Abstract
Understanding human and animal mobility patterns is a key to predict local and global disease spread. We analysed the nomad herds’ movement network in a pilot area of northern Senegal and used exponential random graph models (ERGM) to investigate the reasons behind these movements. We interviewed 132 nomadic herders to collect information about nomad herd structures, movements, and reasons for taking specific routes or gathering in certain areas. We constructed a spatially explicit network with villages as the nodes and nomad herds’ movements as the connecting edges. The final ERGM showed that node and edge attributes such as presence of cattle in the herd (odds ratio = 12, CI: 5.3, 27.3), morbidity (odds ratio = 3.6, CI: 2.3, 5.7), and lack of water (odds ratio = 2, CI: 1.3, 3.1) were important predictors of nomad herds’ movements. This study not only provides valuable information for monitoring important livestock diseases such as Rift Valley Fever in Senegal, but also helps implement outreach, education, and intervention programs for other emerging and endemic diseases affecting nomadic herds.
| Original language | English (US) |
|---|---|
| Journal | Transboundary and Emerging Diseases |
| DOIs | |
| State | Published - Jan 1 2019 |
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Keywords
- ERGM
- livestock
- network analysis
- nomadic
- risk-based surveillance
- Senegal
ASJC Scopus subject areas
- Immunology and Microbiology(all)
- veterinary(all)
Cite this
Application of exponential random graph models to determine nomadic herders’ movements in Senegal. / Belkhiria, Jaber; Lo, Modou Moustapha; Sow, Fafa; Martinez Lopez, Beatriz; Chevalier, Veronique.
In: Transboundary and Emerging Diseases, 01.01.2019.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Application of exponential random graph models to determine nomadic herders’ movements in Senegal
AU - Belkhiria, Jaber
AU - Lo, Modou Moustapha
AU - Sow, Fafa
AU - Martinez Lopez, Beatriz
AU - Chevalier, Veronique
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Understanding human and animal mobility patterns is a key to predict local and global disease spread. We analysed the nomad herds’ movement network in a pilot area of northern Senegal and used exponential random graph models (ERGM) to investigate the reasons behind these movements. We interviewed 132 nomadic herders to collect information about nomad herd structures, movements, and reasons for taking specific routes or gathering in certain areas. We constructed a spatially explicit network with villages as the nodes and nomad herds’ movements as the connecting edges. The final ERGM showed that node and edge attributes such as presence of cattle in the herd (odds ratio = 12, CI: 5.3, 27.3), morbidity (odds ratio = 3.6, CI: 2.3, 5.7), and lack of water (odds ratio = 2, CI: 1.3, 3.1) were important predictors of nomad herds’ movements. This study not only provides valuable information for monitoring important livestock diseases such as Rift Valley Fever in Senegal, but also helps implement outreach, education, and intervention programs for other emerging and endemic diseases affecting nomadic herds.
AB - Understanding human and animal mobility patterns is a key to predict local and global disease spread. We analysed the nomad herds’ movement network in a pilot area of northern Senegal and used exponential random graph models (ERGM) to investigate the reasons behind these movements. We interviewed 132 nomadic herders to collect information about nomad herd structures, movements, and reasons for taking specific routes or gathering in certain areas. We constructed a spatially explicit network with villages as the nodes and nomad herds’ movements as the connecting edges. The final ERGM showed that node and edge attributes such as presence of cattle in the herd (odds ratio = 12, CI: 5.3, 27.3), morbidity (odds ratio = 3.6, CI: 2.3, 5.7), and lack of water (odds ratio = 2, CI: 1.3, 3.1) were important predictors of nomad herds’ movements. This study not only provides valuable information for monitoring important livestock diseases such as Rift Valley Fever in Senegal, but also helps implement outreach, education, and intervention programs for other emerging and endemic diseases affecting nomadic herds.
KW - ERGM
KW - livestock
KW - network analysis
KW - nomadic
KW - risk-based surveillance
KW - Senegal
UR - http://www.scopus.com/inward/record.url?scp=85065715106&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065715106&partnerID=8YFLogxK
U2 - 10.1111/tbed.13198
DO - 10.1111/tbed.13198
M3 - Article
JO - Transboundary and Emerging Diseases
JF - Transboundary and Emerging Diseases
SN - 1865-1674
ER -