Skip directly to site content Skip directly to page options Skip directly to A-Z link Skip directly to A-Z link Skip directly to A-Z link
Volume 26, Number 7—July 2020

Identifying Locations with Possible Undetected Imported Severe Acute Respiratory Syndrome Coronavirus 2 Cases by Using Importation Predictions

Pablo Martinez De Salazar1, René Niehus1, Aimee Taylor1, Caroline O’Flaherty Buckee, and Marc LipsitchComments to Author 
Author affiliations: Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

Main Article


Surveillance capacity of locations with and without imported-and-reported cases of severe acute respiratory syndrome coronavirus 2, 2020*

Surveillance capacity No. locations
0 cases >1 case
High 35 14 49
Low 138 7 145
Total 173 21 194

*Aggregated case counts collected during January 20–February 4, 2020. Surveillance capacity reported by category 2, Early Detection and Reporting of Epidemics of Potential International Concern, of the Global Health Security Index (3). High surveillance capacity is defined as 1st quartile ranking of the GHS Index; low surveillance capacity are locations below the 1st quartile ranking of the GHS.

Main Article

  1. Zhou  P, Yang  XL, Wang  XG, Hu  B, Zhang  L, Zhang  W, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579:2703.
  2. Wu  JT, Leung  K, Leung  GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. Lancet. 2020;395:68997. DOIPubMedGoogle Scholar
  3. World Health Organization. Coronavirus disease 2019 (COVID-19) situation report—15, 4 Feb 2020 [cited 2020 Feb 14].
  4. Nuclear Threat Initiative and Johns Hopkins Center for Health Security. Global health security index [cited 2020 Feb 14].
  5. US Environmental Protection Agency. Data quality assessment: statistical methods for practitioners EPA QA/G9-S [cited 2020 Feb 14]. Washington: The Agency; 2006.
  6. Lamichhane  S, Sen  P, Dickens  AM, Hyötyläinen  T, Orešič  M. An overview of metabolomics data analysis: current tools and future perspectives. In: Jaumot J, Bedia C, Tauler R, editors. Comprehensive analytical chemistry. Vol. 82. Amsterdam: Elsevier; 2018. p. 387–413.
  7. Gelman  A, Hill  J. Analytical methods for social research. In: Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press; 2006. p. 235–236.
  8. Wickham  H. ggplot2: elegant graphics for data analysis. New York: Springer; 2016.

Main Article

1These authors contributed equally to this article.

Page created: April 02, 2020
Page updated: June 18, 2020
Page reviewed: June 18, 2020
The conclusions, findings, and opinions expressed by authors contributing to this journal do not necessarily reflect the official position of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.