1. K-State home
  2. »Network Science and Engineering Group
  3. »NetSE Projects
  4. »Network Science Projects
  5. »Modeling a Rift Valley fever risk surveillance system and testing efficient mitigation strategies for the United States

Network Science and Engineering Group

Contact us

3108 Engineering Hall
1701D Platt St.
Manhattan, KS 66506
785-532-5600
Fax: 785-532-1188

Hours: 8 am-12pm, 1pm-5pm M-F

Modeling a Rift Valley fever risk surveillance system and testing efficient mitigation strategies for the United States

Rift Valley Fever virus (RVFv) has been expanding its geographical distribution with important implications for both human and animal health. The emergence of Rift Valley Fever (RVF) in the Middle East, and its continuing presence in many areas of Africa, has negatively impacted both medical and veterinary morbidity, mortality, and economic endpoints. Furthermore, worldwide attention should be directed towards the broader infection dynamics of RVFv, since suitable host, vector and environmental conditions for additional epidemics likely exist on other continents; including Asia, Europe and the Americas. We propose a new  models of RVF to assess disease spread in both time and in space; with the latter driven as a function of contact networks. Humans and livestock hosts and two species of vector mosquitoes are included in the model either explicitly or implicitly. Our models are based on contact networks, where nodes of the networks can represent either geographical regions and links represent the level of contact between regional pairings for each set of species, or nodes can represent individual animals. The inclusion of specifics on human, animal, and vector movements among regions is important to modeling RVF.

Supported by the Kansas Bioscience Authority for the DHS Center of Excellence for Emerging and Zoonotic Animal Diseases

Investigators

Faculty
Students
  • Ling Xue (PhD)
  • Phillip Schumm (PhD)
  • Ala Fard (MS)
  • Futing Fan (MS)

Summary of Results

stochastic

  • Derived the network level reproduction number and its bounds for Rift Valley fever meta-population model, and studied the role of livestock movement rates and disease parameters on the epidemic threshold of networks,
  • Generalized an explicit expression of a network level reproduction number for a disease involving multiple species with both vertical and horizontal transmission,
  • Completed case study of hypothetical Rift Valley fever virus spread in ranching areas of Texas on hierarchical large scale networks,
  • Developed a stochastic meta-population model to study dynamic transmission of Rift Valley fever,
  • Compared 2010 livestock and human incidence data in three provinces of South Africa with Monte Carlo simulation results.
  • Through a large-scale maximum entropy optimization formulation, we estimated cattle movement parameters to characterize the movements of cattle across 10 Central States and 1034 counties of the United States. Inputs to the estimation problem are taken from the United States Department of Agriculture National Agricultural Statistics Service database. We compared stochastic subpopulation-based movements generated from the estimated parameters to operation-based movements published by the United States Department of Agriculture. For future Census of Agriculture distributions, we proposed a series of questions that enable improvements for our method without compromising the privacy of cattle operations. Our novel method to estimate cattle movements across large US regions characterizes county-level stratified subpopulations of cattle for data-driven livestock modeling. Our estimated movement parameters suggest a significant risk level for US cattle systems.

Publications

L. Xue, H. M. Scott, L. W. Cohnstaedt, C. Scoglio
A network-based meta-population approach to model Rift Valley fever epidemics
Journal of Theoretical Biology, Volume 306, Pages 129–144, 2012

L. Xue, C. Scoglio
The network level reproduction number for infectious diseases with both vertical and horizontal transmission
Mathematical Biosciences, 243: 67-80, 2013

L. Xue, L. W. Cohnstaedt, H. M. Scott, C. Scoglio
A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America
PLOS ONE 8:e62049, 2013

L. Xue, C. Scoglio
Network-level reproduction number and extinction threshold for vector-borne diseases 
Mathematical Biosciences and Engineering 12(3):565-84, 2015

P. Schumm, C. Scoglio, H. M. Scott
An estimation of cattle movement parameters in the Central States of the US
Computers and Electronics in Agriculture, Volume 116, Pages 191-200, 2015

F. Sahneh, F. Fan, C. Scoglio
Generalized Epidemic Modeling Framework – GEMF. Software package 
available at http://ece.k-state.edu/netse/software/index.html, 2015

C. Bosca, M. Riad, S.C. Britch, F.D. Sahneh, A.A. Fard, L.W. Cohnstaedt, K.J. Linthicum, C. Scoglio
Testing Interventions for Rift Valley Fever using an Individual-based Network Model
Submitted, 2015

Data

Data on cattle movements parameters   Cattle Movement Estimates