LIVIVO - Search results -

Search results

Result 1 - 10 of total 47

Search options

Article: A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic: The COVID-19 Application in Italy.

Savini, Lara / Candeloro, Luca / Calistri, Paolo / Conte, Annamaria

2020 Volume 8, Issue 6

Abstract: In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the ... ...

Abstract	In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible-Infectious stochastic model and we estimated a municipality-specific infection contact rate () to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high , due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.
Keywords	covid19
Language	English
Publishing date	2020-06-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2720891-6
ISSN	2076-2607
ISSN	2076-2607
DOI	10.3390/microorganisms8060911
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article: A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic: The COVID-19 Application in Italy

Savini, Lara / Candeloro, Luca / Calistri, Paolo / Conte, Annamaria

Microorganisms. 2020 June 16, v. 8, no. 6

2020

Abstract	In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible–Infectious stochastic model and we estimated a municipality-specific infection contact rate (β) to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high β, due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different β values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.
Keywords	COVID-19 infection ; census data ; humans ; population density ; stochastic processes ; Italy
Language	English
Dates of publication	2020-0616
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2720891-6
ISSN	2076-2607
ISSN	2076-2607
DOI	10.3390/microorganisms8060911
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Article ; Online: Insights for brucellosis eradication in Italy through a model-based spread evaluation in grazing livestock - Sicily case study.

Savini, Lara / Candeloro, Luca / Calistri, Paolo / Di Lorenzo, Alessio / Perilli, Margherita / Giovannini, Armando / De Massis, Fabrizio

Veterinaria italiana

2023 Volume 59, Issue 1, Page(s) 51–63

Abstract: Brucellosis is one of the world's major zoonotic pathogens and is responsible for enormous economic losses as well as considerable human morbidity in endemic areas. Definitive control of human brucellosis requires control of brucellosis in livestock ... ...

Abstract	Brucellosis is one of the world's major zoonotic pathogens and is responsible for enormous economic losses as well as considerable human morbidity in endemic areas. Definitive control of human brucellosis requires control of brucellosis in livestock through practical solutions that can be easily applied to the field. In Italy, brucellosis remains endemic in several southern provinces, particularly in Sicily Region. The purpose of this paper is to describe the developed brucellosis model and its applications, trying to reproduce as faithfully as possible the complex transmission process of brucellosis accounting for the mixing of grazing animals. The model focuses on the contaminated environment rather than on the infected animal, uses real data from the main grazing areas of the Sicily Region, and aims to identify the best control options for minimizing the spread (and the prevalence) and to reach the eradication within the concerned areas. Simulation results confirmed the efficacy of an earlier application of the controls, showed the control should take place 30 days after going to pasture, and the culling time being negligible. Moreover, results highlighted the importance of the timing of both births and grazing pastures (and their interaction) more than other factors. As these factors are region‑specific, the study encourages the adoption of different and new eradication tools, tuned on the grazing and commercial behavior of each region. This study will be further extended to improve the model's adaptability to the real world, with the purpose of making the model an operational tool able to help decision makers in accelerating brucellosis eradication in Italy.
MeSH term(s)	Animals ; Humans ; Sicily/epidemiology ; Livestock ; Brucellosis/epidemiology ; Brucellosis/prevention & control ; Brucellosis/veterinary ; Prevalence
Language	English
Publishing date	2023-03-31
Publishing country	Italy
Document type	Journal Article
ZDB-ID	2536397-9
ISSN	1828-1427 ; 0505-401X
ISSN (online)	1828-1427
ISSN	0505-401X
DOI	10.12834/VetIt.2934.20799.1
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic

Lara Savini / Luca Candeloro / Paolo Calistri / Annamaria Conte

Microorganisms, Vol 8, Iss 911, p

The COVID-19 Application in Italy

2020 Volume 911

Abstract	In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible–Infectious stochastic model and we estimated a municipality-specific infection contact rate () to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high , due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.
Keywords	COVID-19 ; commuting census data ; municipality-specific infection contact rate ; vulnerability ; infectious disease modeling ; Biology (General) ; QH301-705.5 ; covid19
Subject code	910
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: EpiExploreR: A Shiny Web Application for the Analysis of Animal Disease Data.

Savini, Lara / Candeloro, Luca / Perticara, Samuel / Conte, Annamaria

Microorganisms

2019 Volume 7, Issue 12

Abstract: Emerging and re-emerging infectious diseases are a significant public and animal health threat. In some zoonosis, the early detection of virus spread in animals is a crucial early warning for humans. The analyses of animal surveillance data are therefore ...

Abstract	Emerging and re-emerging infectious diseases are a significant public and animal health threat. In some zoonosis, the early detection of virus spread in animals is a crucial early warning for humans. The analyses of animal surveillance data are therefore of paramount importance for public health authorities to identify the appropriate control measure and intervention strategies in case of epidemics. The interaction among host, vectors, pathogen and environment require the analysis of more complex and diverse data coming from different sources. There is a wide range of spatiotemporal methods that can be applied as a surveillance tool for cluster detection, identification of risk areas and risk factors and disease transmission pattern evaluation. However, despite the growing effort, most of the recent integrated applications still lack of managing simultaneously different datasets and at the same time making available an analytical tool for a complete epidemiological assessment. In this paper, we present EpiExploreR, a user-friendly, flexible, R-Shiny web application. EpiExploreR provides tools integrating common approaches to analyze spatiotemporal data on animal diseases in Italy, including notified outbreaks, surveillance of vectors, animal movements data and remotely sensed data. Data exploration and analysis results are displayed through an interactive map, tables and graphs. EpiExploreR is addressed to scientists and researchers, including public and animal health professionals wishing to test hypotheses and explore data on surveillance activities.
Language	English
Publishing date	2019-12-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2720891-6
ISSN	2076-2607
ISSN	2076-2607
DOI	10.3390/microorganisms7120680
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic: The COVID-19 Application in Italy

Savini, Lara / Candeloro, Luca / Calistri, Paolo / Conte, Annamaria

Abstract	In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible-Infectious stochastic model and we estimated a municipality-specific infection contact rate () to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high , due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #599128
Database	COVID19

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾

Article ; Online: A New Weighted Degree Centrality Measure: The Application in an Animal Disease Epidemic.

Candeloro, Luca / Savini, Lara / Conte, Annamaria

PloS one

2016 Volume 11, Issue 11, Page(s) e0165781

Abstract: In recent years researchers have investigated a growing number of weighted heterogeneous networks, where connections are not merely binary entities, but are proportional to the intensity or capacity of the connections among the various elements. ... ...

Abstract	In recent years researchers have investigated a growing number of weighted heterogeneous networks, where connections are not merely binary entities, but are proportional to the intensity or capacity of the connections among the various elements. Different degree centrality measures have been proposed for this kind of networks. In this work we propose weighted degree and strength centrality measures (WDC and WSC). Using a reducing factor we correct classical centrality measures (CD) to account for tie weights distribution. The bigger the departure from equal weights distribution, the greater the reduction. These measures are applied to a real network of Italian livestock movements as an example. A simulation model has been developed to predict disease spread into Italian regions according to animal movements and animal population density. Model's results, expressed as infected regions and number of times a region gets infected, were related to weighted and classical degree centrality measures. WDC and WSC were shown to be more efficient in predicting node's risk and vulnerability. The proposed measures and their application in an animal network could be used to support surveillance and infection control strategy plans.
MeSH term(s)	Animal Diseases/epidemiology ; Animals ; Epidemics ; Models, Theoretical
Language	English
Publishing date	2016-11-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0165781
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Disease persistence on temporal contact networks accounting for heterogeneous infectious periods.

Darbon, Alexandre / Colombi, Davide / Valdano, Eugenio / Savini, Lara / Giovannini, Armando / Colizza, Vittoria

Royal Society open science

2019 Volume 6, Issue 1, Page(s) 181404

Abstract: The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This ... ...

Abstract	The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealistic, as hosts may have different infectious periods, due, for instance, to individual host-pathogen interactions or inhomogeneous access to treatment. While previous work accounted for this heterogeneity in static networks, a full theoretical understanding of the interplay of varying infectious periods and time-evolving contacts is still missing. Here, we consider a susceptible-infectious-susceptible epidemic on a temporal network with host-specific average infectious periods, and develop an analytical framework to estimate the epidemic threshold, i.e. the critical transmissibility for disease spread in the host population. Integrating contact data for transmission with outbreak data and epidemiological estimates, we apply our framework to three real-world case studies exploring different epidemic contexts-the persistence of bovine tuberculosis in southern Italy, the spread of nosocomial infections in a hospital, and the diffusion of pandemic influenza in a school. We find that the homogeneous parametrization may cause important biases in the assessment of the epidemic risk of the host population. Our approach is also able to identify groups of hosts mostly responsible for disease diffusion who may be targeted for prevention and control, aiding public health interventions.
Language	English
Publishing date	2019-01-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2787755-3
ISSN	2054-5703
ISSN	2054-5703
DOI	10.1098/rsos.181404
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: A New Weighted Degree Centrality Measure

Luca Candeloro / Lara Savini / Annamaria Conte

PLoS ONE, Vol 11, Iss 11, p e

The Application in an Animal Disease Epidemic.

2016 Volume 0165781

Abstract	In recent years researchers have investigated a growing number of weighted heterogeneous networks, where connections are not merely binary entities, but are proportional to the intensity or capacity of the connections among the various elements. Different degree centrality measures have been proposed for this kind of networks. In this work we propose weighted degree and strength centrality measures (WDC and WSC). Using a reducing factor we correct classical centrality measures (CD) to account for tie weights distribution. The bigger the departure from equal weights distribution, the greater the reduction. These measures are applied to a real network of Italian livestock movements as an example. A simulation model has been developed to predict disease spread into Italian regions according to animal movements and animal population density. Model's results, expressed as infected regions and number of times a region gets infected, were related to weighted and classical degree centrality measures. WDC and WSC were shown to be more efficient in predicting node's risk and vulnerability. The proposed measures and their application in an animal network could be used to support surveillance and infection control strategy plans.
Keywords	Medicine ; R ; Science ; Q
Subject code	001
Language	English
Publishing date	2016-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Disease persistence on temporal contact networks accounting for heterogeneous infectious periods

Alexandre Darbon / Davide Colombi / Eugenio Valdano / Lara Savini / Armando Giovannini / Vittoria Colizza

Royal Society Open Science, Vol 6, Iss

2019 Volume 1

Abstract	The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealistic, as hosts may have different infectious periods, due, for instance, to individual host–pathogen interactions or inhomogeneous access to treatment. While previous work accounted for this heterogeneity in static networks, a full theoretical understanding of the interplay of varying infectious periods and time-evolving contacts is still missing. Here, we consider a susceptible-infectious-susceptible epidemic on a temporal network with host-specific average infectious periods, and develop an analytical framework to estimate the epidemic threshold, i.e. the critical transmissibility for disease spread in the host population. Integrating contact data for transmission with outbreak data and epidemiological estimates, we apply our framework to three real-world case studies exploring different epidemic contexts—the persistence of bovine tuberculosis in southern Italy, the spread of nosocomial infections in a hospital, and the diffusion of pandemic influenza in a school. We find that the homogeneous parametrization may cause important biases in the assessment of the epidemic risk of the host population. Our approach is also able to identify groups of hosts mostly responsible for disease diffusion who may be targeted for prevention and control, aiding public health interventions.
Keywords	susceptible-infectious-susceptible model ; epidemic spread ; temporal network ; epidemic threshold ; mathematical modelling ; Science ; Q
Subject code	612
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	The Royal Society
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED