Mysterud Atle, Viljugrein Hildegunn, Rolandsen Christer M, Belsare Aniruddha V
Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences, University of Oslo, PO Box 1066, Blindern, 0316 Oslo, Norway.
Norwegian Veterinary Institute, PO Box 750 Sentrum, 0106 Oslo, Norway.
R Soc Open Sci. 2021 Mar 10;8(3):210124. doi: 10.1098/rsos.210124.
The intensive harvesting of hosts is often the only practicable strategy for controlling emerging wildlife diseases. Several harvesting approaches have been explored theoretically with the objective of lowering transmission rates, decreasing the transmission period or specifically targeting spatial disease clusters or high-risk demographic groups. Here, we present a novel model-based approach to evaluate alternative harvest regimes, in terms of demographic composition and rates, intended to increase the probability to remove all infected individuals in the population during the early phase of an outbreak. We tested the utility of the method for the elimination of chronic wasting disease based on empirical data for reindeer () in Norway, in populations with (Nordfjella) and without (Hardangervidda) knowledge about exact disease prevalence and population abundance. Low and medium harvest intensities were unsuccessful in eliminating the disease, even at low prevalence. High-intensity harvesting had a high likelihood of eliminating the disease, but probability was strongly influenced by the disease prevalence. We suggest that the uncertainty about disease prevalence can be mitigated by using an adaptive management approach: forecast from models after each harvest season with updated data, derive prevalence estimates and forecast further harvesting. We identified the problems arising from disease surveillance with large fluctuations in harvesting pressure and hence sample sizes. The elimination method may be suitable for pathogens that cause long-lasting infections and with slow epidemic growth, but the method should only be attempted if there is a low risk of reinfection, either by a new disease introduction event (e.g. dispersing hosts) or due to environmental reservoirs. Our simulations highlighted the short time window when such a strategy is likely to be successful before approaching near complete eradication of the population.
对宿主进行密集捕杀往往是控制新出现的野生动物疾病的唯一可行策略。理论上已经探索了几种捕杀方法，目的是降低传播率、缩短传播期或专门针对空间疾病聚集区或高风险人群。在此，我们提出一种基于模型的新方法，从人口组成和比率方面评估替代捕杀方案，旨在提高在疫情早期阶段清除种群中所有感染个体的概率。我们根据挪威驯鹿的经验数据，在已知（诺德菲耶拉）和未知（哈当厄高原）确切疾病流行率和种群数量的种群中，测试了该方法对消除慢性消耗病的效用。即使在低流行率情况下，低强度和中等强度的捕杀也未能成功消除疾病。高强度捕杀有很高的可能性消除疾病，但概率受疾病流行率的强烈影响。我们建议，可以通过采用适应性管理方法来减轻疾病流行率的不确定性：在每个捕杀季节后根据更新的数据从模型进行预测，得出流行率估计值并预测进一步的捕杀。我们确定了疾病监测中因捕杀压力以及样本量大幅波动而产生的问题。这种消除方法可能适用于导致长期感染且流行增长缓慢的病原体，但只有在通过新的疾病引入事件（如宿主扩散）或环境储存库再次感染风险较低时，才应尝试使用该方法。我们的模拟突出了在接近完全根除种群之前该策略可能成功的短时间窗口。
