Short-term leprosy forecasting from an expert opinion survey
We conducted an expert survey of leprosy (Hansen's Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health.
Errataetall: |
ErratumIn: PLoS One. 2017 Dec 14;12 (12 ):e0189976. - PMID 29240832 |
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Medienart: |
E-Artikel |
Erscheinungsjahr: |
2017 |
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Erschienen: |
2017 |
Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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Enthalten in: |
PloS one - 12(2017), 8 vom: 24., Seite e0182245 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Deiner, Michael S [VerfasserIn] |
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Date Completed 18.10.2017 Date Revised 26.02.2021 published: Electronic-eCollection ErratumIn: PLoS One. 2017 Dec 14;12 (12 ):e0189976. - PMID 29240832 Citation Status MEDLINE |
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doi: |
10.1371/journal.pone.0182245 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM274867664 |
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520 | |a We conducted an expert survey of leprosy (Hansen's Disease) and neglected tropical disease experts in February 2016. Experts were asked to forecast the next year of reported cases for the world, for the top three countries, and for selected states and territories of India. A total of 103 respondents answered at least one forecasting question. We elicited lower and upper confidence bounds. Comparing these results to regression and exponential smoothing, we found no evidence that any forecasting method outperformed the others. We found evidence that experts who believed it was more likely to achieve global interruption of transmission goals and disability reduction goals had higher error scores for India and Indonesia, but lower for Brazil. Even for a disease whose epidemiology changes on a slow time scale, forecasting exercises such as we conducted are simple and practical. We believe they can be used on a routine basis in public health | ||
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