The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.

<p>sMOA outperforms the majority of all models and best-in-class models if the validation date cut off is between October 2020 and March 2023. Directly before October 2020, there was a dip in incidence case counts that sMOA failed to forecast accurately that caused the initial lower performanc...

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Main Author: Alexander C. Murph (21587737) (author)
Other Authors: G. Casey Gibson (21587740) (author), Elizabeth B. Amona (21587743) (author), Lauren J. Beesley (6836693) (author), Lauren A. Castro (8463561) (author), Sara Y. Del Valle (7465541) (author), Dave Osthus (3216351) (author)
Published: 2025
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author Alexander C. Murph (21587737)
author2 G. Casey Gibson (21587740)
Elizabeth B. Amona (21587743)
Lauren J. Beesley (6836693)
Lauren A. Castro (8463561)
Sara Y. Del Valle (7465541)
Dave Osthus (3216351)
author2_role author
author
author
author
author
author
author_facet Alexander C. Murph (21587737)
G. Casey Gibson (21587740)
Elizabeth B. Amona (21587743)
Lauren J. Beesley (6836693)
Lauren A. Castro (8463561)
Sara Y. Del Valle (7465541)
Dave Osthus (3216351)
author_role author
dc.creator.none.fl_str_mv Alexander C. Murph (21587737)
G. Casey Gibson (21587740)
Elizabeth B. Amona (21587743)
Lauren J. Beesley (6836693)
Lauren A. Castro (8463561)
Sara Y. Del Valle (7465541)
Dave Osthus (3216351)
dc.date.none.fl_str_mv 2025-06-23T17:49:46Z
dc.identifier.none.fl_str_mv 10.1371/journal.pcbi.1013203.g005
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/The_proportion_of_all_models_black_and_best-in-class_models_red_sMOA_outperforms_in_MAE_top_and_WIS_bottom_if_the_validation_window_ranged_from_August_2020_through_the_x-axis_date_/29386141
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Ecology
Inorganic Chemistry
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
synthetically generated segments
maintain high accuracy
instead matching segments
developing versatile approaches
observed time series
local behavior observed
emerging global epidemic
19 forecasting hub
new method inspired
historical time series
div >< p
time series data
time series
local behaviors
historical data
emerging epidemics
19 pandemic
synthetic method
synthetic </
strengthening preparedness
possible </
performing 78
past decade
particularly evident
parametric nature
novel pandemics
model circumvents
known values
highly adaptable
gained popularity
early stages
disease trends
directly follow
competitive performance
broad range
best match
dc.title.none.fl_str_mv The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>sMOA outperforms the majority of all models and best-in-class models if the validation date cut off is between October 2020 and March 2023. Directly before October 2020, there was a dip in incidence case counts that sMOA failed to forecast accurately that caused the initial lower performance.</p>
eu_rights_str_mv openAccess
id Manara_6d8dd2f9b496ba8c0dfd29ebf361fc3b
identifier_str_mv 10.1371/journal.pcbi.1013203.g005
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29386141
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.Alexander C. Murph (21587737)G. Casey Gibson (21587740)Elizabeth B. Amona (21587743)Lauren J. Beesley (6836693)Lauren A. Castro (8463561)Sara Y. Del Valle (7465541)Dave Osthus (3216351)MedicineEcologyInorganic ChemistryInfectious DiseasesBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsynthetically generated segmentsmaintain high accuracyinstead matching segmentsdeveloping versatile approachesobserved time serieslocal behavior observedemerging global epidemic19 forecasting hubnew method inspiredhistorical time seriesdiv >< ptime series datatime serieslocal behaviorshistorical dataemerging epidemics19 pandemicsynthetic methodsynthetic </strengthening preparednesspossible </performing 78past decadeparticularly evidentparametric naturenovel pandemicsmodel circumventsknown valueshighly adaptablegained popularityearly stagesdisease trendsdirectly followcompetitive performancebroad rangebest match<p>sMOA outperforms the majority of all models and best-in-class models if the validation date cut off is between October 2020 and March 2023. Directly before October 2020, there was a dip in incidence case counts that sMOA failed to forecast accurately that caused the initial lower performance.</p>2025-06-23T17:49:46ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pcbi.1013203.g005https://figshare.com/articles/figure/The_proportion_of_all_models_black_and_best-in-class_models_red_sMOA_outperforms_in_MAE_top_and_WIS_bottom_if_the_validation_window_ranged_from_August_2020_through_the_x-axis_date_/29386141CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/293861412025-06-23T17:49:46Z
spellingShingle The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
Alexander C. Murph (21587737)
Medicine
Ecology
Inorganic Chemistry
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
synthetically generated segments
maintain high accuracy
instead matching segments
developing versatile approaches
observed time series
local behavior observed
emerging global epidemic
19 forecasting hub
new method inspired
historical time series
div >< p
time series data
time series
local behaviors
historical data
emerging epidemics
19 pandemic
synthetic method
synthetic </
strengthening preparedness
possible </
performing 78
past decade
particularly evident
parametric nature
novel pandemics
model circumvents
known values
highly adaptable
gained popularity
early stages
disease trends
directly follow
competitive performance
broad range
best match
status_str publishedVersion
title The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
title_full The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
title_fullStr The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
title_full_unstemmed The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
title_short The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
title_sort The proportion of all models (black) and best-in-class models (red) sMOA outperforms in MAE (top) and WIS (bottom) if the validation window ranged from August 2020 through the x-axis date.
topic Medicine
Ecology
Inorganic Chemistry
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
synthetically generated segments
maintain high accuracy
instead matching segments
developing versatile approaches
observed time series
local behavior observed
emerging global epidemic
19 forecasting hub
new method inspired
historical time series
div >< p
time series data
time series
local behaviors
historical data
emerging epidemics
19 pandemic
synthetic method
synthetic </
strengthening preparedness
possible </
performing 78
past decade
particularly evident
parametric nature
novel pandemics
model circumvents
known values
highly adaptable
gained popularity
early stages
disease trends
directly follow
competitive performance
broad range
best match