Loading…
Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases
Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several...
Saved in:
Published in: | arXiv.org 2023-01 |
---|---|
Main Authors: | , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Ciss, Mamadou Giacomini, Alessandra Diouf, Mame Nahé Delabouglise, Alexis Mesdour, Asma Katherin Garcia Garcia Munoz, Facundo Cardinale, Eric Lo, Mbargou Adji Marème Gaye Fall, Mathioro Ndiaye, Khady Assane Guèye Fall Catherine Cetre Sossah Apolloni, Andrea |
description | Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study we simulated the introduction of F.A.S.T. (Foot and Mouth Similar Transboundary) diseases in Senegal and used data taken from 2020 Sanitary certificates (LPS, laissez-passer sanitaire) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion. |
format | article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2770818087</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2770818087</sourcerecordid><originalsourceid>FETCH-proquest_journals_27708180873</originalsourceid><addsrcrecordid>eNqNzL2OwjAQBGALCQkEvMNK1EjGAZKeH10PPVolG1hw1sHrQHfPTkD3AFdNMTPfwIxdli0Xxcq5kZmp3qy1bpO79Tobm98daRm5TRwEQg3pSlBiSp4ApQJt0HuIXcOCkhRSxIpAKL1CvAMLHEnogv475qb13J8_VB3i19IuPom9Rynp46NwT0LFSqikUzOs0SvN_nJi5of9afuzaGN4dKTpfAtdlL46uzy3xbKwRZ79b_UGvsdQkA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2770818087</pqid></control><display><type>article</type><title>Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases</title><source>Publicly Available Content Database</source><creator>Ciss, Mamadou ; Giacomini, Alessandra ; Diouf, Mame Nahé ; Delabouglise, Alexis ; Mesdour, Asma ; Katherin Garcia Garcia ; Munoz, Facundo ; Cardinale, Eric ; Lo, Mbargou ; Adji Marème Gaye ; Fall, Mathioro ; Ndiaye, Khady ; Assane Guèye Fall ; Catherine Cetre Sossah ; Apolloni, Andrea</creator><creatorcontrib>Ciss, Mamadou ; Giacomini, Alessandra ; Diouf, Mame Nahé ; Delabouglise, Alexis ; Mesdour, Asma ; Katherin Garcia Garcia ; Munoz, Facundo ; Cardinale, Eric ; Lo, Mbargou ; Adji Marème Gaye ; Fall, Mathioro ; Ndiaye, Khady ; Assane Guèye Fall ; Catherine Cetre Sossah ; Apolloni, Andrea</creatorcontrib><description>Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study we simulated the introduction of F.A.S.T. (Foot and Mouth Similar Transboundary) diseases in Senegal and used data taken from 2020 Sanitary certificates (LPS, laissez-passer sanitaire) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Animal health ; Diffusion ; Disease ; Early warning systems ; Indicators ; Livestock ; Nodes ; Structural analysis ; Surveillance ; Surveillance systems</subject><ispartof>arXiv.org, 2023-01</ispartof><rights>2023. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2770818087?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25753,37012,44590</link.rule.ids></links><search><creatorcontrib>Ciss, Mamadou</creatorcontrib><creatorcontrib>Giacomini, Alessandra</creatorcontrib><creatorcontrib>Diouf, Mame Nahé</creatorcontrib><creatorcontrib>Delabouglise, Alexis</creatorcontrib><creatorcontrib>Mesdour, Asma</creatorcontrib><creatorcontrib>Katherin Garcia Garcia</creatorcontrib><creatorcontrib>Munoz, Facundo</creatorcontrib><creatorcontrib>Cardinale, Eric</creatorcontrib><creatorcontrib>Lo, Mbargou</creatorcontrib><creatorcontrib>Adji Marème Gaye</creatorcontrib><creatorcontrib>Fall, Mathioro</creatorcontrib><creatorcontrib>Ndiaye, Khady</creatorcontrib><creatorcontrib>Assane Guèye Fall</creatorcontrib><creatorcontrib>Catherine Cetre Sossah</creatorcontrib><creatorcontrib>Apolloni, Andrea</creatorcontrib><title>Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases</title><title>arXiv.org</title><description>Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study we simulated the introduction of F.A.S.T. (Foot and Mouth Similar Transboundary) diseases in Senegal and used data taken from 2020 Sanitary certificates (LPS, laissez-passer sanitaire) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion.</description><subject>Animal health</subject><subject>Diffusion</subject><subject>Disease</subject><subject>Early warning systems</subject><subject>Indicators</subject><subject>Livestock</subject><subject>Nodes</subject><subject>Structural analysis</subject><subject>Surveillance</subject><subject>Surveillance systems</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNqNzL2OwjAQBGALCQkEvMNK1EjGAZKeH10PPVolG1hw1sHrQHfPTkD3AFdNMTPfwIxdli0Xxcq5kZmp3qy1bpO79Tobm98daRm5TRwEQg3pSlBiSp4ApQJt0HuIXcOCkhRSxIpAKL1CvAMLHEnogv475qb13J8_VB3i19IuPom9Rynp46NwT0LFSqikUzOs0SvN_nJi5of9afuzaGN4dKTpfAtdlL46uzy3xbKwRZ79b_UGvsdQkA</recordid><startdate>20230122</startdate><enddate>20230122</enddate><creator>Ciss, Mamadou</creator><creator>Giacomini, Alessandra</creator><creator>Diouf, Mame Nahé</creator><creator>Delabouglise, Alexis</creator><creator>Mesdour, Asma</creator><creator>Katherin Garcia Garcia</creator><creator>Munoz, Facundo</creator><creator>Cardinale, Eric</creator><creator>Lo, Mbargou</creator><creator>Adji Marème Gaye</creator><creator>Fall, Mathioro</creator><creator>Ndiaye, Khady</creator><creator>Assane Guèye Fall</creator><creator>Catherine Cetre Sossah</creator><creator>Apolloni, Andrea</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20230122</creationdate><title>Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases</title><author>Ciss, Mamadou ; Giacomini, Alessandra ; Diouf, Mame Nahé ; Delabouglise, Alexis ; Mesdour, Asma ; Katherin Garcia Garcia ; Munoz, Facundo ; Cardinale, Eric ; Lo, Mbargou ; Adji Marème Gaye ; Fall, Mathioro ; Ndiaye, Khady ; Assane Guèye Fall ; Catherine Cetre Sossah ; Apolloni, Andrea</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_27708180873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Animal health</topic><topic>Diffusion</topic><topic>Disease</topic><topic>Early warning systems</topic><topic>Indicators</topic><topic>Livestock</topic><topic>Nodes</topic><topic>Structural analysis</topic><topic>Surveillance</topic><topic>Surveillance systems</topic><toplevel>online_resources</toplevel><creatorcontrib>Ciss, Mamadou</creatorcontrib><creatorcontrib>Giacomini, Alessandra</creatorcontrib><creatorcontrib>Diouf, Mame Nahé</creatorcontrib><creatorcontrib>Delabouglise, Alexis</creatorcontrib><creatorcontrib>Mesdour, Asma</creatorcontrib><creatorcontrib>Katherin Garcia Garcia</creatorcontrib><creatorcontrib>Munoz, Facundo</creatorcontrib><creatorcontrib>Cardinale, Eric</creatorcontrib><creatorcontrib>Lo, Mbargou</creatorcontrib><creatorcontrib>Adji Marème Gaye</creatorcontrib><creatorcontrib>Fall, Mathioro</creatorcontrib><creatorcontrib>Ndiaye, Khady</creatorcontrib><creatorcontrib>Assane Guèye Fall</creatorcontrib><creatorcontrib>Catherine Cetre Sossah</creatorcontrib><creatorcontrib>Apolloni, Andrea</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ciss, Mamadou</au><au>Giacomini, Alessandra</au><au>Diouf, Mame Nahé</au><au>Delabouglise, Alexis</au><au>Mesdour, Asma</au><au>Katherin Garcia Garcia</au><au>Munoz, Facundo</au><au>Cardinale, Eric</au><au>Lo, Mbargou</au><au>Adji Marème Gaye</au><au>Fall, Mathioro</au><au>Ndiaye, Khady</au><au>Assane Guèye Fall</au><au>Catherine Cetre Sossah</au><au>Apolloni, Andrea</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases</atitle><jtitle>arXiv.org</jtitle><date>2023-01-22</date><risdate>2023</risdate><eissn>2331-8422</eissn><abstract>Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study we simulated the introduction of F.A.S.T. (Foot and Mouth Similar Transboundary) diseases in Senegal and used data taken from 2020 Sanitary certificates (LPS, laissez-passer sanitaire) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2023-01 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2770818087 |
source | Publicly Available Content Database |
subjects | Animal health Diffusion Disease Early warning systems Indicators Livestock Nodes Structural analysis Surveillance Surveillance systems |
title | Description of the cattle and small ruminants trade network in Senegal and implication for the surveillance of animal diseases |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T12%3A46%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Description%20of%20the%20cattle%20and%20small%20ruminants%20trade%20network%20in%20Senegal%20and%20implication%20for%20the%20surveillance%20of%20animal%20diseases&rft.jtitle=arXiv.org&rft.au=Ciss,%20Mamadou&rft.date=2023-01-22&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2770818087%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-proquest_journals_27708180873%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2770818087&rft_id=info:pmid/&rfr_iscdi=true |