Analysis of performance improvements and bias associated with the use of human mobility data in covid-19 case prediction models
Published in ACM Journal on Computing and Sustainable Societies, 2023
We conducted a systematic analysis of the impact of incorporating human mobility data in COVID-19 case prediction models, examining both performance improvements and potential biases across different regions and demographic groups.
Recommended citation: Abrar, S.M., Awasthi, N., Smolyak, D., & Frias-Martinez, V. (2023). Analysis of performance improvements and bias associated with the use of human mobility data in COVID-19 case prediction models. ACM Journal on Computing and Sustainable Societies, 1(2), 1-36.
Recommended citation: Abrar, S.M., Awasthi, N., Smolyak, D., & Frias-Martinez, V. (2023). Analysis of performance improvements and bias associated with the use of human mobility data in COVID-19 case prediction models. ACM Journal on Computing and Sustainable Societies, 1(2), 1-36.
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