Replicating superspreader dynamics with compartmental models.
Sci Rep
; 13(1): 15319, 2023 09 15.
Article
en En
| MEDLINE
| ID: mdl-37714942
ABSTRACT
Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
3_ND
Problema de salud:
3_neglected_diseases
Asunto principal:
Epidemias
/
Modelos Epidemiológicos
Tipo de estudio:
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Sci Rep
Año:
2023
Tipo del documento:
Article
País de afiliación:
Australia