Event Abstract

Spatiotemporal patterns of historic animal Anthrax outbreaks in Minnesota and Kazakhstan

  • 1 University of Minnesota Twin Cities, United States
  • 2 S. Seifullin Kazakh Agro Technical University, Kazakhstan

The epidemiological triad recognizes the effect that the interaction between host, pathogen, and environment has on the resulting disease pattern in a population. Yet the influences of each triad component may dramatically vary for different conditions. For example, the recurrence of Anthrax in endemic areas is believed to be correlated with environmental characteristics, suggesting that comparable epidemiological patterns should be evidenced in regions with similar environmental conditions, despite differences in the demographic, socio-economic, and historical backgrounds. The objective here was to compare the spatiotemporal patterns of historic animal Anthrax records from two endemic sites that are located at a similar latitude but have been subjected to different demographic and socio-economic conditions. The spatiotemporal directionality test and scan statistics were used to compare between the sites. The spatiotemporal directionality tests and scan statistics were used to compare between the sites. Reported animal Anthrax cases in Minnesota, USA (n=289 cases between 1912-2014) and Kazakhstan (n=3,997 cases between 1933-2014) were analyzed. Epidemic curves indicated sporadic Anthrax outbreaks in Minnesota, whereas a long-term epidemic was detected in Kazakhstan. A comparable seasonality of the animal Anthrax cases was observed at both sites with a peak in August. The maximum time-span between cases at the same location were 55 and 60 years apart for Minnesota and Kazakhstan respectively. Disease hotspots were recognized in both settings, with spatially overlapping clusters years apart. Distribution of the spatiotemporal cluster radii between study sites supported the suggestion of site-specific control zones. Further studies are needed to investigate the association of trigger events that lead to the space-time specific Anthrax outbreaks at both the sites. Spatiotemporal patterns of Anthrax occurrence in both endemic regions were attributed to multiple potential trigger events including major river floods, changes in land use, agriculture, and susceptible livestock populations. Results here help to understand the long-term epidemiological dynamics of Anthrax while providing suggestions to the design and implementation of prevention and control programs, in endemic settings.

Acknowledgements

This study was funded in part by: 1) AMP: the Minnesota Discovery, Research, and Innovation Economy (MnDRIVE) program of the Office of the Vice President for Research (OVPR) of the University of Minnesota and 2) SKA: Scientific Thematic “Zonification of Kazakhstan according to biosecurity categories with regard to dangerous infectious animal diseases” under the Program #249 of funding scientific researches in agro-industry and environmental management by the Ministry of Agriculture of Kazakhstan

References

Kanankege KST, Abdrakhmanov SK, Alvarez J, Glaser L, Bender JB, Mukhanbetkaliyev YY, Korennoy FI, Kadyrov AS, Abdrakhmanova AS, Perez AM. Comparison of spatiotemporal patterns of historic natural Anthrax outbreaks in Minnesota and Kazakhstan. Plos One. 2019 May 17;14(5):e0217144. doi: 10.1371/journal.pone.0217144. eCollection 2019

Keywords: Anthrax, spatiotemperal model, Minnesota (USA), Kazakhstan, Cluster analisys

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Spatio-temporal surveillance and modeling approaches

Citation: Kanankege KS, Abdrakhmanov S and Perez AM (2019). Spatiotemporal patterns of historic animal Anthrax outbreaks in Minnesota and Kazakhstan. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00067

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Received: 09 Jun 2019; Published Online: 27 Sep 2019.

* Correspondence: Mx. Kaushi S Kanankege, University of Minnesota Twin Cities, St. Paul, United States, kanan009@umn.edu