論文

査読有り 筆頭著者 最終著者 責任著者
2018年3月1日

Future risk of dengue fever to workforce and industry through global supply chain

Mitigation and Adaptation Strategies for Global Change
  • Katsuyuki Nakano

23
3
開始ページ
433
終了ページ
449
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s11027-017-9741-4
出版者・発行元
Springer Netherlands

The primary vector of the dengue fever virus, the Aedes aegypti mosquito, is distributed across the tropical and sub-tropical latitudes
however, the area at risk of infection has been expanding steadily. This study aimed to identify the industries most vulnerable to the effects of dengue fever by 2030. The assessment was done by considering the international supply chain, with aspects such as the labor intensity, and the relevant geographical and socioeconomic aspects being taken into account. In addition, multi-regional input-output tables were employed to analyze the ripple effects of productivity losses resulting from workers contracting the disease. The results indicate that more than 10% of the workers involved in the supply chain of all the major industries in the United States (USA), China, Japan, and Germany could be considered at risk of contracting dengue fever by 2030. Moreover, the risk was even higher in India and Brazil, namely, more than 70%. The effect of widespread dengue fever infection could influence industrial activities severely, not only in the regions most at risk (India and Brazil) but also in the other regions (USA, Japan, and Germany). Labor-intensive industries, such as agriculture, fisheries, and the distribution sector are particularly at risk and will have to consider appropriate contingency measures. It is recommended that the downstream side of the supply chain, the industries in the USA, Japan, and Germany, supports the introduction of worker’s health management system against the infectious disease into their business partners. This study employed limited data and only estimated the possible effects of the disease by 2030. Further comprehensive analysis is required with more data modeled for the future to verify and enhance the reliability of the present results.

リンク情報
DOI
https://doi.org/10.1007/s11027-017-9741-4
URL
http://orcid.org/0000-0001-5123-5510
ID情報
  • DOI : 10.1007/s11027-017-9741-4
  • ISSN : 1573-1596
  • ISSN : 1381-2386
  • ORCIDのPut Code : 31150850
  • SCOPUS ID : 85015684934

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