Cargando…

Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models

BACKGROUND: Trachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion. METHODS: The Program for the Rapid Eliminati...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Fengchen, Porco, Travis C., Amza, Abdou, Kadri, Boubacar, Nassirou, Baido, West, Sheila K., Bailey, Robin L., Keenan, Jeremy D., Solomon, Anthony W., Emerson, Paul M., Gambhir, Manoj, Lietman, Thomas M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547743/
https://www.ncbi.nlm.nih.gov/pubmed/26302380
http://dx.doi.org/10.1371/journal.pntd.0004000
_version_ 1782387104197640192
author Liu, Fengchen
Porco, Travis C.
Amza, Abdou
Kadri, Boubacar
Nassirou, Baido
West, Sheila K.
Bailey, Robin L.
Keenan, Jeremy D.
Solomon, Anthony W.
Emerson, Paul M.
Gambhir, Manoj
Lietman, Thomas M.
author_facet Liu, Fengchen
Porco, Travis C.
Amza, Abdou
Kadri, Boubacar
Nassirou, Baido
West, Sheila K.
Bailey, Robin L.
Keenan, Jeremy D.
Solomon, Anthony W.
Emerson, Paul M.
Gambhir, Manoj
Lietman, Thomas M.
author_sort Liu, Fengchen
collection PubMed
description BACKGROUND: Trachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion. METHODS: The Program for the Rapid Elimination of Trachoma trials estimated longitudinal prevalence of ocular chlamydial infection from 24 communities treated annually with mass azithromycin. Given antibiotic coverage and biannual assessments from baseline through 30 months, forecasts of the prevalence of infection in each of the 24 communities at 36 months were made by three methods: the sum of 15 experts’ opinion, statistical regression of the square-root-transformed prevalence, and a stochastic hidden Markov model of infection transmission (Susceptible-Infectious-Susceptible, or SIS model). All forecasters were masked to the 36-month results and to the other forecasts. Forecasts of the 24 communities were scored by the likelihood of the observed results and compared using Wilcoxon’s signed-rank statistic. FINDINGS: Regression and SIS hidden Markov models had significantly better likelihood than community expert opinion (p = 0.004 and p = 0.01, respectively). All forecasts scored better when perturbed to decrease Fisher’s information. Each individual expert’s forecast was poorer than the sum of experts. INTERPRETATION: Regression and SIS models performed significantly better than expert opinion, although all forecasts were overly confident. Further model refinements may score better, although would need to be tested and compared in new masked studies. Construction of guidelines that rely on forecasting future prevalence could consider use of mathematical and statistical models.
format Online
Article
Text
id pubmed-4547743
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-45477432015-09-01 Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models Liu, Fengchen Porco, Travis C. Amza, Abdou Kadri, Boubacar Nassirou, Baido West, Sheila K. Bailey, Robin L. Keenan, Jeremy D. Solomon, Anthony W. Emerson, Paul M. Gambhir, Manoj Lietman, Thomas M. PLoS Negl Trop Dis Research Article BACKGROUND: Trachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion. METHODS: The Program for the Rapid Elimination of Trachoma trials estimated longitudinal prevalence of ocular chlamydial infection from 24 communities treated annually with mass azithromycin. Given antibiotic coverage and biannual assessments from baseline through 30 months, forecasts of the prevalence of infection in each of the 24 communities at 36 months were made by three methods: the sum of 15 experts’ opinion, statistical regression of the square-root-transformed prevalence, and a stochastic hidden Markov model of infection transmission (Susceptible-Infectious-Susceptible, or SIS model). All forecasters were masked to the 36-month results and to the other forecasts. Forecasts of the 24 communities were scored by the likelihood of the observed results and compared using Wilcoxon’s signed-rank statistic. FINDINGS: Regression and SIS hidden Markov models had significantly better likelihood than community expert opinion (p = 0.004 and p = 0.01, respectively). All forecasts scored better when perturbed to decrease Fisher’s information. Each individual expert’s forecast was poorer than the sum of experts. INTERPRETATION: Regression and SIS models performed significantly better than expert opinion, although all forecasts were overly confident. Further model refinements may score better, although would need to be tested and compared in new masked studies. Construction of guidelines that rely on forecasting future prevalence could consider use of mathematical and statistical models. Public Library of Science 2015-08-24 /pmc/articles/PMC4547743/ /pubmed/26302380 http://dx.doi.org/10.1371/journal.pntd.0004000 Text en © 2015 Liu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Liu, Fengchen
Porco, Travis C.
Amza, Abdou
Kadri, Boubacar
Nassirou, Baido
West, Sheila K.
Bailey, Robin L.
Keenan, Jeremy D.
Solomon, Anthony W.
Emerson, Paul M.
Gambhir, Manoj
Lietman, Thomas M.
Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title_full Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title_fullStr Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title_full_unstemmed Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title_short Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models
title_sort short-term forecasting of the prevalence of trachoma: expert opinion, statistical regression, versus transmission models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547743/
https://www.ncbi.nlm.nih.gov/pubmed/26302380
http://dx.doi.org/10.1371/journal.pntd.0004000
work_keys_str_mv AT liufengchen shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT porcotravisc shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT amzaabdou shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT kadriboubacar shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT nassiroubaido shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT westsheilak shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT baileyrobinl shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT keenanjeremyd shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT solomonanthonyw shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT emersonpaulm shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT gambhirmanoj shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels
AT lietmanthomasm shorttermforecastingoftheprevalenceoftrachomaexpertopinionstatisticalregressionversustransmissionmodels