Predictive Hematological Modeling for Field-Based Diagnosis of Haemoparasitic Infections in Ruminants in Resource Limited Setting

_Abstract

_{Objective: This study leveraged statistical modeling and clinical pathology to develop a predictive framework for field diagnosis due to significant impairment of livestock productivity in tropical regions with Haemoparasitic infections but their diagnosis in resource-limited settings remains challenging.}

_{Materials and Method: A cross-sectional analysis of 112 ruminants (57 cattle, 55 small ruminants) at an abattoir in Ibadan, Nigeria was conducted. Blood samples were collected for Giemsa-stained microscopy (definitive diagnosis) and full hematological profiling, including packed cell volume (PCV), hemoglobin (Hb), white blood cell count (WBC), platelet count, and neutrophil-lymphocyte ratio (NLR). Data were analyzed in R (v4.0+) using both parametric and non-parametric tests. Univariable and multivariable logistic regression were employed to identify hematological predictors of infection, with model performance quantified by Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) analysis.}

_{Results: The analysis revealed that infection with Trypanosoma, Babesia, Theileria, or Anaplasma species caused significant hematological alterations: profound anemia (mean PCV drop: 21.4% vs. 30.8% in healthy, p<0.0001), leukocytosis, elevated NLR (5.8 vs. 2.1, p<0.0001), and thrombocytopenia (78 vs. 125 × 10³/μL, p=0.001). Analytics derived a highly predictive diagnostic triad: PCV <24%, NLR >4, and platelets <150 × 10³/μL. This composite metric achieved a >90% probability of detecting subclinical infection in critical cases (PCV <20%, NLR >6, platelets <60 × 10³/μL), as validated by bootstrap resampling. Breed-specific baselines (e.g., resilient Ndama cattle vs. susceptible Red Bororo) were critical for accurate interpretation.}

_{Conclusion: This study provides a robust, statistically-derived hematological model that serves as a cost-effective, field-deployable tool for the early triage and management of haemoparasitism, enabling data-driven decisions in settings without access to advanced diagnostics.}

_{Keywords:Breed-Specific Susceptibility, Field Diagnostics Hemoparasitic Infections, Predictive Hematology,Ruminant Healt}