Systematic prediction of spatiotemporal transmission of potential respiratory pandemics in China [0.03%]
中国潜在呼吸道大流行空间 temporal 传播的系统预测Spatial-temporal Transmission Prediction for Potential Respiratory Pandemics in China
Xiao Liu,Yanxia Sun,Rui Shen et al.
Xiao Liu et al.
Population movement significantly influences respiratory disease transmission; however, movement restrictions can impose substantial societal burdens. To understand spatiotemporal characteristic of a potential respiratory pandemic in Chines...
Puhua Niu,Byung-Jun Yoon,Xiaoning Qian
Puhua Niu
In this study, we focus on developing efficient calibration methods via Bayesian decision-making for the family of compartmental epidemiological models. The existing calibration methods usually assume that the compartmental model is cheap i...
Emilio Molina,Diego Olguín,Antoine Brault et al.
Emilio Molina et al.
The present paper proposes a novel methodology for evaluating the impact of a vaccination plan against a transmissible disease. The methodology has two distinct stages. The initial stage comprises a compartmental model that describes the tr...
Mark P Rast,Luke I Rast
Mark P Rast
Effective public health decisions require early reliable inference of infectious disease properties. In this paper we assess the ability to infer infectious disease attributes from population-level stochastic epidemic trajectories. In parti...
Dengue fever prediction based on meteorological features and deep learning models [0.03%]
基于气象特征和深度学习模型的登革热预测
Yunyun Cheng,Rong Cheng,Ting Xu et al.
Yunyun Cheng et al.
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...
Absolute humidity drives seasonal influenza A transmission in Hong Kong through social contact modulation: Evidence from compartmental modeling [0.03%]
绝对湿度通过调节社会接触驱动香港季节性流感A传播： compartmental 模型证据
Guanlin Ou,Wenjun Ma,Yanying Mo et al.
Guanlin Ou et al.
Background: Prior studies propose a U-shaped humidity-influenza relationship, yet the interplay between humidity-driven contact behaviors and transmission dynamics remains unclear. ...
Warming temperatures reduce lifespan and vectorial capacity of Anopheles mosquitoes in Ghana [0.03%]
温度升高缩短加纳按蚊寿命并降低其传播能力
Edmund I Yamba,Kingsley Badu,Thomas A Kyeimiah et al.
Edmund I Yamba et al.
Climate change and variability are altering the ecology of malaria vectors, with implications for disease transmission in sub-Saharan Africa. In this study, we analysed long-term historical temperature, rainfall and relative humidity data a...
Study on the resurgence of pertussis based on a stage-structured dynamic model [0.03%]
基于阶段结构动力学模型的百日咳复发研究
Yifei Qiao,Jijun Zhao
Yifei Qiao
Although pertussis vaccination has effectively reduced the global incidence rate and mortality, pertussis resurgence has been observed in many countries in recent years. This study aims to untangle the changes in dynamic transmission charac...
Spatio-temporal forecasting of dengue in the Americas through hybrid mechanistic and data-driven models: Systematic review and meta-analysis [0.03%]
美洲登革热时空预测的机制和数据驱动模型混合方法：系统综述和荟萃分析
Jenniffer Alejandra Castellanos Garzón,Luis Fernando Plaza Gálvez,Kelly Fernanda Plaza Bastidas et al.
Jenniffer Alejandra Castellanos Garzón et al.
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 quantifie...
Integrating Kolmogorov-Arnold networks with ordinary differential equations for efficient, interpretable, and robust deep learning: Epidemiology of infectious diseases as a case study [0.03%]
基于柯尔莫哥洛夫-阿诺德网络与常微分方程的高效、可解释和鲁棒深度学习：传染病流行病学为例研究
Kexin Ma,Xu Lu,Nicola Luigi Bragazzi et al.
Kexin Ma et al.
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 c...