Your browser doesn't support javascript.
COVID-19 seeding time and doubling time model: an early epidemic risk assessment tool.
Zhou, Lei; Liu, Jiang-Mei; Dong, Xiao-Ping; McGoogan, Jennifer M; Wu, Zun-You.
  • Zhou L; Public Health Emergency Center, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China.
  • Liu JM; National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China.
  • Dong XP; Global Health Center, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China.
  • McGoogan JM; National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China.
  • Wu ZY; National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, 155 Changbai Road, Changping District, Beijing, 102206, China. wuzy@263.net.
Infect Dis Poverty ; 9(1): 76, 2020 Jun 23.
Article in English | MEDLINE | ID: covidwho-611626
ABSTRACT

BACKGROUND:

As COVID-19 makes its way around the globe, each nation must decide when and how to respond. Yet many knowledge gaps persist, and many countries lack the capacity to develop complex models to assess risk and response. This paper aimed to meet this need by developing a model that uses case reporting data as input and provides a four-tiered risk assessment output.

METHODS:

We used publicly available, country/territory level case reporting data to determine median seeding number, mean seeding time (ST), and several measures of mean doubling time (DT) for COVID-19. We then structured our model as a coordinate plane with ST on the x-axis, DT on the y-axis, and mean ST and mean DT dividing the plane into four quadrants, each assigned a risk level. Sensitivity analysis was performed and countries/territories early in their outbreaks were assessed for risk.

RESULTS:

Our main finding was that among 45 countries/territories evaluated, 87% were at high risk for their outbreaks entering a rapid growth phase epidemic. We furthermore found that the model was sensitive to changes in DT, and that these changes were consistent with what is officially known of cases reported and control strategies implemented in those countries.

CONCLUSIONS:

Our main finding is that the ST/DT Model can be used to produce meaningful assessments of the risk of escalation in country/territory-level COVID-19 epidemics using only case reporting data. Our model can help support timely, decisive action at the national level as leaders and other decision makers face of the serious public health threat that is COVID-19.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Risk Assessment / Betacoronavirus Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Infect Dis Poverty Year: 2020 Document Type: Article Affiliation country: S40249-020-00685-4

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Risk Assessment / Betacoronavirus Type of study: Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Infect Dis Poverty Year: 2020 Document Type: Article Affiliation country: S40249-020-00685-4