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The impact of HIV infection and socioeconomic factors on the incidence of gonorrhea: A county-level, US-wide analysis

BACKGROUND: Gonorrhea is the second most commonly reported identifiable disease in the United States (U.S.). Importantly, more than 25% of gonorrheal infections demonstrate antibiotic resistance, leading the Centers for Disease Control and Prevention (CDC) to classify gonorrhea as an “urgent threat”...

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Detalles Bibliográficos
Autores principales: Andreatos, Nikolaos, Grigoras, Christos, Shehadeh, Fadi, Pliakos, Elina Eleftheria, Stoukides, Georgianna, Port, Jenna, Flokas, Myrto Eleni, Mylonakis, Eleftherios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580927/
https://www.ncbi.nlm.nih.gov/pubmed/28863154
http://dx.doi.org/10.1371/journal.pone.0183938
Descripción
Sumario:BACKGROUND: Gonorrhea is the second most commonly reported identifiable disease in the United States (U.S.). Importantly, more than 25% of gonorrheal infections demonstrate antibiotic resistance, leading the Centers for Disease Control and Prevention (CDC) to classify gonorrhea as an “urgent threat”. METHODS: We examined the association of gonorrhea infection rates with the incidence of HIV and socioeconomic factors. A county-level multivariable model was then constructed. RESULTS: Multivariable analysis demonstrated that HIV incidence [Coefficient (Coeff): 1.26, 95% Confidence Interval (CI): 0.86, 1.66, P<0.001] exhibited the most powerful independent association with the incidence of gonorrhea and predicted 40% of the observed variation in gonorrhea infection rates. Sociodemographic factors like county urban ranking (Coeff: 0.12, 95% CI: 0.03, 0.20, P = 0.005), percentage of women (Coeff: 0.41, 95% CI: 0.28, 0.53, P<0.001) and percentage of individuals under the poverty line (Coeff: 0.45, 95% CI: 0.32, 0.57, P<0.001) exerted a secondary impact. A regression model that incorporated these variables predicted 56% of the observed variation in gonorrhea incidence (Pmodel<0.001, R(2) model = 0.56). CONCLUSIONS: Gonorrhea and HIV infection exhibited a powerful correlation thus emphasizing the benefits of comprehensive screening for sexually transmitted infections (STIs) and the value of pre-exposure prophylaxis for HIV among patients visiting an STI clinic. Furthermore, sociodemographic factors also impacted gonorrhea incidence, thus suggesting another possible focus for public health initiatives.