ArticlePLoS neglected tropical diseases2015
Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models.
Article in PLoS neglected tropical diseases, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT00792922 (Research to Programs for Trachoma Elimination), which is not on this map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Research to Programs for Trachoma Elimination: Antibiotic Trial
Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 22 citations in OpenAlex.
- Antibiotics for trachoma.The Cochrane database of systematic reviews · 2019Pooled it
- Pooled it
- Forecasting the elimination of active trachoma: An empirical model.PLoS neglected tropical diseases · 2022Article
- Predicting future community-level ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data.PLoS neglected tropical diseases · 2022Article
- Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth until May 2020.BMC medical research methodology · 2020Article
- Assessing the performance of real-time epidemic forecasts: A case study of Ebola in the Western Area region of Sierra Leone, 2014-15.PLoS computational biology · 2019Article
- Models of Trachoma Transmission and Their Policy Implications: From Control to Elimination.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2018Review
- Targeted Treatment of Yaws With Household Contact Tracing: How Much Do We Miss?American journal of epidemiology · 2018Article
- Clinical signs of trachoma are prevalent among Solomon Islanders who have no persistent markers of prior infection withWellcome open research · 2018Article
- Probabilistic forecasts of trachoma transmission at the district level: A statistical model comparison.Epidemics · 2017Article
- Differential Effects of Azithromycin, Doxycycline, and Cotrimoxazole in Ingested Blood on the Vectorial Capacity of Malaria Mosquitoes.Open forum infectious diseases · 2016Article
- Short-term forecasting of the prevalence of clinical trachoma: utility of including delayed recovery and tests for infection.Parasites & vectors · 2015Article
- Correction: Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion, Statistical Regression, versus Transmission Models.PLoS neglected tropical diseases · 2015Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors at 8 institutions in 5 countries.
Funding
Abstract
backgroundTrachoma 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.
methodsThe 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.
findingsRegression 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.
interpretationRegression 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.
trial registrationClinicaltrials.gov NCT00792922.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.