Chad W Milando,George G Vega Yon,Kaitlyn Johnson et al.
Chad W Milando et al.
The reproductive number, Rt, is a popular metric used for monitoring infectious diseases. Rt describes the expected number of infections that will be generated from a single infection at time t, which maps nicely to the likelihood that dise...
Impact of COVID-19 on the transmission dynamics of HFMD associated enterovirus serotypes in Japan: A modelling study of surveillance data [0.03%]
日本新冠疫情对肠道病毒血清型的手足口病传播动力学的影响：基于监测数据的建模研究
Xuemei Yan,Nicholas C Grassly,Margarita Pons-Salort
Xuemei Yan
A notable decline in incidence of hand, foot, and mouth disease (HFMD) was observed globally since the beginning of the COVID-19 pandemic, indicating a change in the transmission dynamics of enteroviruses (EVs) causing HFMD. This study esti...
Spatiotemporal transmission of influenza in the US during the 2022/23 season [0.03%]
2022至2023年美国流感时空传播规律分析
Alexia Couture,Matthew Biggerstaff,Michael Sheppard et al.
Alexia Couture et al.
Understanding the spatiotemporal dynamics of seasonal influenza spread across the United States (US) is crucial for informed public health planning. We explored patterns of influenza transmission during the 2022/23 season in the US and used...
Sequential federated analysis of early outbreak data applied to incubation period estimation [0.03%]
应用于估算潜伏期的早期流行病学数据分析的序贯联合方法
Simon Busch-Moreno,Moritz U G Kraemer
Simon Busch-Moreno
Early outbreak data analysis is critical for informing about their potential impact and interventions. However, data obtained early in outbreaks are often sensitive and subject to strict privacy restrictions. Thus, federated analysis, which...
Short term forecast of new daily pandemic hospitalizations: A time series model for a single hospital [0.03%]
短期预测新的每日大流行住院人数：单个医院的时间序列模型
Lieke Fleur Heupink,Espen Rostrup Nakstad,Hilde Lurås et al.
Lieke Fleur Heupink et al.
Reliable hospital admission can aid contingency planning during pandemics. While some studies have developed models for predicting new hospitalizations, most focus on data at the regional or national level. During health crises, a predictio...
Changing contact patterns in Newfoundland and Labrador, Canada in response to public health measures during the COVID-19 pandemic [0.03%]
加拿大纽芬兰和拉布拉多省居民在新冠肺炎疫情期间对公共卫生措施的响应及接触模式的变化
Renny Doig,Amy Hurford,Suzette Spurrell et al.
Renny Doig et al.
The provincial government of Newfoundland and Labrador, Canada implemented a contact tracing program as part of a containment strategy during the COVID-19 pandemic. A high proportion of cases were detected and contact traced, and our analys...
From wastewater to infection estimates: Incident COVID-19 infections during Omicron in the U.S [0.03%]
从废水到感染估计：美国奥米克戎疫情期间的新增新冠感染人数
Rachel Lobay,Ajitesh Srivastava,Daniel J McDonald
Rachel Lobay
Reconstructing the course of the COVID-19 pandemic through estimating incident infections is important for assessing disease burden and characterizing transmission dynamics. While wastewater concentration data have been used to estimate inf...
ML-ABC: Machine-learning assisted Approximate Bayesian Computation for efficient calibration of agent-based models for pandemic outbreak analysis [0.03%]
用于大流行病爆发分析的代理基模型的高效校准的机器学习辅助近似贝叶斯计算(ML-ABC)
Thomas Bayley,Tony Ward,Fabian Sturman et al.
Thomas Bayley et al.
Mathematical modelling with agent-based models (ABMs) has gained popularity during the COVID-19 pandemic, but their complexity makes efficient and robust calibration to data challenging, particularly when applying Bayesian methods to quanti...
Predicting local COVID-19 emergences: A time-series classification approach and value of data from social media, search engines, and neighbouring regions [0.03%]
预测局部COVID-19爆发：时间序列分类方法及社交网络、搜索引擎和相邻区域数据的价值
Erin E Rees,Mani Sotoodeh,José Denis-Robichaud et al.
Erin E Rees et al.
Background: Early warning for known infectious disease threats use methods that focus on detection of outbreaks, often at large geographical scales. However, earlier warning, specifically at the onset of disease emergence...
A robust compartmental modeling framework for infectious disease monitoring and analysis via fractional differential equations [0.03%]
基于分数阶微分方程的传染病监测与分析的鲁棒隔室模型框架
Farrukh A Chishtie,John Drozd,X Li et al.
Farrukh A Chishtie et al.
This study presents a comprehensive framework for infectious disease monitoring using fractional differential equations, specifically developing the SEIQRDP (Susceptible, Exposed, Infected, Quarantined, Recovered, Deceased, Protected) model...