人类免疫缺陷病毒 (HIV) 感染者患人乳头瘤病毒 (HPV) 相关癌症的负担要高得多。因果因素包括行为因素和生物因素。虽然药物和护理支持干预措施有助于解决合并感染的生物风险，但由于社会条件是行为的常见驱动因素，结构干预措施是行为干预的关键部分。我们的目标是开发一个联合 HIV-HPV 模型来评估每个因素的贡献，为随后的干预分析提供信息。虽然区室模型足以用于较快传播的 HPV，但网络模型适用于较慢传播的 HIV。然而，考虑到不同亚人群的疾病流行病学和疾病负担差异巨大，使用网络模型对 HIV 和 HPV 进行联合建模可能会产生计算复杂性。我们应用了最近开发的基于混合代理的隔室（MAC）模拟技术，该技术模拟至少患有一种传播较慢的疾病的人及其作为网络中的代理的直接接触者，以及在隔室模型中模拟所有其他人，包括患有传播较快的疾病的人，通过不断发展的接触网络算法维持两个模型之间的动态。我们模拟了美国异性恋女性、异性恋男性和男男性行为者（仅男性和男性和女性）(MSM) 中的 HIV 和 HPV，这些混合但具有不同 HIV 负担的亚人群以及女性中的宫颈癌。我们进行了数值分析，以评估行为和生物学因素对感染艾滋病毒的女性患宫颈癌风险的影响。 HIV、HPV 和宫颈癌的模型输出与监测估计值相比较。与未感染艾滋病毒的女性相比，感染艾滋病毒的女性中 HPV 相对患病率（1.67 倍）和宫颈癌相对发病率（3.​​6 倍）的模型估计值也与文献中观察性研究报告的结果相似。 HPV 患病率增加归因于生物因素的比例为 22-38%，宫颈癌发病率增加归因于生物因素的比例为 80%，其余归因于行为。行为和生物因素导致 HPV 患病率和宫颈癌发病率增加，这表明需要采取行为、结构和药物干预措施。与个体和关节疾病指标相关的模型结果的有效性可作为 MAC 模拟技术的概念验证。了解行为和生物风险因素的贡献有助于为干预措施提供信息。未来的工作可以扩展该模型，以模拟性行为和护理行为作为社会条件的函数，以共同评估艾滋病毒和宫颈癌预防的行为、结构和药物干预措施。版权所有：© 2023 Zhu，Gopalappa。这是一篇根据知识共享署名许可条款分发的开放获取文章，允许在任何媒体上不受限制地使用、分发和复制，前提是注明原始作者和来源。

Persons living with human immunodeficiency virus (HIV) have a disproportionately higher burden of human papillomavirus infection (HPV)-related cancers. Causal factors include both behavioral and biological. While pharmaceutical and care support interventions help address biological risk of coinfection, as social conditions are common drivers of behaviors, structural interventions are key part of behavioral interventions. Our objective is to develop a joint HIV-HPV model to evaluate the contribution of each factor, to subsequently inform intervention analyses. While compartmental modeling is sufficient for faster spreading HPV, network modeling is suitable for slower spreading HIV. However, using network modeling for jointly modeling HIV and HPV can generate computational complexities given their vastly varying disease epidemiology and disease burden across sub-population groups. We applied a recently developed mixed agent-based compartmental (MAC) simulation technique, which simulates persons with at least one slower spreading disease and their immediate contacts as agents in a network, and all other persons including those with faster spreading diseases in a compartmental model, with an evolving contact network algorithm maintaining the dynamics between the two models. We simulated HIV and HPV in the U.S. among heterosexual female, heterosexual male, and men who have sex with men (men only and men and women) (MSM), sub-populations that mix but have varying HIV burden, and cervical cancer among women. We conducted numerical analyses to evaluate the contribution of behavioral and biological factors to risk of cervical cancer among women with HIV. The model outputs for HIV, HPV, and cervical cancer compared well with surveillance estimates. Model estimates for relative prevalence of HPV (1.67 times) and relative incidence of cervical cancer (3.6 times), among women with HIV compared to women without, were also similar to that reported in observational studies in the literature. The fraction attributed to biological factors ranged from 22-38% for increased HPV prevalence and 80% for increased cervical cancer incidence, the remaining attributed to behavioral. The attribution of both behavioral and biological factors to increased HPV prevalence and cervical cancer incidence suggest the need for behavioral, structural, and pharmaceutical interventions. Validity of model results related to both individual and joint disease metrics serves as proof-of-concept of the MAC simulation technique. Understanding the contribution of behavioral and biological factors of risk helps inform interventions. Future work can expand the model to simulate sexual and care behaviors as functions of social conditions to jointly evaluate behavioral, structural, and pharmaceutical interventions for HIV and cervical cancer prevention.Copyright: © 2023 Zhao, Gopalappa. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.