Mathematical indices for the influence of risk factors on the lethality of a disease
Metadatos
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Springer
Materia
Epidemiology Comorbidity Lethality Equal attribution index Shapley value index COVID-19
Fecha
2021-12-08Referencia bibliográfica
Martínez, R., Sánchez-Soriano, J. Mathematical indices for the influence of risk factors on the lethality of a disease. J. Math. Biol. 83, 74 (2021). [https://doi.org/10.1007/s00285-021-01700-4]
Patrocinador
R&D&I project grants ECO2017-86245-P PID2020-114309GB-I00 MCIN/AEI/10.13039/501100011033; "ERDF A way of making Europe"/EU MCIN/AEI/10.13039/501100011033 PGC2018-097965-B-I00; Junta de Andalucia P18-FR-2933; FEDER UGR A-SEJ-14-UGR20; Grupos PAIDI SEJ660; Generalitat Valenciana European Commission General Electric PROMETEO/2021/063Resumen
We develop a theoretical model to measure the relative relevance of different pathologies
of the lethality of a disease in society. This approach allows a ranking of diseases
to be determined, which can assist in establishing priorities for vaccination campaigns
or prevention strategies. Among all possible measurements, we identify three families
of rules that satisfy a combination of relevant properties: neutrality, irrelevance, and
one of three composition concepts. One of these families includes, for instance, the
Shapley value of the associated cooperative game. The other two families also include
simple and intuitive indices. As an illustration, we measure the relative relevance of
several pathologies in lethality due to COVID-19.