{"doi":"10.1093/gigascience/giab009","title":"Evaluating short-term forecasting of COVID-19 cases among different epidemiological models under a Bayesian framework","abstract":"BACKGROUND: Forecasting of COVID-19 cases daily and weekly has been one of the challenges posed to governments and the health sector globally. To facilitate informed public health decisions, the concerned parties rely on short-term daily projections generated via predictive modeling. We calibrate stochastic variants of growth models and the standard susceptible-infectious-removed model into 1 Bayesian framework to evaluate and compare their short-term forecasts. RESULTS: We implement rolling-origin cross-validation to compare the short-term forecasting performance of the stochastic epidemiological models and an autoregressive moving average model across 20 countries that had the most confirmed COVID-19 cases as of August 22, 2020. CONCLUSION: None of the models proved to be a gold standard across all regions, while all outperformed the autoregressive moving average model in terms of the accuracy of forecast and interpretability.","journal":"GigaScience","year":2021,"id":186614,"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":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9456,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":744830,"name":"Tejasv Bedi","orcid":"0000-0001-7532-4075","position":1,"is_corresponding":false},{"id":703181,"name":"Christoph U. Lehmann","orcid":"0000-0001-9559-4646","position":2,"is_corresponding":false},{"id":27515,"name":"Guanghua Xiao","orcid":"0000-0001-9387-9883","position":3,"is_corresponding":false},{"id":326811,"name":"Yang Xie","orcid":"0000-0001-9456-1762","position":4,"is_corresponding":false},{"id":352535,"name":"Qiwei Li","orcid":"0000-0002-1020-3050","position":0,"is_corresponding":true}],"reference_count":82,"raw_metadata":null,"created_at":"2026-07-18T23:48:46.850806Z","pmid":"33604654","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":[]}