Data from: Co-infections and environmental conditions drive the distributions of blood parasites in wild birds

Experimental work increasingly suggests that non-random pathogen associations can affect the spread or severity of disease. Yet due to difficulties distinguishing and interpreting co-infections, evidence for the presence and directionality of pathogen co-occurrences in wildlife is rudimentary.

We provide empirical evidence for pathogen co-occurrences by analysing infection matrices for avian malaria (Haemoproteus and Plasmodium spp.) and parasitic filarial nematodes (microfilariae) in wild birds (New Caledonian Zosterops spp.).

Using visual and genus-specific molecular parasite screening, we identified high levels of co-infections that would have been missed using PCR alone. Avian malaria lineages were assigned to species level using morphological descriptions. We estimated parasite co-occurrence probabilities, while accounting for environmental predictors, in a hierarchical multivariate logistic regression.

Co-infections occurred in 36% of infected birds. We identified both positively and negatively correlated parasite co-occurrence probabilities when accounting for host, habitat and island effects. Two of three pairwise avian malaria co-occurrences were strongly negative, despite each malaria parasite occurring across all islands and habitats. Birds with microfilariae had elevated heterophil to lymphocyte ratios and were all co-infected with avian malaria, consistent with evidence that host immune modulation by parasitic nematodes facilitates malaria co-infections. Importantly, co-occurrence patterns with microfilariae varied in direction among avian malaria species; two malaria parasites correlated positively but a third correlated negatively with microfilariae.

We show that wildlife co-infections are frequent, possibly affecting infection rates through competition or facilitation. We argue that combining multiple diagnostic screening methods with multivariate logistic regression offers a platform to disentangle impacts of environmental factors and parasite co-occurrences on wildlife disease.

越来越多的实验研究表明，非随机的病原体关联可影响疾病的传播或严重程度。然而，由于难以区分和解读共感染现象，目前关于野生动物体内病原体共现现象的存在性与方向性的证据仍十分有限。

本研究通过分析野生鸟类（新喀里多尼亚绣眼鸟属Zosterops spp.物种）的感染矩阵，为病原体共现现象提供实证依据，所涉病原体包括禽疟原虫（avian malaria，涵盖Haemoproteus属与Plasmodium属物种）以及寄生丝状线虫（filarial nematodes，其感染阶段为微丝蚴microfilariae）。

本研究采用目视镜检与属特异性分子寄生虫筛查联用的方案，检出了大量仅通过聚合酶链式反应（PCR）无法发现的共感染病例。研究人员通过形态学描述将禽疟原虫谱系鉴定至物种水平，并借助分层多变量逻辑回归（hierarchical multivariate logistic regression）模型，在纳入环境预测因子的前提下估算了病原体的共现概率。

共感染发生于36%的受感染野生鸟类中。在纳入宿主、栖息地与岛屿效应的分析框架下，本研究检出了呈正相关与负相关的病原体共现概率模式。尽管两种疟原虫均广泛分布于各岛屿与栖息地，但三对两两禽疟原虫共现组合中有两对呈现显著负相关。携带微丝蚴（microfilariae）的鸟类异嗜性粒细胞与淋巴细胞比值（heterophil to lymphocyte ratios）升高，且全部合并感染了禽疟原虫，这与寄生线虫通过调控宿主免疫促进疟原虫共感染的研究结论一致。值得注意的是，微丝蚴与不同禽疟原虫物种的共现模式存在方向差异：两种疟原虫与微丝蚴呈正相关，而第三种疟原虫则与微丝蚴呈负相关。

本研究证实野生鸟类共感染现象十分普遍，其可能通过竞争或易化作用影响感染率。我们认为，将多种诊断筛查方法与多变量逻辑回归分析相结合，可为厘清环境因子与病原体共现现象对野生动物疾病的影响提供一套可行的研究框架。