BACKGROUND The most severe bacterial disease of honeybees is American foulbrood (AFB). The epidemiology of AFB is driven by the extreme spore resilience, the difficulty of bees to remove these spores, and the considerable incidence of undetected spore-producing colonies. The honeybee collective defence mechanisms and their feedback on colony development, which involves a division of labour at multiple levels of colony organization, are difficult to model. To better predict disease outbreaks we need to understand the feedback between colony development and disease progression within the colony. We therefore developed Bayesian models with data from forty AFB-diseased colonies monitored over an entire foraging season to (i) investigate the relationship between spore production and symptoms, (ii) disentangle the feedback loops between AFB epidemiology and natural colony development, and (iii) discuss whether larger insect societies promote or limit within-colony disease transmission. RESULTS Rather than identifying a fixed spore count threshold for clinical symptoms, we estimated the probabilities around the relationship between spore counts and symptoms, taking into account modulators such as brood amount/number of bees and time post infection. We identified a decrease over time in the bees-to-brood ratio related to disease development, which should ultimately induce colony collapse. Lastly, two contrasting theories predict that larger colonies could promote either higher (classical epidemiological SIR-model) or lower (increasing spatial nest segregation and more effective pathogen removal) disease prevalence. CONCLUSIONS AFB followed the predictions of the SIR-model, partly because disease prevalence and brood removal are decoupled, with worker bees acting more as disease vectors, infecting new brood, than as agents of social immunity, by removing infected brood. We therefore established a direct link between disease prevalence and social group size for a eusocial insect. We furthermore provide a probabilistic description of the relationship between AFB spore counts and symptoms, and how disease development and colony strength over a season modulate this relationship. These results help to better understand disease development within honeybee colonies, provide important estimates for further epidemiological modelling, and gained important insights into the optimal sampling strategy for practical beekeeping and honeybee research.

中文翻译：

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蜂群中的美国腐臭幼虫：孢子与症状的关系和反馈。

背景技术蜜蜂最严重的细菌性疾病是美洲幼虫腐臭病(AFB)。AFB 的流行病学是由极端的孢子恢复力、蜜蜂去除这些孢子的困难以及大量未检测到的产生孢子的菌落所驱动的。蜜蜂的集体防御机制及其对蜂群发展的反馈，涉及蜂群组织多个层面的分工，很难建模。为了更好地预测疾病爆发，我们需要了解菌落发育和菌落内疾病进展之间的反馈。因此，我们利用在整个觅食季节监测的 40 个 AFB 患病菌落的数据开发了贝叶斯模型，以 (i) 研究孢子产生和症状之间的关系，(ii) 理清 AFB 流行病学和自然菌落发育之间的反馈循环，以及 (iii) ）讨论较大的昆虫社会是否促进或限制群体内疾病的传播。结果我们没有确定临床症状的固定孢子计数阈值，而是估计了孢子计数和症状之间关系的概率，考虑了诸如巢量/蜜蜂数量和感染后时间等调节因素。我们发现，随着时间的推移，与疾病发展相关的蜜蜂与幼蜂的比例下降，这最终会导致蜂群崩溃。最后，两种截然不同的理论预测，较大的菌落可能会提高（经典流行病学 SIR 模型）或降低（增加空间巢隔离和更有效地清除病原体）疾病患病率。结论 AFB 遵循了 SIR 模型的预测，部分原因是疾病流行和蜂巢清除是脱钩的，工蜂更多地充当疾病媒介，感染新的蜂巢，而不是作为社会免疫​​媒介，通过清除受感染的蜂巢。因此，我们在真社会性昆虫的疾病患病率和社会群体规模之间建立了直接联系。我们还提供了 AFB 孢子计数和症状之间关系的概率描述，以及一个季节内疾病的发展和菌落强度如何调节这种关系。这些结果有助于更好地了解蜂群内疾病的发展，为进一步的流行病学建模提供重要的估计，并获得对实际养蜂和蜜蜂研究的最佳采样策略的重要见解。