ArticleSexually transmitted diseases2016
Influence of Detection Method and Study Area Scale on Syphilis Cluster Identification in North Carolina.
Article in Sexually transmitted diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Distribution of reported syphilis cases in South China: spatiotemporal analysis.Scientific reports · 2018Trial
- Spatiotemporal distribution of syphilis in Mainland China during the 17 years from 2004 to 2020.BMC public health · 2026Article
- Enhancing insights in sexually transmitted infection mapping: Syphilis in Forsyth County, North Carolina, a case study.PLoS computational biology · 2024Article
- CONGENITAL SYPHILIS IN THE PARAÍBA VALLEY USING A SPATIAL APPROACH.Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo · 2020Article
- Syphilis in pregnant women and congenital syphilis: spatial pattern and relationship with social determinants of health in Mato Grosso.Revista da Sociedade Brasileira de Medicina Tropical · 2020Article
- Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings.International journal of health geographics · 2018Article
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Authors and funding
8 authors.
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Abstract
backgroundIdentifying geographical clusters of sexually transmitted infections can aid in targeting prevention and control efforts. However, detectable clusters can vary between detection methods because of different underlying assumptions. Furthermore, because disease burden is not geographically homogenous, the reference population is sensitive to the study area scale, affecting cluster outcomes. We investigated the influence of cluster detection method and geographical scale on syphilis cluster detection in Mecklenburg County, North Carolina.
methodsWe analyzed primary and secondary syphilis cases reported in North Carolina (2003-2010). Primary and secondary syphilis incidence rates were estimated using census tract-level population estimates. We used 2 cluster detection methods: local Moran's I using an areal adjacency matrix and Kulldorff's spatial scan statistic using a variable size moving circular window. We evaluated 3 study area scales: North Carolina, Piedmont region, and Mecklenburg County. We focused our investigation on Mecklenburg, an urban county with historically high syphilis rates.
resultsSyphilis clusters detected using local Moran's I and Kulldorff's scan statistic overlapped but varied in size and composition. Because we reduced the scale to a high-incidence urban area, the reference syphilis rate increased, leading to the identification of smaller clusters with higher incidence. Cluster demographic characteristics differed when the study area was reduced to a high-incidence urban county.
conclusionsOur results underscore the importance of selecting the correct scale for analysis to more precisely identify areas with high disease burden. A more complete understanding of high-burden cluster location can inform resource allocation for geographically targeted sexually transmitted infection interventions.
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