analysis procedure with a p-value<0.001 Results: The study was completed by participation of 219 individuals, 54(24.7%) females and 165(75.3%) males. All students with age between 18-30 years who completed the questionnaire both physically and online. The results of the cross-sectional study showed that depression p-value=0.30, anxiety p=0.03 and stress p=0.01. Conclusion: The incidence of post-COVID-19 quarantine psychological complications was quite high among university students of Islamabad due to home-based and administrative quarantine during lockdown measures for conserving their physical and mental health and daily life activities. The current study concludes that stress, anxiety and depression were quite common in students of universities due to quarantine.

COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world. Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases. In this study, we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases, deaths, and recoveries in Pakistan for the upcoming month until the end of July. For the decomposition of data, the Ensemble Empirical Mode Decomposition (EEMD) technique is applied. EEMD decomposes the data into small components, called Intrinsic Mode Functions (IMFs). For individual IMFs modelling, we use the Autoregressive Integrated Moving Average (ARIMA) model. The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates. Our analyses reveal that the number of recoveries, new cases, and deaths are increasing in Pakistan exponentially. Based on the selected EEMD-ARIMA model, the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020, which is an increase of almost 1.46 times with a 95% prediction interval of 246,529 to 376,379. The 95% prediction interval for recovery is 162,414 to 224,579, with an increase of almost two times in total from 100802 to 193495 by 31 July 2020. On the other hand, the deaths are expected to increase from 4395 to 6751, which is almost 1.54 times, with a 95% prediction interval of 5617 to 7885. Thus, the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020. They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19, and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios. The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.

Religious Suasion in Health Beliefs and Behaviour: A Field Experiment during the COVID-19 Outbreak in Pakistan

Religious Suasion in Health Beliefs and Behaviour: A Field Experiment during the COVID-19 Outbreak in Pakistan

The primary purpose of this research is to acquire a profound comprehension of the impacts of Corporate Social Responsibility (CSR) on the operations of firms and on society as a whole, with Pakistan serving as the focal point of the research. This study's objective is to determine whether or not there is a moderating effect of CEO power on the relationships that exist between CSR, ownership concentration, and efficient business practices. In-depth research has been conducted on fifty different non-financial enterprises in Pakistan to see how well they performed before, during, and after the Covid-19 Pandemic. On the data that has been gathered, descriptive statistics and regression analysis have been carried out with the assistance of SPSS. The research found that in the middle of the Covid-19 outbreak in Pakistan, the degree of authority held by CEOs had a major impact on the dynamics of the economy. The authority of the Chief Executive Officer (CEO) has a significant impact on the relationship between corporate social responsibility (CSR) and the performance of an organization. Even in a developing country like Pakistan, the present study highlights the importance of corporate social responsibility (CSR) and the positive influence it may have on the bottom line of a firm. The purpose of this study is to investigate the beneficial benefits that corporate social responsibility (CSR) has on society, with a particular emphasis on emerging countries such as Pakistan. This research serves as a useful guide by emphasising how important CSR is for linking together the success of businesses and the well-being of the society in which they operate.

The EU Response to COVID-19: From Reactive Policies to Strategic Decision-Making.

Coronavirus Disease 2019: Coronaviruses and Kidney Injury.

Public Acceptance of Measures to Control Infectious Diseases Under Different Scenarios of Severity and Transmissibility

This paper presents a number of deterministic models for theoretically assessing the potential impact of an imperfect prophylactic HIV-1 vaccine that has five biological modes of action, namely "take," "degree," "duration," "infectiousness," and "progression," and can lead to increased risky behavior. The models, which are of the form of systems of nonlinear differential equations, are constructed via a progressive refinement of a basic model to incorporate more realistic features of HIV pathogenesis and epidemiology such as staged progression, differential infectivity, and HIV transmission by AIDS patients. The models are analyzed to gain insights into the qualitative features of the associated equilibria. This allows the determination of important epidemiological thresholds such as the basic reproduction numbers and a measure for vaccine impact or efficacy. The key findings of the study include the following (i) if the vaccinated reproduction number is greater than unity, each of the models considered has a locally unstable disease-free equilibrium and a unique endemic equilibrium; (ii) owing to the vaccine-induced backward bifurcation in these models, the classical epidemiological requirement of vaccinated reproduction number being less than unity does not guarantee disease elimination in these models; (iii) an imperfect vaccine will reduce HIV prevalence and mortality if the reproduction number for a wholly vaccinated population is less than the corresponding reproduction number in the absence of vaccination; (iv) the expressions for the vaccine characteristics of the refined models take the same general structure as those of the basic model.

This paper proposed a delayed fractional-order SEIHR-M model incorporating media influence to investigate the transmission dynamics of COVID-19 in Malaysia. By integrating fractional-order dynamics and time-delay media influence into a unified epidemic framework, this novel structure more accurately captures both memory effects and behavioral response lags in the context of COVID-19. Theoretical analysis verified the existence, non-negativity, and boundedness of the solutions, ensuring the biological feasibility of the model. The basic reproduction number was derived using the next-generation matrix method, serving as a key metric for evaluating disease transmission and model stability. Furthermore, when , the disease-free equilibrium is locally asymptotically stable regardless of the value of the delay parameter . When 1$$\\end{document}]]>, the stability of the endemic equilibrium exhibits two scenarios: if , sufficient conditions for local asymptotic stability are provided; if 0$$\\end{document}]]>, there exists a critical delay . The endemic equilibrium remains locally asymptotically stable for but becomes unstable for \ au _0$$\\end{document}]]>, undergoing a Hopf bifurcation at , leading to periodic oscillations. The numerical simulation results not only validate the theoretical analysis but also show that as the fractional-order parameter increases, the system exhibits more pronounced oscillations; furthermore, longer delay times facilitate the emergence of these oscillatory behaviors, making the epidemic more prone to recurrent and periodic fluctuations. By fitting the model with early COVID-19 data from Malaysia, the feasibility and applicability of the model are further validated, and the superior fitting performance of the fractional-order delay model compared to the corresponding integer-order model is highlighted. Finally, sensitivity analysis results show that media interventions have a significant impact on epidemic spread, further demonstrating that timely and effective information dissemination plays a crucial role in reducing the peak of infections and controlling the epidemic.

An SVEIR SARS-CoV-2 Omicron variant model is proposed to provide some insights to coordinate non-pharmaceutical interventions (NPIs) and vaccination. Mathematically, we define the basic reproduction number {mathscr {R}}_{0} and the effective reproduction number {mathscr {R}}_{e} to measure the infection potential of Omicron variant and formulate an optimal disease control strategy. Our inversion results imply that the sick period of Omicron variant in the United States is longer than that of Delta variant in India. The decrease in the infectious period of the infection with infectiousness implies that the risk of hospitalization is reduced; but the increasing period of the infection with non-infectiousness signifies that Omicron variant lengthens the period of nucleic acid test being negative. Optimistically, Omicron’s death rate is only a quarter of Delta’s. Moreover, we forecast that the cumulative cases will exceed 100 million in the United States on February 28, 2022, and the daily confirmed cases will reach a peak on February 2, 2022. The results of parameters sensitivity analysis imply that NPIs are helpful to reduce the number of confirmed cases. In particular, NPIs are indispensable even if all the people were vaccinated when the efficiency of vaccine is relatively low. By simulating the relationships of the effective reproduction number {mathscr {R}}_{e}, the vaccination rate and the efficacy of vaccine, we find that it is impossible to achieve the herd immunity without NPIs while the efficiency of vaccine is lower than 88.7%. Therefore, the herd immunity area is defined by the evolution of relationships between the vaccination rate and the efficacy of vaccine. Finally, we present that the disease-induced mortality rate demonstrates the periodic oscillation and an almost periodic function is deduced to match the curve. A discussion completes the paper.

Over the last 2 decades, successful public health interventions have altered the epidemiology of viral hepatitis in the United States. Vaccination of children and adolescents has reduced the incidence of hepatitis A virus (HAV) and hepatitis B virus (HBV) infections to historic lows. American Indians/Alaskan Natives, a population whose HBV rate was once 5 times that of other racial/ethnic populations, now has the lowest (0.5 cases per 100 000).1–3 Since the adoption in 1991 of a strategy to eliminate HBV transmission, HBV vaccination of infants, children, and adolescents has largely contributed to an 81% decline in new cases of HBV, and infant HBV vaccination is now on par with that of other vaccines in the childhood schedule. (1,2,4,5) With more than 90% of pregnant women screened for HBV infection and postexposure prophylaxis 85% to 95% effective in preventing mother-to-child HBV transmission at delivery, substantial progress has been made in the prevention of perinatal HBV infections.4 In the absence of a vaccine to prevent HCV, the advent of laboratory testing in 1992 to protect the nation’s blood supply and prevention efforts to reduce risk behaviors among injection drug users (IDUs) have led to a 78% decline in new HCV infections.1,2,6 Health care–related transmission of HBV and HCV is now rare thanks to widespread vaccination of health care workers and the adoption of universal infection control procedures.7 Although these prevention successes are remarkable, challenges remain. Despite the existence of risk-based vaccination recommendations, HAV and HBV infections remain common.3,5 In 2006, an estimated 32000 persons were infected with HAV, with risks highest among international travelers, individuals in close contact with infected persons, men who have sex with men, and IDUs; food-borne outbreaks also continue to be reported.2 Of an estimated 46000 new HBV infections in 2006, more than 80% were attributable to injection drug use and high-risk sexual activity.2,5 Children continue to be infected at birth. Of approximately 24000 infants born to HBV-infected women annually, only about one quarter complete case management and are tested for infection or susceptibility (CDC, unpublished data, 2007). In 2006, a total of 86 perinatal HBV cases were reported to the CDC, but testing and reporting are incomplete; thus, the true number of perinatal HBV cases per year is likely 10 to 20 times higher. Approximately half of persons with chronic HBV in the United States are Asian Americans (CDC, unpublished data, 2006). HBV-related liver cancer is a leading cause of cancer deaths in this population.8 Although the incidence of HBV infection in the United States is declining, the prevalence of chronic HBV is sustained by immigration from HBV-endemic countries in Asia, Africa, and Eastern Europe; each year, an estimated 40000 persons with chronic HBV immigrate to the United States from these countries.5 In 2006, approximately 20000 persons were infected with HCV.2 Injection drug use was responsible for most of these new cases, and at least one third of IDUs are HCV infected.9 Despite the decline in the number of new infections, the number of persons with chronic viral hepatitis is over 4 million, including 3.2 million chronic HCV infections and 800 000 to 1.4 million chronic HBV infections (CDC, unpublished data, 2006).10 Chronic viral hepatitis is a major cause of morbidity responsible for approximately two thirds of chronic liver disease and conservatively 9000 deaths per year. 11,12 Mortality from HCV is expected to rise as the HCV-infected population ages, extending their years of living with the infection and increasing their risk of liver cirrhosis and cancer.13 Cofactors such as HIV infection and alcohol use accelerate the progression of HCV; approximately 25% of the 1 million persons infected with HIV are co-infected with HCV.6 Finally, cases of health care–associated HBV and HCV transmission continue to occur. The changing epidemiology of viral hepatitis reveals both gaps in the delivery of proven interventions and new opportunities to reduce the health consequences of chronic disease. The Centers for Disease Control and Prevention (CDC) has identified new priorities to improve current programs and develop new prevention goals.

A novel covid-19 mathematical model with fractional derivatives: Singular and nonsingular kernels.

At least 25% of coronary patients have sudden death or nonfatal myocardial infarction without prior symptoms.1 Therefore, the search for coronary patients with subclinical disease who could potentially benefit from intensive primary prevention efforts is critically important. The American Heart Association’s (AHA) Prevention V Conference, “Beyond Secondary Prevention: Identifying the High Risk Patient for Primary Prevention,” addressed ways to identify more patients who are asymptomatic and clinically free of coronary heart disease (CHD) but at sufficiently high risk for a future coronary event to justify more intensive risk reduction efforts.2 In this report, we amplify on key findings and recommendations of the AHA Prevention V conference, highlight new research since the conference, and propose an approach to the use of office-based testing and additional noninvasive procedures in selected patients to better define their coronary event risk. The recommendations are concordant with the recently released approach to risk assessment and management from the third report of the Adult Treatment Panel of the National Cholesterol Education Program (ATP-III).3 Enthusiasm for primary prevention and risk assessment in asymptomatic people has been spurred by recent advances in prevention research. Lipid-lowering trials demonstrated that primary prevention of coronary events is feasible, evidenced by the West of Scotland Coronary Primary Prevention Study (WOSCOPS) trial4 of hypercholesterolemic men and by the Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS) trial5 in average or typical risk men and women with only moderate lipid abnormalities. Aspirin6 or ACE inhibitors7 can also reduce risk in selected asymptomatic, high-risk people. Emerging coronary risk factors have been described including inflammatory, infectious, and thrombotic markers,8 and there has been a steady flow of reports that focus attention on potential new ways of predicting coronary risk.9 In addition, noninvasive tests for subclinical atherosclerotic disease are available …

In this paper we prove sufficient conditions for Ψ-exponential asymptotic stability in variation on R+ of trivial solution of the system x ′ = F (t, x) and for Ψexponential asymptotic stability on R+ of trivial solution of the system x ′ = F (t, x) + G(t, x).