Dataset Information

Syphilis prevalence trends in adult women in 132 countries - estimations using the Spectrum Sexually Transmitted Infections model.

ABSTRACT: We estimated national-level trends in the prevalence of probable active syphilis in adult women using the Spectrum Sexually Transmitted Infections (STI) model to inform program planning, target-setting, and progress evaluation in STI control. The model fitted smoothed-splines polynomial regressions to data from antenatal clinic surveys and screening and representative household surveys, adjusted for diagnostic test performance and weighted by national coverage. Eligible countries had ≥1 data point from 2010 or later and ≥3 from 2000 or later from adult populations considered representative of the general female population (pregnant women or community-based studies). Between 2012 and 2016, the prevalence of probable active syphilis in women decreased in 54 (41%) of 132 eligible countries; this decrease was substantive (≥10% proportionally, ≥0.10% percentage-point absolute difference and non-overlapping 95% confidence intervals in 2012 and 2016) in 5 countries. Restricting eligible data to prevalence measurements of dual treponemal and non-treponemal testing limited estimates to 85 countries; of these, 45 countries (53%) showed a decrease. These standardized trend estimates highlight the need for increased investment in national syphilis surveillance and control efforts if the World Health Organization target of a 90% reduction in the incidence of syphilis between 2018 and 2030 is to be met.

SUBMITTER: Korenromp EL

PROVIDER: S-EPMC6068092 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Syphilis prevalence trends in adult women in 132 countries - estimations using the Spectrum Sexually Transmitted Infections model.

Korenromp Eline L EL Mahiané S Guy SG Nagelkerke Nico N Taylor Melanie M MM Williams Rebecca R Chico R Matthew RM Pretorius Carel C Abu-Raddad Laith J LJ Rowley Jane J

Scientific reports 20180731 1

We estimated national-level trends in the prevalence of probable active syphilis in adult women using the Spectrum Sexually Transmitted Infections (STI) model to inform program planning, target-setting, and progress evaluation in STI control. The model fitted smoothed-splines polynomial regressions to data from antenatal clinic surveys and screening and representative household surveys, adjusted for diagnostic test performance and weighted by national coverage. Eligible countries had ≥1 data poi ...[more]

PMID: 30065272

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Project description:IntroductionSexually Transmitted Infections (STIs) have always represented a public health concern in the military, yet most studies rely on self-reports among non-random samples of military populations. In addition, most of the studies exploring STI rates among the military focus on US service members. This paper assesses the prevalence and correlates of STIs in the French military using biomarkers and compares self-reported versus diagnosed STIs.MethodsData are drawn from the COSEMIL study, a national sexual health survey conducted in the French military in 2014 and 2015. A random sample of 784 men and 141 women aged 18-57 years completed a self-administered questionnaire and provided biological samples for STI testing. We used logistic regression modeling to identify the correlates of STI diagnosis and self-reports.ResultsThe prevalence of diagnosed STIs was 4.7% [3.8-5.9], mostly due to Chlamydia trachomatis. This rate was four times higher than the 12 months self-reported rate of 1.1% [0.6-2.3]. Reported STI rates were similar among men and women (1.1% versus 1.8%), but diagnosed STI rates were twice as high among females versus males (10.4% versus 4.1%, p = 0.007). There were significant differences in the determinants of reported versus diagnosed STIs. In particular, age and sexual orientation were associated with reported STIs, but not with diagnosed STIs. Conversely, STI counseling and depression were associated with STI diagnosis but not with STI reports.ConclusionThis study underlines the need to use biomarkers in population-based surveys, given the differential and substantial underreporting of STIs. Results also highlight the need for programmatic adaptation to address gender inequalities in STI rates, by developing women's health services in the French military. Addressing such needs not only benefits women but could also serve as a strategy to reduce overall STI rates as most military women have military partners, increasing the risk of internal transmission.

Project description:BackgroundSexually transmitted infections (STIs) pose a significant public health challenge in the United States. Traditional surveillance systems are adversely affected by data quality issues, underreporting of cases, and reporting delays, resulting in missed prevention opportunities to respond to trends in disease prevalence. Search engine data can potentially facilitate an efficient and economical enhancement to surveillance reporting systems established for STIs.ObjectiveWe aimed to develop and train a predictive model using reported STI case data from Chicago, Illinois, and to investigate the model's predictive capacity, timeliness, and ability to target interventions to subpopulations using Google Trends data.MethodsDeidentified STI case data for chlamydia, gonorrhea, and primary and secondary syphilis from 2011-2017 were obtained from the Chicago Department of Public Health. The data set included race/ethnicity, age, and birth sex. Google Correlate was used to identify the top 100 correlated search terms with "STD symptoms," and an autocrawler was established using Google Health Application Programming Interface to collect the search volume for each term. Elastic net regression was used to evaluate prediction accuracy, and cross-correlation analysis was used to identify timeliness of prediction. Subgroup elastic net regression analysis was performed for race, sex, and age.ResultsFor gonorrhea and chlamydia, actual and predicted STI values correlated moderately in 2011 (chlamydia: r=0.65; gonorrhea: r=0.72) but correlated highly (chlamydia: r=0.90; gonorrhea: r=0.94) from 2012 to 2017. However, for primary and secondary syphilis, the high correlation was observed only for 2012 (r=0.79), 2013 (r=0.77), 2016 (0.80), and 2017 (r=0.84), with 2011, 2014, and 2015 showing moderate correlations (r=0.55-0.70). Model performance was the most accurate (highest correlation and lowest mean absolute error) for gonorrhea. Subgroup analyses improved model fit across disease and year. Regression models using search terms selected from the cross-correlation analysis improved the prediction accuracy and timeliness across diseases and years.ConclusionsIntegrating nowcasting with Google Trends in surveillance activities can potentially enhance the prediction and timeliness of outbreak detection and response as well as target interventions to subpopulations. Future studies should prospectively examine the utility of Google Trends applied to STI surveillance and response.

Dataset Information

Syphilis prevalence trends in adult women in 132 countries - estimations using the Spectrum Sexually Transmitted Infections model.

Publications

Syphilis prevalence trends in adult women in 132 countries - estimations using the Spectrum Sexually Transmitted Infections model.

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