مقاله انگلیسی رایگان در مورد شناسایی منابع عفونت آنفلوانزای مرغی – IEEE 2019

IEEE

 

مشخصات مقاله
ترجمه عنوان مقاله شناسایی منابع عفونت آنفلوانزای مرغی (A (H7N9 در شبکه حمل و نقل طیور زنده در طول موج پنجم در چین
عنوان انگلیسی مقاله Detection of Infection Sources for Avian Influenza A(H7N9) in Live Poultry Transport Network During the Fifth Wave in China
انتشار مقاله سال ۲۰۱۹
تعداد صفحات مقاله انگلیسی ۲۰ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه IEEE
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journals List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۴٫۶۴۱ در سال ۲۰۱۸
شاخص H_index ۵۶ در سال ۲۰۱۹
شاخص SJR ۰٫۶۰۹ در سال ۲۰۱۸
شناسه ISSN ۲۱۶۹-۳۵۳۶
شاخص Quartile (چارک) Q2 در سال ۲۰۱۸
مدل مفهومی ندارد
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر، پزشکی
گرایش های مرتبط مهندسی الگوریتم و محاسبات، بهداشت عمومی
نوع ارائه مقاله
ژورنال
مجله / کنفرانس دسترسی – IEEE Access
دانشگاه  Data Science and Technology, North University of China, Taiyuan 030012, China
کلمات کلیدی شبکه حمل و نقل طیور زنده، آنفلوانزای مرغی (A (H7N9، مدل انتقال، شناسایی منابع عفونت
کلمات کلیدی انگلیسی  Live poultry transport network, avian influenza A(H7N9), transmission model, detecting infection sources
شناسه دیجیتال – doi
https://doi.org/10.1109/ACCESS.2019.2949606
کد محصول  E13920
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
دانلود رایگان مقاله دانلود رایگان مقاله انگلیسی
سفارش ترجمه این مقاله سفارش ترجمه این مقاله

 

فهرست مطالب مقاله:
Abstract
I. Introduction
II. Data and Network Construction
III. Transmission Model
IV. Algorithm
V. Results
Authors
Figures
References

 

بخشی از متن مقاله:
Abstract

Numerous studies have demonstrated that exposure to live poultry or live poultry markets is the significant risk factor for human infection with avian influenza A(H7N9). However, the specific live poultry markets that are major infection sources for A(H7N9) human cases have not been explored in detail. In this study, we extract data associated with poultry farms, live poultry markets and farmers’ markets from Baidu Map using the JavaScript language and then construct the live poultry transport network. From this, we establish our A(H7N9) transmission model over the network based upon probabilistic discrete-time Markov chain. On the basis of the obtained network and model, we propose spatiotemporal backward detection and forward transmission algorithms to detect the most likely infection sources and to compute the first arrival times of the infection sources. Our simulations use these algorithms to identify the specific locations of the infection sources, the first arrival times of the infection sources and the most likely transmission map of the A(H7N9) virus along the live poultry transport network. The results reveal that, in addition to the hazards posed by the live poultry markets, backyard poultry also contributed to A(H7N9) human infections; this risk source was significant especially in the newly affected provinces, in the fifth wave of infection. In particular, by analyzing the temperature characteristics at a given location when the infection source arrived, we find that the risk of human infection with the influenza A(H7N9) virus was high under 9 ◦C∼۱۹◦C; moderate under 0◦C∼۹ ◦C or 19◦C∼۲۵◦C; and low for temperatures < 0 ◦C or > 25◦C. Our results suggest that strengthening the supervision of the live poultry market system and immunizing poultry at both live poultry markets and the backyard poultry operations under the high risk temperature band of 9 ◦C∼۱۹◦C, will be able to significantly contribute to the control of avian influenza A(H7N9) in the future.

Introduction

The novel avian influenza A(H7N9) virus emerged in 2013. It is a bird flu strain of the influenza virus A (avian influenza virus or bird flu virus) [1]. The avian influenza A(H7N9) virus is only transmitted between poultry or from poultry to human. Human can be infected through direct exposure to poultry, poultry secretions or excreta, inhalation of viral aerosols, and exposure to environments contaminated with the virus [2]–[۴]. Human cases of A(H7N9) infection have occurred since 2013, during the annual winter-spring epidemics in mainland China [5], [6]. After peaking in 2013-2014, the human infection cohort in subsequent epidemics was generally smaller [7], but it sharply increased in the fifth epidemic wave in December 2016 [8]. This fifth epidemic wave (lasting from October 1st, 2016, to September 31st, 2017) was the most significant up until that point; 746 human cases were reported across 27 provinces in mainland China. The A(H7N9) virus strains circulating among poultry had been classified as low pathogenicity avian influenza (LPAI) in the previous four epidemic waves in China [9], but evolved to be highly pathogenic in poultry in the fifth epidemic wave [10]. The earlier start date, larger epidemic size, wider epidemic range and higher pathogenicity in the fifth epidemic wave A(H7N9) prompted panic and aroused public concern. Most of the confirmed A(H7N9) cases in human had an etiology involving a history of recent exposure to live poultry or potentially contaminated environments, especially the live poultry markets, where live poultry is sold [11], [12].

ارسال دیدگاه

نشانی ایمیل شما منتشر نخواهد شد.