生物科学和医学领域的科学家，英语和简体中文都是你的专长。将以下段落准确地翻译成简体中文，符合学术论文的语言表达规范，并保持原句的结构。 宫颈癌（CC）在全球女性中的发病率和死亡率上排名第四。人类乳头瘤病毒（HPV）疫苗接种和筛查计划可以显著降低宫颈癌的死亡率。因此，执行成本效益高的公共卫生政策以预防和监测宫颈癌至关重要。然而，制定能最大程度利用现有资源的政策并不容易，因为它需要对不断变化的人口做出长期成本和效果的预测。预测公共卫生政策的结果这一较为简单的任务也很困难，因此，为决策者设计出最佳利用现有资源的政策是一个艰巨的挑战。 本文提出了一种基于微分方程的细粒度流行病学模拟模型，可以有效预测包括疫苗接种和筛查在内的宫颈癌公共卫生政策的成本和效果。该模型表示人群动态、人群内HPV传播、感染清除的可能性、病毒引起的癌前病变和最终导致宫颈癌的情况，以及接种疫苗和筛查早期发现的免疫力。 我们提供了一种将人口、流行病和干预措施关注点分离的分类建模方法。我们使用哥伦比亚的案例研究实际数据来实例化模型，并分析其结果，展示了我们的建模方法如何支持CEA研究。此外，我们在一个开源软件工具中实现了模型，可以同时定义和评估多个政策。借助该工具的支持，我们在30年的时间范围内分析了54个政策，并以最近使用的宫颈癌政策作为比较对象。我们确定了8个主导政策，最佳政策的ICER为630万哥伦比亚比索（COP）每年挽救一个DALY。我们还根据可用的人口和HPV流行数据对该建模方法进行了验证。通过单向敏感性分析评估了关键参数值（贴现率、筛查测试的敏感性）的不确定性对结果的影响。 我们的建模方法可以为医疗决策者提供有价值的支持。将其实施为自动化工具可根据特定国家的数据进行分析定制，灵活定义待评估的公共卫生政策，并进行成本和效果的细粒度分析。 © 2023.作者。

Cervical cancer (CC) is globally ranked fourth in terms of incidence and mortality among women. Vaccination against Human Papillomavirus (HPV) and screening programs can significantly reduce CC mortality rates. Hence, executing cost-effective public health policies for prevention and surveillance is crucial. However, defining policies that make the best use of the available resources is not easy, as it requires predicting the long-term costs and results of interventions on a changing population. Since the simpler task of predicting the results of public health policies is difficult, devising those that make the best usage of available resources is an arduous challenge for decision-makers.This paper proposes a fine-grained epidemiological simulation model based on differential equations, to effectively predict the costs and effectiveness of CC public health policies that include vaccination and screening. The model represents population dynamics, HPV transmission within the population, likelihood of infection clearance, virus-induced appearance of precancerous lesions and eventually CC, as well as immunity gained with vaccination and early detection with screening.We offer a compartmentalized modeling approach that separates population, epidemics, and intervention concerns. We instantiate models with actual data from a Colombian case study and analyze their results to show how our modeling approach can support CEA studies. Moreover, we implement models in an open-source software tool to simultaneously define and evaluate multiple policies. With the support of the tool, we analyze 54 policies within a 30-year time horizon and use as a comparator the CC policy that has been used until recently. We identify 8 dominant policies, the best one with an ICER of 6.3 million COP (Colombian Pesos) per averted DALY. We also validate the modeling approach against the available population and HPV epidemic data. The effects of uncertainty in the values of key parameters (discount rate, sensitivity of screening tests) is evaluated through one-way sensitivity analysis.Our modeling approach can provide valuable support for healthcare decision-makers. The implementation into an automated tool allows customizing the analysis with country-specific data, flexibly defining public health policies to be evaluated, and conducting disaggregate analyses of their cost and effectiveness.© 2023. The Author(s).