@article{fdi:010079819,
  title = {{COMOKIT} : a modeling kit to understand, analyze, and compare the impacts of mitigation policies against the {COVID}-19 epidemic at the scale of a city},
  author = {{G}audou, {B}enoit and {H}uynh, {N}. {Q}. and {P}hilippon, {D}amien and {B}rugiere, {A}. and {C}hapuis, {K}. and {T}aillandier, {P}. and {L}armande, {P}ierre and {D}rogoul, {A}lexis},
  editor = {},
  language = {{ENG}},
  abstract = {{S}ince its emergence in {C}hina, the {COVID}-19 pandemic has spread rapidly around the world. {F}aced with this unknown disease, public health authorities were forced to experiment, in a short period of time, with various combinations of interventions at different scales. {H}owever, as the pandemic progresses, there is an urgent need for tools and methodologies to quickly analyze the effectiveness of responses against {COVID}-19 in different communities and contexts. {I}n this perspective, computer modeling appears to be an invaluable lever as it allows for thein silicoexploration of a range of intervention strategies prior to the potential field implementation phase. {M}ore specifically, we argue that, in order to take into account important dimensions of policy actions, such as the heterogeneity of the individual response or the spatial aspect of containment strategies, the branch of computer modeling known asagent-based modelingis of immense interest. {W}e present in this paper an agent-based modeling framework called {COVID}-19 {M}odeling {K}it ({COMOKIT}), designed to be generic, scalable and thus portable in a variety of social and geographical contexts. {COMOKIT} combines models of person-to-person and environmental transmission, a model of individual epidemiological status evolution, an agenda-based 1-h time step model of human mobility, and an intervention model. {I}t is designed to be modular and flexible enough to allow modelers and users to represent different strategies and study their impacts in multiple social, epidemiological or economic scenarios. {S}everal large-scale experiments are analyzed in this paper and allow us to show the potentialities of {COMOKIT} in terms of analysis and comparison of the impacts of public health policies in a realistic case study.},
  keywords = {{COVID}-19 ; agent-based modeling ({ABM}) ; epidemiological modeling ; {GAMA} ; platform ; computer simulation ({CS})},
  booktitle = {},
  journal = {{F}rontiers in {P}ublic {H}ealth},
  volume = {8},
  numero = {},
  pages = {563247 [18 p.]},
  year = {2020},
  DOI = {10.3389/fpubh.2020.563247},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079819},
}