@article{72d82aae768b44ad94f4f3e551819156,
title = "The promise and perils of Unit 731 data to advance COVID-19 research",
keywords = "COVID-19, diseases, disorders, epilepsy, infections, injuries, public health, vaccines",
author = "Zhaohui Su and Dean McDonnell and Ali Cheshmehzangi and Jaffar Abbas and Xiaoshan Li and Yuyang Cai",
note = "Funding Information: Funding This work was supported by the National Natural Science Foundation of China (71432006); the National Social Science Fund of China (17BSH056); and the Shanghai Jiao Tong University think tank research project (ZKYJ-20200114). Disclaimer The views, thoughts, and opinions expressed in this study belong solely to the authors, and not necessarily to the authors{\textquoteright} employers, organizations, committees, or other groups or individuals. Competing interests None declared. Patient consent for publication Not required. Provenance and peer review Not commissioned; externally peer reviewed. Data availability statement Data are available upon reasonable request. Open access This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.",
year = "2021",
month = may,
day = "20",
doi = "10.1136/bmjgh-2020-004772",
language = "English",
volume = "6",
journal = "BMJ Global Health",
issn = "2059-7908",
publisher = "BMJ Publishing Group",
number = "5",
}
