Paradoxes in the co-evolution of contagions and institutions
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Epidemic models study the spread of undesired agents through populations, be it infectious diseases through a country, misinformation in social media, or pests infesting a region. In combating these epidemics, we rely neither on global top-down interventions, nor solely on individual adaptations. Instead, interventions commonly come from local institutions such as public health departments, moderation teams on social media platforms, or other forms of group governance. Classic models, which are often individual or agent-based, are ill-suited to capture local adaptations. We leverage developments of institutional dynamics based on cultural group selection to study how groups attempt local control of an epidemic by taking inspiration from the successes and failures of other groups. Incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation. When groups per..., , , # Paradoxes in the co-evolution of contagions and institutions
[https://doi.org/10.5061/dryad.3ffbg79s8](https://doi.org/10.5061/dryad.3ffbg79s8)
We use group-based models as set of master equations to study the impact of institutional policies on contagion. We find that incorporating institutional changes into epidemic dynamics reveals paradoxes: a higher transmission rate can result in smaller outbreaks as does decreasing the speed of institutional adaptation.
See README.md within the included zip file for more details.Â
## Code/Software
The code to reproduce the results of this paper can be found at [jstonge/hello-gmes/src/examples](https://github.com/jstonge/hello-gmes/tree/main/src/examples). The code depends on the Git submodule [jstonge/InstitutionalDynamics.jl, ](https://github.com/jstonge/InstitutionalDynamics.jl)which contain the model written in [Julia](https://julialang.org/). Make sure to follow the instructions on the README to get started. In addition to the script t...
创建时间:
2024-07-04



