Non-pharmaceutical Strategies Research Articles

Rethinking interventions for dementia through a nonpharmaceutical lens: An analysis of five interventions

ABSTRACT The future welfare of older adults is a worldwide concern. By 2034, it is estimated that individuals 65 and older in the U.S. will be 77 million. Consequently, this reality will impact healthcare facilities and increase Medicare and Medicaid costs, resulting in higher incidents of homeless older adults, children caring for parents, the need for more caregivers, and an increased number of older individuals experiencing various forms of dementia. To address these concerns, the current trend for treating the onset of dementia and Alzheimer’s disease has been moving toward nonpharmaceutical interventions. Even though researchers have tapped into the benefits of several nonpharmaceutical treatments, there appears to be a constant debate on establishing which method is most effective. Deciding on best practices and methods to slow down and/or halt the progression of dementia is the gap this research needs to fill. To provide clarity on the topic, an analysis of alternative interventions to treat the onset of dementia is what this paper strived to achieve. The analysis involved comparing and contrasting the benefits of each intervention as well as illustrating the implications of the findings. In this regard, a systematic review was conducted examining the benefits of five nonpharmaceutical strategies; mental training, music therapy, technology usage, physical activity, and social interaction. Although findings revealed some form of improvement in each of the nonpharmacological interventions examined, the overarching theme appeared to lean toward providing mental stimulation. It was also not conclusive that physical activity prevented cognitive decline. More research is recommended.

Effectiveness of multi-modal home-based videoconference interventions on sleep in older adults: study protocol for a randomized controlled trial.

Aging is characterized by substantial changes in sleep architecture that negatively impact fitness, quality of life, mood, and cognitive functioning. Older adults often fail to reach the recommended level of physical activity to prevent the age-related decline in sleep function, partly because of geographical barriers. Implementing home-based interventions could surmount these obstacles, thereby encouraging older adults to stay active, with videoconference administration emerging as a promising solution. Increasing the availability of biological rhythms synchronizers, such as physical activity, light exposure, or vestibular stimulation, represents a viable non-pharmacological strategy for entraining circadian rhythms and potentially fortifying the sleep-wake cycle, thereby enhancing sleep in aging. This study aims to (1) assess the impact of remote physical exercise training and its combination with bright light exposure, and (2) investigate the specific contribution of galvanic vestibular stimulation, to sleep quality among healthy older adults with sleep complaints. One hundred healthy older adults aged 60-70 years with sleep complaints will be randomly allocated to one of four groups: a physical exercise training group (n = 25), a physical exercise training combined with bright light exposure group (n = 25), a galvanic vestibular stimulation group (n = 25) or a control group (i.e., health education) (n = 25). While physical exercise training and health education will be supervised via videoconference at home, bright light exposure (for the physical exercise training combined with bright light exposure group) and vestibular stimulation will be self-administered at home. Pre-and post-tests will be conducted to evaluate various parameters, including sleep (polysomnography, subjective questionnaires), circadian rhythms (actigraphy, temperature), fitness (physical: VO2 peak, muscular function; and motor: balance, and functional mobility), cognition (executive function, long-term memory), quality of life and mood (anxiety and depression). The findings will be anticipated to inform the development of recommendations and non-pharmaceutical preventive strategies for enhancing sleep quality in older adults, potentially leading to improvements in fitness, cognition, quality of life, and mood throughout aging.

Impact of alternative Non-Pharmaceutical Interventions strategies for controlling COVID-19 outbreak in Bangladesh: A modeling study.

The COVID-19 pandemic has been a major health concern in Bangladesh until very recently. Although the Bangladesh government has employed various infection control strategies, more targeted Non-Pharmaceutical interventions (NPIs), including school closure, mask-wearing, hand washing, and social distancing have gained special attention. Despite significant long-term adverse effects of school closures, authorities have opted to keep schools closed to curb the spread of COVID-19 infection. However, there is limited knowledge about the impact of reopening schools alongside other NPI measures on the course of the epidemic. In this study, we implemented a mathematical modeling framework developed by the CoMo Consortium to explore the impact of NPIs on the dynamics of the COVID-19 outbreak and deaths for Bangladesh. For robustness, the results of prediction models are then validated through model calibration with incidence and mortality data and using external sources. Hypothetical projections are made under alternative NPIs where we compare the impact of current NPIs with school closures versus enhanced NPIs with school openings. Results suggest that enhanced NPIs with schools opened may have lower COVID-19 related prevalence and deaths. This finding indicates that enhanced NPIs and school openings may mitigate the long-term negative impacts of COVID-19 in low- and middle-income countries. Potential shortcomings and ways to improve the research are also discussed.

Safe discontinuation of psychotropic drugs in older people? : New evidence and practical approach

Many older patients are permanently prescribed one or more psychotropic drugs for treatment of symptoms, such as behavioral and psychological symptoms in dementia, depressive symptoms, anxiety, and insomnia. They therefore contribute to the risk of polypharmacy. Recently, deprescribing studies have been published in order to clarify if inadequate medications can be safely discontinued. This mini-review summarizes the study results and derives practical recommendations for routine use. A literature search was carried out in PubMed for clinical studies on deprescribing in association with psychotropic substances. After removal of duplications, 12heterogeneous clinical studies were identified and reduction of psychotropic substances could be successfully achieved in 8studies. In four of these studies psychological, behavioral and functional endpoints were reported. Criteria for successful deprescribing of sedatives were in particular motivation, information and sufficient cooperation of the patients and for antipsychotic drugs in people with dementia, the sustainable establishment of nonpharmaceutical treatment strategies. Deprescribing was not attempted in cases of ahistory of severe chronic mental illness and in cases of severe behavioral symptoms in dementia. Evidence for antidepressants was not sufficient to extract practical recommendations. Safe deprescribing of antipsychotic drugs in patients with dementia is justified if non-pharmacological treatment options are sustainably implemented, and for sedative drugs in well-informed, highly motivated and cooperative patients.

Social adaptive behavior and oscillatory prevalence in an epidemic model on evolving random geometric graphs

Our recent experience with the COVID-19 pandemic amply shows that spatial effects like the mobility of agents and average interpersonal distance, together with the adaptation of agents, are very important in deciding the outcome of epidemic dynamics. Structural and dynamical aspects of random geometric graphs are widely employed in describing processes with a spatial dependence, such as the spread of an airborne disease. In this work, we investigate the interplay between spatial factors, such as agent mobility and average interpersonal distance, and the adaptive responses of individuals to an ongoing epidemic within the framework of random geometric graphs. We show that such spatial factors, together with the adaptive behavior of the agents in response to the prevailing level of global epidemic, can give rise to oscillatory prevalence even with the classical SIR framework. We characterize in detail the effects of social adaptation and mobility of agents on the disease dynamics and obtain the threshold values. We also study the effects of delayed adaptive response of agents on epidemic dynamics. We show that a delay in executing non-pharmaceutical spatial mitigation strategies can amplify oscillatory prevalence tendencies and can have non-linear effects on peak prevalence. This underscores the importance of early implementation of adaptive strategies coupled with the dissemination of real-time prevalence information to manage and control the epidemic effectively.

AutomatedFace Mask Detection Using Pretrained CNN

In recent times, the use of face masks has emerged as a critical subject. Automated facial mask detection can curb the transmission of the COVID-19 virus and SARS-VIRUS within communal areas by identifying individuals who are not utilizing masks. In this work, a pretrained Convolutional Neural Network (CNN) with model ResNet-50, which is initially trained on the Image Net competition data, is utilized. This model is augmented with a 300-linear layer network and fine-tuned on a dataset that comprises 1,000 facial images. During the evaluation of the validation dataset consisting of approximately 800 face images, the model achieved an impressive 99% accuracy. Its primary objective is to discover if an individual is wearing a facial mask using a cropped image of their face. By leveraging such advanced technologies, we can contribute significantly to public health and safety measures in the ongoing battle against COVID-19 and SARS-VIRUS.Keywords:CNNCOVID-19Face Mask Detection (FMD) SARSDOI: 10.22401/ANJS.26.4.12*corresponding author email: farah.saad@nahrainuniv.edu.iqThis work is licensed under a Creative Commons Attribution 4.0 International License1.Introduction COVID-19 (CO ronaVIrus Disease of 2019) and SARS(Severe Acute Respiratory Syndrome) are two viral respiratory illnesses caused by coronaviruses, both of which have had important global impacts on public health [1]. These contagious diseases emerged in different time frames but share similarities in their mode of transmission and clinical presentation, prompting the search for effective non-pharmaceutical strategies to mitigate their spread [2]. One essential strategy to reduce the transmission of respiratory droplets, which can carry the viruses, is the widespread adoption of face masks in public spaces. However, monitoring and ensuring compliance with mask-wearing practices in crowded areas can be challenging, particularly in densely populated regions. Automatic face mask detection (FMD) systems powered by advanced technologies offer a potential solution to this challenge [3]. Convolutional Neural Networks (CNNs) and deep learning techniques have demonstrated remarkable success in computer vision tasks, including image classification [4]. In this context, utilizing pretrained CNN models, such as ResNet-50, has shown promising results for identifying faces wearing or not wearing masks. In this work, we explore applying a pretrained ResNet-50 CNN model fine-tuned on a well-balanced dataset of 12,000cropped photos of faces with and without masks. The goal is to create an accurate and reliable FMD (Face Mask Detection) system that can automatically identify individuals who are not wearing masks in public spaces. Through this work, we aim to contribute to the expanding realm of research on FMD as a crucial tool to prevent the spread of respiratory illnesses. The successful implementation of such technology has the ability to play a significant role in safeguarding public health, improving safety measures, and aiding in the ongoing battle against COVID-19 and SARS in various community settings.

Overcoming treatment gaps in the management of depression with non-pharmacological adjunctive strategies

There is considerable evidence that simple, cost-effective, non-pharmaceutical strategies can be readily implemented to improve outcomes in the treatment of depression. It is estimated that 4.4% of the world’s population suffers from depression. Despite being a major public health concern and the availability of both pharmacological and non-pharmacological treatments, many depressed people remain undiagnosed and receive no or inappropriate treatment. Several possible underlying factor of treatment gap can be identified in relation to pharmacotherapy and psychotherapy of depression, including side effects, partial remission, treatment-resistant depression and the limited availability of psychotherapy. In addition to developing new therapeutic options, much more could be done to optimise the use of existing therapies, including combining available drug treatments with quick, simple and cost-effective non-pharmacological methods: low-intensity psychological interventions, online self-help tools and lifestyle medicine. In addition to increasing the effectiveness of treatments, prevention is equally important: awareness programs to further reduce the treatment gap, and community dissemination of the life skills that help maintain positive mental health.

Modeling the effect of non-pharmaceutical measures and vaccination on the spread of two variants of COVID-19 in India

An RNA virus, SARS-CoV-2 is capable of mutation, and vaccines developed to combat its earlier strains are comparatively less effective against its new emerging variants of concern. Therefore, it is proposed to formulate a two-strain COVID-19 deterministic model that incorporates non-pharmaceutical preventive strategies along with an imperfect and leaky vaccine. The control reproduction number (denoted by Rc) of the model is calculated using the next-generation matrix method. Rigorous model analysis elucidates that its disease-free equilibrium (DFE) is locally asymptotically stable when Rc<1. Using the central manifold theorem, the occurrence of subcritical bifurcation is proved when the relevant conditions required for its existence hold. However, the model exhibits transcritical bifurcation when the vaccinated population does not get infected. Additionally, the DFE point of this reduced case is globally asymptotically stable when Rc is sufficiently less than 1. Moreover, the model is analyzed to reveal the presence and global asymptotic stability (using the Lyapunov function approach) of endemic equilibrium points. The introduced model is calibrated and cross-validated with observed daily and cumulative data of Delta (1 April 2021 to 30 November 2021) and Omicron variant (1 December 2021 to 15 February 2022). Data fitting depicts that competitive exclusion exists among the variants as the Omicron variant tends to extinct other variants prevalent in that duration within a restricted timeframe. The model is examined, using the known and calibrated parameter values corresponding to the Omicron variant, to examine the impression of vaccination, quarantine, isolation, and lockdown on the prevalence of illness in India. The impact of fluctuations in vaccine and infection-induced immunities on daily and cumulative cases is studied. It is observed that vaccine-derived immunity exerts a greater influence on the current wave of the pandemic as compared to subsequent waves while natural infection immunity has a significant impact on future waves of the pandemic. Furthermore, there is a possibility of a future wave of the Omicron variant but with a relatively low peak. The minimum percentage of vaccinated people required to reach community-wide herd immunity has been estimated with respect to vaccine efficacy and various non-pharmaceutical control parameters.

Barriers to COVID-19 Prevention Measures Among People Experiencing Homelessness with Substance Use Disorder or Serious Mental Illness.

People experiencing homelessness (PEH) are at disproportionate risk of becoming infected and having severe illness from coronavirus disease 2019 (COVID-19), especially when residing in congregate settings like homeless shelters. Behavioral health problems related to substance use disorder (SUD) and severe mental illness (SMI) may have created additional challenges for PEH to practice prevention measures like mask wearing, physical distancing, handwashing, and quarantine and isolation. The study objective was to understand the perceived barriers PEH face regarding COVID-19 non-pharmaceutical prevention strategies and identify recommendations for overcoming barriers. From August-October 2020, qualitative phone interviews with 50 purposively selected behavioral health professionals across the United States serving PEH with SUD or SMI were conducted. Professionals described that PEH faced barriers to prevention that were structural (e.g., access to necessary resources), behavioral (related to SUD or SMI), or related to the priority of other needs. Recommendations to overcome these barriers included providing free prevention resources (e.g., masks and hand sanitizer), providing education about importance of prevention strategies, and prioritizing access to stable housing. Interviews took place before COVID-19 vaccines were available, so barriers to vaccination are not included in this paper. Findings can help support tailored approaches during COVID-19 and future public health threats.

Effects of Lockdown on Utilisation of Health Care and Mental Health of Pregnant Women in Rural Areas of Balasore, Odisha, India: Experiences Learnt from the COVID-19 Pandemic

Most of the countries around the world accepted and introduced lockdown as one of the major non-pharmaceutical strategies to slow down the spread of COVID-19. However, the pandemic and various lockdown measures introduced to mitigate it were expected to affect the population in many ways. This study aimed at analysing the problems of health care utilisation encountered by pregnant women in selected rural areas of the district of Balasore in Odisha and assessing the effect of lockdown on the mental health of the women. Besides, the study also attempted to explore the extent of precautionary measures practised by women in the study area. It is a cross-sectional study based on the data obtained through a semi-structured interview schedule, from 150 currently married rural women in the reproductive age group including 100 pregnant women selected through a multistage sampling process. Pregnant women in this study were conscious about COVID-19 and most of them preferred to stay back at home and wash their hands/use masks frequently. Unavailability of doctors and long waiting time etc. were reported as problems encountered at the health centre. The effect of the COVID-19 lockdown on the mental health of pregnant women was clearly evident, and the two biggest reasons were lockdown-induced immobility and reduced income. Pregnant women, who are highly vulnerable in general, were affected badly due to the COVID-19 lockdown and it is certainly a challenge for the policy makers to address the issue in times of such exigencies in the future.

Effects of Music, Massage, Exercise, or Acupuncture in the Treatment of Depression Among College Students: A Network Meta-Analysis.

To assess the therapeutic impacts of exercise, massage, and music interventions on college students experiencing depression by employing a mesh meta-analysis approach. This research intends to offer valuable insights to aid in the development of non-pharmaceutical treatment strategies for depression. We conducted a thorough search across various databases including Cochrane, PubMed, Embase, Web of Science, CNKI, and Wanfang to explore the effects of music, massage, aerobic exercise, fitness Qigong, yoga, tai chi, ball games, strength training, dance, whole body vibration training, and high-intensity interval training on the treatment of depression in college students. The search period was from January 1, 2023, which marks the establishment of each database. Subsequently, a mesh meta-analysis was performed using the "Stata 15.1" software, incorporating outcome indicators from 24 included literature comprising a total of 1458 patients. Based on the ranking of the optimal intervention effects of various non-pharmaceutical methods, the order, from highest to lowest probability, was as follows: high-intensity interval training (96%), yoga (94.90%), dance (78.30%), music (73.30%), ball games (62.50%), strength training (51.70%), aerobic training (45.30%), tai chi (35.40%), vibration training (27.30%), massage (20.10%), qigong (14.30%), and no intervention (1.00%). This ranking aligns closely with the findings obtained from pairwise comparisons between different interventions. High-intensity interval training is likely to yield the most effective therapeutic results for college students with depression. In the pairwise comparison of different interventions, High-intensity interval training is also better than most interventions. However, to establish its intervention effect more conclusively, further validation through additional high-quality randomized controlled trials is necessary.

The Portuguese Public Hospitals Performance Evolution before and during the SARS-CoV-2 Pandemic (2017–2022)

COVID-19 is a disease caused by SARS-CoV-2, which has spread worldwide since the beginning of 2020. Several pharmaceutical and non-pharmaceutical strategies were proposed to contain the virus, including vaccination and lockdowns. One of the consequences of the pandemic was the denial or delay of access to convenient healthcare services, but also potentially the increase in adverse events within those services, like the number of hospital infections. Therefore, the main question here is about what happened to the performance of Portuguese public hospitals. The main goal of this work was to test if the Portuguese public hospitals’ performance has been affected by the SARS-CoV-2 pandemic. We used the Benefit-of-Doubt method integrated with the Malmquist Index to analyze the performance evolution over time. Then, we employed a multiple regression model to test whether some pandemic-related variables could explain the performance results. We considered a database of 40 Portuguese public hospitals evaluated from January 2017 to May 2022. The period 2017 to 2019 corresponds to the baseline (pre-pandemic), against which the remaining period will be compared (during the pandemic). We also considered fourteen variables characterizing hospital quality, divided into three main performance definitions (efficiency and productivity; access; safety and care appropriateness). As potential explanatory variables, we consider seven dimensions, including vaccination rate and the need for intensive care for COVID-19-infected people. The results suggest that COVID-19 pandemic features help explain the drop in access after 2020, but not the evolution of safety and appropriateness of care, which surprisingly increased the whole time.

An overview of prescribing practice and non-pharmacological treatments in COPD

Chronic obstructive pulmonary disease (COPD) is a common heterogenous disease with significant personal implications, responsible for substantial healthcare costs. The goal of treatment and management in COPD is to control symptoms, and reduce risk and frequency of exacerbations and hospitalisations using a patient-centred approach. This article summarises the main current pharmaceutical and non-pharmaceutical management strategies in COPD, drawing on contemporaneous clinical guidelines and evidence, and highlight how emerging COPD endotypes and phenotypes are enhancing our understanding. An overview of inhaled medications, the mainstay of COPD treatment, is discussed, as well as the significance of device selection related to personal and physical considerations. Acute and long-term treatment and the criteria for specialist referral and medical management in complex patients is also presented.

Spatio-temporal dynamic of the COVID-19 epidemic and the impact of imported cases in Rwanda

IntroductionAfrica was threatened by the coronavirus disease 2019 (COVID-19) due to the limited health care infrastructure. Rwanda has consistently used non-pharmaceutical strategies, such as lockdown, curfew, and enforcement of prevention measures to control the spread of COVID-19. Despite the mitigation measures taken, the country has faced a series of outbreaks in 2020 and 2021.In this paper, we investigate the nature of epidemic phenomena in Rwanda and the impact of imported cases on the spread of COVID-19 using endemic-epidemic spatio-temporal models. Our study provides a framework for understanding the dynamics of the epidemic in Rwanda and monitoring its phenomena to inform public health decision-makers for timely and targeted interventions.ResultsThe findings provide insights into the effects of lockdown and imported infections in Rwanda’s COVID-19 outbreaks. The findings showed that imported infections are dominated by locally transmitted cases. The high incidence was predominant in urban areas and at the borders of Rwanda with its neighboring countries. The inter-district spread of COVID-19 was very limited due to mitigation measures taken in Rwanda.ConclusionThe study recommends using evidence-based decisions in the management of epidemics and integrating statistical models in the analytics component of the health information system.

Modeling a traffic light warning system for acute respiratory infections

The high morbidity of acute respiratory infections constitutes a crucial global health burden. In particular, for SARS-CoV-2, non-pharmaceutical intervention geared to enforce social distancing policies, vaccination, and treatments will remain an essential part of public health policies to mitigate and control disease outbreaks. However, the implementation of mitigation measures directed to increase social distancing when the risk of contagion is a complex enterprise because of the impact of NPI on beliefs, political views, economic issues, and, in general, public perception. The way of implementing these mitigation policies studied in this work is the so-called traffic-light monitoring system that attempts to regulate the application of measures that include restrictions on mobility and the size of meetings, among other non-pharmaceutical strategies. Balanced enforcement and relaxation of measures guided through a traffic-light system that considers public risk perception and economic costs may improve the public health benefit of the policies while reducing their cost. We derive a model for the epidemiological traffic-light policies based on the best response for trigger measures driven by the risk perception of people, instantaneous reproduction number, and the prevalence of a hypothetical acute respiratory infection. With numerical experiments, we evaluate and identify the role of appreciation from a hypothetical controller that could opt for protocols aligned with the cost due to the burden of the underlying disease and the economic cost of implementing measures. As the world faces new acute respiratory outbreaks, our results provide a methodology to evaluate and develop traffic light policies resulting from a delicate balance between health benefits and economic implications.

Safe discontinuation of psychotropic drugs in older people? : New evidence and practical approach

Many older patients are permanently prescribed one or more psychotropic drugs for treatment of symptoms, such as behavioral and psychological symptoms in dementia, depressive symptoms, anxiety, and insomnia. They therefore contribute to the risk of polypharmacy. Recently, deprescribing studies have been published in order to clarify if inadequate medications can be safely discontinued. This mini-review summarizes the study results and derives practical recommendations for routine use. A literature search was carried out in PubMed for clinical studies on deprescribing in association with psychotropic substances. After removal of duplications, 12heterogeneous clinical studies were identified and reduction of psychotropic substances could be successfully achieved in 8studies. In four of these studies psychological, behavioral and functional endpoints were reported. Criteria for successful deprescribing of sedatives were in particular motivation, information and sufficient cooperation of the patients and for antipsychotic drugs in people with dementia, the sustainable establishment of nonpharmaceutical treatment strategies. Deprescribing was not attempted in cases of ahistory of severe chronic mental illness and in cases of severe behavioral symptoms in dementia. Evidence for antidepressants was not sufficient to extract practical recommendations. Safe deprescribing of antipsychotic drugs in patients with dementia is justified if non-pharmacological treatment options are sustainably implemented, and for sedative drugs in well-informed, highly motivated and cooperative patients.

Optimal non-pharmaceutical pandemic response strategies depend critically on time horizons and costs

The COVID-19 pandemic has called for swift action from local governments, which have instated non-pharmaceutical interventions (NPIs) to curb the spread of the disease. The swift implementation of social distancing policies has raised questions about the costs and benefits of strategies that either aim to keep cases as low as possible (suppression) or aim to reach herd immunity quickly (mitigation) to tackle the COVID-19 pandemic. While curbing COVID-19 required blunt instruments, it is unclear whether a less-transmissible and less-deadly emerging pathogen would justify the same response. This paper illuminates this question using a parsimonious transmission model by formulating the social distancing lives vs. livelihoods dilemma as a boundary value problem using calculus of variations. In this setup, society balances the costs and benefits of social distancing contingent on the costs of reducing transmission relative to the burden imposed by the disease. We consider both single-objective and multi-objective formulations of the problem. To the best of our knowledge, our approach is distinct in the sense that strategies emerge from the problem structure rather than being imposed a priori. We find that the relative time-horizon of the pandemic (i.e., the time it takes to develop effective vaccines and treatments) and the relative cost of social distancing influence the choice of the optimal policy. Unsurprisingly, we find that the appropriate policy response depends on these two factors. We discuss the conditions under which each policy archetype (suppression vs. mitigation) appears to be the most appropriate.

Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions

Coronaviruses are types of viruses that are widely spread in humans, birds, and other mammals, leading to hepatic, respiratory, neurologic, and enteric diseases. The disease is presently a pandemic with great medical, economical, and political impacts, and it is mostly spread through physical contact. To extinct the virus, keeping physical distance and taking vaccine are key. In this study, a dynamical transmission compartment model for coronavirus (COVID-19) is designed and rigorously analyzed using Routh–Hurwitz condition for the stability analysis. A global dynamics of mathematical formulation was investigated with the help of a constructed Lyapunov function. We further examined parameter sensitivities (local and global) to identify terms with greater impact or influence on the dynamics of the disease. Our approach is data driven to test the efficacy of the proposed model. The formulation was incorporated with available confirmed cases from January 22, 2020, to December 20, 2021, and parameterized using real-time series data that were collected on a daily basis for the first 705 days for fourteen countries, out of which the model was simulated using four selected countries: USA, Italy, South Africa, and Nigeria. A least square technique was adopted for the estimation of parameters. The simulated solutions of the model were analyzed using MAPLE-18 with Runge–Kutta–Felberg method (RKF45 solver). The model entrenched parameters analysis revealed that there are both disease-free and endemic equilibrium points. The solutions depicted that the free equilibrium point for COVID-19 is asymptotic locally stable, when the epidemiological reproduction number condition (R_{0}<1). The simulation results unveiled that the pandemic can be controlled if other control measures, such as face mask wearing in public areas and washing of hands, are combined with high level of compliance to physical distancing. Furthermore, an autonomous derivative equation for the five-dimensional deterministic was done with two control terms and constant rates for the pharmaceutical and non-pharmaceutical strategies. The Lagrangian and Hamilton were formulated to study the model optimal control existence, using Pontryagin’s Maximum Principle describing the optimal control terms. The designed objective functional reduced the intervention costs and infections. We concluded that the COVID-19 curve can be flattened through strict compliance to both pharmaceutical and non-pharmaceutical strategies. The more the compliance level to physical distance and taking of vaccine, the earlier the curve is flattened and the earlier the economy will be bounce-back.

Feasibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen self-testing in school and summer camp attendees.

SARS-CoV-2 screening is one of the pillars of non-pharmaceutical preventive strategies to early identify and isolate infected individuals and therefore decrease community incidence. We assessed the feasibility of severe acute respiratory syndrome coronavirus 2 self-testing with antigen-detecting rapid diagnostic tests in attendees of educational settings. A total of 305 students (88.15%) and 41 staff (11.85%) from 9 to 56 years old participated in the self-testing procedure and answered the survey at the end of the study. 91.3% (n = 313) did not need help, 96.1% of participants reported the same outcome as the healthcare workers. 94.5% strongly or slightly agree with the statement "I would repeat the experience". The study demonstrates that self-testing is acceptable and usable in children, adolescents and adults when the epidemiological situation may require a systematic screening of these populations, although supervision by health care or previously trained personnel is recommended for younger age groups.

COVID-19, mobility restriction, and sexual behavior among a cohort of people of reproductive age: Nigeria.

One of the non-pharmaceutical strategies adopted by various governments to control the spread of COVID-19 is mobility restriction (MR), popularly known as a lockdown. Evidence shows that MR has some unintended consequences, such as increased cases of domestic violence, rape, pornography, sex chats, incest, and other unhealthy sexual behaviors (SBs). The study examined the influence of MR on SB in Owerri via a cross-sectional quantitative approach. A total of 425 interviewees were randomly chosen among people of a reproductive age. Data were analyzed using univariate, bivariate, and multivariate levels of analysis. A significant relationship exists between selected socio-demographic characteristics, such as age and marital status, and the ability of people to cope with sexual abstinence. Results from the logistic regression analysis further illustrated this observation as during MR people were twice as likely to engage in prolific sex chats that could spur other harmful SBs. It is recommended that people should be allowed to determine whether they would like to stay with their partners in subsequent lockdowns, or otherwise, to prevent some of the unpleasant SBs recorded.