Work

A cost-effective plan for global testing - an infection rate stratified, algorithm guided, multiple-level, continuously pooled testing strategy

Year: 2020

Type: article

Source: The Science of The Total Environment

DOI: 10.1016/j.scitotenv.2020.144251

Authors: Tianshu Gu, Lan Yao, Xia Meng, J. Carolyn Graff, Donald Thomason, Jing Li, Wei Dong, Yan Jiao, Lotfi Aleya, Marcello Maida, Cong-Yi Wang, Barbara Zangerl, Sem Genini, Kunal Ray, Emanuel Goldman, Jiafu Ji, Andrei V. Alexandrov, Dianjun Sun, Weikuan Gu, Yongjun Wang

Institutions: University of Tennessee Health Science Center, Capital Medical University, Beijing Tian Tan Hospital, Harbin Medical University, Chinese Center For Disease Control and Prevention, Campbell Clinic, Centre National de la Recherche Scientifique, Laboratoire Chrono-Environnement, Université Bourgogne Franche-Comté, Tongji Hospital, Huazhong University of Science and Technology, UNSW Sydney, Academy of Scientific and Innovative Research, Rutgers, The State University of New Jersey, Rutgers New Jersey Medical School, Peking University, Peking University Cancer Hospital, Memphis VA Medical Center

Language: English

Topic: SARS-CoV-2 detection and testing

Subfield: Infectious Diseases

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: U.S. Department of Health and Human Services, U.S. Department of Veterans Affairs

Award: G1463410536

OpenAlex ID: W3116477169

FWCI: 0.197

Cites: 23

Cited by: 8

Related to: 10