COVID-19 seeding time and doubling time model: an early epidemic risk assessment tool.
Infect Dis Poverty
; 9(1): 76, 2020 Jun 23.
Artículo
en Inglés
| 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.Palabras clave
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
Neumonía Viral
/
Infecciones por Coronavirus
/
Medición de Riesgo
/
Betacoronavirus
Tipo de estudio:
Estudio experimental
/
Estudio observacional
/
Estudio pronóstico
Límite:
Humanos
Idioma:
Inglés
Revista:
Infect Dis Poverty
Año:
2020
Tipo del documento:
Artículo
País de afiliación:
S40249-020-00685-4
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