Disease outbreaks can have substantial impacts on wild populations, but the often patchy or anecdotal evidence of these impacts impedes our ability to understand outbreak dynamics. Recently however, a severe disease outbreak occurred in a group of very well-studied organisms-sea stars along the west coast of North America. We analyzed nearly two decades of data from a coordinated monitoring eff...

BACKGROUND Research has been conducted on interventions to control dengue transmission and respond to outbreaks. A summary of the available evidence will help inform disease control policy decisions and research directions, both for dengue and, more broadly, for all Aedes-borne arboviral diseases. METHOD A research-to-policy forum was convened by TDR, the Special Programme for Research and Tr...

BACKGROUND A dengue early warning system aims to prevent a dengue outbreak by providing an accurate prediction of a rise in dengue cases and sufficient time to allow timely decisions and preventive measures to be taken by local authorities. This study seeks to identify the optimal lead time for warning of dengue cases in Singapore given the duration required by a local authority to curb an outb...

This document gives an introduction to the use of the function hhh4 for modelling univariate and multivariate time series of infectious disease counts. The function is part of the R-package surveillance, which provides tools for the visualization, modelling and monitoring of surveillance time series. The basic functionality of surveillance is introduced in the package vignette (Höhle et al., 20...

The recent outbreak of information demand for financial investment management forces to look for novel ways of quantitative data analysis. Relying only on traditional data sources means to loose the edge over the competence and become irrelevant in the future. On the other hand, the Big Data and Data Analytics trends are getting traction in financial domain and are being sought as highly benefi...

We propose a new method to analyze outbreak data of an infectious disease such as classical swine fever. The underlying model is a two-type branching process. It is used to deduce information concerning the epidemic from detected cases. In particular, the method leads to prediction of the future course of the epidemic and hence can be used as a basis for control policy decisions. We test the mo...

We propose a new method to analyse outbreak data of an infectious disease such as classical swine fever. The underlying model is a two-type branching process. It is used to deduce information concerning the epidemic from detected cases. In particular, the method leads to prediction of the future course of the epidemic, and hence can be used as a basis for control policy decisions. We test the m...

We consider a stochastic Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological model with a contact rate that fluctuates seasonally. Through the use of a nonlinear, stochastic projection, we are able to analytically determine the lower dimensional manifold on which the deterministic and stochastic dynamics correctly interact. Our method produces a low dimensional stochastic model that c...