arXiv subjects

I. Ghosh

Publications and source records attributed to I. Ghosh.

3 recordsLinked to original sources

arXiv2025

Disrupting the scammer lifecycle: A dynamically-consistent numerical analysis of a compartment model for scam-victim dynamics

Online deception and financial scams represent a pervasive threat in the digital age, yet a quantitative analysis and understanding of their propagation is lacking. This study introduces a novel model based on the framework of epidemiological models to describe the interaction between scammers and their victims. We propose a five-compartment deterministic model ($S-V-R-A_s-R_s$) calibrated using longitudinal data in fraud reports from the Canadian Anti-Fraud Centre. The model's theoretical properties are established, including the non-negativity of the state variables and the stability threshold defined by the basic reproduction number ($\mathcal{R}_0$). A non-standard finite difference scheme is developed for the numerical simulations to ensure dynamical consistency between the continuous deterministic model and its discrete equivalent. A key finding of the model sensitivity analysis indicates that the proliferation of scams is overwhelmingly driven by the lifecycle of scammers, their recruitment, attrition, and arrest, rather than the susceptibility of the victim population. The results of this study provide strong quantitative evidence that the most effective control strategies are those that directly disrupt the scammers' population. Overall, this study provides a crucial model for designing and evaluating evidence-based policies to combat the scourge of cybercrime.

math.DS↗

arXiv2025

A mathematical model of HPAI transmission between dairy cattle and wild birds with environmental effects

Highly pathogenic avian influenza (HPAI), particularly H5N1, poses an increasing threat at the wildlife--livestock--environment interface, with recent detections in dairy cattle motivating multi-host transmission models. We develop and analyse a deterministic compartmental model for HPAI transmission among cattle, wild birds, and a shared contaminated environment. The model combines an SEIR structure for cattle with an SIR framework for wild birds and includes environmentally mediated transmission. We establish positivity and boundedness, characterise the disease-free and endemic equilibria, and derive the basic reproduction number $\mathcal R_0$ as the spectral radius of a reduced next-generation matrix representing coupled transmission pathways. We also establish threshold and global stability properties of the equilibria. Numerical simulations illustrate extinction, persistence, and parameter-dependent disease dynamics. Global sensitivity analysis identifies cattle recovery, cattle-to-cattle transmission, environmental viral decay, and environmental transmission as the principal determinants of $\mathcal R_0$ within the parameter ranges considered. Response-surface and intervention analyses indicate that reducing cattle-to-cattle transmission produces the greatest reduction in transmission potential and peak cattle infection, while increasing cattle recovery provides an additional effective pathway. Reducing environmental transmission alone has a comparatively small effect under the baseline parameterisation. Within the model assumptions and parameter ranges considered, the findings provide qualitative insights into the relative effects of transmission pathways and potential control measures.

q-bio.PE↗

arXiv2023

Anticipating dengue outbreaks using a novel hybrid ARIMA-ARNN model with exogenous variables

Dengue incidence forecasting using hybrid models has been surging in the data rich world. Hybridization of statistical time series forecasting models and machine learning models are explored for dengue forecasting with different degrees of success. In this paper, we propose a multivariate expansion of the hybrid ARIMA-ARNN model. The main motivation is to propose a novel hybridization and apply it to dengue outbreak prediction. The asymptotic stationarity of the proposed model has been established. We check the forecasting capability and robustness of the forecasts through numerical experiments. State-of-the-art forecasting models for multivariate time series data are compared with the proposed model using accuracy metrics. Dengue incidence data from San Juan and Iquitos are utilized along with rainfall as an exogenous variable. Results indicate that the proposed model improves the ARIMAX forecasts in some situations and closely follows it otherwise. The theoretical as well as experimental results reinforce that the proposed model has the potential to act as a candidate for early warning of dengue outbreaks. The proposed model can be readily generalized to incorporate more exogenous variables and also applied to other time series forecasting problems wherever exogenous variable(s) are available.

q-bio.PE↗