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Response to Valle and Zorello Laporta: Clarifying the Use of Instrumental Variable Methods to Understand the Effects of Environmental Change on Infectious Disease Transmission.
MacDonald, Andrew J; Mordecai, Erin A.
Afiliação
  • MacDonald AJ; Earth Research Institute and Bren School of Environmental Science and Management, University of California, Santa Barbara, California.
  • Mordecai EA; Department of Biology, Stanford University, Stanford, California.
Am J Trop Med Hyg ; 105(6): 1456-1459, 2021 09 27.
Article em En | MEDLINE | ID: mdl-34583331
ABSTRACT
Identifying the effects of environmental change on the transmission of vectorborne and zoonotic diseases is of fundamental importance in the face of rapid global change. Causal inference approaches, including instrumental variable (IV) estimation, hold promise in disentangling plausibly causal relationships from observational data in these complex systems. Valle and Zorello Laporta recently critiqued the application of such approaches in our recent study of the effects of deforestation on malaria transmission in the Brazilian Amazon on the grounds that key statistical assumptions were not met. Here, we respond to this critique by 1) deriving the IV estimator to clarify the assumptions that Valle and Zorello Laporta conflate and misrepresent in their critique, 2) discussing these key assumptions as they relate to our original study and how our original approach reasonably satisfies the assumptions, and 3) presenting model results using alternative instrumental variables that can be argued more strongly satisfy key assumptions, illustrating that our results and original conclusion-that deforestation drives malaria transmission-remain unchanged.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Causalidade Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Causalidade Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2021 Tipo de documento: Article