{"doi":"10.1101/2020.12.13.20248129","title":"Using Mobility Data to Understand and Forecast COVID19 Dynamics","abstract":"Disease dynamics, human mobility, and public policies co-evolve during a pandemic such as COVID-19. Understanding dynamic human mobility changes and spatial interaction patterns are crucial for understanding and forecasting COVID-19 dynamics. We introduce a novel graph-based neural network(GNN) to incorporate global aggregated mobility flows for a better understanding of the impact of human mobility on COVID-19 dynamics as well as better forecasting of disease dynamics. We propose a recurrent message passing graph neural network that embeds spatio-temporal disease dynamics and human mobility dynamics for daily state-level new confirmed cases forecasting. This work represents one of the early papers on the use of GNNs to forecast COVID-19 incidence dynamics and our methods are competitive to existing methods. We show that the spatial and temporal dynamic mobility graph leveraged by the graph neural network enables better long-term forecasting performance compared to baselines.","journal":"medRxiv","year":2020,"id":119216,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":25,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9382,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":554908,"name":"Xue Ben","orcid":null,"position":1,"is_corresponding":false},{"id":244676,"name":"Aniruddha Adiga","orcid":"0000-0002-5396-1978","position":2,"is_corresponding":false},{"id":496015,"name":"Adam Sadilek","orcid":"0000-0003-0784-7098","position":3,"is_corresponding":false},{"id":554909,"name":"Ashish V. Tendulkar","orcid":null,"position":4,"is_corresponding":false},{"id":244680,"name":"Srinivasan Venkatramanan","orcid":"0000-0002-0874-8692","position":5,"is_corresponding":false},{"id":244681,"name":"Anil Vullikanti","orcid":"0000-0002-8597-6197","position":6,"is_corresponding":false},{"id":553741,"name":"Gaurav Aggarwal","orcid":"0000-0002-8180-9287","position":7,"is_corresponding":false},{"id":553742,"name":"Alok Talekar","orcid":"0009-0007-4604-2328","position":8,"is_corresponding":false},{"id":465156,"name":"Jiangzhuo Chen","orcid":"0000-0002-2729-3881","position":9,"is_corresponding":false},{"id":244678,"name":"Bryan Lewis","orcid":"0000-0003-0793-6082","position":10,"is_corresponding":false},{"id":553743,"name":"Samarth Swarup","orcid":"0000-0003-3615-1663","position":11,"is_corresponding":false},{"id":554910,"name":"Amol Kapoor","orcid":null,"position":12,"is_corresponding":false},{"id":317349,"name":"Milind Tambe","orcid":"0000-0003-3296-3672","position":13,"is_corresponding":false},{"id":244679,"name":"Madhav Marathe","orcid":"0000-0003-1653-0658","position":14,"is_corresponding":false},{"id":488390,"name":"Lijing Wang","orcid":"0000-0002-0836-9190","position":0,"is_corresponding":true}],"reference_count":16,"raw_metadata":null,"created_at":"2026-07-18T23:14:08.313144Z","pmid":"33354685","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}