Sexually transmitted infections · 2010
The distribution of chlamydia, gonorrhoea and syphilis cases across states and counties in the USA, 2007.
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Chesson Harrell W, Sternberg Maya, Leichliter Jami S, Aral Sevgi O
Аннотация
OBJECTIVES: To examine the distribution of chlamydia, gonorrhoea and syphilis in the USA through the use of Lorenz curves and Gini coefficients.
METHODS: The distribution of three sexually transmitted diseases (STD; chlamydia, gonorrhoea and primary and secondary syphilis) was examined across states and counties in the USA in 2007, based on reported case numbers. Gini coefficients, which can range from 0 (equality in STD rates across geographical units) to 1 (complete inequality such that all STD occur in one geographical unit) were calculated.
RESULTS: Overall, chlamydia was the most evenly distributed and syphilis was the most concentrated of the three STD examined. The Gini coefficients for chlamydia, gonorrhoea and syphilis were 0.121, 0.255 and 0.334, respectively, when examined across states, and 0.319, 0.494 and 0.630, respectively, when examined across counties. Differences in Gini coefficients were observed when the STD distributions were examined by sex, race/ethnicity and age group.
CONCLUSIONS: The use of Lorenz curves and Gini coefficients can help to assess inequalities in the distribution of STD, to gauge the suitability of geographically targeted interventions, and to help in determining the epidemic phase of STD. Having a better understanding of the disparities in the distribution of STD across states and counties by sex, race/ethnicity and age group might help in understanding why disparities in STD rates exist across different groups and in developing interventions to address these disparities.
METHODS: The distribution of three sexually transmitted diseases (STD; chlamydia, gonorrhoea and primary and secondary syphilis) was examined across states and counties in the USA in 2007, based on reported case numbers. Gini coefficients, which can range from 0 (equality in STD rates across geographical units) to 1 (complete inequality such that all STD occur in one geographical unit) were calculated.
RESULTS: Overall, chlamydia was the most evenly distributed and syphilis was the most concentrated of the three STD examined. The Gini coefficients for chlamydia, gonorrhoea and syphilis were 0.121, 0.255 and 0.334, respectively, when examined across states, and 0.319, 0.494 and 0.630, respectively, when examined across counties. Differences in Gini coefficients were observed when the STD distributions were examined by sex, race/ethnicity and age group.
CONCLUSIONS: The use of Lorenz curves and Gini coefficients can help to assess inequalities in the distribution of STD, to gauge the suitability of geographically targeted interventions, and to help in determining the epidemic phase of STD. Having a better understanding of the disparities in the distribution of STD across states and counties by sex, race/ethnicity and age group might help in understanding why disparities in STD rates exist across different groups and in developing interventions to address these disparities.