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Skrip LA, Selvaraj P, Hagedorn B, Ouédraogo AL, Noori N, Orcutt A, Mistry D, Bedson J, Hébert-Dufresne L, Scarpino SV, Althouse BM. Seeding COVID-19 across Sub-Saharan Africa: An Analysis of Reported Importation Events across 49 Countries. Am J Trop Med Hyg 2021; 104:1694-1702. [PMID: 33684067 PMCID: PMC8103462 DOI: 10.4269/ajtmh.20-1502] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 02/01/2021] [Indexed: 01/10/2023] Open
Abstract
The first case of COVID-19 in sub-Saharan Africa (SSA) was reported by Nigeria on February 27, 2020. Whereas case counts in the entire region remain considerably less than those being reported by individual countries in Europe, Asia, and the Americas, variation in preparedness and response capacity as well as in data availability has raised concerns about undetected transmission events in the SSA region. To capture epidemiological details related to early transmission events into and within countries, a line list was developed from publicly available data on institutional websites, situation reports, press releases, and social media accounts. The availability of indicators-gender, age, travel history, date of arrival in country, reporting date of confirmation, and how detected-for each imported case was assessed. We evaluated the relationship between the time to first reported importation and the Global Health Security Index (GHSI) overall score; 13,201 confirmed cases of COVID-19 were reported by 48 countries in SSA during the 54 days following the first known introduction to the region. Of the 2,516 cases for which travel history information was publicly available, 1,129 (44.9%) were considered importation events. Imported cases tended to be male (65.0%), with a median age of 41.0 years (range: 6 weeks-88 years; IQR: 31-54 years). A country's time to report its first importation was not related to the GHSI overall score, after controlling for air traffic. Countries in SSA generally reported with less publicly available detail over time and tended to have greater information on imported than local cases.
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Affiliation(s)
- Laura A. Skrip
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Prashanth Selvaraj
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Brittany Hagedorn
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Andre Lin Ouédraogo
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Navideh Noori
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Amanda Orcutt
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Dina Mistry
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Jamie Bedson
- Consultant to the Bill & Melinda Gates Foundation, Seattle, Washington
| | - Laurent Hébert-Dufresne
- Department of Computer Science, Vermont Complex Systems Center, University of Vermont, Burlington, Vermont;,Department of Computer Science, University of Vermont, Burlington, Vermont
| | - Samuel V. Scarpino
- Network Science Institute, Northeastern University, Boston, Massachusetts;,Department of Marine and Environmental Sciences, Northeastern University, Boston, Massachusetts;,Department of Physics, Northeastern University, Boston, Massachusetts;,Department of Health Sciences, Northeastern University, Boston, Massachusetts;,ISI Foundation, Turin, Italy
| | - Benjamin M. Althouse
- Institute for Disease Modeling, Global Health, Bill & Melinda Gates Foundation, Seattle, Washington;,University of Washington, Seattle, Washington;,New Mexico State University, Las Cruces, New Mexico,Address correspondence to Benjamin M. Althouse, Institute for Disease Modeling, Global Health Division Bill & Melinda Gates Foundation, 500 5th Ave. N, Seattle, WA 98109. E-mail:
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Kane PF, Orcutt A. Equivalency of protein determination in feed on Bran & Luebbe Traacs 800 autoanalyzer with AOAC semiautomated method: minicollaborative study. J Assoc Off Anal Chem 1990; 73:31-4. [PMID: 2312510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
A new generation of autoanalyzers was collaboratively studied for equivalency with instrumentation described in the AOAC method for crude protein in animal feeds. Twenty predigested samples were analyzed by 4 collaborators using standards that were provided. Means were comparable; the overall average difference was 0.07% protein. Analysis of variance indicated no evidence for an instrument difference. The method describing use of the Traacs 800 autoanalyzer as an alternative system has been adopted official first action.
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Affiliation(s)
- P F Kane
- Purdue University, Department of Biochemistry, West Lafayette, IN 47907
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