Search results for "Surveillance"

Bayesian Markov switching models for the early detection of influenza epidemics

2008

The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…

Prospective analysis of infectious disease surveillance data using syndromic information.

2014

In this paper, we describe a Bayesian hierarchical Poisson model for the prospective analysis of data for infectious diseases. The proposed model consists of two components. The first component describes the behavior of disease during nonepidemic periods and the second component represents the increase in disease counts due to the presence of an epidemic. A novelty of our model formulation is that the parameters describing the spread of epidemics are allowed to vary in both space and time. We also show how syndromic information can be incorporated into the model to provide a better description of the data and more accurate one-step-ahead forecasts. These real-time forecasts can be used to …

Effects of record linkage errors on registry-based follow-up studies

1997

The importance of reliable record linkage for high quality-population-based disease registration is widely recognized. Systematic methodologic work is lacking, however, on the effects of record linkage errors on the use of disease registries for epidemiologic purposes. The present paper provides algebraic models describing the effects of record linkage errors on monitoring survival of registered patients, which is commonly performed by matching registry records against a database of death certificates, and on registry-based incidence follow-up of external cohorts. Homonym errors, that is, erroneous linkage of records that pertain to distinct individuals, lead to underestimation of survival …

Prospective surveillance of multivariate spatial disease data

2012

Surveillance systems are often focused on more than one disease within a predefined area. On those occasions when outbreaks of disease are likely to be correlated, the use of multivariate surveillance techniques integrating information from multiple diseases allows us to improve the sensitivity and timeliness of outbreak detection. In this article, we present an extension of the surveillance conditional predictive ordinate to monitor multivariate spatial disease data. The proposed surveillance technique, which is defined for each small area and time period as the conditional predictive distribution of those counts of disease higher than expected given the data observed up to the previous t…

Lead-time and overdiagnosis estimation in neuroblastoma screening.

2003

In Germany, neuroblastoma is the most frequent extracranial solid childhood tumour. Its properties made it seem an ideal candidate for screening. A German trial assessed the effect of screening at one year of age from 1995-2001 in a nationwide project. We present here the methods developed for the estimation of lead-time and overdiagnosis in this project. Follow up on 1.5 million screened children and 2.1 million control children is currently available until June 2002. Ascertainment of control cohort cases and false negative cases is complete up to this date. A method for determining an empirical lead-time distribution and overdiagnosis estimate from comparing the age specific incidences in…

Spatio-temporal small area surveillance of the COVID-19 pandemic

2022

Abstract The emergence of COVID-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with small units of analysis, are a priority in this context. These models provide geographically detailed and temporally updated overviews of the current state of the pandemic, making public health interventions more effective. These models also allow estimating epidemiological indicators highly demanded for COVID-19 surveillance, such as the instantaneous reproduction number R t , even for small areas. In this paper, we propose a new spatio-temporal spline model particularly suited for COVID-19 surveillance, which allows estimating a…

Les chiffres du crime en débat. Pour une exploitation raisonnée des statistiques pénales en sciences sociales

2007

Mini-drones swarms and their potential in conflict situations

2021

Drones are currently used for a wide range of operations, such as border surveillance, general surveillance, reconnaissance, transport, aerial photography, traffic control, earth observation, communications, broadcasting, and armed attacks. This paper examines the swarming and associated abilities to overwhelm a combatant as well as bring extra functionality by means of extra sensors spread throughout the swarm. The strategy of stealth is becoming increasingly less effective. Combatants can not only sense them, but can also successfully destroy them (although this cannot be said for nano-drones). For mini-drones, objectives can be enhanced by the strategy of overwhelming. peerReviewed

Sorveglianza e governamentalità

2023

The essay looks for the new forms of surveillance in our digital societies, under the perspective of the foucauldian category of Governementality.

Antibakteriālo līdzekļu patēriņš un tā izmaiņas Latvijas slimnīcās

2013

Elektroniskā versija nesatur pielikumus