Emerging Pandemic Infectious Disease Threats

Pandemic infectious diseases are caused by pathogens that have adapted well to growth and reproduction within the human host and that through unique environmental, socioeconomic, and cultural circumstances are able to rapidly spread across national boundaries and even globally. Although uncommon and caused by relatively few pathogens, the extraordinary human, economic, and societal losses caused by pandemic diseases as exemplified by coronavirus disease 2019 (COVID-19) make pandemic diseases of unique importance to clinicians, immunologists, and many other scientists and healthcare professionals. The pathogenesis of pandemic diseases is complex and unique to each pathogen, but common to all is widespread immunologic naïveté within the host population. In this chapter, we consider the pathogens of greatest concern for their pandemic potential. Most of these organisms are viruses, including betacoronaviruses, alpha influenza virus, Ebola virus, and the flaviviruses, but numerous bacteria are also emerging with pandemic disease potential. For each organism, we consider the factors, especially immunologic, that lead to pandemic spread and prospects for effective therapy and prevention. © 2023 Elsevier Ltd. All rights reserved.

Pandemic Diseases and Re-examination of the Concept of National Security

Pandemics are not a new phenomenon in human history or international relations. Over the centuries, pandemics have affected the course of human history by changing people's perceptions and approach regarding national security and international stability. Pandemics have also affected mobility and behavior among different communities of the world. In today's world of proliferating nontraditional challenges, pandemics are the newest addition to a growing list of national security threats and government priorities. The coronavirus pandemic is prompting national governments around the world to re-examine and update their national security concept and devise new, more effective measures to manage and mitigate the impacts of public health crises. © 2023 World Scientific Publishing Company.

Retrospective Characterization of the COVID-19 Epidemic in Four Selected European Countries Via Change Point Analysis

The focus of this contribution is to show how the course of the pandemic can be retrospectively investigated in terms of change points detection. At this aim, an automatic method based on recursive partitioning is employed, considering the time series of the 14-day notification rate of newly reported COVID-19 cases per 100,000 population collected by the European Centre for Disease Prevention and Control. The application shows that the pandemic, at the individual country level, can be broken into different periods that do not correspond to the common notion of wave as a natural pattern of peaks and valleys implying predictable rises and falls. This retrospective analysis can be useful either to evaluate the implemented measures or to define adequate policies for the future. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Peace, Pandemics, and Conflict

This chapter explores the nexus between peace, pandemics, and conflict. It begins by discussing the role that disease has had in shaping human history. The risk of a natural pandemic becoming an extinction-level threat to humanity is then assessed. Pandemics' effects on making conflict more likely are identified as an under-researched area. Peacebuilding opportunities alongside pandemic preparedness and response are discussed. The chapter then concludes with a discussion of critical questions for future research on the relationships between peace, pandemics, and conflict. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Does paid sick leave encourage staying at home? Evidence from the United States during a pandemic.

We study the impact of a temporary U.S. paid sick leave mandate that became effective April 1st, 2020 on self-quarantining, proxied by physical mobility behaviors gleaned from cellular devices. We study this policy using generalized difference-in-differences methods, leveraging pre-policy county-level heterogeneity in the share of workers likely eligible for paid sick leave benefits. We find that the policy leads to increased self-quarantining as proxied by staying home. We also find that COVID-19 confirmed cases decline post-policy.

Mutations in SARS-CoV-2: Insights on structure, variants, vaccines, and biomedical interventions.

COVID-19 is a worldwide pandemic caused by SARS-coronavirus-2 (SARS-CoV-2). Less than a year after the emergence of the Covid-19 pandemic, many vaccines have arrived on the market with innovative technologies in the field of vaccinology. Based on the use of messenger RNA (mRNA) encoding the Spike SARS-Cov-2 protein or on the use of recombinant adenovirus vectors enabling the gene encoding the Spike protein to be introduced into our cells, these strategies make it possible to envisage the vaccination in a new light with tools that are more scalable than the vaccine strategies used so far. Faced with the appearance of new variants, which will gradually take precedence over the strain at the origin of the pandemic, these new strategies will allow a much faster update of vaccines to fight against these new variants, some of which may escape neutralization by vaccine antibodies. However, only a vaccination policy based on rapid and massive vaccination of the population but requiring a supply of sufficient doses could make it possible to combat the emergence of these variants. Indeed, the greater the number of infected individuals, the faster the virus multiplies, with an increased risk of the emergence of variants in these RNA viruses. This review will discuss SARS-CoV-2 pathophysiology and evolution approaches in altered transmission platforms and emphasize the different mutations and how they influence the virus characteristics. Also, this article summarizes the common vaccines and the implication of the mutations and genetic variety of SARS-CoV-2 on the COVID-19 biomedical arbitrations.

Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of Tropical Andean South America: a spatiotemporally disaggregated time series analysis.

Background: The COVID-19 pandemic has caused societal disruption globally and South America has been hit harder than other lower-income regions. This study modeled effects of 6 weather variables on district-level SARS-CoV-2 reproduction numbers (R t ) in three contiguous countries of Tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors. Methods: Daily time-series data on SARS-CoV-2 infections were sourced from health authorities of the three countries at the smallest available administrative level. R t values were calculated and merged by date and unit ID with variables from a Unified COVID-19 dataset and other publicly available sources for May - December 2020. Generalized additive models were fitted. Findings: Relative humidity and solar radiation were inversely associated with SARS-CoV-2 R t . Days with radiation above 1,000 KJ/m2 saw a 1.3%, and those with humidity above 50%, a 0.9% reduction in R t . Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with least population mobility. Wind speed, temperature, region, aggregate government policy response and population age structure had little impact. The fully adjusted model explained 4.3% of R t variance. Interpretation: Dry atmospheric conditions of low humidity increase, and higher solar radiation decrease district-level SARS-CoV-2 reproduction numbers, effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures. Funding: NASA's Group on Earth Observations Work Programme (16-GEO16-0047).

The protective role of corporate social responsibility performance during the coronavirus pandemic disease, performance evaluation using a mathematical model of the directional distance function

The outbreak of coronavirus worldwide has created many problems for companies. Companies are looking for a suitable solution to overcome this crisis. One of the measures that can reduce the negative effects of this crisis is the expansion of corporate social responsibility (CSR) activities. The purpose of this study was to investigate the protective role of the performance of CSR activities from stock returns and its effect on shareholder attention during coronary heart disease. This study is an event study that is considered for a period of six months from the beginning of the outbreak of coronavirus in Iran (February 2020) to the end of August 2020. The data analysis was performed using Eviews software and information of 33 sample member companies listed on the Tehran Stock Exchange, in three industries: pharmaceutical, food, and transportation, by least squares regression (OLS) method. The results show that the performance of CSR activities related to community indicators, employee relations, and human rights in the event periods have a positive role on the corporate stock returns and other activities do not play an effective role. The results also show that the performance of CSR has a positive and significant effect on the attention of shareholders. Using the obtained results, it can be concluded that corporations can attract stakeholders and protect the value of the companies by increasing the performance of CSR activities, especially in the community, employee relations, and human rights during the coronavirus pandemic disease period.

Optimal control strategy to control pandemic Covid-19 using MSILIHR_V Model

Many researchers began doing studies about pandemic COVID-19 which began to spread from Wuhan, China in 2019 to all around the world and so far, numerous researches have been done around the world to control this contagious disease. In this paper, we proposed a MSIlIhR-V mathematical model to study the spreading of pandemic COVID-19. This paper is aimed to study the vaccination effect in the control of the disease propagation rate. Another goal of this paper is to find the maximum number of susceptible people, minimum number of infected people, and the best value for number of vaccination people. The Jacobian matrix was obtained in the virus absenteeism equilibrium point for the proposed dynamical system. The spectral radius method was applied to find the analytical formula for the reproductive number. Reproductive number is one of the most benefit and important tools to study of epidemic model's stability and instability. In the following, by adding a controller to the model and also using the optimal control strategy, model performance was improved. To validate of the proposed models with controller and without controller we use the real data of COVID-19 from 4 January, 2021 up to 14 June, 2021 in Iran. Maple and MATLAB software's will be used for programming. We will use Maple software for analytical parts and MATLAB software for numerical and simulation parts.

Mathematical Insight of COVID-19 Infection—A Modeling Approach

Application of mathematics has gotten progressively abundant in epidemic disease research. The complexity of disease is appropriate to quantitative methodologies as it gives difficulties and chances to new turns of events. Thusly, computational modeling demonstrating to epidemiology research by assisting with clarifying components and by giving quantitative expectations that can be approved. The ongoing extension of quantitative models tends to numerous inquiries with respect to Epidemic disease (COVID-19) inception, and treatment reactions and opposition. These models have allowed researchers to better understand the physical phenomena. Computational models can supplement exploratory and clinical investigations, yet additionally challenge flow standards, reclassify our comprehension of systems driving epidemiology and shape future research. © 2021 Scrivener Publishing LLC.

Identification of SARS-CoV-2 by Gold Nanoparticles

The SARS-CoV-2 outbreaks highlighted the need for effective, reliable, fast, easy-to-do and cheap diagnostics procedures. We pragmatically experienced that an early positive-case detection, inevitably coupled with a mass vaccination campaign, is a milestone to control the COVID-19 pandemic. Gold nanoparticles (AuNPs) can indeed play a crucial role in this context, as their physicochemical, optics and electronics properties are being extensively used in photothermal therapy (PTT), radiation therapy (RT), drug delivery and diagnostic. AuNPs can be synthesized by several approaches to obtain different sizes and shapes that can be easily functionalized with many kinds of molecules such as antibodies, proteins, probes, and lipids. In addition, AuNPs showed high biocompatibility making them useful tool in medicine field. We thus reviewed here the most relevant evidence on AuNPs as effective way to detect the presence of SARS-CoV-2 antigens. We trust future diagnostic efforts must take this 'old-fashioned' nanotechnology tool into consideration for the development and commercialization of reliable and feasible detection kits.

Postulation of Siddha tri-humoral vitiation in pathogenesis of novel Corona virus disease

Background: On March 12, 2020, WHO declared Novel Coronavirus disease as a pandemic outbreak all over the world. The outbreak had led the medical sector to a new platform, in the implementation of ancient knowledge of the Siddha medicine in treatment, management, and prevention of this prevailing pandemic. According to Siddha science, any vitiation in the life force is the main cause of diseases in human beings. pandemic diseases caused due to infectious microorganisms are called 'Kona' Noigal' in various Siddha literatures. Aim and objective: To classify the Novel Coronavirus disease based on the Siddha Humoural principles and to elicit the changes of Ninety-six Thatthuvam (Ninety - six basic principles), Uyir Thathukkal and Udal Thathukkal. Materials and methods: This study is accomplished mainly for literature research. Various Siddha texts such as Sattamuni gnanam, Agathiyar Gunavagadam, Agathiyar vallathi Naadi, Theraiyar Sekarappa, etc. were referred. Numerous research articles on COVID 19 were critically reviewed from Scopus, PubMed, Google Scholar, etc. Discussion: By critically reviewing the signs and symptoms of COVID-19 with Siddha science, the authors had thrown light especially on the involvement of all basic components of the Tri thodam particularly Mukkutram verupadu (Tri humoral vitiation) in eliciting the pathogenesis of the disease. Conclusion: In this scientific review, the authors have attempted to comprehend the pathogenesis of Novel coronavirus disease in the context of Siddha's basic principles.

A Chilean Experience of Telestroke in a COVID-19 Pandemic Year.

BACKGROUND AND PURPOSE: Telemedicine for stroke patients' care (telestroke [TS]) has grown notably in recent decades and may offer advantages during health crisis. Hospital admissions related to stroke have decreased globally during the COVID-19 pandemic, but scarce information is available regarding the effect of COVID-19 in TS. Using a population-based TS registry, we investigated the impact of the first year of the COVID-19 pandemic throughout our TS network in Santiago, Chile. METHODS: Stroke codes evaluated after the onset of COVID-19 restrictions in Chile (defined as March 15, 2020) were compared with those evaluated in 2019. We analyzed differences between number of stroke codes, thrombolysis rate, stroke severity, and time from the stroke onset to hospital admission. RESULTS: We observed that the number of stroke codes and the number of patients undergoing reperfusion therapy did not change significantly (p = 0.669 and 0.415, respectively). No differences were found with respect to the median time from the stroke onset to admission (p = 0.581) or in National Institutes of Health Stroke Scale (NIHSS) scores (p = 0.055). The decision-making-to-needle time was significantly shorter in the COVID-19 period (median 5 min [IQR 3-8], p < 0.016), but no significant changes were found at the other times. CONCLUSIONS: This study demonstrates the potential of adapting TS to extreme situations such as the COVID-19 pandemic, as well as the importance of establishing networks that facilitate patient access to quality treatments.

Production of recombinant SARS-CoV-2 3CL-protease: The key for the development of protease inhibitors screening kit in search of potential herb cure for COVID-19

Coronavirus disease-19 (COVID-19) pandemic caused millions of deaths and socio-economics damage worldwide. Corresponding to this, many studies on antiviral drugs exploration are rising to investigate the potential of drug compounds that can repress the replication of the SARS-CoV-2 virus by targeting its main protease named 3-chymotrypsin like protease (3CLpro). Without 3CLpro splicing, polyproteins of SARS-CoV-2 will not function to form new virions. We conducted an in silico thermodynamic study, and found several already known compounds from natural sources such as lovastatin, quinidine, and quinine were potential in inhibiting 3CLpro. However, most of the findings still need further wet-lab experiments to confirm their activity against it. To facilitate rapid screening of protease inhibitors, we aim to develop a screening kit for researchers with focus studies on herbal sources for COVID-19 treatments. Hence, the development of 3CLpro as the target of inhibition screening is essential. Our current work focused on the expression of the SARS-CoV-2 3CL Pro gene harbored by pET-32b(+) in E. coli BL21(DE3) and its purification. The recombinant E.coli were cultivated in LB media at 37 °C with 5 hours IPTG-induced phase followed by crude protein lysate extraction by sonication, and then Ni-NTA purification. A band of recombinant 3CLpro protein (33.8 kDa) detected by SDS PAGE and Western blotting after Ni-NTA purification was specific and clear, showing the right size of our protein interest. A final concentrated protein mixture obtained by 10-kDa membrane filtration displayed >90% purity with a total protein of 2.497 mg mL-1. Further functional assays and inhibitory tests with several natural compounds showed that 3CLpro functioned well as a drug target. © Published under licence by IOP Publishing Ltd.

Hematological and Serological Parameters for Detection of Covid-19

Coronavirus disease (COVID-19) appeared as outbreak in 2019 in Wuhan, China. It has been classified as pandemic disease and more severe than predicted;with infections already recorded in a variety of countries. This study aims to confirm the COVID-19 infection through the following tests: hematological, C-reactive protein (CRP). Samples were collected from the infected patients and sent to the National Flu Center (Central Public Health Laboratory) for COVID-19 (positive or negative) diagnosis by the RT-PCR technique. In this study, sixty five of COVID-19 patients and twenty five of healthy control samples male and female were collected in Iraq. There are significant differences in the parameters of the hematological markers for patients in comparing with the control group and no significant differences were observed in Hb when RBC and GRAN percent rise in patients relative to the control group with P=0.0395 and P=0.0354 respectively comparing with the control group. White blood cells (WBC), Lymphocyte (LYM%), Platelets (PIT), monocyte (Mid%), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean platelet volume (MPV), plateletcrit (PCT) was drop dramatically in patients compared to control group. Fifty-one of patients for whom the test was given exhibited a positive (CRP) result. Likewise, the results showed that few patients were negative to CRP test. The Hematological parameters levels (HCT, MCV, MCH, Pelt, WBC, LYM, Mid, MPV, PCT) decreased, but Hb, RBC, GRAN% increased. C-reactive protein test showed a positive result in 85% of patients which can be considered an indicator for predicting severity infection with COVID-19. © 2022. All Rights Reserved.

In-silico investigation of phytochemicals from Asparagus racemosus as plausible antiviral agent in COVID-19.

COVID-19 has ravaged the world and is the greatest of pandemics in human history, in the absence of treatment or vaccine the mortality and morbidity rates are very high. The present investigation was undertaken to screen and identify the potent leads from the Indian Ayurvedic herb, Asparagus racemosus (Willd.) against SARS-CoV-2 using molecular docking and dynamics studies. The docking analysis was performed on the Glide module of Schrödinger suite on two different proteins from SARS-CoV-2 viz. NSP15 Endoribonuclease and spike receptor-binding domain. Asparoside-C, Asparoside-D and Asparoside -F were found to be most effective against both the proteins as confirmed through their docking score and affinity. Further, the 100 ns molecular dynamics study also confirmed the potential of these compounds from reasonably lower root mean square deviations and better stabilization of Asparoside-C and Asparoside-F in spike receptor-binding domain and NSP15 Endoribonuclease respectively. MM-GBSA based binding free energy calculations also suggest the most favourable binding affinities of Asparoside-C and Asparoside-F with binding energies of -62.61 and -55.19 Kcal/mol respectively with spike receptor-binding domain and NSP15 Endoribonuclease. HighlightsAsparagus racemosus have antiviral potentialPhytochemicals of Shatavari showed promising in-silico docking and MD resultsAsparaoside-C and Asparoside-F has good binding with target proteinsAsparagus racemosus holds promise as SARS-COV-2 (S) and (N) proteins inhibitor Communicated by Ramaswamy H. Sarma.

Repositioning of Fungal-based Peptides as Modulators of Angiotensin-converting Enzyme-related Carboxypeptidase, SARS-coronavirus HR2 Domain, and Coronavirus Disease 2019 Main Protease.

BACKGROUND AND OBJECTIVES: Angiotensin-converting enzyme-related carboxypeptidase, SARS-Coronavirus HR2 Domain, and COVID-19 main protease are essential for the cellular entry and replication of coronavirus in the host. This study investigated the putative inhibitory action of peptides form medicinal mushrooms, namely Pseudoplectania nigrella, Russula paludosa, and Clitocybe sinopica, towards selected proteins through computational studies. MATERIALS AND METHODS: The respective physicochemical properties of selected peptides were predicted using ProtParam tool, while the binding modes and binding free energy of selected peptides toward proteins were computed through HawkDock server. The structural flexibility and stability of docked protein-peptide complexes were assessed through iMODS server. RESULTS: The peptides showed an optimum binding afinity with the molecular targets; plectasin from P. nigrella showed the highest binding free energy compared to peptides from R. paludosa and C. sinopica. Besides, molecular dynamic simulations showed all fungal-based peptides could influence the flexibility and stability of selected proteins. CONCLUSION: The study revealed fungal-based peptides could be explored as functional modulators of essential proteins that are involved in the cellular entry of coronavirus.

Potential Drugs for the Treatment of COVID-19: Synthesis, Brief History and Application.

Coronaviruses (CoVs) belong to the Betacoronavirus group, an unusually large RNA genome characterized by club-like spikes that project from their surface. An outbreak of a novel coronavirus 2019 (nCOVID-19) already showed a unique replication strategy and infection that has posed significant threat to international health and the economy around the globe. Scientists around the world are investigating few previously used clinical drugs for the treatment of COVID-19. This review provides synthesis and mode of action of recently investigated drugs like Chloroquine, Hydroxychloroquine, Ivermectin, Selamectin, Remdesivir, Baricitinib, Darunavir, Favipiravir, Lopinavir/ ritonavir and Mefloquine hydrochloride that constitute an option for COVID-19 treatment.

Controlling of pandemic COVID-19 using optimal control theory.

In 2019, a new infectious disease called pandemic COVID-19 began to spread from Wuhan, China. In spite of the efforts to stop the disease, being out of the control of the governments it spread rapidly all over the world. From then on, much research has been done in the world with the aim of controlling this contagious disease. A mathematical model for modeling the spread of COVID-19 and also controlling the spread of the disease has been presented in this paper. We find the disease-free equilibrium points as trivial equilibrium (TE), virus absenteeism equilibrium (VAE) and virus incidence equilibrium (VIE) for the proposed model; and at the trivial equilibrium point for the presented dynamic system we obtain the Jacobian matrix so as to be used in finding the largest eigenvalue. Radius spectral method has been used for finding the reproductive number. In the following, by adding a controller to the model and also using the theory of optimal control, we can improve the performance of the model. We must have a correct understanding of the system i.e. how it works, the various variables affecting the system, and the interaction of the variables on each other. To search for the optimal values, we need to use an appropriate optimization method. Given the limitations and needs of the problem, the aim of the optimization is to find the best solutions, to find conditions that result in the maximum of susceptiblity, the minimum of infection, and optimal quarantination.

Retrospective and prospective application of robots and artificial intelligence in global pandemic and epidemic diseases.

About 4.25% of people have lost their lives due to COVID-19 disease, among SARS-CoV-2 infected patients. In an unforeseen situation, approximately 25,000 frontline healthcare workers have also been infected by this disease while providing treatment to the infected patients. In this devastating scenario, without any drug or vaccine available for the treatment, frontline healthcare workers are highly prone to viral infection. However, some countries are drastically facing a shortage of healthcare workers in hospitals. METHODS: The literature search was conducted in ScienceDirect and ResearchGate, using words "Medical Robots", and "AI in Covid-19" as descriptors. To identify and evaluate the articles that create the impact of robots and artificial intelligence in pandemic diseases. Eligible articles were included publications and laboratory studies before and after covid-19 and also the prospective and retrospective of application of Robots and AI. CONCLUSION: In this pandemic situation, robots were employed in some countries during the COVID-19 outbreak, which are medical robots, UV-disinfectant robots, social robots, drones, and COBOTS. Implementation of these robots was found effective in successful disease management, treatment, most importantly ensures the safety of healthcare workers. Mainly, the Disposal of deceased bodies and the location and transportation of infected patients to hospitals and hospitals were tough tasks and risk of infection. These tasks will be performed by employing mobile robots and automated guided robots respectively. Therefore, in the future, advanced automated robots would be a promising choice in hospitals and healthcare centers to minimize the risk of frontline healthcare workers.

Cerca de un 4,25% de personas han perdido la vida a causa de la COVID-19, entre los pacientes infectados por SARS-CoV-2. En esta situación imprevista, aproximadamente 25.000 trabajadores sanitarios de primera línea se han visto también infectados por esta enfermedad, al proporcionar tratamiento a los pacientes infectados. En este escenario devastador, en el que no se dispone de fármacos o vacunas para el tratamiento, el personal sanitario de primera línea está altamente expuesto a la infección vírica. Sin embargo, algunos países se están enfrentando a un recorte drástico de personal sanitario en sus hospitales. MÉTODOS: Se realizó una búsqueda en la literatura en ScienceDirect y ResearchGate, utilizando los términos «medical robots¼ y «AI in COVID-19¼ como factores descriptivos, para identificar y evaluar los artículos que crean el impacto de los robots y la inteligencia artificial (AI) en las pandemias. Los artículos elegibles incluyeron publicaciones y estudios de laboratorio, antes y después de la COVID-19, y también la aplicación prospectiva y retrospectiva de robots e AI. CONCLUSIÓN: En esta situación de pandemia, algunos países utilizaron robots durante el brote de COVID-19, es decir, robots médicos, robots desinfectantes de rayos UV, robots sociales, drones, y cobots. Se encontró que la implementación de estos robots era eficaz para la gestión y tratamiento de la enfermedad y, más importantemente, la garantía de la seguridad del personal sanitario. En particular, la eliminación de cadáveres y la localización y transporte de pacientes infectados a los hospitales eran tareas duras que suponían un riesgo de infección. Dichas tareas podrán realizarse utilizando robots móviles y robots automatizados, respectivamente. Por tanto, en el futuro, los robots automatizados avanzados constituirán una elección prometedora en hospitales y centros sanitarios, para minimizar el riesgo del personal sanitario de primera línea.