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Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China
BACKGROUND: Urogenital Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection (STI) globally. Reviews suggest high and persistently endemic STI epidemics in low and middle income countries. However population-based prevalence estimates in these settings are less common,...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315467/ https://www.ncbi.nlm.nih.gov/pubmed/34327356 http://dx.doi.org/10.1016/j.lanwpc.2021.100143 |
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author | Smith, M. Kumi Searle, Kelly M. Yang, Wenyue Rapheal, Erica Wang, Cheng Zhao, Peizhen Yang, Ligang Huang, Shujie Yang, Bin |
author_facet | Smith, M. Kumi Searle, Kelly M. Yang, Wenyue Rapheal, Erica Wang, Cheng Zhao, Peizhen Yang, Ligang Huang, Shujie Yang, Bin |
author_sort | Smith, M. Kumi |
collection | PubMed |
description | BACKGROUND: Urogenital Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection (STI) globally. Reviews suggest high and persistently endemic STI epidemics in low and middle income countries. However population-based prevalence estimates in these settings are less common, underscoring the need for analyses of available data to characterize patterns of disease burden. We identified spatio-temporal clusters and key behavioral, social, or environmental factors contribution to transmission in order to inform the prioritization and targeting of evidence based interventions. METHODS: Using 11 years of data (2006–2016) from the chlamydia case report system of Guangdong, China, we identified county level spatio-temporal hot and cold spots using the Getis-Ord Gi* statistic and discrete Poisson models in SaTScan 9.6. We also estimated associations between observed distribution patterns and area-level demographic, social, and economic factors using quasi-Poisson regression models that controlled for annual counts of certified laboratories to account for fluctuations in location-specific detection capacity. FINDINGS: Cluster analysis indicates an expanding chlamydia epidemic in Guangdong, with cases clustered in regions of greatest economic activity. Greater male-to-female sex ratio (RR, 3.63; 95% CI, 1.41–9.45) and greater urbanicity (RR, 2.44; 95% CI, 1.98–2.99) were predictive of higher chlamydia case occurrence. INTERPRETATION: We found that chlamydia case occurrence in Guangdong province has been accelerating over the past 11 years and that its expansion is tied to indicators of social and economic development. These estimates not only identify high prevalence regions to target but also areas where data gaps potentially remain. The salience of sex ratios and urbanicity may best be understood through the lens of China's modern history of labor migration which has reshaped the gender dynamics and health access landscape of urban China. Future chlamydia control efforts will require a population-based approach focused on reengaging sexually active adults of diverse economic and migratory backgrounds. FUNDING: This was an unfunded study using routinely collected public health data. |
format | Online Article Text |
id | pubmed-8315467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83154672021-07-28 Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China Smith, M. Kumi Searle, Kelly M. Yang, Wenyue Rapheal, Erica Wang, Cheng Zhao, Peizhen Yang, Ligang Huang, Shujie Yang, Bin Lancet Reg Health West Pac Research Paper BACKGROUND: Urogenital Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection (STI) globally. Reviews suggest high and persistently endemic STI epidemics in low and middle income countries. However population-based prevalence estimates in these settings are less common, underscoring the need for analyses of available data to characterize patterns of disease burden. We identified spatio-temporal clusters and key behavioral, social, or environmental factors contribution to transmission in order to inform the prioritization and targeting of evidence based interventions. METHODS: Using 11 years of data (2006–2016) from the chlamydia case report system of Guangdong, China, we identified county level spatio-temporal hot and cold spots using the Getis-Ord Gi* statistic and discrete Poisson models in SaTScan 9.6. We also estimated associations between observed distribution patterns and area-level demographic, social, and economic factors using quasi-Poisson regression models that controlled for annual counts of certified laboratories to account for fluctuations in location-specific detection capacity. FINDINGS: Cluster analysis indicates an expanding chlamydia epidemic in Guangdong, with cases clustered in regions of greatest economic activity. Greater male-to-female sex ratio (RR, 3.63; 95% CI, 1.41–9.45) and greater urbanicity (RR, 2.44; 95% CI, 1.98–2.99) were predictive of higher chlamydia case occurrence. INTERPRETATION: We found that chlamydia case occurrence in Guangdong province has been accelerating over the past 11 years and that its expansion is tied to indicators of social and economic development. These estimates not only identify high prevalence regions to target but also areas where data gaps potentially remain. The salience of sex ratios and urbanicity may best be understood through the lens of China's modern history of labor migration which has reshaped the gender dynamics and health access landscape of urban China. Future chlamydia control efforts will require a population-based approach focused on reengaging sexually active adults of diverse economic and migratory backgrounds. FUNDING: This was an unfunded study using routinely collected public health data. Elsevier 2021-04-27 /pmc/articles/PMC8315467/ /pubmed/34327356 http://dx.doi.org/10.1016/j.lanwpc.2021.100143 Text en © 2021 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Smith, M. Kumi Searle, Kelly M. Yang, Wenyue Rapheal, Erica Wang, Cheng Zhao, Peizhen Yang, Ligang Huang, Shujie Yang, Bin Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title | Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title_full | Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title_fullStr | Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title_full_unstemmed | Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title_short | Spatiotemporal analysis of 11 years of Chlamydia trachomatis data from southern China |
title_sort | spatiotemporal analysis of 11 years of chlamydia trachomatis data from southern china |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8315467/ https://www.ncbi.nlm.nih.gov/pubmed/34327356 http://dx.doi.org/10.1016/j.lanwpc.2021.100143 |
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