间接传播在突发感染事件中作用的平均场分析
A mean field analysis of the role of indirect transmission in emergent infection events
AI总结：
本研究通过平均场房室模型，以疥癣病为例，发现仅通过污染物间接传播即可导致疾病出现并持续，定义了基于有效繁殖数的新阈值，为疾病干预评估提供了新视角。
摘要：
我们开发了一个数学模型，以疥癣病为例，研究间接传播在传染病传播中的作用。该疾病可通过感染宿主与易感宿主之间的直接接触传播，也可在潜在宿主遇到环境中沉积的感染性螨虫和幼虫（通常称为污染物）时间接传播。我们关注的是探索这些传染性储库作为突发感染事件触发因素和疾病稳定储库的潜力。为此，我们的平均场房室模型纳入了通过污染物间接传播驱动的流行病学动态。我们识别了系统可能进入的不同类型的动态，这些动态由直接和间接传播的不同水平控制。其中，我们发现了一种新的状态，即疾病可以仅通过污染物出现并持续存在，而无需直接传播。这种系统可能性揭示了一条进化途径，可使寄生虫在宿主共同进化之外增强其适应性。我们还基于有效繁殖数定义了一个新的阈值，使我们能够预测疾病持续存在的条件。我们的模型通过纳入真实系统中观察到的特征，使我们能够评估各种疾病干预措施的有效性。我们希望这有助于更好地理解传染病爆发。
英文摘要：
We developed a mathematical model to investigate the role of indirect transmission in the spread of infectious diseases, using the illustrative example of sarcoptic mange as a case study. This disease can be transmitted through direct contact between an infected host and a susceptible one, or indirectly when potential hosts encounter infectious mites and larvae deposited in the environment, commonly referred to as fomites. Our focus is on exploring the potential of these infectious reservoirs as triggers for emerging infection events and as stable reservoirs of the disease. To achieve this, our mean field compartmental model incorporates the epidemiological dynamics driven by indirect transmission via fomites. We identify different types of dynamics that the system can go into, controlled by different levels of direct and indirect transmission. Among these, we find a new regime where the disease can emerge and persist over time solely through fomites, without the necessity for direct transmission. This possibility of the system reveals an evolutionary pathway that could enable the parasite to enhance its fitness beyond host co-evolution. We also define a new threshold based on an effective reproductive number, that enables us to predict the conditions for disease persistence. Our model allows us to assess the potential effectiveness of various disease intervention measures by incorporating a feature observed in real systems. We hope this contributes to a better understanding of infectious disease outbreaks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
