A nowcasting framework for correcting for reporting delays in malaria surveillance

A nowcasting framework for correcting for reporting delays in malaria surveillance

Time lags in reporting to national surveillance systems represent a major barrier for the control of infectious diseases, preventing timely decision making and resource allocation. This issue is particularly acute for infectious diseases like malaria, which often impact rural and remote communities...

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Bibliographic Details
Main Authors: Buckee, C.O (Author), Clementson, C. (Author), Cox, H. (Author), De Salazar, P.M (Author), Jones-Weekes, S. (Author), Menkir, T.F (Author), Poirier, C. (Author), Santillana, M. (Author), Saul, M. (Author)
Format: Article
Language:English
Published: Public Library of Science 2021
Subjects:
Article
data analysis
data system
diagnostic accuracy
disease elimination
disease surveillance
endemic disease
Guyana
health survey
human
Humans
information processing
information service
malaria
Malaria
Models, Statistical
nowcasting
Population Surveillance
resource allocation
Retrospective Studies
retrospective study
statistical model
time factor
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