本文關(guān)鍵詞：疾病數(shù)學(xué)模型和傳播動力學(xué)研究的流行病學(xué)意義，由筆耕文化傳播整理發(fā)布。

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預(yù)防醫(yī)學(xué)與衛(wèi)生學(xué)

疾病傳播動力學(xué)

     A method for simulating epidemic in transmission dynamics study

     疾病傳播動力學(xué)研究中的流行模擬方法

短句來源

     Results: DecisionPro Markov model described the epidemic model visually.

     結(jié)果:DecisionPro Markov模型可以直觀地描述疾病傳播動力學(xué)模型。

短句來源

     Application of time-domain statistical analysis in the dynamics of epidemic outbreaks

     時域統(tǒng)計分析在疾病傳播動力學(xué)中的應(yīng)用

短句來源

     New results in the dynamics of epidemic outbreaks obtained by time-domain statistical analysis are presented.

     文章介紹了運(yùn)用時域統(tǒng)計分析進(jìn)行疾病傳播動力學(xué)研究所得到的新結(jié)果.

短句來源

     Objective:To develop a method for simulating epidemic in transmission dynamics study.

     目的:建立疾病傳播動力學(xué)研究中模擬流行的方法。

短句來源

     Epidemiological significance of studies on mathematical model and transmission dynamics of diseases.

     疾病數(shù)學(xué)模型和傳播動力學(xué)研究的流行病學(xué)意義

短句來源

     A method for simulating epidemic in transmission dynamics study

     疾病傳播動力學(xué)研究中的流行模擬方法

短句來源

     Application of time-domain statistical analysis in the dynamics of epidemic outbreaks

     時域統(tǒng)計分析在疾病傳播動力學(xué)中的應(yīng)用

短句來源

     Sexually transmitted diseases in children

     兒童性傳播疾病

短句來源

     Mathematical model and transmission dynamics of malaria.

     瘧疾數(shù)學(xué)模型和傳播動力學(xué)

短句來源

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  disease transmission dynamics

This article introduces an age-structured epidemiological model for the disease transmission dynamics of hepatitis?C.

Furthermore, we stress the value and importance of understanding the epidemiologic control points that drive infectious disease transmission dynamics.

Objective To further understend the difference of transmission dynamics among three mosquito born diseases,dengue fever,malaria and filariasis and is relation with control effect. Methods By the mathematic model the quantitative dynamics analysis and comparison among the three diseases were carried out. Results The transmission velocity(i.e.vectorial capacity,VC)and epidemic velocity(EV)of dengue fever is the most high-speed but its transmission potential(i.e.basic reproduction rate,BRR)is lower and the...

Objective To further understend the difference of transmission dynamics among three mosquito born diseases,dengue fever,malaria and filariasis and is relation with control effect. Methods By the mathematic model the quantitative dynamics analysis and comparison among the three diseases were carried out. Results The transmission velocity(i.e.vectorial capacity,VC)and epidemic velocity(EV)of dengue fever is the most high-speed but its transmission potential(i.e.basic reproduction rate,BRR)is lower and the man-biting rate needed for maintain the lowest transmission is higher which suggested that it is easier to control its transmission by reducing the mosquito population;The transmission and epidemic velocity of malaria is slight lower than that of dengue fever,but its transmission potential is much high than that of dengue fever,and its critical man-biting rate is also very low which indicated that it is not only easy to cause the endemicity also the epidemicity,but also hard to control its transmission and it is necessary to take integrated control measured;The transmission and epidemic velocity of filariasis is very low and its transmission potential is also very low so it is possible to control even interrupt its transmission only by single mesures aiming the infection source. Conclusion There are evident differences in transmission dynamics among the three mosquito born diseases which is the fundumental reason of frming different epidemic characterestic and of leading to variant control effects among the three diseases.

目的　為進(jìn)一步了解登革熱、瘧疾和絲蟲病三種蚊傳疾病在傳播動力學(xué)上的差異及其與防治效應(yīng)的關(guān)系。方法　通過數(shù)學(xué)模型 ,對三種疾病的傳播動力學(xué)進(jìn)行定量分析和比較。結(jié)果　登革熱的傳播速率 (即媒介能量 )和流行速率最高 ,但傳播潛能 (即基本繁殖率 )較低 ,維持最低傳播所需的叮人率 (即臨界叮人率 )也較高 ,提示通過降低蚊群數(shù)量即有可能較容易地達(dá)到控制傳播的目的 ;瘧疾的傳播和流行速率略低于登革熱 ,但傳播潛能比登革熱高得多 ,臨界叮人率也很低 ,表明瘧疾不但容易引發(fā)地方性流行和暴發(fā)性流行 ,而且較難以控制和消滅 ,必須采取嚴(yán)密的綜合性防治措施 ;絲蟲病的傳播速率和流行速率非常慢 ,傳播潛能也非常低 ,提示有可能通過單一的控制傳染源措施 ,容易地控制甚至阻斷其傳播。結(jié)論　三種蚊傳疾病在傳播動力學(xué)上存在明顯的差異 ,這是導(dǎo)致三種疾病不同的流行病學(xué)特征和不同的防治效應(yīng)的根本原因

New results in the dynamics of epidemic outbreaks obtained by time-domain statistical analysis are presented. Once the parameters of the time-domain statistical distributions for the incubation period and active period of an epidemic disease are given, the dynamics of the disease outbreak in a closed system with given infection probability can be completely determined by solving stochastic differential-integrative equations. Calculation shows that, after a long enough time, the final infection rate of the system...

New results in the dynamics of epidemic outbreaks obtained by time-domain statistical analysis are presented. Once the parameters of the time-domain statistical distributions for the incubation period and active period of an epidemic disease are given, the dynamics of the disease outbreak in a closed system with given infection probability can be completely determined by solving stochastic differential-integrative equations. Calculation shows that, after a long enough time, the final infection rate of the system is determined by the index T2 = cNt2 , where is the infection probability of individuals in the system, N the number of individuals, and t2 the average length of the active period of the disease. If τ2 > 3, the final infection rate of the system may reach 100% , so τ2 can also be called the risk index. In the early days of the epidemic, the oscillatory and intermittent behavior of the new-active rate is determined by another index, τ1 =cNt1 where t1 is the average length of the incubation period. This theory overcomes the drawback of the SIR model which does nottake sufficient account of the time-domain statistics, and can provide a better theoretical prediction for the infection dynamics in a closed system.

文章介紹了運(yùn)用時域統(tǒng)計分析進(jìn)行疾病傳播動力學(xué)研究所得到的新結(jié)果.在給定某一類疾病的潛伏期和活動期的時域統(tǒng)計分布參數(shù)后,該疾病在具有一定感染幾率的封閉系統(tǒng)中的傳播動力學(xué)過程即可通過求解概率微分積分方程來決定.計算結(jié)果表明,在經(jīng)過長時間傳播后,該系統(tǒng)的最終被感染率由指數(shù)τ2=cNt2決定,這里c是系統(tǒng)內(nèi)個體的接觸感染幾率,Ⅳ是系統(tǒng)所包含的個體數(shù)量,t2是疾病活動期的平均時間長度.如果τ2>3,則該系統(tǒng)的最終被感染率可達(dá)到100％,因此τ2又稱為疾病傳播的危險指數(shù).而在疾病傳播的初期,新發(fā)病例所出現(xiàn)的振蕩和間歇行為則由另一個指數(shù)τ1=cNt1決定,這里t1是平均潛伏期的長度.這一理論較好地彌補(bǔ)了以往常用的SIR模型對時域統(tǒng)計考慮不足的缺陷,從而對疾病在封閉系統(tǒng)中的傳播動力學(xué)過程給出理論預(yù)測.

Objective:To develop a method for simulating epidemic in transmission dynamics study. Methods: Markov model in software Vanguard DecisionPro based on transmission dynamics model was used to mimic epidemic. As an example, epidemic simulation and abstract study of epidemic model of SARS in Beijing were done to illustrate its application. Results: DecisionPro Markov model described the epidemic model visually. In the Markov model, values of parameters were modified easily by programming method. Real-time change...

Objective:To develop a method for simulating epidemic in transmission dynamics study. Methods: Markov model in software Vanguard DecisionPro based on transmission dynamics model was used to mimic epidemic. As an example, epidemic simulation and abstract study of epidemic model of SARS in Beijing were done to illustrate its application. Results: DecisionPro Markov model described the epidemic model visually. In the Markov model, values of parameters were modified easily by programming method. Real-time change of state variables was observed, which could predict the trend of epidemic. By sensitive analysis, we were able to study the interaction between model variables and by scenario method, we could evaluate impacts of value changes of input variables on epidemic quantitatively. It was found that our method was an appropriate method for epidemic simulation research and could be used to quantitatively evaluate the effectiveness of intervention measures. Conclusion: DecisionPro Markov model is ideal in epidemic simulation and can be used to make an abstract study of transmission dynamics model.

目的:建立疾病傳播動力學(xué)研究中模擬流行的方法。方法:在建立傳染病傳播動力學(xué)模型的基礎(chǔ)上,采用Van guard DecisionPro軟件中的Markov模型方法模擬疾病流行,以北京SARS流行模擬及模型的抽象研究為例說明其應(yīng)用。結(jié)果:DecisionPro Markov模型可以直觀地描述疾病傳播動力學(xué)模型。在Markov模型中,各模型參數(shù)取值可以隨時調(diào)整,并可通過編程實現(xiàn);可以觀察模型狀態(tài)變量的實時變化,預(yù)測疾病的流行趨勢;通過敏感性分析功能,可以研究模型變量之間相互作用的規(guī)律;通過想定研究方法,可以定量評價輸入?yún)?shù)變化對流行的影響。實例研究發(fā)現(xiàn),該方法很適合流行模擬研究,可以用于干預(yù)措施效果的定量評價。結(jié)論:DecisionPro Markov模型方法是一種較為理想的模擬疾病流行的方法,可以用于傳播動力學(xué)模型的抽象研究。

  本文關(guān)鍵詞：疾病數(shù)學(xué)模型和傳播動力學(xué)研究的流行病學(xué)意義，由筆耕文化傳播整理發(fā)布。