The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel ma...The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR(Susceptible-Exposed-Infectious-Recovered)framework to incorporate treatment and hospitalization compartments.The population is divided into eight compartments,with infectious individuals further categorized into influenza infectious,corona infectious,and co-infection cases.The proposed mathematical model is constrained to adhere to fundamental epidemiological properties,such as non-negativity and boundedness within a feasible region.Additionally,the model is demonstrated to be well-posed with a unique solution.Equilibrium points,including the disease-free and endemic equilibria,are identified,and various properties related to these equilibrium points,such as the basic reproduction number,are determined.Local and global sensitivity analyses are performed to identify the parameters that highly influence disease dynamics and the reproduction number.Knowing the most influential parameters is crucial for understanding their impact on the co-infection’s spread and severity.Furthermore,an optimal control problem is defined to minimize disease transmission and to control strategy costs.The purpose of our study is to identify the most effective(optimal)control strategies for mitigating the spread of the co-infection with minimum cost of the controls.The results illustrate the effectiveness of the implemented control strategies in managing the co-infection’s impact on the population’s health.This mathematical modeling and control strategy framework provides valuable tools for understanding and combating the dual threat of corona and influenza co-infection,helping public health authorities and policymakers make informed decisions in the face of these intertwined epidemics.展开更多
副流感病毒(PIV)液膜或气溶胶经过针阵列对板电晕放电处理,对收集处理前后的病毒液进行血凝效 价和血红蛋白值(OD值)分析,确证非热放电对病毒的灭活作用．结果显示,液膜中87．5％以上的病毒经15 min 放电处理即被灭活;气溶胶中50％以上...副流感病毒(PIV)液膜或气溶胶经过针阵列对板电晕放电处理,对收集处理前后的病毒液进行血凝效 价和血红蛋白值(OD值)分析,确证非热放电对病毒的灭活作用．结果显示,液膜中87．5％以上的病毒经15 min 放电处理即被灭活;气溶胶中50％以上的病毒经一次放电处理后即被灭活．分析认为,非热放电产生的高能电 子、紫外光及自由基对空气中携带的PIV病毒具有高效的灭活作用;针阵列对板电晕放电电场同时有利于高效 捕获空气中的PIV病毒载体,从而在放电场中灭活PIV病毒．展开更多
During the month which began just prior to the start of April 2020, the New York City mortality rate for COVID-19 infection increased continuously and gradually, from 1% - 2% at the beginning of the month, to a peak o...During the month which began just prior to the start of April 2020, the New York City mortality rate for COVID-19 infection increased continuously and gradually, from 1% - 2% at the beginning of the month, to a peak of about 11% by early May. During this same period, the total number of cases increased from about 20,000 to about 200,000. Since there is no reason, a priori, to expect the mortality rate of any single disease to have any particular mathematical relationship to the number of cases, a statistical analysis would appear to be in order. This analysis is presented, and one possible interpretation is suggested.展开更多
基金supported by NASA Oklahoma Established Program to Stimulate Competitive Research(EPSCoR)Infrastructure Development,“Machine Learning Ocean World Biosignature Detection from Mass Spec”(PI:BrettMcKinney),Grant No.80NSSC24M0109Tandy School of Computer Science,University of Tulsa.
文摘The co-infection of corona and influenza viruses has emerged as a significant threat to global public health due to their shared modes of transmission and overlapping clinical symptoms.This article presents a novel mathematical model that addresses the dynamics of this co-infection by extending the SEIR(Susceptible-Exposed-Infectious-Recovered)framework to incorporate treatment and hospitalization compartments.The population is divided into eight compartments,with infectious individuals further categorized into influenza infectious,corona infectious,and co-infection cases.The proposed mathematical model is constrained to adhere to fundamental epidemiological properties,such as non-negativity and boundedness within a feasible region.Additionally,the model is demonstrated to be well-posed with a unique solution.Equilibrium points,including the disease-free and endemic equilibria,are identified,and various properties related to these equilibrium points,such as the basic reproduction number,are determined.Local and global sensitivity analyses are performed to identify the parameters that highly influence disease dynamics and the reproduction number.Knowing the most influential parameters is crucial for understanding their impact on the co-infection’s spread and severity.Furthermore,an optimal control problem is defined to minimize disease transmission and to control strategy costs.The purpose of our study is to identify the most effective(optimal)control strategies for mitigating the spread of the co-infection with minimum cost of the controls.The results illustrate the effectiveness of the implemented control strategies in managing the co-infection’s impact on the population’s health.This mathematical modeling and control strategy framework provides valuable tools for understanding and combating the dual threat of corona and influenza co-infection,helping public health authorities and policymakers make informed decisions in the face of these intertwined epidemics.
文摘[目的]获得全球范围内人兽共患病及其病原微生物研究现状和热点变化趋势信息,为我国人兽共患病的防控提供参考。[方法]利用COOC 12.6和Citespace 5.8 R1软件对Pubmed数据库中的人兽共患病及其病原微生物相关的关键词进行了频次统计、共现分析、聚类分析、时间线分析和突现词分析。[结果]根据Pubmed数据库中2001—2021年关键词频次统计和共现分析结果,国际关注度较高的人兽共患病及其病原微生物有以下3类:第1类为常见的人兽共患病病原,包括布鲁菌(Brucella)、戊型肝炎病毒(hepatitis E virus)、链球菌(Streptococcus)、大肠杆菌(Escherichia coli)和沙门菌(Salmonella)等,需要持续关注;第2类为近些年在国际上被广泛关注的人兽共患病病原,如新型冠状病毒(SARS-CoV-2)和甲型流感病毒(influenza A virus)等,需要更为深入研究,以尽早控制这些病原的扩散;第3类为在国外特定地区曾大规模出现的人兽共患病,如Q热(Q fever)和中东呼吸综合征(middle east respiratory syndrome,MERS)等,应当重点关注其输入性风险,避免这些疾病在我国暴发。除疾病和病原微生物外,与检测和诊断相关的关键词,如系统发育(phylogeny)和聚合酶链式反应(PCR)等关键词的关注度也较高。聚类分析生成了10个聚类,蜱媒传染病大类提示蜱虫在人兽共患病传播中的作用。时间线和突现词分析结果显示,在病原微生物中,对甲型流感病毒以及新型冠状病毒等的关注度还在逐渐增加。同时,病原微生物检测技术正在从特定序列检测向全基因组学检测技术发展,这些领域极有可能是今后的研究方向和趋势。[结论]结果提示,人们对人兽共患病及其病原微生物研究的关注度越来越高,人兽共患病病原微生物检测技术正在发生更新和迭代。我国应重点关注甲型流感以及新型冠状病毒肺炎等疾病的防控,并适当关注蜱媒传染病。这些信息的获取可为我国的人兽共患病的防控提供参考。
文摘During the month which began just prior to the start of April 2020, the New York City mortality rate for COVID-19 infection increased continuously and gradually, from 1% - 2% at the beginning of the month, to a peak of about 11% by early May. During this same period, the total number of cases increased from about 20,000 to about 200,000. Since there is no reason, a priori, to expect the mortality rate of any single disease to have any particular mathematical relationship to the number of cases, a statistical analysis would appear to be in order. This analysis is presented, and one possible interpretation is suggested.
