ArticleInternational journal of epidemiology2022
Model-based geostatistics enables more precise estimates of neglected tropical-disease prevalence in elimination settings: mapping trachoma prevalence in Ethiopia.
Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Scaling trachoma surveillance in endemic areas using machine learning.BMC infectious diseases · 2026Article
- Using Model-Based Geostatistics to Refine Population-Based Estimates of Trachoma Prevalence: Update from a Technical Consultation.The American journal of tropical medicine and hygiene · 2025Article
- Spatial-temporal risk of Opisthorchis felineus infection in Western Siberia and the Ural Region of Russian Federation: a joint Bayesian modelling study based on survey and surveillance data.Infectious diseases of poverty · 2025Article
- Characterizing trachoma elimination using serology.Nature communications · 2025Article
- Understanding the impact of covariates for trachoma prevalence prediction using geostatistical methods.BMC global and public health · 2025Article
- Assessing the prevalence of trachoma in the East, North, Far North and Adamaoua regions of Cameroon, 2016-2022.International health · 2025Article
- Using ESPEN data for evidence-based control of neglected tropical diseases in sub-Saharan Africa: A comprehensive model-based geostatistical analysis of soil-transmitted helminths.PLoS neglected tropical diseases · 2025Article
- Prevalence of Trachoma in Four Evaluation Units in Yemen after Implementation of Trachoma Elimination Measures.Ophthalmic epidemiology · 2024Article
- Challenges and motivating factors for integrating geostatistical models in targeted schistosomiasis control: A qualitative case study in Northwestern Tanzania.PLoS neglected tropical diseases · 2024Article
- Predicting the Environmental Suitability and Identifying Climate and Sociodemographic Correlates of Guinea Worm (Dracunculus medinensis) in Chad.The American journal of tropical medicine and hygiene · 2024Article
- District-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Article
- Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach.Scientific reports · 2024Article
- Spatial and network mapping of comorbidity with trachoma and visual-impairing NCDs in a pastoralist community in Kenya: implications for SDGs and UHC.International health · 2024Article
- Tropical Data: Approach and Methodology as Applied to Trachoma Prevalence Surveys.Ophthalmic epidemiology · 2023Article
- Trachoma: The Last Decade?Ophthalmic epidemiology · 2023Article
- Using model-based geostatistics for assessing the elimination of trachoma.PLoS neglected tropical diseases · 2023Article
- Monitoring transmission intensity of trachoma with serology.Nature communications · 2023Article
- Monitoring transmission intensity of trachoma with serology.medRxiv : the preprint server for health sciences · 2023Article
- Predicting future community-level ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data.PLoS neglected tropical diseases · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
Abstract
backgroundAs the prevalences of neglected tropical diseases reduce to low levels in some countries, policymakers require precise disease estimates to decide whether the set public health targets have been met. At low prevalence levels, traditional statistical methods produce imprecise estimates. More modern geospatial statistical methods can deliver the required level of precision for accurate decision-making.
methodsUsing spatially referenced data from 3567 cluster locations in Ethiopia in the years 2017, 2018 and 2019, we developed a geostatistical model to estimate the prevalence of trachomatous trichiasis and to calculate the probability that the trachomatous trichiasis component of the elimination of trachoma as a public health problem has already been achieved for each of 482 evaluation units. We also compared the precision of traditional and geostatistical approaches by the ratios of the lengths of their 95% predictive intervals.
resultsThe elimination threshold of trachomatous trichiasis (prevalence ≤ 0.2% in individuals aged ≥15 years) is met with a probability of 0.9 or more in 8 out of the 482 evaluation units assessed, and with a probability of ≤0.1 in 469 evaluation units. For the remaining five evaluation units, the probability of elimination is between 0.45 and 0.65. Prevalence estimates were, on average, 10 times more precise than estimates obtained using the traditional approach.
conclusionsBy accounting for and exploiting spatial correlation in the prevalence data, we achieved remarkably improved precision of prevalence estimates compared with the traditional approach. The geostatistical approach also delivers predictions for unsampled evaluation units that are geographically close to sampled evaluation units.
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