ArticleEpidemics2023
Accounting for historical injustices in mathematical models of infectious disease transmission: An analytic overview.
Article in Epidemics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Do COVID-19 Infectious Disease Models Incorporate the Social Determinants of Health? A Systematic Review.Public health reviews · 2024Pooled it
- Then And Now: Umbrella Variables Mask Temporal Mechanisms Of Structural Racism In US Urban Environments.Critical public health · 2025Article
- The impact of historical redlining policies on community composition and the COVID-19 pandemic in Boston.PloS one · 2025Article
- Managing spatio-temporal heterogeneity of susceptibles by embedding it into an homogeneous model: A mechanistic and deep learning study.PLoS computational biology · 2024Article
- Construction of effective reproduction number of infectious disease individuals based on spatiotemporal discriminant search model: take hand-foot-mouth disease as an example.BMC medical research methodology · 2024Article
- Incorporating social vulnerability in infectious disease mathematical modelling: a scoping review.BMC medicine · 2024Article
- Gaps and inconsistencies in the current knowledge and implementation of biosafety and biosecurity practices for rickettsial pathogens.BMC infectious diseases · 2024Review
- What's next: using infectious disease mathematical modelling to address health disparities.International journal of epidemiology · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Differences in infectious disease risk, acquisition, and severity arise from intersectional systems of oppression and resulting historical injustices that shape individual behavior and circumstance. We define historical injustices as distinct events and policies that arise out of intersectional systems of oppression. We view historical injustices as a medium through which structural forces affect health both directly and indirectly, and are thus important to study in the context of infectious disease disparities. In this critical analysis we aim to highlight the importance of incorporating historical injustices into mathematical models of infectious disease transmission and provide context on the methodologies to do so. We offer two illustrations of elements of model building (i.e., parameterization, validation and calibration) that can allow for a better understanding of health disparities in infectious disease outcomes. Mathematical models that do not recognize the historical forces that underlie infectious disease dynamics inevitably lead to the individualization of our focus and the recommendation of untenable individual-behavioral prescriptions to address the burden of infectious disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.