ArticlePloS one2022
Mapping local hot spots with routine tuberculosis data: A pragmatic approach to identify spatial variability.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review.BMC public health · 2023Pooled it
- Multilevel determinants of knowledge on TB transmission among women of reproductive age.IJTLD open · 2026Article
- Spatio-temporal trends, distribution and prediction of tuberculosis incidence in Uganda (2020-2025).BMC infectious diseases · 2025Article
- Adaptive bandit algorithms increase efficiency of mobile tuberculosis screening programs.Scientific reports · 2025Article
- Geographical location and genotyping analysis of pulmonary tuberculosis in the state of Nuevo Leon, Mexico.Scientific reports · 2025Article
- Surveillance of tuberculosis incidence and mortality through spatio-temporal analysis in Oyo State, Nigeria.PloS one · 2025Article
- Integrating geographic information systems into veterinary education within the one health framework: an interdisciplinary approach.Frontiers in veterinary science · 2025Article
- Effectiveness of Using AI-Driven Hotspot Mapping for Active Case Finding of Tuberculosis in Southwestern Nigeria.Tropical medicine and infectious disease · 2024Article
- Spatial Distribution of Drug-ResistantPathogens (Basel, Switzerland) · 2023Article
- Precision geospatial targeting for cost-effective tuberculosis case finding in Eastern Uganda: a quasi-experimental study.Therapeutic advances in infectious diseaseArticle
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Authors and funding
11 authors.
Funding
Abstract
objectiveTo use routinely collected data, with the addition of geographic information and census data, to identify local hot spots of rates of reported tuberculosis cases.
designResidential locations of tuberculosis cases identified from eight public health facilities in Lima, Peru (2013-2018) were linked to census data to calculate neighborhood-level annual case rates. Heat maps of tuberculosis case rates by neighborhood were created. Local indicators of spatial autocorrelation, Moran's I, were used to identify where in the study area spatial clusters and outliers of tuberculosis case rates were occurring. Age- and sex-stratified case rates were also assessed.
resultsWe identified reports of 1,295 TB cases across 74 neighborhoods during the five-year study period, for an average annual rate of 124.2 reported TB cases per 100,000 population. In evaluating case rates by individual neighborhood, we identified a median rate of reported cases of 123.6 and a range from 0 to 800 cases per 100,000 population. Individuals aged 15-44 years old and men had higher case rates than other age groups and women. Locations of both hot and cold spots overlapped across age- and gender-specific maps.
conclusionsThere is significant geographic heterogeneity in rates of reported TB cases and evident hot and cold spots within the study area. Characterization of the spatial distribution of these rates and local hot spots may be one practical tool to inform the work of local coalitions to target TB interventions in their zones.
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