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Systems Thinking for Effective Interventions in Global Environmental Health.
McAlister, Martha M; Zhang, Qiong; Annis, Jonathan; Schweitzer, Ryan W; Guidotti, Sunny; Mihelcic, James R.
  • McAlister MM; Department of Civil & Environmental Engineering, University of South Florida, 4202 E Fowler Ave, Tampa, Florida 33620, United States.
  • Zhang Q; Department of Civil & Environmental Engineering, University of South Florida, 4202 E Fowler Ave, Tampa, Florida 33620, United States.
  • Annis J; USAID Uganda Sanitation for Health Activity, Tetra Tech, Plot 12A, Farady Road, Bugolobi, Kampala, Uganda.
  • Schweitzer RW; Independent, 349 West Parkwood Road, Decatur, Georgia 30030, United States.
  • Guidotti S; Latin America and Caribbean Regional Office, UNICEF, PO Box 0843-03045, Panama City, 07144, Panama.
  • Mihelcic JR; Department of Civil & Environmental Engineering, University of South Florida, 4202 E Fowler Ave, Tampa, Florida 33620, United States.
Environ Sci Technol ; 56(2): 732-738, 2022 01 18.
Article en En | MEDLINE | ID: mdl-34982546
ABSTRACT
Environmental health risks such as household air pollution due to burning solid fuels, inadequate water, sanitation, and hygiene, and chemical pollution disproportionately affect the poorest and most marginalized populations. While billions of dollars and countless hours of research have been applied toward addressing these issues in both development and humanitarian contexts, many interventions fail to achieve or sustain desired outcomes over time. This pattern points to the perpetuation of linear thinking, despite the complex nature of environmental health within these contexts. There is a need and an opportunity to engage in critical reflection of the dominant paradigms in the global environmental health community, including how they affect decision-making and collective learning. These paradigms should be adapted as needed toward the integration of diverse perspectives and the uptake of systems thinking. Participatory modeling, complexity-aware monitoring, and virtual simulation modeling can help achieve this. Additionally, virtual simulation modeling is relatively inexpensive and can provide a low-stakes environment for testing interventions before implementation.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Saneamiento / Higiene Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Saneamiento / Higiene Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article