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Based on the SEIR model, two compartments for self-protection and isolation are introduced, and a more general infectious disease transmission model is proposed.Through qualitative analysis of the model, the basic reproduction number of the model is calculated, and the local asymptotic stability of the disease-free equilibrium point and the endemic equilibrium point of the model is analyzed through eigenvalue theory and Routh-Hurwitz criterion.The numerical simulation and fitting results of COVID-19 virus show that the proposed SEIQRP model can effectively describe the dynamic transmission process of the infectious disease.In the model, the three parameters, i.e.protection rate, incubation period isolation rate, and infected person isolation rate play a very critical role in the spread of the disease.Raising people's awareness of self-protection, focusing on screening for patients in the incubation period, and isolating and treating infected people can effectively reduce the spread of infectious diseases. © 2023 Northeastern University.All rights reserved.
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After the outbreak of corona virus, all counties are paying special attention to their healthcare infrastructure. During second phase of covid-19, entire world has seen health care crisis. Large number of people died globally. Entire world was affected mentally or physically. There is a great need to strengthen the healthcare infrastructure, to vaccinate the population against covid virus infection and to take proper precaution to avoid spread of the virus, so that the world will not see such deadly days again. This paper discusses how technologies like Internet of Things (IoT), Artificial Intelligence (AI), Drones etc can help in remote monitoring of patients, judicious hospital admission, conscious distribution of lifesaving drugs etc. Investment in technology with not only help in the reduction of spread of the virus but will also help in fighting with all other future pandemics. All the countries must have to invest more on latest technologies in their healthcare to make themselves ready for such future pandemics. When the things will improve, the new normal will be very much different from the life that was before pandemic. IoT, AI and other technologies will become the non-separatable part of our life. © 2023 Bharati Vidyapeeth, New Delhi.
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COVID-19 vaccines, approved under emergency use authorization, were not required to meet serialization requirements, but they have been properly labelled to meet US Food and Drug Administration (FDA) requirements, he says, complete with 2D barcodes with GTIN, lot, and expiry date. The company decided to serialize its Diprovan anesthetic, a workhorse generic product, using radio frequency identification tags containing the four identifiers (2). "If an agent is handling your product on your behalf, they need to leverage GS1 Standards including GTINs for products [and] global location numbers (GLNs) for physical locations, and share data electronically using electronic product code information services (EPCIS) to capture events from manufacturing to serialization [and] capping to shipping.
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Globally, the COVID-19 pandemic's development has presented significant societal and economic challenges. The carriers of COVID-19 transmission have also been identified as asymptomatic infected people. Yet, most epidemic models do not consider their impact when accounting for the disease's indirect transmission. This study suggested and investigated a mathematical model replicating the spread of coronavirus disease among asymptomatic infected people. A study was conducted on every aspect of the system's solution. The equilibrium points and the basic reproduction number were computed. The endemic equilibrium point and the disease-free equilibrium point had both undergone local stability analyses. A geometric technique was used to look into the global dynamics of the endemic point, whereas the Castillo-Chavez theorem was used to look into the global stability of the disease-free point. The system's transcritical bifurcation at the disease-free point was discovered to exist. The system parameters were changed using the basic reproduction number's sensitivity technique. Ultimately, a numerical simulation was used to apply the model to the population of Iraq in order to validate the findings and define the factors that regulate illness breakout.
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BackgroundAnti-MDA5 antibody-positive dermatomyositis (anti-MDA5+DM) is a rare autoimmune disease associated with a high mortality rate due to rapid-progressive interstitial lung disease (RP-ILD), particularly in East Asia[1]. MDA5, acts as a cytoplasmic sensor of viral RNA, thus activating antiviral responses including the type I interferon (IFN) signaling pathway[2]. The involvement of type 1 IFN in the pathogenesis of MDA5+DM has been proposed based on the significantly elevated expression of its downstream stimulated genes(ISG) in muscle, skin, lung, and peripheral blood[3;4]. Janus kinase inhibitor, which targets the IFN pathway, combined with glucocorticoid could improve the survival of early-stage MDA5+DM-ILD patients[5]. In clinical practice, there is still an urgent demand for sensitive biomarkers to facilitate clinical risk assessment and precise treatment.ObjectivesThis study aimed to investigate the clinical significance of interferon score, especially IFN-I score, in patients with anti-MDA5+DM.MethodsDifferent subtypes of idiopathic inflammatory myopathy, including anti-MDA5+DM(n=61), anti-MDA5-DM(n=20), antisynthetase syndrome(ASS,n=22),polymyositis(PM,n=6) and immune-mediated necrotizing myopathy(IMNM,n=9), and 58 healthy controls were enrolled.. A multiplex quantitative real-time PCR(RT-qPCR) assay using four TaqMan probes was utilized to evaluate two type I ISGs (IFI44, MX1, which are used for IFN-I score), one type II ISG (IRF1), and one housekeeping gene (HRPT1). Clinical features and disease activity index were compared between high and low IFN-I score groups in 61 anti-MDA5+DM patients. The association between laboratory findings and the predictive value of baseline IFN-I score level for mortality was analyzed.ResultsThe IFN scores were significantly higher in patients with anti-MDA5+DM than in HC (Figure 1A). The IFN-I score correlated positively with serum IFN α(r = 0.335, P =0.008), ferritin (r = 0.302, P = 0.018), and Myositis Disease Activity Assessment Visual Analogue Scale (MYOACT) score(r=0.426, P=0.001). Compared with patients with low IFN-I scores, patients with high IFN-I scores showed increased MYOACT score, CRP, AST, ferritin, and the percentages of plasma cells (PC%) but decreased lymphocyte count, natural killer cell count, and monocyte count. The 3-month survival rate was significantly lower in patients with IFN-I score > 4.9 than in those with IFN-I score ≤ 4.9(72.9% vs. 100%, P=0.044)(Figure 1B).ConclusionIFN score, especially IFN-I score, detected by multiplex RT-qPCR, can be a valuable biomarker for monitoring disease activity and predicting mortality in anti-MDA5+DM patients.References[1]I.E. Lundberg, M. Fujimoto, J. Vencovsky, R. Aggarwal, M. Holmqvist, L. Christopher-Stine, A.L. Mammen, and F.W. Miller, Idiopathic inflammatory myopathies. Nat Rev Dis Primers 7 (2021) 86.[2]G. Liu, J.H. Lee, Z.M. Parker, D. Acharya, J.J. Chiang, M. van Gent, W. Riedl, M.E. Davis-Gardner, E. Wies, C. Chiang, and M.U. Gack, ISG15-dependent activation of the sensor MDA5 is antagonized by the SARS-CoV-2 papain-like protease to evade host innate immunity. Nat Microbiol 6 (2021) 467-478.[3]G.M. Moneta, D. Pires Marafon, E. Marasco, S. Rosina, M. Verardo, C. Fiorillo, C. Minetti, L. Bracci-Laudiero, A. Ravelli, F. De Benedetti, and R. Nicolai, Muscle Expression of Type I and Type II Interferons Is Increased in Juvenile Dermatomyositis and Related to Clinical and Histologic Features. Arthritis Rheumatol 71 (2019) 1011-1021.[4]Y. Ye, Z. Chen, S. Jiang, F. Jia, T. Li, X. Lu, J. Xue, X. Lian, J. Ma, P. Hao, L. Lu, S. Ye, N. Shen, C. Bao, Q. Fu, and X. Zhang, Single-cell profiling reveals distinct adaptive immune hallmarks in MDA5+ dermatomyositis with therapeutic implications. Nat Commun 13 (2022) 6458.[5]Z. Chen, X. Wang, and S. Ye, Tofacitinib in Amyopathic Dermatomyositis–Associated Interstitial Lung Disease. New England Journal of Medicine 381 (2019) 291-293.AcknowledgementsThis work was supported by the National Natural Science Foundation of China [81974251], and Shanghai Hospital Develop ent Center, Joint Research of New Advanced Technology Project [SHDC12018106]Disclosure of InterestsNone Declared.
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A horrifying number of people died because of the COVID-19 pandemic. There was an unexpected threat to food systems, public health, and the workplace. The pandemic has severely disturbed society and there was a serious impediment to the economy. The world went through an unprecedented state of chaos during this period. To avoid anything similar, we can only be cautious. The project aims to develop a web application for the preliminary detection of COVID-19 using Artificial Intelligence(AI). This project would enable faster coordination, secured data storage, and normalized statistics. First, the available chest X-ray datasets were collected and classified as Covid, Non-Covid, and Normal. Then they were trained using various state-of-the-art pre-trained Convolutional Neural Network (CNN) models with the help of Tensor-flow. Further, they were ranked based on their accuracy. The best-performing models were ensembled into a single model to improve the performance. The model with the highest accuracy was transformed into an application programming interface (API) and integrated with the Decentralized application (D-App). The user needs to upload an image of their chest X-ray, and the D-App then suggests if they should take a reverse transcription-polymerase chain reaction (RT-PCR) test for confirmation. © 2022 IEEE.
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The outbreak of COVID-19 has increased the demand for new drug development. That has led to a growing interest in chemoinformatics, which is valuable information technology to predict chemical reactions. The use of enzymes as catalysts is gaining importance in terms of the environment and reaction efficiency. In order to predict the best enzyme to obtain the desired product, the target chemical equation is compared with typical chemical equations of enzymes classified by Enzyme Commission number (EC number) using clustering. The EC number of the chemical equation that is evaluated to have the highest similarity is predicted. © 2023, ICIC International. All rights reserved.
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This unprecedented time of the COVID-19 outbreak challenged the status-quo whether it is on business operation, political leadership, scientific capability, engineering implementation, data analysis, and strategic thinking, in terms of resiliency, agility, and innovativeness. Due to some identified constraints, while addressing the issue of global health, human ingenuity has proven again that in times of crisis, it is our best asset. Constraints like limited testing capacity and lack of real-time information regarding the spread of the virus, are the highest priority in the mitigation process, aside from the development of vaccines and the pushing through of vaccination programs. Using the available Chest X-Ray Images dataset and an AI-Computer Vision Technique called Convolutional Neural Network, features of the images were extracted and classified as COVID-19 positive or not. This paper proposes the usage of the 18-layer Residual Neural Network (ResNet-18) as an architecture instead of other ResNet with a higher number of layers. The researcher achieves the highest validation accuracy of 99.26%. Moving forward, using this lower number of layers in training a model classifier, resolves the issue of device constraints such as storage capacity and computing resources while still assuring highly accurate outputs. © 2022 IEEE.
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Bulgaria has the lowest COVID-19 vaccination rate in the European Union and the second-highest COVID-19 mortality rate in the world. That is why we think it is important better to understand the reason for this situation and to analyse the development of the disease over time. In this paper, an extended time-dependent SEIRS model SEIRS-VB is used to investigate the long-term behaviour of the COVID-19 epidemic. This model includes vaccination and vital dynamics. To apply the SEIRS-VB model some numerical simulation tools have been developed and for this reason a family of time-discrete variants are introduced. Suitable inverse problems for the identification of parameters in discrete models are solved. A methodology is proposed for selecting a discrete model from the constructed family, which has the closest parameter values to these in the differential SEIRS-VB model. To validate the studied models, Bulgarian COVID-19 data are used. To obtain all these results for the discrete models a mathematical analysis is carried out to illustrate some biological properties of the differential model SEIRS-VB, such as the non-negativity, boundedness, existence, and uniqueness. Using the next-generation method, the basic reproduction number associated with the model in the autonomous case is defined. The local stability of the disease-free equilibrium point is studied. Finally, a sensitivity analysis of the basic reproduction number is performed.
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As tuberculosis (TB) patients do not have lifetime immunity, environmental transmission is one of the key reasons why TB has not been entirely eradicated. In this study, an SVEIRB model of recurrent TB considering environmental transmission was developed to explore the transmission kinetics of recurrent TB in the setting of environmental transmission, exogenous infection, and prophylaxis. A more thorough explanation of the effect of environmental transmission on recurrent TB can be found in the model's underlying regeneration numbers. The global stability of disease-free and local equilibrium points can be discussed by looking at the relevant characteristic equations. The Lyapunov functions and the LaSalle invariance principle are used to show that the local equilibrium point is globally stable, and TB will persist if the basic reproduction number is larger. Conversely, the disease will disappear if the basic reproduction number is less than one. The impact of environmental transmission on the spread of tuberculosis was further demonstrated by numerical simulations, which also demonstrated that vaccination and reducing the presence of the virus in the environment are both efficient approaches to control the disease's spread.
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Humanity is currently living a true nightmare never seen before due to the pandemic caused by COVID-19 disease, scientific researchers are working day and night to find an ideal vaccine that eradicates this pandemic. The purpose of this paper is to investigate a SIHV pandemic model taking into account a vaccination strategy. For this aim, we consider a model with four compartments that describes the interaction between the susceptible cases S, the real infected cases I, the hospitalized, confirmed infected cases H and the vaccinated-treated individuals V. We establish the local stability of our model, depending on the basic reproduction number, by using the Routh-Hurwitz theorem. We perform some numerical simulations in order to confirm our theoretical results and discuss the effect of the rate of vaccination on controlling the spread of COVID-19. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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Objectives: COVID-19 reached its fourth year of pandemic since 2020. The repeated waves of infections have been driven by multiple factors such as pathological traits of variants, diagnostic accuracy, and vaccination conditions. This study revisits and analyzes the dynamic processes of viral transmission to generate new scientific knowledge. Method(s): A cascade model of viral transmission from one case to another was developed, and theoretically analyzed how the number of infected cases at time t, D+[t], can be changed at time t+1, D+[t+1], considering six parameters: 1) k:level of transmission, 2) Rt: effective reproduction number, 3) rho: capture rate of infected cases, 4) theta: immunity protection rate in individuals, 5) epsilon: evasion rate from vaccines, and 6) Sn: test sensitivity. Result(s): The formula which associates D+[t] with D+[t+1] was given as follows: D+[t+1] = K.D+[t], where K = {(1-Sn) + (1-rho) / rho}{1-Rtk (1-theta(1-epsilon))k} / {1-Rt (1-theta(1-epsilon))}. Also, assuming K be smaller than 1, the lower limit of test sensitivity to stop the viral transmission was formulated: Sn > {Rt (1-theta(1-epsilon))-Rtk(1-theta(1-epsilon))k} / {(1-Rtk(1-theta(1-epsilon))k)rho}. In example computations, the formula indicated that a one-off PCR test with the sensitivity of 85% would not be sufficient to contain highly contagious infections such as the Omicron variants, and that it would be practically impossible to control the situation with the immune-evasive sub-variants in circulation. Conclusion(s): The theory developed in this study broadens the science on evidence-based public health and will be useful for outcomes studies and informed decisions on public policy for pandemic control.Copyright © 2023
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COVID-19 is the short name of the coronavirus disease discovered in Wuhan, China, in 2019. In the context of Tanzania, we develop a mathematical model in this work that compares lockdown and quarantine. Again, we provide evidence in favor of local and global stability, with the basic reproduction number, R 0 , determined to be 0.31 at the diagnostic test rates k 1 = k 2 = 0.05. In comparison to the lockdown, it has been discovered that isolating (or quarantining) affected individuals is the most effective way to stop the spread of COVID-19. Additionally, it is advised that governments in Tanzania and other African countries permit their citizens to go about their daily lives as long as they take the necessary precautions, such as donning face masks, washing their hands, and avoiding crowded gatherings in case of a recurrence of any form of COVID-19. [ FROM AUTHOR] Copyright of Computational & Mathematical Methods in Medicine is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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In this paper, we introduce a SIVR model using the Laplace Adomian decomposition. This model focuses on a new trend in mathematical epidemiology dedicated to studying the characteristics of vaccination of infected communities. We analyze the epidemiological parameters using equilibrium stability and numerical analysis techniques. New mathematical strategies are also applied to establish our epidemic model, which is a pandemic model as well. In addition, we mathematically establish the chance for the next wave of any pandemic disease and show that a consistent vaccination strategy could control it. Our proposal is the first model introducing a vaccination strategy to actively infected cases. We are sure this work will serve as the basis for future research on COVID-19 and pandemic diseases since our study also considers the vaccinated population. © 2023 by the authors.
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The physical and mental health of older adults is a critical issue that is often overlooked. With the recent increase in the number of people infected with the new variants of coronavirus, we are facing several problems, including a dearth of high-quality medical care. iAssist aims to be a platform that primarily focuses on the social benefit of promptly delivering medical aid to the elderly in our nation. It enables a variety of functions, such as doctor appointments, medicine orders, and lab appointments under one roof, with the goal of assisting caregivers, such as family members and healthcare professionals. Additionally, it offers a chatbot component that uses a social media messaging service, to inform users of new developments and assist in swiftly answering user questions. The technology stack used in iAssist makes the platform efficient and user-friendly for everyone involved. © 2022 IEEE.
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Beside the unexpected toll of mortality and morbidity caused by COVID-19 worldwide, low- and middle-income countries are more suffering from the devastating issues on economic and social life. This disease has fostered mathematical modelling. In this paper, a SEIAR mathematical model is presented to illustrate how policymakers may apply efficient strategies to end or at least to control the devastating wide spread of COVID-19. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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BackgroundLong-term glucocorticoid (GC) exposure leads to systemic bone loss and fracture. In addition, GC is known to increase white blood cell (WBC) amount and change the distribution of differential count (DC). Neutrophil-to-Lymphocyte ratio (NLR) has been studied as an optimal marker of subclinical inflammation, predicting the prognosis of cardiovascular diseases, cancers and even covid-19 infection. For patients under long-term GC exposure, the hemogram change might be a potential parameter to predict prognosis.ObjectivesThis pilot study aims to investigate if GC related WBC-DC change, including NLR, is associated with future fractures during 3 years follow-up.MethodsThis retrospective study is based on a registry, conducted in Kaohsiung Chang Gung Memorial Hospital, Taiwan, from September 2014 till April 2021, aimed to monitor bone mineral density (BMD) changes and fractures in patients with autoimmune diseases. All recruited patients were followed at least 3 years and took X-ray images annually to capture new fragility fracture, including morphometric vertebral fractures. We screened participants who used GC continuously at least 3 months before the index day. We recorded the complete blood count (CBC) and WBC-DC values at least twice during the period of 3 months before and after the index day, and excluded patients who were febrile, under infection status, diagnosed as cancers or cardiovascular diseases at the index day. The NLR was calculated by the absolute neutrophil count divided by absolute lymphocyte count individually.ResultsA total of 346 participants were enrolled in current study, and 101 (29.2%) suffered from new fragility fracture in 3 years. Among patients with fracture and non-fracture, conventional fracture risk factors, such as age, BMD, and previous fracture remained significantly different, while the WBC revealed no difference (Table 1). Nevertheless, the absolute neutrophil and lymphocyte count were significantly higher and lower in the fracture group, respectively, and no difference in the monocyte, eosinophil, and basophil count. We compared different WBC ratio, and NLR is significantly higher in the fracture group, providing the odds ratio of 1.24 (95% confidence interval 1.07-1.44, p=0.005). Figure 1 showed that the observed fracture risk raised as the NLR values increased.ConclusionIn patients under long-term GC, NLR might be a helpful marker to predict fracture, and higher NLR indicates higher fracture risks.Figure 1.Observed fracture rate is associated with baseline NLR[Figure omitted. See PDF]Table 1.Demographic characteristics of enrolled patients on long-term glucocorticoid.Fracture N=101No-Fracture N=245p-valueAge63.7 ± 9.056.5 ± 9.6<0.001*Sex(women)89(88.1)210(85.7)0.55BMI24.1 ± 3.923.4 ± 3.90.14Previous Fracture64(63.4)55(22.4)<0.001*Total hip BMD0.738 ± 0.1330.790 ± 0.1220.001*Femoral neck BMD0.575 ± 0.1130.626 ± 0.109<0.001*Lumbar BMD0.841 ± 0.2000.855 ± 0.1500.49WBC7.3 ± 2.16.9 ±1.70.14Hemoglobin12.8 ± 1.512.9 ± 1.40.33Platelet239.2 ± 64.7247.9 ± 71.40.30Neutrophil67.3 ± 9.764.3 ± 9.70.009*Lymphocyte24.3 ± 8.726.6 ± 9.50.04*Monocyte6.2 ± 1.86.3 ± 1.60.52Eosinophil1.8 ± 1.81.9 ± 1.30.77Basophil0.4 ± 0.20.4 ± 0.20.18NLR (Neutrophil to lymphocyte)3.3 ± 1.72.8 ± 1.40.004*NMR (Neutrophil to monocyte)11.9 ± 4.511.0 ± 3.60.04*LMR (Lymphocyte to monocyte)4.2 ± 1.74.5 ± 1.90.20AcknowledgementsThis work was supported by funding grant CMRPG8J0331 from the Chang Gung Memorial Hospital (https://www.cgmh.org.tw).Disclosure of InterestsNone Declared.
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The study aimed to assess the impact of the COVID-19 pandemic on the financial condition and mortality in Polish voivodeships. To achieve this objective, the relationship between the number of deaths before and during the pandemic and the financial condition of the provinces in Poland was studied. The study covered the years 2017–2020, for which a one-way ANOVA was used to verify whether there was a relationship between the level of a province's financial condition and the number of deaths. The results of the study are surprising and show that before the COVID-19 pandemic, there was a higher number of deaths in provinces that were better off financially, but the relationship was not statistically significant. In contrast, during the pandemic, a statistically significant strong negative correlation between these values was proven, which, in practice, shows that regions with better financial conditions had a higher number of deaths during COVID-19.
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Long-tailed macaque (Macaca fascicularis is one of the most common primates in Indonesia. In Sleman, Yogyakarta, Indonesia, the long-tailed macaque is habituated in Merapi Forest. The study aims to estimate the long-tailed macaque population and re-identification of groups. Moreover, we will observe the social structures that probably changed because of the interruption of interaction with visitors after the closure of the Tlogo Muncar area during the COVID-19 pandemic. The estimation population study was done using the concentration method. The long-tailed macaque group in Tlogo Muncar consists of three groups: Waterfalls, Mosque, and Joglo Trubus. The study was also identifying the alpha male of each group. The dataset obtained was processed using Microsoft Excel and analyzed descriptively. The results show that the estimated long-tailed macaque population in Tlogo Muncar area is 282 individuals. Alpha male identification of each group found alpha males in the Waterfall Group characterized by a lump on the left eyelid and a wound on the left hand. The alpha male of the Mosque Group is marked by a lump on his left eyelid with maxillary prognathism, while the alpha male of the Joglo Trubus Group has transverse scratches on the nose. The results showed an increase in the long-tailed macaque population in Tlogo Muncar area from 201 individuals in 2021 to 282 individuals in 2022. The increase of ecological pressure perhaps caused the rise in population number in 2022 during the closure of the area, to which the adult female responded by increasing their reproduction rate. The reopening of Tlogo Muncar after the Covid-19 pandemic has increased feed availability and attracted monkeys to forage outside the forest.
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Several efforts have been recently devoted to the studies on epidemic mathematical models based on fractional-order operators, by virtue of their capability to take into account memory effects and nonlocal features. The aim of this paper is to make a contribution to the topic by introducing a novel Covid-19 model described by non-integer-order difference equations. By conducting a stability analysis, the paper shows that the conceived system has two fixed points at most, i.e. a disease-free fixed point and an endemic fixed point. In particular, a theorem is proved, which assures the global stability of the disease-free fixed point, indicating that the pandemic will disappear when a simple condition on the system parameters is satisfied. Finally, simulation results are carried out with the aim to highlight the capability of the conceived approach.