Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany.
PLoS One
; 16(8): e0254660, 2021.
Article
em En
| MEDLINE
| ID: mdl-34407071
ABSTRACT
The SARS-CoV-2 virus has spread around the world with over 100 million infections to date, and currently many countries are fighting the second wave of infections. With neither sufficient vaccination capacity nor effective medication, non-pharmaceutical interventions (NPIs) remain the measure of choice. However, NPIs place a great burden on society, the mental health of individuals, and economics. Therefore the cost/benefit ratio must be carefully balanced and a target-oriented small-scale implementation of these NPIs could help achieve this balance. To this end, we introduce a modified SEIRD-class compartment model and parametrize it locally for all 412 districts of Germany. The NPIs are modeled at district level by time varying contact rates. This high spatial resolution makes it possible to apply geostatistical methods to analyse the spatial patterns of the pandemic in Germany and to compare the results of different spatial resolutions. We find that the modified SEIRD model can successfully be fitted to the COVID-19 cases in German districts, states, and also nationwide. We propose the correlation length as a further measure, besides the weekly incidence rates, to describe the current situation of the epidemic.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Controle de Doenças Transmissíveis
/
Pandemias
/
COVID-19
Tipo de estudo:
Incidence_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
PLoS One
Assunto da revista:
CIENCIA
/
MEDICINA
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Alemanha