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Saman Hosseini

Publications and source records attributed to Saman Hosseini.

5 recordsLinked to original sources
arXiv2026

A two-parameter, minimal-data model to predict dengue cases: the 2022-2023 outbreak in Florida, USA

Reliable and timely dengue predictions can provide an actionable lead time for targeted vector control and clinical preparedness, reducing preventable disease and health-system costs in at-risk communities. However, many forecasting approaches depend on site-specific covariates and entomological surveillance, which limits portability to data-sparse settings. In this work, we mathematically prove that a parabolic ICC structure, previously established for the basic SIR model, also holds in a substantially more complex model: a two-population (human-mosquito) four-serotype dengue transmission model with primary and secondary infections and mild/severe disease classes. To predict the number of new cases, we propose a data-parsimonious (DP) framework built on the incidence-cumulative cases (ICC) curve that requires only the human incidence time series of the target season and estimates only two parameters, thereby reducing estimation noise and computational burden. We further develop a Bayesian extension that accounts for case-reporting and fitting uncertainty, producing calibrated predictive intervals. The Bayesian model yields improved predictive performance compared to the parabolic ICC model. We evaluate the framework for dengue outbreaks in Florida in 2022-2023, where standardized clinical tests and reporting support accurate case determination.

stat.AP↗
arXiv2025

A Data-Parsimonious Model for Long-Term Risk Assessments of West Nile Virus Spillover

Many West Nile virus (WNV) forecasting frameworks incorporate entomological or avian surveillance data, which may be unavailable in some regions. We introduce a novel data-parsimonious probabilistic model to predict both the timing of outbreak onset and the seasonal severity of WNV spillover. Our approach combines a temperature-driven compartmental model of WNV with nonparametric kernel density estimation methods to construct a joint probability density function and a Poisson rate surface as function of mosquito abundance and normalized cumulative temperature. Calibrated on human incidence records, the model produces reliable forecasts several months before the transmission season begins, supporting proactive mitigation efforts. We evaluated the framework across three counties in California (Orange, Los Angeles, and Riverside), two in Texas (Dallas and Harris), and one in Florida (Duval), representing completely different ecology and distinct climatic regimes, and observed strong agreement across multiple performance metrics.

stat.AP↗
arXiv2025

Probabilistic Assessment of West Nile Virus Spillover Risk Using a Compartmental Mechanistic Model

This paper presents a novel probabilistic approach for assessing the risk of West Nile Disease (WND) spillover to the human population. The assessment has been conducted under two different scenarios: (1) assessment of the onset of spillover, and (2) assessment of the severity of the epidemic after the onset of the disease. A compartmental model of differential equations is developed to describe the disease transmission mechanism, and a probability density function for pathogen spillover to humans is derived based on the model for the assessment of the risk of the spillover onset and the severity of the epidemic. The prediction strategy involves making a long-term forecast and then updating it with a short-term (lead time of two weeks or daily). The methodology is demonstrated using detailed outbreak data from high-case counties in California, including Orange County, Los Angeles County, and Kern County. The predicted results are compared with actual infection dates reported by the California Department of Public Health for 2022-2024 to assess prediction accuracy. The performance accuracy is evaluated using a logarithmic scoring system and compared with one of the most renowned predictive models to assess its effectiveness. In all prediction scenarios, the model demonstrated strong performance. Lastly, the method is applied to explore the impact of global warming on spillover risk, revealing an increasing trend in the number of high-risk days and a shift toward a greater proportion of these days over time for the onset of the disease.

stat.AP↗
arXiv2019

Some Investigations about the Properties of Maximum Likelihood Estimations Based on Lower Record Values for a Sub-Family of the Exponential Family

Here, in this paper it has been considered a sub family of exponential family. Maximum likelihood estimations (MLE) for the parameter of this family, probability density function, and cumulative density function based on a sample and based on lower record values have been obtained. It has been considered Mean Square Error (MSE) as a criterion for determining which is better in different situations. Additionally, it has been proved some theories about the relations between MLE based on lower record values and based on a random sample. Also, some interesting asymptotically properties for these estimations have been shown during some theories.

math.ST↗