Ensemble Learning: Predicting Human Pathogenicity of Hematophagous Arthropod Vector-Borne Viruses

Hematophagous arthropods occupy a pivotal role in ecosystems, serving as vectors for a wide array of pathogens with significant implications for public health. Their capacity to harbor and transmit viruses through biting actions creates a substantial risk of zoonotic spillover. Despite the advancements in metagenomic approaches for virus discovery in vectors, the isolation and cultivation of viruses still pose significant challenges, thereby limiting comprehensive assessments of their pathogenicity. Here, we curated two datasets: one with 294 viruses, characterized by 37 epidemiological features, encompassing virus information and host associations; the second with 71,622 sequences of hematophagous arthropod vector-borne viruses, annotated with 33 sequence features. Two XGBoost models were developed to predict arbovirus human pathogenicity—one integrating macroscopic eco-epidemiological data, the other incorporating virus-related sequence features. The macroscopic model identified non-vector host transmission as a key determinant, especially involving Perissodactyla, Artiodactyla, and Carnivora Order. The sequence-based model demonstrated that viral adhesion and viral invasion had distinct trends with consistent increase and decrease in the likelihood of virus pathogenicity to humans, respectively. With validated through an independent dataset, the model exhibited a congruous alignment with documented pathogenicity outcomes. Together, the models offer a holistic framework for assessing the pathogenic potential of viruses transmitted by hematophagous arthropods. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The laboratory conducting this research is funded by grants from the National Key Research and Development Program of China (2019YFC1200501). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The data supporting the findings of this study are available upon reasonable request from the author. Researchers interested in accessing the dataset for further exploration or verification are encouraged to contact Huakai Hu at hhyu98{at}163.com for assistance. We are committed to promoting transparency and collaboration in scientific research, and we welcome inquiries regarding the data underlying our published results.