Grider John F, Udell Bradley J, Reichert Brian E, Foster Jeffrey T, Kendall William L, Cheng Tina L, Frick Winifred F
Colorado Cooperative Fish and Wildlife Research Unit, Colorado State University, 1484 Campus Delivery, Fort Collins, CO, 80523, USA.
Colorado Parks and Wildlife, Wildlife Health Program, 4330 Laporte Avenue, Fort Collins, CO, 80521, USA.
Sci Rep. 2025 Mar 19;15(1):9423. doi: 10.1038/s41598-025-93865-x.
The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as 'inconclusive' and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling for Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence of Pd at bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHM's results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHM's estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had been Pd positive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding of Pd dynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability.
使用定量实时聚合酶链反应（qPCR）监测病原体很常见；然而，缺乏考虑观察过程、病原体存在动态和病原体负荷的定量框架。这在疾病进展的早期阶段可能会出现问题，此时低水平检测可能被视为“不确定”并被排除在分析之外。或者，一个考虑到检测不完善的框架将提供更可靠的推断。为了更好地估计病原体动态，我们开发了一种分层多尺度动态占用障碍模型（MS-DOHM）。该模型使用了在对白鼻综合征病原体——毁灭柱孢（Pd）进行采样期间收集的数据，白鼻综合征是一种真菌疾病，已导致北美几种冬眠蝙蝠的数量严重下降。该模型使我们能够估计蝙蝠冬眠地Pd的初始占用率、定殖率、持续率和患病率。此外，利用循环阈值与病原体负荷之间的关系，我们估计了病原体的可检测性，并对预期的菌落和蝙蝠病原体负荷进行了建模。为了评估MS-DOHM估计病原体动态的能力，我们将MS-DOHM的结果与动态占用模型以及简单检测/未检测的结果进行了比较。MS-DOHM对地点水平病原体存在的估计比动态占用模型的估计高出11.9%，比简单占用估计高出35.7%。在我们的建模框架中纳入患病率和负荷后，病原体到达的估计分别比动态占用模型和简单检测/未检测早两到三年。与简单值相比，MS-DOHM预测菌落上的病原体负荷更大；然而，我们发现模型估计值与简单患病率值之间没有差异。虽然该模型预测地点水平患病率不会下降，但在长期呈Pd阳性的菌落中，存在病原体负荷下降的情况。我们的研究结果表明，在多个尺度上考虑病原体负荷和患病率会改变我们对Pd动态的理解，可能允许更早的保护干预。此外，我们发现考虑冬眠地内和个体间的病原体负荷和患病率会产生一个拟合更好、预测能力更强的模型。
