Addressing the socioeconomic divide in computational modeling for infectious diseases

The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics, yet these concepts are often at the margins of the computational modeling community. Building on recent research studies in the area of digital and computational epidemiology, we provide a se...

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Detalles Bibliográficos
Autores principales: Tizzoni, Michele, Nsoesie, Elaine O., Gauvin, Laetitia, Karsai, Márton, Perra, Nicola, Bansal, Shweta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9130127/
https://www.ncbi.nlm.nih.gov/pubmed/35610237
http://dx.doi.org/10.1038/s41467-022-30688-8
Descripción
Sumario:The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics, yet these concepts are often at the margins of the computational modeling community. Building on recent research studies in the area of digital and computational epidemiology, we provide a set of practical and methodological recommendations to address socioeconomic vulnerabilities in epidemic models.

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