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Social cohesion and passive adaptation in relation to climate change and disease
Social cohesion and passive adaptation in relation to climate change and disease
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Social cohesion and passive adaptation in relation to climate change and disease
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Social cohesion and passive adaptation in relation to climate change and disease
Social cohesion and passive adaptation in relation to climate change and disease
Journal Article

Social cohesion and passive adaptation in relation to climate change and disease

2019
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Overview
The authors developed an agent-based model in which household agents can choose between two behavioral strategies that offer different levels of protection against environmentally mediated disease transmission. One behavioral strategy is initially set as more protective, leading households to adopt it widely, but its efficacy is sensitive to variable weather conditions and stressors such as floods or droughts that modify the disease transmission system. The efficacy of the second strategy is initially moderate relative to the first and is insensitive to environmental changes. The authors examined how social cohesion (defined as the average number of household social network connections) influences health outcomes when households attempt to identify an optimal strategy by copying the behaviors of socially connected neighbours who seem to have adapted successfully in the past. In the face of uncertainty in predicting future environmental stressors due to climate change, strategies to improve effective adaptation to optimal disease prevention strategies should balance between intervention efforts that promote protective behaviours based on current scientific understanding and the need to guard against the crystallization of inflexible norms. Developing generalizable models allows us to integrate a wide range of theories and multiple datasets pertaining to the relationship between social mechanisms and adaptation, which can provide further understanding of future climate change impacts. Models such as the one the authors present can generate hypotheses about the mechanisms that underlie the dynamics of adaptation events and suggest specific points of measurement to assess the impact of these mechanisms. They can be incorporated as modules within predictive simulations for specific socio-ecological contexts. (6 Figures, 48 References)