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When surveillance data of infectious disease incidence (e.g. weekly case counts) are disaggregated by demographic indicators, disparities in long-run health outcomes between these groups become apparent. Accurate identification of high-risk…

统计方法学 · 统计学 2026-05-29 Miles Moran , Rob Trangucci , Lisa Madsen

The integration of empirical data in computational frameworks to model the spread of infectious diseases poses challenges that are becoming pressing with the increasing availability of high-resolution information on human mobility and…

种群与进化 · 定量生物学 2013-04-24 Anna Machens , Francesco Gesualdo , Caterina Rizzo , Alberto E Tozzi , Alain Barrat , Ciro Cattuto

Spatio-temporal models for infection counts generally follow themes of the broader disease mapping literature, but may need to address specific features of spatio-temporal infection data including considerable time fluctuations (with…

应用统计 · 统计学 2022-02-22 P. Congdon

Short-time human travel behaviour can be described by a power law with respect to distance. We incorporate this information in space-time models for infectious disease surveillance data to better capture the dynamics of disease spread. Two…

统计方法学 · 统计学 2014-11-25 Sebastian Meyer , Leonhard Held

Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for realism in addressing complex public health questions is…

Social contact matrices are essential tools in infectious disease epidemiology as they quantify close-range human contact patterns which directly drive the transmission of airborne infectious diseases. In this work we propose a Bayesian…

统计方法学 · 统计学 2026-05-11 Shozen Dan , David A. van Dyk , Zhi Ling , Swapnil Mishra , Oliver Ratmann

We consider an age-structured epidemic model with two basic public health interventions: (i) identifying and isolating symptomatic cases, and (ii) tracing and quarantine of the contacts of identified infectives. The dynamics of the infected…

种群与进化 · 定量生物学 2014-03-13 Xi Huo

Passenger contact in public transit (PT) networks can be a key mediate in the spreading of infectious diseases. This paper proposes a time-varying weighted PT encounter network to model the spreading of infectious diseases through the PT…

物理与社会 · 物理学 2020-11-24 Baichuan Mo , Kairui Feng , Yu Shen , Clarence Tam , Daqing Li , Yafeng Yin , Jinhua Zhao

Network--based epidemic models that account for heterogeneous contact patterns are extensively used to predict and control the diffusion of infectious diseases. We use census and survey data to reconstruct a geo--referenced and…

社会与信息网络 · 计算机科学 2026-05-19 Alessandro Celestini , Francesca Colaiori , Stefano Guarino , Enrico Mastrostefano , Lena Rebecca Zastrow

Socio-demographic factors influence social contact patterns and play a fundamental role in shaping the transmission dynamics of infectious diseases. However, compartment-based models of infectious disease dynamics commonly consider the…

物理与社会 · 物理学 2026-05-15 Vincent X. Lomas , Tim Chambers , Leighton Watson , Michael Plank

Acute respiratory diseases are transmitted over networks of social contacts. Large-scale simulation models are used to predict epidemic dynamics and evaluate the impact of various interventions, but the contact behavior in these models is…

应用统计 · 统计学 2012-08-27 Gail E. Potter , Mark S. Handcock , Ira M. Longini, , M. Elizabeth Halloran

In this paper we study a diffusive age structured epidemic model with disease transmission between vector and host populations. The dynamics of the populations are described by reaction-diffusion equations, with infection age structure of…

偏微分方程分析 · 数学 2017-06-15 William E. Fitzgibbon , Jeffrey J. Morgan , Glenn F. Webb , Yixiang Wu

I study the spreading of infectious diseases on heterogeneous populations. I represent the population structure by a contact-graph where vertices represent agents and edges represent disease transmission channels among them. The population…

种群与进化 · 定量生物学 2009-11-13 Alexei Vazquez

The spread of infectious diseases crucially depends on the pattern of contacts among individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. Few empirical studies are however available that…

Understanding how age-specific social contact patterns and susceptibility influence infectious disease transmission is crucial for accurate epidemic modeling. This study presents an eigenvector-based sensitivity analysis framework to…

种群与进化 · 定量生物学 2025-11-21 Evans Kiptoo Korir , Zsolt Vizi

Capturing the structured mixing within a population is key to the reliable projection of infectious disease dynamics and hence informed control. Both heterogeneity in the number of contacts and age-structured mixing have been repeatedly…

社会与信息网络 · 计算机科学 2026-03-17 Luke Murray Kearney , Emma L Davis , Matt J Keeling

Mathematical models have been used to understand the spread patterns of infectious diseases such as Coronavirus Disease 2019 (COVID-19). The transmission component of the models can be modelled in an age-dependent manner via introducing…

定量方法 · 定量生物学 2022-11-15 Evans Kiptoo Korir , Zsolt Vizi

Understanding age-group dynamics of infectious diseases is a fundamental issue for both scientific study and policymaking. Age-structure epidemic models were developed in order to study and improve our understanding of these dynamics. By…

种群与进化 · 定量生物学 2019-11-22 Rami Yaari , Amit Huppert , Itai Dattner

Contact matrices have become a key ingredient of modern epidemic models. They account for the stratification of contacts for the age of individuals and, in some cases, the context of their interactions. However, age and context are not the…

物理与社会 · 物理学 2023-07-03 Adriana Manna , Lorenzo Dall'Amico , Michele Tizzoni , Marton Karsai , Nicola Perra

Infectious disease transmission dynamics are particularly sensitive to social contact patterns, and the precautions people take to limit disease transmission. It depends on the age distribution of the community. Thus, knowing the…

种群与进化 · 定量生物学 2022-04-19 Vijay Pal Bajiya , Jai Prakash Tripathi , Ranjit Kumar Upadhyay
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