Predicting the potential risk area of illegal vaccine trade in China

Abstract Since the disclosure of the “Illegal vaccine operation series case in Jinan, Shandong” in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to...

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Autores principales:	Yilan Liao, Yanhui Lei, Zhoupeng Ren, Huiyan Chen, Dongyue Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b5d660afb14f433abd82945bdc11ea6e
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spelling	oai:doaj.org-article:b5d660afb14f433abd82945bdc11ea6e2021-12-02T16:06:05ZPredicting the potential risk area of illegal vaccine trade in China10.1038/s41598-017-03512-32045-2322https://doaj.org/article/b5d660afb14f433abd82945bdc11ea6e2017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03512-3https://doaj.org/toc/2045-2322Abstract Since the disclosure of the “Illegal vaccine operation series case in Jinan, Shandong” in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to scientifically and scrupulously predict the possible geographic distribution of illegal vaccines in China, and provide a foundation to guide future governmental policies and actions. A species distribution model was used because of the advantages of using presence/pseudo-absence or presence-only data, and it performs well with incomplete species distribution data. A series of socioeconomic variables were used to simulate habitat suitability distribution. Maxent (Maximum Entropy Model) and GARP (Genetic Algorithm for Rule set Production) were used to predict the risks of illegal vaccines in China, and define the spatial distribution and significant factors of the area at risk from illegal vaccines. Jackknife tests were used to evaluate the relative importance of socioeconomic variables. It was found that: (1) Shandong, Hebei, Henan, Jiangsu and Anhui are the main high-risk areas impacted by the vaccines involved in Jinan case. (2) Population density and industrial structure are the main socioeconomic factors affecting areas which may be at risk from illegal vaccines.Yilan LiaoYanhui LeiZhoupeng RenHuiyan ChenDongyue LiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-10 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yilan Liao Yanhui Lei Zhoupeng Ren Huiyan Chen Dongyue Li Predicting the potential risk area of illegal vaccine trade in China
description	Abstract Since the disclosure of the “Illegal vaccine operation series case in Jinan, Shandong” in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to scientifically and scrupulously predict the possible geographic distribution of illegal vaccines in China, and provide a foundation to guide future governmental policies and actions. A species distribution model was used because of the advantages of using presence/pseudo-absence or presence-only data, and it performs well with incomplete species distribution data. A series of socioeconomic variables were used to simulate habitat suitability distribution. Maxent (Maximum Entropy Model) and GARP (Genetic Algorithm for Rule set Production) were used to predict the risks of illegal vaccines in China, and define the spatial distribution and significant factors of the area at risk from illegal vaccines. Jackknife tests were used to evaluate the relative importance of socioeconomic variables. It was found that: (1) Shandong, Hebei, Henan, Jiangsu and Anhui are the main high-risk areas impacted by the vaccines involved in Jinan case. (2) Population density and industrial structure are the main socioeconomic factors affecting areas which may be at risk from illegal vaccines.
format	article
author	Yilan Liao Yanhui Lei Zhoupeng Ren Huiyan Chen Dongyue Li
author_facet	Yilan Liao Yanhui Lei Zhoupeng Ren Huiyan Chen Dongyue Li
author_sort	Yilan Liao
title	Predicting the potential risk area of illegal vaccine trade in China
title_short	Predicting the potential risk area of illegal vaccine trade in China
title_full	Predicting the potential risk area of illegal vaccine trade in China
title_fullStr	Predicting the potential risk area of illegal vaccine trade in China
title_full_unstemmed	Predicting the potential risk area of illegal vaccine trade in China
title_sort	predicting the potential risk area of illegal vaccine trade in china
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/b5d660afb14f433abd82945bdc11ea6e
work_keys_str_mv	AT yilanliao predictingthepotentialriskareaofillegalvaccinetradeinchina AT yanhuilei predictingthepotentialriskareaofillegalvaccinetradeinchina AT zhoupengren predictingthepotentialriskareaofillegalvaccinetradeinchina AT huiyanchen predictingthepotentialriskareaofillegalvaccinetradeinchina AT dongyueli predictingthepotentialriskareaofillegalvaccinetradeinchina
_version_	1718385110922821632

Predicting the potential risk area of illegal vaccine trade in China

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