Bayesian spatio-temporal modelling to assess the role of extreme weather, land use change and socio-economic trends on cryptosporidiosis in Australia, 2001-2018.

Forbes, Owen; Hosking, Rose; Mokany, Karel; Lal, Aparna

Forbes, Owen; Hosking, Rose; Mokany, Karel; Lal, Aparna.

Afiliación

Forbes O; Research School of Population Health, Australian National University, Acton, Australia; School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia; ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), Brisbane, Australia.
Hosking R; Research School of Population Health, Australian National University, Acton, Australia.
Mokany K; Macroecological Modelling, CSIRO Land & Water, Black Mountain Laboratories, Canberra, ACT, Australia.
Lal A; Research School of Population Health, Australian National University, Acton, Australia. Electronic address: Aparna.lal@anu.edu.au.

Sci Total Environ ; 791: 148243, 2021 Oct 15.

Article en En | MEDLINE | ID: mdl-34412375

Asunto(s)

Criptosporidiosis; Clima Extremo; Australia/epidemiología; Teorema de Bayes; Criptosporidiosis/epidemiología; Humanos; Factores Socioeconómicos

Palabras clave

Disease risk; Extreme; Habitat; Rainfall; Spatio-temporal

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Criptosporidiosis / Clima Extremo Tipo de estudio: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Oceania Idioma: En Revista: Sci Total Environ Año: 2021 Tipo del documento: Article País de afiliación: Australia

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