Dueling biological and social contagions.
Sci Rep
; 7: 43634, 2017 03 02.
Article
en En
| MEDLINE
| ID: mdl-28252663
ABSTRACT
Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of "dueling contagions", with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
/
2_ODS3
Problema de salud:
1_doencas_nao_transmissiveis
/
1_doencas_transmissiveis
/
2_enfermedades_transmissibles
/
2_muertes_prematuras_enfermedades_notrasmisibles
Asunto principal:
Conducta Social
/
Conductas Relacionadas con la Salud
/
Conocimientos, Actitudes y Práctica en Salud
/
Modelos Teóricos
Tipo de estudio:
Qualitative_research
Aspecto:
Determinantes_sociais_saude
Límite:
Humans
Idioma:
En
Revista:
Sci Rep
Año:
2017
Tipo del documento:
Article
País de afiliación:
Estados Unidos