From the *Division of Health Policy and Management, University of Minnesota School of Public Health; †J. Kahn and Associates, LLC; ‡Healthy Youth Development - Prevention Research Center, Division of General Pediatrics and Adolescent Health, Department of Pediatrics, University of Minnesota Medical School; and §Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN.
Sex Transm Dis. 2017 Oct;44(10):619-626. doi: 10.1097/OLQ.0000000000000653.
Mathematical models are important tools for assessing prevention and management strategies for sexually transmitted infections. These models are usually developed for a single infection and require calibration to observed epidemiological trends in the infection of interest. Incorporating other outcomes of sexual behavior into the model, such as pregnancy, may better inform the calibration process.
We developed a mathematical model of chlamydia transmission and pregnancy in Minnesota adolescents aged 15 to 19 years. We calibrated the model to statewide rates of reported chlamydia cases alone (chlamydia calibration) and in combination with pregnancy rates (dual calibration). We evaluated the impact of calibrating to different outcomes of sexual behavior on estimated input parameter values, predicted epidemiological outcomes, and predicted impact of chlamydia prevention interventions.
The two calibration scenarios produced different estimates of the probability of condom use, the probability of chlamydia transmission per sex act, the proportion of asymptomatic infections, and the screening rate among men. These differences resulted in the dual calibration scenario predicting lower prevalence and incidence of chlamydia compared with calibrating to chlamydia cases alone. When evaluating the impact of a 10% increase in condom use, the dual calibration scenario predicted fewer infections averted over 5 years compared with chlamydia calibration alone [111 (6.8%) vs 158 (8.5%)].
While pregnancy and chlamydia in adolescents are often considered separately, both are outcomes of unprotected sexual activity. Incorporating both as calibration targets in a model of chlamydia transmission resulted in different parameter estimates, potentially impacting the intervention effectiveness predicted by the model.
数学模型是评估性传播感染预防和管理策略的重要工具。这些模型通常是为单一感染而开发的，需要根据所关注感染的观察到的流行病学趋势进行校准。将性行为的其他结果（如怀孕）纳入模型中，可以更好地为校准过程提供信息。
我们开发了一个在明尼苏达州 15 至 19 岁青少年中传播和怀孕的衣原体数学模型。我们仅对全州报告的衣原体病例（衣原体校准）和与怀孕率结合进行了模型校准（双重校准）。我们评估了针对不同性行为结果进行校准对估计输入参数值、预测流行病学结果和预测衣原体预防干预效果的影响。
两种校准方案产生了不同的估计值，包括性行为时使用安全套的概率、每次性行为传播衣原体的概率、无症状感染的比例和男性的筛查率。这些差异导致双重校准方案预测的衣原体患病率和发病率低于仅针对衣原体病例进行校准的情况。当评估 10%的安全套使用率增加的影响时，双重校准方案预测在 5 年内可避免的感染人数少于仅针对衣原体进行校准的情况[111（6.8%）与 158（8.5%）]。
尽管青少年中的怀孕和衣原体通常被视为单独的问题，但它们都是无保护性行为的结果。将两者都作为衣原体传播模型的校准目标纳入其中，会导致不同的参数估计，从而可能影响模型预测的干预效果。
