The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics. Here, the authors provide a set of practical and methodological recommendations to address socioeconomic vulnerabilities in epidemic models.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.

Addressing the socioeconomic divide in computational modeling for infectious diseases / Tizzoni, Michele; Nsoesie, Elaine O; Gauvin, Laetitia; Karsai, Márton; Perra, Nicola; Bansal, Shweta. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 13:1(2022), pp. 2897.1-2897.7. [10.1038/s41467-022-30688-8]

Addressing the socioeconomic divide in computational modeling for infectious diseases

Tizzoni, Michele
Primo
;
2022-01-01

Abstract

The COVID-19 pandemic has highlighted how structural social inequities fundamentally shape disease dynamics. Here, the authors provide a set of practical and methodological recommendations to address socioeconomic vulnerabilities in epidemic models.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.
2022
1
Tizzoni, Michele; Nsoesie, Elaine O; Gauvin, Laetitia; Karsai, Márton; Perra, Nicola; Bansal, Shweta
Addressing the socioeconomic divide in computational modeling for infectious diseases / Tizzoni, Michele; Nsoesie, Elaine O; Gauvin, Laetitia; Karsai, Márton; Perra, Nicola; Bansal, Shweta. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 13:1(2022), pp. 2897.1-2897.7. [10.1038/s41467-022-30688-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/355645
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