美國NovaBios埃博拉病毒檢測試劑盒（膠體金法）

廣州健侖生物科技有限公司

本司長期供應埃博拉病毒檢測試劑盒，其主要品牌包括美國NovaBios、廣州創侖等CDC使用的進口產品，試劑盒的實驗方法包括膠體金方法、ELISA方法、PCR方法等。

歡迎咨詢

歡迎咨詢2042552662

埃博拉病毒IgM、IgG、ELISA檢測試劑、埃博拉快速檢測試劑盒、

埃博拉病毒核酸檢測試劑盒（熒光探針PCR）

西非工作、旅游埃博拉檢測試劑盒

美國CDC使用的埃博拉診斷試劑——美國的NovaBios

美國NovaBios 埃博拉病毒檢測試劑盒（膠體金法）

【埃博拉簡介】

埃博拉（Ebola virus）又譯作伊波拉病毒。是一種十分罕見的病毒，1976年在蘇丹南部和剛果（金）（舊稱扎伊爾）的埃博拉河地區發現它的存在后，引起醫學界的廣泛關注和重視，“埃博拉”由此而得名。是一個用來稱呼一群屬于纖維病毒科埃博拉病毒屬下數種病毒的通用術語。是一種能引起人類和靈長類動物產生埃博拉出血熱的烈性傳染病病毒，有很高的死亡率，在50%至90%之間，致死原因主要為中風、心肌梗塞、低血容量休克或多發性器官衰竭。

埃博拉出血熱（EBHF）是由一種絲狀病毒感染導致的急性出血性、動物源性傳染病。1976年，埃博拉出血熱在非洲的蘇丹和扎伊爾暴發，病死率高達50% ～ 90% 。因該病始發于扎伊爾北部的埃博拉河流，并在該區域嚴重流行，故命名為埃博拉病毒，其形態學、致病性等與馬爾堡病毒相似，但免疫原性有所區別。

【產品介紹】

該產品是世界衛生組織（WHO）*個批準用于埃博拉病毒檢測的診斷試劑卡。不需要借助其他實驗儀器設備，只需要采取幾滴血清、血漿、血液樣品，既可以檢測，并在15分鐘內就可以得知結果是否感染埃博拉病毒。該產品具有靈敏度高、操作方便、實驗時間短等特點。

美國NovaBios

對于引入風險的估計，zui核心的問題便是如何通過動態模型或是統計模型將風險量化。這里介紹一種比較直觀簡介的估計方式，首先把引入風險分為相對引入風險(relative import risk)和引入風險(absolute import risk)。不妨假設X為疫情爆發區域的某個機場，而Y則是世界上任意一塊區域，那么我們可以通過條件概率的形式來定義相對引入風險，即P(Y|X)。而對于引入風險我們則可以通過聯合概率來定義，即P(X,Y)=P(Y|X)P(X)，這里需要注意的是P(X)往往遠小于P(Y|X)，因此P(X,Y)也會遠遠小于P(Y|X)。在實際應用中，相對風險較風險而言更有價值，其主要原因在于P(X)的估計在大部分時間都難以實現，事實上P(X)的估計需要依賴于大量的參數來描述X所在地區的各類因素，而風險的估計卻恰恰依賴于P(X)。與此相反，相對風險的計算則僅僅需要各機場人口流動的數據即可，即無需考慮地區本身的相關因素。
2. 由移動通信數據預測疫情
　　埃博拉病毒在西非的爆發引起了*的關注，人們紛紛把注意力頭像了機場等引起人口流動的公共場所，正如上一節所說，機場數據的確對于流行病學家等研究者們而言具有*的分析價值，但除此之外，基于手機移動端產生的數據同樣應用潛力。
　　用戶每次利用手機通話的過程中都會同時產生相應的通話記錄數據，其中自然也包含了、通話時間以及大致的通信地點等重要信息。對于運營商而言，這些數據可以為各地基站的部署提供參考從而提升通信網絡。另一方面對于城市規劃者而言則可以基于該數據判斷相關地點是否需要拓展相應的公共交通設施。
　　然而除了上述這些相對常用的應用外，在流行病學的應用卻更令人期待，更激動人心。事實上到目前為止一般情況下對于疾病擴散建模的常用方法依然是基于人口普查的數據以及相關調查。然而對于通信記錄數據，人們卻可以得到實時更新的數據，也就是說在實際應用中無需估計某地區的人口是否會遷移。同時幸運的是，在近幾年中確實并不缺乏類似的成功案例。2009年在墨西哥爆發的豬流感，研究人員就曾利用通信數據監測公眾對于政府發布的健康預警信息的反應。此后2010年隨海地地震爆發的霍亂疫情，研究人員則同樣基于手機通信數據建模并給出了zui需要援助地點的*估計。
　　在對于埃博拉病毒研究的實際操作中卻更為復雜，一個zui主要的原因在于西非大部分民眾并沒有手機或者其他通信設備。不過盡管如此，某種程度上它卻依然優于基于陳舊數據的統計分析。事實上研究人員如果可以從一個傳染病爆發的地域追蹤到人口的流動，那么對于下一個zui有可能爆發傳染病的地點就會有一個比較有效的估計和預測，從而可以提前展開合理有效的資源配置。遺憾的是，盡管很多相關的機構都做了很大程度的努力，但出于隱私等問題的考慮，電信運營商依然不允許研究人員使用這部分數據。

美國NovaBios

我司還提供其它進口或國產試劑盒：登革熱、瘧疾、乙腦、寨卡、黃熱病、基孔肯雅熱、克錐蟲病、違禁品濫用、肺炎球菌、軍團菌等試劑盒以及日本生研細菌分型診斷血清、德國SiFin診斷血清、丹麥SSI診斷血清等產品。

想了解更多的NovaBios產品及服務請掃描下方二維碼：

【公司名稱】 廣州健侖生物科技有限公司
【市場部】    楊永漢

【】 
【騰訊  】 2042552662
【公司地址】 廣州清華科技園創新基地番禺石樓鎮創啟路63號二期2幢101-103室

For the introduction of risk estimates, the core issue is how to quantify the risk through dynamic models or statistical models. Here is a more intuitive introduction to the introduction of the estimation method, first of all into the risk of relative risk and relative risk (absolute import risk). It is assumed that X is an airport in the outbreak area, and Y is any piece of the world, then we can define the relative introduction risk through the conditional probability form, ie P (Y | X). (X, Y) = P (Y | X) P (X), it is important to note that P (X) is often much smaller than P (Y | X) for the absolute introduction of the risk that we can be defined by the joint probability ), So P (X, Y) will be much smaller than P (Y | X). In practice, the relative risk is more valuable than the absolute risk, the main reason is that P (X) estimates are difficult to achieve for most of the time, in fact P (X) estimates need to rely on a large number of parameters to describe X where the various factors, while the absolute risk estimates are dependent on P (X). In contrast, the relative risk calculation requires only the data of the airport's population flows, that is, without regard to the relevant factors of the region itself.
2. Forecast the epidemic by communication data
The outbreak of the Ebola virus in West Africa has aroused worldwide attention, and there has been a public eye that has attracted attention to the airport and so on. As mentioned in the previous section, the airport data is indeed for epidemiologists and other researchers In terms of a very high analytical value, but in addition, based on the phone data generated by the same great potential.
The user each time using the phone call process will also produce the corresponding call record data, which naturally contains the phone number, talk time and approximate communication location and other important information. For operators, these data can provide a reference for the deployment of base stations to enhance the communication network. On the other hand, for urban planners, it is possible to determine whether the relevant sites need to expand the corresponding public transport facilities based on the data.
However, in addition to these relatively common applications, the epidemiology of the application is more exciting and more exciting. In fact, the usual method of modeling the spread of disease in general is still based on census data and related surveys. However, for communication record data, people can get real-time updated data, that is to say in practical applications do not need to estimate whether a region's population will migrate. Fortunay, in recent years, there is no lack of similar success stories. In 2009, swine flu broke out in Mexico, where researchers used communication data to monitor public response to government health warnings. Since 2010, with the Haiti earthquake outbreak of cholera epidemic, the researchers are also based on communication data modeling and gives the most needed assistance to the optimal estimate of the location.
In the actual operation of the Ebola virus research is more complex, one of the most important reason is that most people in West Africa and no phone or other communications equipment. But nevertheless, to some extent it is still better than statistic analysis based on obsolete data. In fact, if researchers can trace from the outbreak of an infectious disease to the flow of population, then the next most likely outbreak of infectious diseases, there will be a more effective location of the estimates and forecasts, which can be ahead of a reasonable and effective resources Configuration. Unfortunay, although many of the relevant agencies have done a lot of effort, but for privacy and other issues to consider, ecom operators still do not allow researchers to use this part of the data.