Artificial Intelligence and Deep Learning in Hantavirus Research:

A Comprehensive Review

Elham Edkndarnia1,*

1 Arab open university-Bahrain

Received: February 10, 2026 Revised: April 11, 2026 Accepted: June 10, 2026 ⋆ Corresponding author

ABSTRACT

Hantavirus remains an important zoonotic threat because of its association with severe human diseases, including

hemorrhagic fever with renal syndrome and hantavirus pulmonary syndrome. Its transmission is strongly influenced

by rodent reservoirs, environmental conditions, human exposure patterns, and regional ecological variability. Recent

advances in artificial intelligence (AI) and deep learning have created new opportunities for improving Hantavirus

detection, outbreak prediction, ecological risk mapping, diagnostic support, and public health surveillance. This

review examines the role of AI-driven methods in Hantavirus research, with emphasis on how machine learning, deep

learning, image-based analysis, epidemiological modeling, and data-driven surveillance can support earlier detection

and more informed decision-making. The review also discusses the potential of AI to integrate heterogeneous data

sources, including clinical records, environmental variables, remote sensing indicators, genomic information, and

epidemiological reports. Despite these advances, several challenges remain, including limited datasets, geographic

bias, model generalization, lack of clinical validation, data imbalance, interpretability concerns, and the need for

real-time deployment. Overall, AI and deep learning offer promising tools for strengthening Hantavirus surveillance

and response, but their practical value depends on transparent models, high-quality data, interdisciplinary validation,

and integration into public health systems.

Keywords: Hantavirus; Artificial intelligence; Deep learning; Disease surveillance; Outbreak prediction

1. INTRODUCTION

Hantavirus represents an important zoonotic viral threat because

of its capacity to cause severe human disease, its dependence

on wildlife reservoirs, and its close relationship with

ecological, environmental, and human behavioral factors. Unlike

many directly transmitted viral infections, Hantavirus

transmission is strongly associated with rodent reservoirs

and human exposure to contaminated excreta, aerosols, or

infected environments. This makes Hantavirus not only a

biomedical concern, but also an ecological and public health

challenge that requires integration between virology, epidemiology,

environmental monitoring, clinical diagnosis, and

surveillance science. The continuing concern surrounding

Hantavirus is reinforced by its pandemic potential, severe

clinical outcomes, and capacity to emerge or re-emerge when

environmental and human conditions favor spillover events

[1].

The clinical importance of Hantavirus is mainly linked to

two major disease patterns: hemorrhagic fever with renal

syndrome and Hantavirus pulmonary syndrome. These syndromes

differ in their geographical distribution, dominant

viral lineages, clinical presentation, and disease severity, but

both reflect the broader ability of Hantaviruses to produce

serious systemic illness. The public health burden of these

infections is intensified by diagnostic difficulty, symptom