AIMC Journal:
Infectious Disease Modelling

Showing 1 to 10 of 11 articles

Dynamic properties of an SARS-CoV-2 epidemic model via stochastic PINNs.

Infectious Disease Modelling Apr 1, 2026
This paper introduces a novel stochastic SEIRV model for investigating the spread of the SARS-CoV-2 epidemic using stochastic physics-informed neural networks (S-PINNs). We first prove the global positivity of solutions via Lyapunov functions and Itô...
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Data-driven model analysis of the impact of environmental and socioeconomic factors on tuberculosis incidence.

Infectious Disease Modelling Feb 26, 2026
Tuberculosis (TB), a global infectious disease, poses a formidable challenge to Taiwan, China, exacerbated by its aging demographic and the incursion of pathogens from Southeast Asia's high-risk districts. In this study, we analyzed data across 19 ci...
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Acute respiratory infection (COVID-19) risk prediction in travelers: A random forest model.

Infectious Disease Modelling Feb 26, 2026
BACKGROUND: Early screening during outbreaks of acute respiratory infections (ARIs) is critical for controlling disease spread among international travelers. However, the massive volume of traveler data generated in a short timeframe makes manual scr...
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From qualitative prediction to quantitative insight: combined meteorological patterns and regional dynamics of severe fever with thrombocytopenia syndrome in Liaoning Province, China, 2010-2024.

Infectious Disease Modelling Jan 30, 2026
BACKGROUND: Severe fever with thrombocytopenia syndrome(SFTS) is an emerging tick-borne disease with an expanding range and increasing public health burden. Meteorology-driven frameworks that integrate qualitative prediction with quantitative risk es...
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Ensemble-labeling of infectious disease time series to evaluate early warning systems.

Infectious Disease Modelling Dec 23, 2025
Early warning systems (EWSs) for detecting disease outbreaks can help make informed public health decisions and organize necessary responses. During the COVID-19 pandemic, several EWSs were proposed that use covariates such as mobility or social medi...
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Dengue fever prediction based on meteorological features and deep learning models.

Infectious Disease Modelling Dec 11, 2025
The dengue fever epidemic is one of the health priorities of the World Health Organization (WHO), and accurately predicting its epidemiological trends is crucial. Multi source geographic data such as temperature, humidity, and precipitation affect th...
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Spatio-temporal forecasting of dengue in the Americas through hybrid mechanistic and data-driven models: Systematic review and meta-analysis.

Infectious Disease Modelling Dec 11, 2025
This systematic review and meta-analysis (PROSPERO: CRD420251130769) synthesises 30 dengue modelling studies conducted in the Americas between 2016 and 2025, evaluating the integration of mechanistic and data-driven approaches. We quantified the reli...
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Integrating Kolmogorov-Arnold networks with ordinary differential equations for efficient, interpretable, and robust deep learning: Epidemiology of infectious diseases as a case study.

Infectious Disease Modelling Dec 10, 2025
This study extends universal differential equation (UDE) frameworks by integrating the Kolmogorov-Arnold Network (KAN) with ordinary differential equations, referred to as KAN-UDE, to achieve efficient and interpretable deep learning. Our case study ...
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Dynamics and forecasting of an age-structured stochastic SIR model with Lévy perturbations via physics-informed neural networks.

Infectious Disease Modelling Nov 12, 2025
Understanding and predicting real-world epidemic dynamics has consistently posed a formidable challenge. This study addresses an age-structured stochastic SIR model incorporating a general incidence rate, high-order white noise, and Lévy jump perturb...
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Dengue forecasting and outbreak detection in Brazil using LSTM: integrating human mobility and climate factors.

Infectious Disease Modelling Nov 5, 2025
BACKGROUND: Dengue fever is a major global health concern, with Brazil experiencing recurrent and severe outbreaks due to its favorable climate factors, socio-environmental conditions, and increasing human mobility. Accurate forecasting of dengue cas...
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