Determinants of Chlamydia, Gonorrhea, and Coinfection in Heterosexual Adolescents Attending the National Public Sexually Transmitted Infection Clinic in Singapore.

BACKGROUND: Amidst recent trends in rising rates of chlamydia and gonorrhea among Singaporean adolescents, there are limited data on risk factors associated with these infections that may inform prevention strategies in this population. METHODS: A cross-sectional study of chlamydia and gonorrhea positivity was conducted among 1458 sexually active heterosexual adolescents between 14 and 19 years old attending the national public sexually transmitted infection clinic from 2006 to 2013. The association with demographic and behavioral characteristics was assessed by crude prevalence ratio, and negative binomial regression modeling was used to obtain adjusted prevalence ratios (aPRs). RESULTS: Chlamydia positivity was found in 23.6% of males and 36.6% of females, gonorrhea positivity in 33.1% of males and 15.9% of adolescent girl, and coinfection positivity in 10.2% of males and 10.1% of females. In multivariable analysis, chlamydia was positively associated with being Malay (aPR, 1.6; 95% confidence interval [CI], 1.1-2.1) and inconsistent condom use for vaginal sex (aPR, 6.5; 95% CI = 2.4-17.4) in males and with being Malay (aPR, 1.9; 95% CI = 1.5-2.4), inconsistent condom use for vaginal sex (aPR, 2.0; 95% CI = 1.1-3.9), and number of lifetime partners in females (aPR, 1.1; 95% CI = 1.0-1.1). Gonorrhea was positively associated with being Malay (aPR, 3.2; 95% CI = 2.4-4.4), inconsistent condom use for vaginal sex (aPR, 5.4; 95% CI = 2.1-14.4), and number of lifetime partners (aPR, 1.1; 95% CI = 1.0-1.1) in males and with being Malay (aPR, 3.7; 95% CI = 2.4-5.7) in females. Malays had a higher proportion of sexual risk behaviors compared with the non-Malays. CONCLUSIONS: Ethnicity and high-risk sexual behaviors are important determinants of chlamydia, gonorrhea, and coinfection for adolescents attending this clinic. Targeted interventions are needed to lower the prevalence of high-risk sexual behaviors for the Malay adolescents in this clinic.

Testing a multi-malaria-model ensemble against 30 years of data in the Kenyan highlands.

BACKGROUND: Multi-model ensembles could overcome challenges resulting from uncertainties in models' initial conditions, parameterization and structural imperfections. They could also quantify in a probabilistic way uncertainties in future climatic conditions and their impacts. METHODS: A four-malaria-model ensemble was implemented to assess the impact of long-term changes in climatic conditions on Plasmodium falciparum malaria morbidity observed in Kericho, in the highlands of Western Kenya, over the period 1979-2009. Input data included quality controlled temperature and rainfall records gathered at a nearby weather station over the historical periods 1979-2009 and 1980-2009, respectively. Simulations included models' sensitivities to changes in sets of parameters and analysis of non-linear changes in the mean duration of host's infectivity to vectors due to increased resistance to anti-malarial drugs. RESULTS: The ensemble explained from 32 to 38% of the variance of the observed P. falciparum malaria incidence. Obtained R²-values were above the results achieved with individual model simulation outputs. Up to 18.6% of the variance of malaria incidence could be attributed to the +0.19 to +0.25°C per decade significant long-term linear trend in near-surface air temperatures. On top of this 18.6%, at least 6% of the variance of malaria incidence could be related to the increased resistance to anti-malarial drugs. Ensemble simulations also suggest that climatic conditions have likely been less favourable to malaria transmission in Kericho in recent years. CONCLUSIONS: Long-term changes in climatic conditions and non-linear changes in the mean duration of host's infectivity are synergistically driving the increasing incidence of P. falciparum malaria in the Kenyan highlands. User-friendly, online-downloadable, open source mathematical tools, such as the one presented here, could improve decision-making processes of local and regional health authorities.