TY - JOUR
T1 - Generalized contact matrices allow integrating socioeconomic variables into epidemic models
AU - Manna, Adriana
AU - Dall’Amico, Lorenzo
AU - Tizzoni, Michele
AU - Karsai, Márton
AU - Perra, Nicola
N1 - Publisher Copyright:
Copyright © 2024 The Authors, some rights reserved.
PY - 2024/10/11
Y1 - 2024/10/11
N2 - Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures and affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age and interaction contexts. Here, we introduce and study generalized contact matrices that stratify contacts across multiple dimensions. We demonstrate a lower-bound theorem proving that disregarding additional dimensions, besides age and context, might lead to an underestimation of the basic reproductive number. By using SES variables in both synthetic and empirical data, we illustrate how generalized contact matrices enhance epidemic models, capturing variations in behaviors such as heterogeneous levels of adherence to nonpharmaceutical interventions among demographic groups. Moreover, we highlight the importance of integrating SES traits into epidemic models, as neglecting them might lead to substantial misrepresentation of epidemic outcomes and dynamics. Our research contributes to the efforts aiming at incorporating socioeconomic and other dimensions into epidemic modeling.
AB - Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures and affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age and interaction contexts. Here, we introduce and study generalized contact matrices that stratify contacts across multiple dimensions. We demonstrate a lower-bound theorem proving that disregarding additional dimensions, besides age and context, might lead to an underestimation of the basic reproductive number. By using SES variables in both synthetic and empirical data, we illustrate how generalized contact matrices enhance epidemic models, capturing variations in behaviors such as heterogeneous levels of adherence to nonpharmaceutical interventions among demographic groups. Moreover, we highlight the importance of integrating SES traits into epidemic models, as neglecting them might lead to substantial misrepresentation of epidemic outcomes and dynamics. Our research contributes to the efforts aiming at incorporating socioeconomic and other dimensions into epidemic modeling.
KW - Communicable Diseases/epidemiology
KW - Epidemics
KW - Humans
KW - Social Class
KW - Socioeconomic Factors
UR - http://www.scopus.com/inward/record.url?scp=85206123151&partnerID=8YFLogxK
U2 - 10.1126/sciadv.adk4606
DO - 10.1126/sciadv.adk4606
M3 - Article
C2 - 39392883
AN - SCOPUS:85206123151
SN - 2375-2548
VL - 10
SP - eadk4606
JO - Science Advances
JF - Science Advances
IS - 41
M1 - eadk4606
ER -