美国NovaBios埃博拉检测试剂盒(胶体金法)
广州健仑生物科技有限公司
本司长期供应埃博拉病毒检测试剂盒,其主要品牌包括美国NovaBios、广州创仑等CDC使用的进口产品,试剂盒的实验方法包括胶体金方法、ELISA方法、PCR方法等。
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埃博拉病毒IgM、IgG、ELISA检测试剂、埃博拉快速检测试剂盒、
埃博拉病毒核酸检测试剂盒(荧光探针PCR)
西非工作、旅游埃博拉检测试剂盒
美国CDC使用的埃博拉诊断试剂——美国的NovaBios
美国NovaBios 埃博拉检测试剂盒(胶体金法)
【埃博拉简介】
埃博拉(Ebola virus)又译作伊波拉病毒。是一种十分罕见的病毒,1976年在苏丹南部和刚果(金)(旧称扎伊尔)的埃博拉河地区发现它的存在后,引起医学界的广泛关注和重视,“埃博拉”由此而得名。是一个用来称呼一群属于纤维病毒科埃博拉病毒属下数种病毒的通用术语。是一种能引起人类和灵长类动物产生埃博拉出血热的烈性传染病病毒,有很高的死亡率,在50%至90%之间,致死原因主要为中风、心肌梗塞、低血容量休克或多发性器官衰竭。
埃博拉出血热(EBHF)是由一种丝状病毒感染导致的急性出血性、动物源性传染病。1976年,埃博拉出血热在非洲的苏丹和扎伊尔暴发,病死率高达50% ~ 90% 。因该病始发于扎伊尔北部的埃博拉河流,并在该区域严重流行,故命名为埃博拉病毒,其形态学、致病性等与马尔堡病毒相似,但免疫原性有所区别。
【产品介绍】
该产品是世界卫生组织(WHO)*个批准用于埃博拉病毒检测的诊断试剂卡。不需要借助其他实验仪器设备,只需要采取几滴血清、血浆、血液样品,既可以检测,并在15分钟内就可以得知结果是否感染埃博拉病毒。该产品具有灵敏度高、操作方便、实验时间短等特点。
埃博拉病毒快速诊断试剂卡 | |
实验方法 | 胶体金法 |
实验样本 | 血清/血浆/全血/唾液 |
灵敏度 | 92% |
特异性 | 99% |
储存条件 | 4~30℃ |
保质期 | 12个月 |
实验时间 | 15分钟 |
美国NovaBios
埃博拉病毒疫情时隔几年便爆发一次,不过之前每次疫情规模都比较小,主要集中在一个地区爆发,并且局限在中非。特别地,刚果民众共和国*曾多次爆发埃博拉疫情。
2014年3月开始爆发的埃博拉病毒疫情的爆发规模引起了社会的关注,并且被世界卫生组织列为“间关注的公共卫生紧急事件”(历史第三次)。首先,这次疫情涉及到了多个国家和地区。全境范围受影响的国家包括几内亚、利比里亚和塞拉利昂。部分领土受影响的地区包括马里的卡伊,西班牙的马德里,美国的达拉斯、德克萨斯州和纽约市,英国苏格兰地区的格拉斯哥市,尼日利亚的拉各斯哈科特港,以及塞内加尔的达喀尔。其次,这次埃博拉病毒疫情出现的病例和死亡数字超过了所有其它疫情的总和。截止2014年12月31号,累计20206人患病,7905人死亡埃博拉。并且数字还在不断增加。而所有的埃博拉护理者,则被美国时代周刊选为2014年的年度人物。
回望过去几十年,人类无疑在信息、科技、生物、医疗等领域取得了今非昔比的成果。反观2014年埃博拉病毒疫情的爆发、传播、媒体报导、控制,我们不禁开始思考在这个大数据时代,数据、统计、理性思考、批判思维能为人类对疫情防控带来什么好处?这篇文章试图从三个角度去阐述大数据如何与疫情防控紧密相连。本文*部分讨论了如何通过交通数据、移动通信数据与社交媒体数据等非传统公共卫生数据来测算乃至预测疫情风险;第二部分重点关注死亡率的不同估算方法带来的对于疫情风险的不同认知;第三部分聚焦在埃博拉病毒疫情的治疗和防控支出数据。
一、数据驱动的疫情预测
1. 由交通数据预测疫情埃博拉
人口流动的日趋频繁使某区域爆发的疫情会给其他国家和地区带来潜在的疫情风险,于是如何对此类疫情风险进行有效的预测和评估自然就成了一个值得探究的课题。本次埃博拉爆发的一个重大特征即是,疫情通过交通运输突破国境,在源爆发地几内亚之外多国肆虐。对于间的人口流动,飞机显然是zui主要的交通方式,因此对机场人口流动数据的统计分析也就成了重中之重。
事实上机场数据也早已被很多领域的研究者们所重视,基于此类数据分析建模的案例也已屡见不鲜。对于埃博拉疫情传播的分析,也有研究人员给出了他们的方法,其中一种就是通过估计引入风险(import risk)的方法来量化埃博拉对某一地区可能造成的影响。
美国NovaBios
我司还提供其它进口或国产试剂盒:登革热、疟疾、乙脑、寨卡、黄热病、基孔肯雅热、克锥虫病、违禁品滥用、肺炎球菌、军团菌等试剂盒以及日本生研细菌分型诊断血清、德国SiFin诊断血清、丹麦SSI诊断血清等产品。
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【公司名称】 广州健仑生物科技有限公司
【市场部】 杨永汉
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【腾讯 】 2042552662
【公司地址】 广州清华科技园创新基地番禺石楼镇创启路63号二期2幢101-103室
Ebola virus outbreak after a few years, but before each time the epidemic is relatively small, mainly concentrated in a region outbreak, and confined to Central Africa. In particular, the history of the Republic of the Congo has repeatedly erupted the Ebola epidemic.
The outbreak of the Ebola virus outbreaks in March 2014 has attracted the attention of the international community and has been listed by the World Health Organization as a "international public health emergency" (the third time in history). First of all, the epidemic related to a number of countries and regions. Countries affected by the whole territory include Guinea, Liberia and Sierra Leone. Some of the areas affected by the territory include Kay in Mali, Madrid, Spain, Dallas, Texas and New York City, Glasgow City, Scotland, Lagos Harbor, Nigeria, and Senegal Kar Second, the Ebola virus outbreak of the case and death figures exceeded the sum of all other epidemics. As of December 31, 2014, a total of 20206 people were sick, 7905 people died Ebola. And the numbers are still increasing. And all the Ebola careers, was the United States Times magazine selected as the 2014 annual figures.
Looking back over the past few decades, mankind is undoubtedly in the information, technology, biotechnology, medical and other fields have achieved the results of today. In view of the outbreak, spread, media coverage and control of the Ebola virus outbreak in 2014, we can not help thinking about the benefits of human disease prevention and control in this era of large data, data, statistics, rational thinking and critical thinking? Article attempts to explain from three angles how large data and epidemic prevention and control are closely linked. The first part of this paper discusses how to measure and even predict the risk of outbreaks through non-traditional public health data such as traffic data, communication data, and social media data. The second part focuses on the different estimates of mortality. The third part focuses on the treatment of Ebola virus outbreaks and prevention and control expenditure data.
First, the data-driven epidemic forecast
1. Forecast data by traffic data Ebola
Increasing global population mobility The outbreak of a region of the epidemic will bring potential risks to other countries and regions around the world, so how to effectively predict and assess the risk of such epidemics is a question worth exploring. The Ebola outbreak of a major feature is that the epidemic through the transport break through the border, in the source of the outbreak of several countries outside of Guinea raging. For the international population movement, the aircraft is obviously the most important mode of transport, so the statistical analysis of the airport population data will become the most important.
In fact, airport data has long been the focus of many areas of the researchers, based on the analysis of such data analysis of the case has also been common. For the analysis of the Ebola epidemic, researchers have also given their approach, one of which is to quantify the possible impact of Ebola on a region by estimating the import risk.