Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022–2023 mpox epidemic is a research paper published in Royal Society Open Science (2024). On theSindex it has a DataRank of 0.615. It has been cited 17 times, with 5 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
Repositories this paper deposited data in (declared in PubMed).
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Base Score Contribution
0.434
From this paper's citation signal
Citation Network Contribution
0.182
From 3 citing papers with measurable signal
Ranked by each citer's contribution to N(p) — log1p(Cq) divided by its reference count — out of 5 citers.
National Institutes of Health
Grant: 3R01GM130900-01A1S1
Ebola modeling: behavior, asymptomatic infection, and contacts (2019-nCoV Admin Supplement)
Georgia State University
National Institutes of Health
National Science Foundation
FWCI
4.19
Citation Percentile
0.9%
Citation Trend
Fields of Study
Keywords
Sustainable Development Goals
S4 Appendix: Tabulation of forecasting performance metrics for each model, location, forecasting horizon. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S4 Appendix: Tabulation of forecasting performance metrics for each model, location, forecasting horizon. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S2 Appendix: Sensitivity analysis comparing forecasting performance across different calibration periods. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S2 Appendix: Sensitivity analysis comparing forecasting performance across different calibration periods. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S1 Appendix: Additional methods. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S1 Appendix: Additional methods. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S3 Appendix: Visualizations of the epidemic phase-specific forecast performance. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.
S3 Appendix: Visualizations of the epidemic phase-specific forecast performance. from Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.