相关论文: Multiscale Influenza Forecasting

Seasonal influenza is a sometimes surprisingly impactful disease, causing thousands of deaths per year along with much additional morbidity. Timely knowledge of the outbreak state is valuable for managing an effective response. The current…

Influenza occurs every season and occasionally causes pandemics. Despite its low mortality rate, influenza is a major public health concern, as it can be complicated by severe diseases like pneumonia. A fast, accurate and low-cost method to…

In this paper, the authors develop a method of detecting correlations between epidemic patterns in different regions that are due to human movement and introduce a null model in which the travel-induced correlations are cancelled. They…

Numerous studies have attempted to model the effect of mass media on the transmission of diseases such as influenza, however quantitative data on media engagement has until recently been difficult to obtain. With the recent explosion of…

Predicting an infectious disease can help reduce its impact by advising public health interventions and personal preventive measures. Novel data streams, such as Internet and social media data, have recently been reported to benefit…

Probabilistic forecasting of infectious diseases is crucial for public health but relies on labor-intensive manual model curation by expert modeling teams. This bespoke development bottlenecks scalability to granular geographic resolutions…

A crucial challenge to successful flare prediction is forecasting periods that transition between "flare-quiet" and "flare-active". Building on earlier studies in this series (Barnes et al. 2016; Leka et al. 2019a,b) in which we describe…

Reliable and timely dengue predictions provide actionable lead time for targeted vector control and clinical preparedness, reducing preventable diseases and health-system costs in at-risk communities. Dengue forecasting often relies on…

In recent years the Centers for Disease Control and Prevention (CDC) have organized FluSight influenza forecasting competitions. To evaluate the participants' forecasts a multibin logarithmic score has been created, which is a non-standard…

We study the spatio-temporal patterns of the proportion of influenza B out of laboratory confirmations of both influenza A and B, with data from 139 countries and regions downloaded from the FluNet compiled by the World Health Organization,…

Accurate prediction of wind power is essential for the grid integration of this intermittent renewable source and aiding grid planners in forecasting available wind capacity. Spatial differences lead to discrepancies in climatological data…

Background: The pandemic of influenza A (H1N1) is a serious on-going global public crisis. Understanding its spreading dynamics is of fundamental importance for both public health and scientific researches. Recent studies have focused…

Climate change stands as one of the most pressing global challenges of the twenty-first century, with far-reaching consequences such as rising sea levels, melting glaciers, and increasingly extreme weather patterns. Accurate forecasting is…

In this paper we present ACEMod, an agent-based modelling framework for studying influenza epidemics in Australia. The simulator is designed to analyse the spatiotemporal spread of contagion and influenza spatial synchrony across the…

A central challenge in every field of biology is to use existing measurements to predict the outcomes of future experiments. In this work, we consider the wealth of antibody inhibition data against variants of the influenza virus. Due to…

This is part of a series of weekly influenza forecasts made during the 2012-2013 influenza season. Here we present results of forecasts initiated following assimilation of observations for Week 1 (i.e. the forecast begins January 6, 2013)…

The Influenza type A virus can be considered as one of the most severe viruses that can infect multiple species with often fatal consequences to the hosts. The Haemagglutinin (HA) gene of the virus has the potential to be a target for…

Epidemics of infectious diseases are an important threat to public health and global economies. Yet, the development of prevention strategies remains a challenging process, as epidemics are non-linear and complex processes. For this reason,…

Accurate prediction of crop yield is critical for supporting food security, agricultural planning, and economic decision-making. However, yield forecasting remains a significant challenge due to the complex and nonlinear relationships…

Early detection and modeling of a contagious epidemic can provide important guidance about quelling the contagion, controlling its spread, or the effective design of countermeasures. A topic of recent interest has been to design social…