ArticleBMJ open2020
Mapping tuberculosis prevalence in Ethiopia: protocol for a geospatial meta-analysis.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medicinal Plants Used for Combating Human Bacterial Diseases in Ethiopia: A Systematic Review.TheScientificWorldJournal · 2026Pooled it
- Quantifying undetected tuberculosis in Ethiopia using a novel geospatial modelling approach.Scientific reports · 2025Article
- Mapping the prevalence of soil-transmitted helminth infections in the Western Pacific Region: a spatial modelling study.The Lancet regional health. Western Pacific · 2025Article
- Mapping tuberculosis prevalence in Africa using a Bayesian geospatial analysis.Communications medicine · 2025Article
- A Meta-Analysis of the Global Prevalence of Temporomandibular Disorders.Journal of clinical medicine · 2024Review
- Protocol for spatial prediction of soil transmitted helminth prevalence in the Western Pacific region using a meta-analytical approach.Systematic reviews · 2024Article
- Spatio-Temporal Pattern of Tuberculosis Distribution in Romania and Particulate Matter Pollution Associated With Risk of Infection.GeoHealth · 2024Article
- Trends of Mycobacterium tuberculosis and rifampicin resistance at the Ho Teaching Hospital in Ghana.PloS one · 2024Article
- Geospatial Overlap of Undernutrition and Tuberculosis in Ethiopia.International journal of environmental research and public health · 2023Article
- Health system delay and its associated factors among tuberculosis patients in Gamo Zone public health facilities, Southern Ethiopia: An institution-based cross-sectional study.Journal of clinical tuberculosis and other mycobacterial diseases · 2022Article
- Finding gaps in routine TB surveillance activities in Bangladesh.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022Article
- Spatial codistribution of HIV, tuberculosis and malaria in Ethiopia.BMJ global health · 2022Article
- Spatial clustering and genetic diversity of Mycobacterium tuberculosis isolate among pulmonary tuberculosis suspected patients, Arsi Zone, Ethiopia.BMC pulmonary medicine · 2021Article
- Spatiotemporal Patterns of Tuberculosis in Hunan Province, China.International journal of environmental research and public health · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionTuberculosis (TB), a major public health concern in Ethiopia, is distributed heterogeneously across the country. Mapping TB prevalence at national and subnational levels can provide information for designing and implementing control strategies. Data for spatial analysis can be obtained through systematic review of the literature, and spatial prediction can be done by meta-analysis of published data (geospatial meta-analysis). Geospatial meta-analysis can increase the power of spatial analytic models by making use of all available data. It can also provide a means for spatial prediction where new survey data in a given area are sparse or not available. In this report, we present a protocol for a geospatial meta-analysis to investigate the spatial patterns of TB prevalence in Ethiopia. METHODS AND ANALYSIS: To conduct this study, a national TB prevalence survey, supplemented with data from a systematic review of published reports, will be used as the source of TB prevalence data. Systematic searching will be conducted in PubMed, Scopus and Web of Science for studies published up to 15 April 2020 to identify all potential publications reporting TB prevalence in Ethiopia. Data for covariates for multivariable analysis will be obtained from different, readily available sources. Extracted TB survey and covariate data will be georeferenced to specific locations or the centroids of small administrative areas. A binomial logistic regression model will be fitted to TB prevalence data using both fixed covariate effects and random geostatistical effects based on the approach of model-based geostatistics. Markov Chain Monte Carlo simulation will be conducted to obtained posterior parameter estimations, including spatially predicted prevalence. ETHICS AND DISSEMINATION: Ethical approval will not be required for this study as it will be based on deidentified, aggregate published data. The final report of this review will be disseminated through publication in a peer-reviewed scientific journal and will also be presented at relevant conferences.
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