ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2024
District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach.
Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- Dynamics of trachoma infection in West Africa revealed by a hidden state model.PLoS computational biology · 2026Article
- Regional Inequalities in Trachoma Prevention in Ethiopia: A Meta-Analysis.Health science reports · 2026Review
- Trachoma prevalence surveys in 15 indigenous and non-indigenous evaluation units in Brazil, 2018-2023.International health · 2026Observational
- Spread of the plague in Venice, 1630-1631: epidemic entropy in a "natural experiment".medRxiv : the preprint server for health sciences · 2025Article
- Trachoma.Lancet (London, England) · 2025Review
- Trachoma in Croatia: How Did it Become a Thing of the Past?Medical archives (Sarajevo, Bosnia and Herzegovina) · 2025Review
- New Tools and Nuanced Interventions to Accelerate Achievement of the 2030 Roadmap for Neglected Tropical Diseases.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
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Authors and funding
37 authors at 19 institutions in 18 countries.
Funding
Abstract
Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation-follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1-9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43-1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.
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Registered trials
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