Objective: The purpose of our study is to show how the relationship between marital adjustment and satisfaction will change in cases of chronic disease in either or both spouses of married couples using a multivariate statistical analysis method. -/- Methods: Marriage adjustment ve marriage satisfaction scales were used. A structural equation modeling - multiple group analysis method was used in the study, which was designed as a relational screening model. -/- Results: In the study, which included 898 participants, 56.6% (...) of the participants were female and 43.4% were male. The mean age of the participants was 36.94 ± 8.72 standard deviations. First, the relationship between marital adjustment and satisfaction was analyzed using structural equation modeling, and the relationship between the scales was found to be statistically significant (p=0.001). In the model, which was significant and sufficient, the variable of chronic disease was coded on the arrow representing the regression coefficient between the scales, and multiple group analysis was applied. The relationship between marital adjustment and satisfaction was found to be weak among individuals with chronic diseases. The rate of marriage satisfaction explaining marriage adjustment was lower in individuals without chronic disease (R2=0.16) than in those without chronic disease (R2=0.10). While ego scores were not significant in individuals without chronic disease (p=0.237), they were statistically significant in individuals with chronic disease (p=0.017). -/- Conclusion: Chronic diseases has been found to have a significant impact on the relationship between spouses. Many studies have examined the effects of chronic diseases on marriage. However, our study differs from other studies because of the analytical methods used. In the scales, it was determined whether the chronic disease showed a change in the relationship between the scales, not the scores in the chronic disease state. (shrink)

Rare diseases pose a particular priority setting problem. The UK gives rare diseases special priority in healthcare priority setting. Effectively, the National Health Service is willing to pay much more to gain a quality-adjusted life-year related to a very rare disease than one related to a more common condition. But should rare diseases receive priority in the allocation of scarce healthcare resources? This article develops and evaluates four arguments in favour of such a priority. These pertain to public values, (...) luck egalitarian distributive justice the epistemic difficulties of obtaining knowledge about rare diseases and the incentives created by a higher willingness to pay. The first is at odds with our knowledge regarding popular opinion. The three other arguments may provide a reason to fund rare diseases generously. However, they are either overinclusive because they would also justify funding for many non-rare diseases or underinclusive in the sense of justifying priority for only some rare diseases. The arguments thus fail to provide a justification that tracks rareness as such. There are no data in this work. (shrink)

To be effective, a medical intervention must improve one's health by targeting a disease. The concept of disease, though, is controversial. Among the leading accounts of disease-naturalism, normativism, hybridism, and eliminativism-I defend a version of hybridism. A hybrid account of disease holds that for a state to be a disease that state must both (i) have a constitutive causal basis and (ii) cause harm. The dual requirement of hybridism entails that a medical intervention, to (...) be deemed effective, must target either the constitutive causal basis of a disease or the harms caused by the disease (or ideally both). This provides a theoretical underpinning to the two principle aims of medical treatment: care and cure. (shrink)

Some ‘naturalist’ accounts of disease employ a biostatistical account of dysfunction, whilst others use a ‘selected effect’ account. Several recent authors have argued that the biostatistical account offers the best hope for a naturalist account of disease. We show that the selected effect account survives the criticisms levelled by these authors relatively unscathed, and has significant advantages over the BST. Moreover, unlike the BST, it has a strong theoretical rationale and can provide substantive reasons to decide difficult cases. (...) This is illustrated by showing how life-history theory clarifies the status of so-called diseases of old age. The selected effect account of function deserves a more prominent place in the philosophy of medicine than it currently occupies. _1_ Introduction _2_ Biostatistical and Selected Effect Accounts of Function _3_ Objections to the Selected Effect Account _3.1_ Boorse _3.2_ Kingma _3.3_ Hausman _3.4_ Murphy and Woolfolk _4_ Problems for the Biostatistical Account _4.1_ Schwartz _5_ Analysis versus Explication _6_ Explicating Dysfunction: Life History Theory and Senescence _7_ Conclusion. (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized (...) through techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (shrink)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for (...) binary classification, identifying the presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be (...) sensitive to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

Response to commentary. We are grateful to Crockett and Craigie for their interesting remarks on our paper. We accept Crockett’s claim that there is a need for caution in drawing inferences about patient groups from work on healthy volunteers in the laboratory. However, we believe that the evidence we cited established a strong presumption that many of the patients who are routinely taking a medication, including many people properly prescribed the medication for a medical condition, have morally significant aspects of (...) their cognition and behavior modified in a way that is unintended and may sometimes be unwelcome. Crockett notes that in some cases the effects of long-term drug use may differ, sometimes markedly, from the effects of short-term use. However, if acute use of a drug affects a neural system involved in mediating moral cognition or behavior, this nevertheless provides some evidence that chronic use of the drug may affect that same system and thus have morally significant effects. It is also plausible, in some cases, that an acute moral effect would give rise to a chronic moral effect via cognitive mechanisms. ... (shrink)

Cardiovascular diseases (CVD) represent a significant cause of morbidity and mortality worldwide, necessitating early detection for effective intervention. This research explores the application of machine learning (ML) algorithms in predicting cardiovascular diseases with enhanced accuracy by integrating optimization techniques. By leveraging data-driven approaches, ML models can analyze vast datasets, identifying patterns and risk factors that traditional methods might overlook. This study focuses on implementing various ML algorithms, such as Decision Trees, Random Forest, Support Vector Machines, and Neural Networks, optimized (...) through techniques like hyperparameter tuning, cross-validation, and feature selection to improve prediction accuracy. (shrink)

Venomous snakebite is a neglected tropical disease and disease of poverty, affecting hundreds of thousands of people annually. The only effective medical intervention for snakebite is antivenom, produced primarily using captive venomous snakes as a source of venom. This paper analyzes snakes’ welfare at venom labs within this global health context. I recommend significant changes to improve the welfare of captive snakes, particularly in light of recent ethological research and attention on snakes. These recommendations are broadly consequentialist, (...) aiming to improve the lives of the snakes and ensure that people have increased access to affordable antivenom. (shrink)

On 11 March 2020, the World Health Organization declared a pandemic of the COVID-19 coronavirus disease that was first recognized in China in late 2019. Among the primary effects caused by the pandemic, there was the dissemination of health preventive measures such as physical distancing, travel restrictions, self-isolation, quarantines, and facility closures. This includes the global disruption of socio-economic systems including the postponement or cancellation of various public events (e.g., sporting, cultural, or religious), supply shortages and fears of the (...) same, schools and universities closure, evacuation of foreign citizens, a rise of unemployment, changes in the international aid schemes, misinformation, and incidents of discrimination toward people affected by or suspected of having the COVID-19 disease. The pandemic has brought to the fore unpreparedness in critical areas that require attention, amid prospects and challenges. Moreover, considerable reorganization efforts are required with implications for assets, resources, norms, and value systems. COVID-19 is challenging the concept of globalization and stimulating responses at the levels of local and regional socio-economic systems that lead to the mobilization of assets that have been unrecognized earlier on, such as various forms of economic capital, social capital, cultural capital, human capital, and creative capital. For example, through digital channels, local groups are forming to create schemes of support for physical and mental wellbeing. These emerging exchanges lead to various social and technological innovations by building on skills and assets that are less important in the free-market economy, such as empathy, skills for crafts, making and fixing; locally grown microgreens; and micromanufacturing. Isolation and local living are also making it much harder to ignore the civic responsibilities towards communities, meant as individuals, vulnerable groups, and local businesses. Whilst the pandemic is limiting physical participation, this challenging time is uncovering alternative ways of mutual support, which may create long-term benefits for socio-economic systems, including environmental and biodiversity protection, reduction of the air pollution, and climate action. The pandemic’s threat to public health will hopefully be overcome with implications for disruption for an extended period that we are unable to forecast at this stage. It is key to focus on studies recognizing the activities and interventions leading to the recovery of socio-economic systems after the pandemic. Reflecting and planning on how societies and economies will go back to “business as usual” requires new forms of communication and cooperation, imaginative design thinking, new styles of management, as well as new tools and forms of participation in various public policies. Many questions related to the care of the vulnerable, economic restart, and the risk of future pandemics, to mention but a few, are already occupying the academic, scientific, experts, and activist communities, who have started to imagine the “new normal.”. (shrink)

Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...) proposed. The aim of this paper is to diagnose tomato diseases based on a dataset containing 11000 picture and 11 classes. The model gave the final accuracy test with Accuracy (99.87%), F1-score (99.87%), Recall (99.87%), and Precision (99.88%) in an estimated time 1.36 second, as with these results it proved its effectiveness and good ability in the classification of the testing data. (shrink)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...) used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

Clinical microbiology serves as a partner to clinicians in the diagnosis and treatment of infectious diseases. Antibiotics are prescribed empirically before the availability of antimicrobial susceptibility testing data, especially when the patient's medical status could deteriorate by suspending the treatment. To investigate the impact of antimicrobial susceptibility testing on the management of outpatients with suspected bacterial infection in Libyan patients, a cross-sectional prospective study concluded on microbial microdroplet culture by including outpatients with suspected bacterial infection, who have done antimicrobial susceptibility (...) testing. Thus, 53 Libyan patients with urinary tract infections and 14 Libyan patients with skin infections were included in this study. Before the availability of antimicrobial susceptibility testing data, 25 patients were appropriately treated while 42 patients were inappropriately treated. After the availability of antimicrobial susceptibility testing data, the number of appropriately treated patients increased to 57 patients. Thus, antimicrobial susceptibility testing improved the management of 41 patients by discontinuing an unnecessary antibiotic in four patients, starting necessary antibiotic therapy in 18 patients, and changing to more appropriate antibiotic in 19 patients. However, the antimicrobial susceptibility testing has no impact on the management of 24 patients and has led to the worsening of the management of two patients. The effect of antimicrobial susceptibility testing of antibiotic de-escalation was assessed in 35 patients; however, antibiotic de-escalation occurred in six patients. Thus, data of antimicrobial susceptibility testing has improved the management of Libyan outpatients with bacterial infection but their role in antibiotic de-escalation was slight. (shrink)

Identifying the necessary and sufficient conditions for individuating and classifying diseases is a matter of great importance in the fields of law, ethics, epidemiology, and of course, medicine. In this paper, I first propose a means of achieving this goal, ensuring that no two distinct disease-types could correctly be ascribed to the same disease-token. I then posit a metaphysical ontology of diseases—that is, I give an account of what a disease is. This is essential to providing the (...) most effective means of interfering with disease processes. Following existing work in the philosophy of medicine and epidemiology (primarily Christopher Boorse; Caroline Whitbeck; Alexander Broadbent), philosophy of biology (Joseph LaPorte; D.L. Hull), conditional analyses of causation (J.L. Mackie; David Lewis), and recent literature on dispositional essentialism (Stephen Mumford and Rani Anjum; Alexander Bird), I endorse a dispositional conception of disease. Following discussion of various conceptions of disease-identity, their relations to the clinical and pathological effects of the diseases in question, and how diseases are treated, I conclude (i) that diseases should be individuated by their causes, and (ii) that diseases are causal processes best seen as simultaneously acting sequences of mutually manifesting dispositions. (shrink)

The highly contagious 2019 novel coronavirus disease (COVID-19) outbreak has not only impacted health systems, economies, and governments, it has also rapidly grown into a global health crisis, which is now threatening the lives of millions of people globally. While, on one hand, medical institutions are critically attempting to find a cure, on the other hand, governments have introduced striking measures and policies to curtail the rapid spread of the disease. Although COVID-19 has achieved pandemic status and is (...) predominantly viewed as a biomedical issue, it is argued that it should also be treated as a psychological crisis. This paper also reviews the literature to examine and comment on the detrimental effects of isolation, which has been enforced as one of the primary preventative measures to manage the spread of COVID-19. This paper further outlines key recommendations that should be addressed across different levels to buffer against the known adverse effects of isolation, which is especially relevant for the current COVID-19 situation, where a large proportion of the global population is isolated, confined, and/or quarantined. (shrink)

Last year saw the 20th anniversary edition of JECP, and in the introduction to the philosophy section of that landmark edition, we posed the question: apart from ethics, what is the role of philosophy ‘at the bedside’? The purpose of this question was not to downplay the significance of ethics to clinical practice. Rather, we raised it as part of a broader argument to the effect that ethical questions – about what we should do in any given situation – are (...) embedded within whole understandings of the situation, inseparable from our beliefs about what is the case, what it is that we feel we can claim to know, as well as the meaning we ascribe to different aspects of the situation or to our perception of it. Philosophy concerns fundamental questions: it is a discipline requiring us to examine the underlying assumptions we bring with us to our thinking about practical problems. Traditional academic philosophers divide their discipline into distinct areas that typically include logic: questions about meaning, truth and validity; ontology: questions about the nature of reality, what exists; epistemology: concerning knowledge; and ethics: how we should live and practice, the nature of value. Any credible attempt to analyse clinical reasoning will require us to think carefully about these types of question and the relationships between them, as they influence our thinking about specific situations and problems. So, the answers to the question we posed, about the role of philosophy at the bedside, are numerous and diverse, and that diversity is illustrated in the contributions to this thematic edition. (shrink)

Plant diseases are numerous in the world of agriculture. These diseases cause a lot of trouble to most farmers. Among these common diseases, we single out the diseases that affect the Passion fruit, which is affected by about seven diseases, with different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily (...) requires human expertise. The first expert system was developed in 1965 by Edward Feigen Baum and Joshua Lederberg of Stanford University in California, U.S. Dendral, as their expert system was later known, was designed to analyses chemical compounds. Expert systems now have commercial applications in fields as diverse as medical diagnosis, petroleum engineering, and financial investing and other areas, and with reference to expert systems and their importance to humans, an integrated expert system has been created in the agricultural field that diagnoses Passion diseases using CLIPS Expert System language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of Passion -related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose Passion -related diseases. Objectives: is to help farmers diagnose Passion diseases in the correct way and how to treat these diseases. Method: The system contains a program project that diagnoses 7 diseases that affect Passion and the seven diseases are: Brown spot, Septoria spot, Root and crown rot, Fusarium wilt, Anthracnose, Woodiness virus, Scab. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing Passion diseases is effective and usable. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we (...) initiated the development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle (...) which is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (shrink)

In recent years, technology has evolved significantly to intervene in the treatment of diseases through diagnosis online before going to the specialist doctor, where it become possible for the patient to know the name of his illness, the specialist doctor who can treat him and the multiple treatment methods through specially designed systems called expert systems. The expert system is based on the principle of asking the user gradual questions about the symptoms he feels, leading him to the result of (...) diagnosing the illness, dealing with it quickly, and tips for permanent treatment. These systems may also help both trainee physicians and physiotherapists. This research paper is a living example of these effective applications, explaining in a simplified manner some of ankle diseases, how to deal with them and methods of physical therapy. The ankle is a small region in the leg. It is two joints, the first consist of three bones (tibia, fibula and talus underneath) which is called true ankle joint. The other is called subtalar joint have two bones: talus on top and calcaneus on the bottom. This tarsus between the end of the leg and the start of the foot facilitates the movement up-down and left-right with no problems in normal case, although, it needs a special case as Physiotherapist when gets injury. We have identified seven ankle diseases: Ankle Sprain, Fracture (of Fibula), Rheumatoid Arthritis, Rheumatoid Fever, Gout, and Osteoarthritis (Degenerative Joint) using SL5 Object Expert System Language in the work of the expert system. (shrink)

Clinical microbiology serves as a partner to clinicians in the diagnosis and treatment of infectious diseases. Antibiotics are prescribed empirically before the availability of antimicrobial susceptibility testing data, especially when the patient's medical status could deteriorate by suspending the treatment. To investigate the impact of antimicrobial susceptibility testing on the management of outpatients with suspected bacterial infection in Libyan patients, a cross-sectional prospective study concluded on microbial microdroplet culture by including outpatients with suspected bacterial infection, who have done antimicrobial susceptibility (...) testing. Thus, 53 Libyan patients with urinary tract infections and 14 Libyan patients with skin infections were included in this study. Before the availability of antimicrobial susceptibility testing data, 25 patients were appropriately treated while 42 patients were inappropriately treated. After the availability of antimicrobial susceptibility testing data, the number of appropriately treated patients increased to 57 patients. Thus, antimicrobial susceptibility testing improved the management of 41 patients by discontinuing an unnecessary antibiotic in four patients, starting necessary antibiotic therapy in 18 patients, and changing to more appropriate antibiotic in 19 patients. However, the antimicrobial susceptibility testing has no impact on the management of 24 patients and has led to the worsening of the management of two patients. The effect of antimicrobial susceptibility testing of antibiotic de-escalation was assessed in 35 patients; however, antibiotic de-escalation occurred in six patients. Thus, data of antimicrobial susceptibility testing has improved the management of Libyan outpatients with bacterial infection but their role in antibiotic de-escalation was slight. (shrink)

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on (...) and take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Nostalgia as one of the complex emotions has been challenged over the past few decades due to its psychological and physiological functions. The present experiment investigates the effect of recalling nostalgic memories on amelioration of homeostatic and health state of people with cardiovascular disease. Method: The participants were 30 patients who were hospitalized for angiography procedure. The research was based on an experimental design with randomized and post-test groups. The instruments used included a thermometer with ° C, a checkout (...) manipulation test, a blood pressure monitor, an ice container and a manual timer, a pain intensity perception scale and Batcho’s nostalgia questionnaire. Results: The results showed that there was a significant difference between the two groups in perceived temperature, the resilience in the face of pain, and the perceived pain. The experimental group perceived higher temperature and showed greater resilience in the face of pain and also lower pain intensity was reported. There was no significant difference in blood pressure between the two groups. Conclusion: The results of this study provide significant evidence for the embodiment emotions hypothesis and positive role of Nostalgia in psychological and physiological homeostatic. Further practical implications of results and suggestions for future research were considered. (shrink)

The cucumber is a creeping vine that roots in the ground and grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant may also root in a soilless medium, whereby it will sprawl along the ground in lieu of a supporting structure. The vine has large leaves that form a canopy over the fruits. Among these common diseases, we single out the diseases that affect the cucumber, which is affected by about 22 diseases, with (...) different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert systems that have become an integral part of human life as they contain several systems and areas, for example: Artificial Intelligence (AI), which refers to systems or devices that simulate Human intelligence to perform tasks that can improve itself based on some human information, and other areas, and with reference to expert systems and their importance to humans, an integrated expert system has been created in the agricultural field that diagnoses cucumber diseases using CLIPS Expert System language Delphi language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of cucumber-related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose cucumber-related diseases. Objectives: is to help farmers diagnose pear diseases in the correct way and how to treat these diseases. Method: The system contains a program that diagnoses 22 diseases that affect cucumber. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing cucumber diseases is effective and usable. (shrink)

Starting from the importance of the figure of the parrhesiastes — the political and therapeutic truth- teller— for Foucault’s understanding of the care of the self, this paper traces the political figuration of the analogy between philosophers and physicians on the one hand, and rhetors and disease on the other in Plato’s Gorgias. I show how rhetoric, in the form of ventriloquism, infects the text itself, and then ask how we account for the effect of the “ contaminated ” (...) philosophical dialogue on our readerly health. Is the text placebo, vaccine, or virus? All of these options, I argue, complicate Foucault’s prescription for parrhesia, requiring us to think anew the continuing political ramifications of the metaphor of care. (shrink)

Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching (...) 97.23%. The model's success is attributed to its ability to effectively leverage attributes related to eating habits, physical condition, and demographic factors. Feature importance analysis reveals key factors contributing to accurate predictions. This paper contributes to the field of health analytics by demonstrating the effectiveness of Random Forest in predicting and categorizing health risks. The insights gained from this research have the potential to inform personalized health interventions and contribute to the advancement of precision health strategies. Furthermore, the study highlights the importance of leveraging machine learning techniques for health risk assessment in diverse populations. (shrink)

After motivating a framework for evaluating top-down, middle-out, middle-in, and bottom-up ontology development strategies, we apply our framework to investigate whether infectious disease ontologies - specifically, the Virus Infectious Disease Ontology (VIDO) and the Coronavirus Infectious Disease Ontology (CIDO) - effectively promote semantic interoperability.

The idea of disease as an objective malfunctioning cannot be accepted for many different reasons. “Malfunctioning” or “failure” have a meaning only if the perfect working condition or normality is univocally determined. The differences between a person and any other person are not unimportant and cannot be ignored neither in diagnosis nor in treatment. These differences can be ascribable to three different sets of reasons: 1.illnesses leave irreversible marks on the organic structure, for they modify the information an organism (...) has at least as far as the neuroendocrine and immune systems are involved; 2.there are individual differences in the immune system; 3.there are individual differences in the functional organization of the brain that are not due only to biological causes. Furthermore the subjective perception of the illness itself must be included among the elements that determine the features of an illness. Notwithstanding the presence of the same symptoms and the same tests readings, two people may perceive their illness in a different way, with effects on the course of the illness itself and the effectiveness of the treatment. The idea of disease also depends on the cultural context. (shrink)

The interplay between the virus, infected cells and immune responses to SARS-CoV-2 is still under debate. By extending the basic model of viral dynamics, we propose here a formal approach to describe neutralisation versus weak (or non-)neutralisation scenarios and compare them with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with the data available in the literature; we show that both weakly neutralising antibodies and ADE can result in final viral clearance or disease progression, but (...) that the immunodynamics are different in each case. As a significant proportion of the world’s population is already naturally immune or vaccinated, we also discuss the implications for secondary infections after vaccination or in the presence of immune system dysfunctions. (shrink)

A central tenet of medical ethics holds that it is permissible to perform a medical intervention on a competent individual only if that individual has given informed consent to the intervention. However, in some circumstances it is tempting to say that the moral reason to obtain informed consent prior to administering a medical intervention is outweighed. For example, if an individual’s refusal to undergo a medical intervention would lead to the transmission of a dangerous infectious disease to other members (...) of the community, one might claim that it would be morally permissible to administer the intervention even in the absence of consent. Indeed, as we shall discuss below, there are a number of examples of public health authorities implementing compulsory or coercive measures for the purposes of infectious disease control (IDC). The plausibility of the thought that non-consensual medical interventions might be justified when performed for the purpose of IDC raises the question of whether such interventions might permissibly be used to realize other public goods. In this article we focus on one possibility: whether it could be permissible to non-consensually impose certain interventions that alter brain states or processes through chemical or physical means on serious criminal offenders. We shall suggest that some such interventions might be permissible if they safely and effectively serve to facilitate the offender’s rehabilitation and thereby prevent criminal recidivism. (shrink)

Introduction: Multiple sclerosis (MS) is an autoimmune disease that causes scar tissue in the nervous system and seriously affects the quality of life of people. Muscle weakness, spasticity and coordination problems are seen primarily in the lower extremities. Strengthening exercises improve muscle strength in people with multiple sclerosis, but there is no consensus on their effect on walking capacity. -/- Methods: To determine the relationship between gluteus maximus muscle strength, ataxia, balance and walking capacity in Multiple Sclerosis. An experimental (...) study design was applied. Gluteus maximus muscle strength was measured using a dynamometer. Walking capacity was determined by the 6-minute walk test (6MWT) and dynamic gait index (DGI). Balance was evaluated with the one-leg standing test (SLS). The severity of ataxia was measured with the International Ataxia Rating Scale (ICARS). Fatigue was evaluated with VAS and quality of life of all patients with SF36 short form. -/- Results: EDSS mean of the study = 3.39 ± 1.4; 2 men and 16 women with mean age = 37.17 ± 9.16 years were included. 6MWT, DGI, ALS, ICARS, VAS were different before and after treatment (p<0.05). There was no significant difference other than physical function and general health among the sub-parameters of SF36 (p>0.05). Correlation of muscle strength with ataxia, gait and balance was not significant (p>0.05) -/- Conclusion: In individuals with MS, the fact that the treatment program consists of modalities that include balance and sensory exercises as well as muscle strengthening exercises increases the success of rehabilitation. (shrink)

I argue that the scope of rational framing effects may be broader than Bermúdez assumes. Even in many “canonical experiments,” the explanation of the judgment reversals or shifts may refer to reasons, including moral ones. Referring to the Asian disease paradigm (ADP), I describe how non-consequentialist reasons related to fairness and the distinction between doing and allowing may help explain and justify the typical pattern of choices in the cases like ADP.

Weak inflammatory response after Salmonella infection can cause persistent infection and facilitate the long survival of pathogens. Honey can induce key immunomodulators such as TNF-α, interleukin-6 (IL-6) and IL-1, that it can be used in the treatment of bacterial infectious diseases caused by Salmonella typhi. The purpose of this study is to determine the effect of honey on the mRNA expression of IL-6 in Salmonella enterica Typhi induced of BABL/c mice. The study used experimental pretest-posttest control design. Honey treatment was (...) given for 7 days commencing after the induction of Salmonella bacteria. 20 BABL/c males mice whose weight 25-29 grams, were divided into four groups where 5 mice per group within; the negative control group was given regular feed without bacteria induction, the positive control group was given regular feed with bacteria induction, 0.27 ml/kg-weight honey group and 0.27 ml/kg-weight of Propolis honey group. Blood samples for examination of mRNA expression was examined three times that prior to the induction, 24 hours after induction and 72 hours after induction of Salmonella. The results showed that 0.27 ml/kg-weight of Propolis honey group showed the highest mRNA expression (p = 0.000) for both after 24 hours after induction of Salmonella typhi (p = 0.000) and 72 hours after induction of Salmonella typhi (p = 0.000). We conclude that there was effect of honey on the mRNA IL-6 expression in Salmonella typhi induced of BALB/c mice. (shrink)

Chronic kidney disease (CKD) is a global health problem with high morbidity and mortality rate, and it induces other diseases. There are no obvious incidental effects during the starting periods of CKD, patients routinely disregard to see the sickness. Early disclosure of CKD enables patients to seek helpful treatment to improve the development of this disease. AI models can effectively assist clinical with achieving this objective on account of their fast and exact affirmation execution. In this appraisal, proposed (...) a Logistic relapse framework for diagnosing CKD. Proposed calculation like NAIVE BAYES , DECISION TREE , KSTAR , LOGISITIC , AND SVM and look at these calculation and get the most noteworthy precision .AI store, which has an enormous number of missing qualities. Missing characteristics are for the most part found, taking everything into account, clinical conditions since patients might miss a couple of assessments for various reasons. By separating the misjudgements delivered by the set up models and proposed a fused model that unites determined backslide and sporadic woods by using perceptron. (shrink)

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. (...) By employing an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious (...) class='Hi'>Disease Ontology (CIDO). As an Open Biomedical Ontology (OBO) library ontology, CIDO is an open source and interoperable with other existing OBO ontologies. In this article, the general architecture and the design patterns of the CIDO are introduced, CIDO representation of coronaviruses, phenotypes, anti-coronavirus drugs and medical devices (e.g. ventilators) are illustrated, and an application of CIDO implemented to identify repurposable drug candidates for effective and safe COVID-19 treatment is presented. (shrink)

The ongoing COVID-19 pandemic has brought science to the fore of public discourse and, considering the complexity of the issues involved, with it also the challenge of effective and informative science communication. This is a particularly contentious topic, in that it is both highly emotional in and of itself; sits at the nexus of the decision-making process regarding the handling of the pandemic, which has effected lockdowns, social behaviour measures, business closures, and others; and concerns the recording and reporting (...) of disease mortality. To clarify a point that has caused much controversy and anger in the public debate, the first part of the present article discusses the very fundamentals underlying the issue of causative attribution with regards to mortality, lays out the foundations of the statistical means of mortality estimation, and concretizes these by analysing the recording and reporting practices adopted in England and their widespread misrepresentations. The second part of the article is empirical in nature. I present data and an analysis of how COVID-19 mortality has been reported in the mainstream media in the UK and the USA, including a comparative analysis both across the two countries as well as across different media outlets. The findings clearly demonstrate a uniform and worrying lack of understanding of the relevant technical subject matter by the media in both countries. Of particular interest is the finding that with a remarkable regularity (????>0.998), the greater the number of articles a media outlet has published on COVID-19 mortality, the greater the proportion of its articles misrepresented the disease mortality figures. (shrink)

Pesticides are the biological pollutants, which are being used by the man to kill the pests for increasing the yield of many crops and insect vectors to control the spread of disease. The tremendous use of pesticides has caused severe health hazards to organisms including human beings due to climate change. Excessive use of pesticides may lead to the destruction of biodiversity. Many birds, aquatic organisms and animals are under the threat of harmful pesticides for their survival. The pesticides (...) effects can be lessen by organizing awareness program among the farmers, special training to them regarding consequences of pesticides, their screening and monitoring methods. (shrink)

During the recent Ebola epidemic, some commentators and stakeholders argued that it would be unethical to carry out a study that withheld a potential treatment from affected individuals with such a serious, untreatable disease. As a result, the initial trials of experimental treatments did not have control arms, despite important scientific reasons for their inclusion. In this paper, we consider whether the duty to rescue entails that it would be unethical to withhold an experimental treatment from patient-participants with serious (...) diseases for which there are no effective treatments, even when doing so is scientifically necessary to test the effectiveness of the treatment. We argue that the duty to rescue will rarely apply. The context of medical research also throws new light on the content of the duty to rescue, since the interests of future patients—who stand to benefit from the fruits of medical research—are relevant to whether the duty applies. (shrink)

The study investigated ethical considerations and science diplomacy on coronavirus disease (Covid-19) pandemic in Nigeria. The outbreak of the coronavirus disease (Covid-19) in Nigeria has spread quickly to about 34 states out of the 36 states and over 5000 persons have tested positive as at the time of this research after the first index case of an Italian and there is a projection that in coming days and weeks the number of infected persons and states will increase. The (...) study was guided by two objectives and also adopted the normative ethical theory. The study employed the methods of exposition and critical analysis to explain better the ethical issues and science diplomacy of Covid-19 pandemic in Nigeria. Data was sourced from secondary sources such as journal articles, newspaper, books and internet sources. The findings of the study showed that the citizens have some obligations that will aid the containment of the virus and as well as the government. The study also found out that science diplomacy was used, which has led to Nigeria collaborating with China to get medical aids to effectively fight the pandemic. Consequently, the study recommended amongst others that the Ministry of Health and the Nigeria Center for Disease Control (NCDC) should adopt and enforce the World Health Organization (WHO) Guidance for Managing Ethical Issues in Infectious Disease Outbreak as a working document in crisis like the Covid-19 pandemic that has ravaged Nigeria and the government should involve more in science diplomacy with other countries so that it will help in the fight against Covid-19 and other diseases that may occur in the future. (shrink)

Purpose of Review Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is identified from Wuhan, China, and has spread almost worldwide. Recently, the newly identified SARS-CoV-2 has been confirmed to kill millions of people worldwide and is dangerous to society health, survival, and livelihood. The people with cardiovascular problems are noticed as most common patients of coronavirus disease 2019 (COVID-19). There is a greater risk of mortality and morbidity in these patients than other patients of COVID-19. In the heart, expressed angiotensin-converting (...) enzyme 2 (ACE2) and response effect of hyperactivity with angiotensin II associated to the renin-angiotensin mechanism are key factors of hypertension, atherosclerosis, and congestive heart failure. -/- Recent Findings Mortality rates have been observed about 10.5% cases in patients with cardiovascular disease; however, a mortality rate of 52% was recorded in patients with heart failure, while 12% recovered ultimately. The occupancy of intense injury controlled by troponin elevation was a noteworthy factor in relation to mortality. Among 187 patients infected with SARS-CoV-2, about 35% were diagnosed with cardiovascular disease (CVD) history and 28% with raised troponin. Troponin elevation was identified more frequently (55%) in patients with cardiovascular diseases. Mortality rate in patients without cardiovascular diseases and normal troponin was 7.6%, normal troponin and cardiovascular disease with 13.3%, augmented troponin and without cardiovascular disease 37.5%, however 69.4% among cardiovascular disease and advanced troponin. -/- Summary The study reflected a significant association of case fatality rate (CFR) to COVID-19 patients with cardiovascular diseases which supposed to be the most common dangerous risk factor and health challenge during the current pandemic situation. (shrink)

Moralising accounts of depression include the idea that depression is a sin or the result of sin, and/or that it is the result of demonic possession which has occurred because of moral or spiritual failure. Increasingly some Christian communities, understandably concerned about the debilitating effects these views have on people with depression, have adopted secular folk psychiatry’s ‘medicalising’ campaign, emphasising that depression is an illness for which, like (so-called) physical illnesses, experients should not be held responsible. This paper argues that (...) both moralising and medicalising models of depression are intellectually and practically (pastorally and therapeutically) problematic, gesturing towards more promising emphases. (shrink)

Today the world is suffering from coronavirus (COVID-19) pandemic illness, and people all around the world stay at home due to its rapid spread. People including students gather information and government instructions through TVs, social media and others around them. Since the classes were canceled in many countries, the novel coronavirus affects students’ interest in coursework. The purpose of this study was to examine the effect of TV news, social media and communication with people on interest in coursework, and mediating (...) roles of fear of contamination, depression, and anxiety on these effects. A path analysis was carried out with the data collected from 773 college students. The results showed that interest in coursework was most strongly affected by communication with people. This was due to its direct and indirect effects. Social media and TV News did not directly affect interest in coursework, but indirectly affected. The study also found that among the three mediator variables, the mediator roles of anxiety was bigger than the others. Understanding the findings of this research has become very important to us, especially at a time when face-to-face lessons have been canceled all over the world and transitioned to online education. Specific recommendations for practitioners and limitations for future research were also provided in the study. (shrink)

COVID-19 demonstrated a global catastrophe that touched everybody, including the scientific community. As we respond and recover rapidly from this pandemic, there is an opportunity to guarantee that the fabric of our society includes sustainability, fairness, and care. However, approaches to environmental health attempt to decrease the population burden of COVID-19, toward saving patients from becoming ill along with preserving the allocation of clinical resources and public safety standards. This paper explores environmental and public health evidence-based practices toward responding to (...) Covid-19. A literature review tried to do a deep dive through the use of various search engines such as Mendeley, Research Gate, CAB Abstract, Google Scholar, Summon, PubMed, Scopus, Hinari, Dimension, OARE Abstract, SSRN, Academia search strategy toward reretrieving research publications, “grey literature” as well as reports from expert working groups. To achieve enhanced population health, it is recommended to adopt widespread evidence-based strategies, particularly in this uncertain time. As only together can evidence-informed decision-making (EIDM) can become a reality which includes effective policies and practices, transparency and accountability of decisions, and equity outcomes; these are all more relevant in resource-constrained contexts, such as Nigeria. Effective and ethical EIDM though requires the production as well as use of high-quality evidence that are timely, appropriate and structured. One way to do so is through co-production. Co-production (or co-creation or co-design) of environmental/public health evidence considered as a key tool for addressing complex global crises such as the high risk of severe COVID-19 in different nations. A significant evidence-based component of environmental/public health (EBEPH) consist of decisions making based on best accessible, evidence that is peer-reviewed; using data as well as systematic information systems; community engagement in policy making; conducting sound evaluation; do thorough program-planning frameworks; as well as disseminating what is being learned. As researchers, scientists, statisticians, journal editors, practitioners, as well as decision-makers strive to improve population health, having a natural tendency toward scrutinizing the scientific literature aimed at novel research findings serving as the foundation for intervention as well as prevention programs. The main inspiration behind conducting research ought to be toward stimulating and collaborating appropriately on public/environmental health action. Hence, there is need for a “Plan B” of effective behavioural, environmental, social as well as systems interventions (BESSI) toward reducing transmission. (shrink)

This paper addresses a family of issues surrounding the biological phenomenon of resistance and its representation in realist ontologies. The treatments of resistance terms in various existing ontologies are examined and found to be either overly narrow, internally inconsistent, or otherwise problematic. We propose a more coherent characterization of resistance in terms of what we shall call blocking dispositions, which are collections of mutually coordinated dispositions which are of such a sort that they cannot undergo simultaneous realization within a single (...) bearer. A definition of ‘protective resistance’ is proposed for use in the Infectious Disease Ontology (IDO) and we show how this definition can be used to characterize the antibiotic resistance in Methicillin-Resistant Staphylococcus aureus (MRSA). The ontological relations between entities in our MRSA case study are used alongside a series of logical inference rules to illustrate logical reasoning about resistance. A description logic representation of blocking dispositions is also provided. We demonstrate that our characterization of resistance is sufficiently general to cover two other cases of resistance in the infectious disease domain involving HIV and malaria. (shrink)

nanological gates, in order to design nano-scale computers with dual-scale capabilities. All living biological systems function due to the molecular interactions of different subsystems. Molecular components (proteins and nucleic acids, lipids and carbohydrates, DNA and RNA) can be used as an inspirational strategy on how to design high-performance NEMS and MEMS that have the required features and characteristics. Considered. In addition, analytical and numerical methods are available for dynamic analysis and three-dimensional geometry, bonding and other properties of atoms and molecules. (...) Thus, electromagnetic and mechanical, and other physical and chemical properties can be studied. Nanostructures and nanosystems can be widely used in medicine and health. Possible applications of nanotechnology include: drug synthesis and drug delivery (therapeutic potential is greatly increased due to the effective direct delivery of new types of drugs to specific sites in the body), nanosurgery and nanotherapy Synthesis and detection of genomes, nano-scale stimuli and sensors (diagnosis and prevention of disease), design and implantation of non-rejection artificial organs and design of high performance nanomaterials. It is important that these technologies change the manufacture of materials, devices and systems. (shrink)

Objective: The coronavirus disease 2019 (Covid-19) has significantly affected human health around the world, causing many complications. However, it is not fully understood how the body compositions of individuals affected in the short or long term after disease. In this study, we aimed to show the effects of Covid-19 on body composition and phase angle values, using Bioelectrical Impedance Analayser. -/- Methods: Subjects were selected from individuals in the 18-60 age group, who had survived COVID-19 disease. 33 (...) individuals who had survived it 1-3 months ago, and 30 individuals who had survived it 3-6 months ago were included in the study. -/- Results: Effects of COVID-19 on basal metabolism and body composition and the ratio of damaged cells in the body after the disease were determined. Basal metabolic rate, lean body mass, body cell mass, total body fluid, intracellular fluid, and phase angle values were found to be significantly changed in the 3-6 months range compared to that of 1-3 months. -/- Conclusion: These results indicate that the basal metabolism and body composition parameters of the body become better, and the proportion of damaged cells decreases as time goes on after suffering COVID-19, reaching values close to normal in 1-3 months and quite better values in 3-6 months. It can be concluded that, although covid-19 influences body composition parameters and cell integrity in survivors of Covid 19 disease, these effects are limited to 3-6 months. (shrink)

Coronavirus disease (Covid-19) is an infectious disease caused by the SARS-CoV-2 virus. Spreading rate of mutated corona virus (delta variant) during second wave was very fast. Most of the people infected with the COVID-19 virus experienced mild to moderate to severe respiratory illness. Although patients in the second wave were younger but the duration of hospitalization and case fatality rate were lower than those in the first wave. During first wave of Covid-19 it was observed that persons above (...) 55 years of age and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease and cancer were more susceptible to develop serious illness but in second it was observed that person between 30 to 55 years along with old age and younger people suffering from hypertension, diabetes and respiratory diseases were more susceptible to this covid-19 virus. The most frequent signs and symptoms in both waves were fever, dyspnea, pneumonia, and cough, and the most relevant comorbidities were cardiovascular diseases, type 2 diabetes mellitus, and chronic neurological diseases. Every country has lost its human resources due to covid-19 virus which not only disturb the social life but economic conditions are also very badly affected. Now we use the resources so rapidly that may create economic imbalance in future. The psychological effect is an essential component of disaster management of infectious pandemics. (shrink)