Influencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challenges.
Epidemics
; 32: 100393, 2020 09.
Article
en En
| MEDLINE
| ID: mdl-32674025
ABSTRACT
Modern data and computational resources, coupled with algorithmic and theoretical advances to exploit these, allow disease dynamic models to be parameterised with increasing detail and accuracy. While this enhances models' usefulness in prediction and policy, major challenges remain. In particular, lack of identifiability of a model's parameters may limit the usefulness of the model. While lack of parameter identifiability may be resolved through incorporation into an inference procedure of prior knowledge, formulating such knowledge is often difficult. Furthermore, there are practical challenges associated with acquiring data of sufficient quantity and quality. Here, we discuss recent progress on these issues.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Salud Pública
/
Enfermedades Transmisibles
/
Política de Salud
/
Modelos Teóricos
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Epidemics
Año:
2020
Tipo del documento:
Article
País de afiliación:
Australia