Presentation at 3rd GRF One Health Summit 2015 Session Integrative Health Risk Management

1. One Health Epidemic Risk
Management in Kazakhstan with
Open-Source EIDSS
Alexey Burdakov 2, Stanislav Kazakov3, Aizhan Esmagambetova1,
Andrey Ukharov2, Damir Kopzhasarov1
1 Committee for Consumer Rights Protection of the Ministry of National Economics
of the Republic of Kazakhstan, Astana, Kazakhstan
2 Black & Veatch, Overland Park, KS, United States of America
3 Scientific and Practical Center for Sanitary Epidemiological Expertise and
Monitoring, Almaty, Kazakhstan
October 5, 2015
GRF 2015
Davos, Switzerland

2. Introduction
 Kazakhstan has natural foci of especially
dangerous pathogens such as plague, tularemia,
anthrax, hemorrhagic fevers, etc.
 World Health Organization (WHO) categorizes
Kazakhstan as a high-risk country for Crimean-Congo
hemorrhagic fever (CCHF)
 CCHF natural foci are present in only 3 of 14 regions,
and only in 27 administrative districts out of 169
 Former USSR countries has standard practice of
sending aggregated digital data on 64 infectious
diseases
 Data is listed according to 3 levels: 1 - district, 2 -
region, 3 – country
 Data has digital and statistical nature, and describes
the epidemic situation over the past period (month,
year)
 Data gives no clue as to the causes and factors
contributing to the growth or reduction of the infectious
incidence rate levels in specific areas
Map of Kazakhstan
Source: www.who.int
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3. Concept
 Objective
 Prevent emergencies of a sanitary-epidemiological nature
 Minimize the damage to the environment and health of the population
 Proposed to develop Regional Sanitary-Epidemiological Passport (RSEP)
 Generated automatically for each and every district of Kazakhstan in real-time
 Based on multi-year databases
 Contains infectious incidence rate dynamics according to the primary (marker) infections
(7 nosologies)
 Includes a forecast for 1-2 years
 Supports predictive GIS maps of natural and soil foci for especially dangerous pathogens (7
nosologies) with a 3-5 year forecast
 To be introduced as a new working tool for field epidemiologists in each district (town)
of Kazakhstan
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4. Regional Sanitary-Epidemiological Passport
(RSEP)
Animal Market in Taraz,
Kazakhstan
Population Density,
Kazakhstan
CCHF Foci Map
Plague Foci Map
Anthrax Outbreaks in
Kazakhstan, 1960-2000
Utilization of Health Services
METHODS
Plague
Tularemia
CCHF
Plague
Tularemia
CCHF
Plague
Tularemia
CCHF
2014 2013 . . .
2014 2013 . . .
2014 2013 . . .
Data Processing
and Forecasting
HistoryCurrentForecast
Increasing
(Critical level)
Epidemic Risks
Stable
(Acceptable level of
sanitary background
impact)
Decreasing
(Less than maximum
during last 10 years)
Regional Sanitary-Epidemiological
Passport (RSEP)
Regional Sanitary-Epidemiological Passport Concept
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5. Open Source Electronic Integrated Disease
Surveillance System (EIDSS)
 Disease surveillance system developed to improve national disease surveillance
 Collect, share and analyze human, veterinary, vector and laboratory data
 One integrated database
 Integration with global data repositories of international entities (WHO, potentially FAO and
OIE)
 Collect case-by-case data for diseases of priority
 Data is collected at the district level and rapidly transferred to the national level
 Near real-time manner
 EIDSS is based on cutting-edge expertise
from CDC, WRAIR,
with more than 100 thousand man-hours
 Open source portal: eidss.codeplex.com
 EIDSS is currently deployed nationally
 Azerbaijan, Georgia, Kazakhstan, Iraq
 Ongoing implementation
 Armenia, Thailand, Ukraine (pending)
EIDSS Implementations Worldwide
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6. EIDSS National Disease Surveillance
System in Kazakhstan
 Implementation in Kazakhstan includes
 All rayons (districts), oblasts (regions) and national level
 586 workstations
 around 800 trained surveillance and laboratory professionals
 covering all 64 reportable diseases (EDP and non-EDP)
KAZAKHSTAN - 400+ sites
HumanVector Diseases: 8249
EIDSS Implementation in Kazakhstan
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7. Crimean-Congo Haemorrhagic Fever Risk
Forecast Example
 EIDSS database loaded with
3 indicator groups for 2007-2011
 Population counts by districts
 Tick infection rate
 CCHF human incidence per 10,000 persons
 Number of people reporting
tick bite complaints
 Forecast for 2013:
 High outbreak
risk estimates –
88.9% accurate
 Medium and low
outbreak risk estimates –
81.3% accurate
CCHF Forecast Map Example
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8. Regional Sanitary-Epidemiological Passport
(RSEP) Development Plan
 STAGE 1: Development of a mathematical RSEP model for Almaty
region
 Plague, tularemia, tick-borne encephalitis, soil foci of anthrax, brucellosis,
and others
 STAGE 2: RSEP developed at stage 1 will be applied to
 South Kazakhstan Province (high population density, high (higher than the
average) level of infectious diseases; borders the Republic of Uzbekistan)
 West Kazakhstan Province (borders the territories of the Russian
Federation)
 East Kazakhstan Province (borders the Russian Federation and the PRC,
which have the common natural foci of plague, tularemia, tick-borne
encephalitis, and others)
 STAGE 3: Verification and Implementation
 Development of regulatory legal base and guiding documents
 Exchange of experiences with the concerned countries of the Central
Asian region and the Caucasus
 Scientific hypothesis verification in 2017
 Implementation and use as a new working tool for field epidemiologists at
district and regional levels
Animal Market in Taraz,
Kazakhstan
Population Density,
Kazakhstan
CCHF Foci Map
Plague Foci Map
Anthrax Outbreaks in
Kazakhstan, 1960-2000
Utilization of Health Services
Plague
Tularemia
CCHF
Plague
Tularemia
CCHF
Plague
Tularemia
CCHF
2014 2013 . . .
2014 2013 . . .
2014 2013 . . .
Data Processing
and Forecasting
HistoryCurrentForecast
Increasing
(Critical level)
Epidemic Risks
Stable
(Acceptable level of
sanitary background
impact)
Decreasing
(Less than maximum
during last 10 years)
Regional Sanitary-Epidemiological
Passport (RSEP)
RSEP
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9. Results
 Proposed concept and methodology for the epidemic risk assessment and
management in the Republic of Kazakhstan’s administrative territories for
implementation as a new working tool (RSEP)
 Validated the concept and methodology on CCHF receiving 81.3% accuracy
(statistical significance is 0.95)
 Epidemic risk assessment and management methodology can be applied regionally
and internationally
 Added value to the One Health approach:
 Methodology brings together data from sanitary-epidemiological, socio-economic, veterinary,
human and vector areas
 Focuses on plague, tularemia, anthrax, CCHF, brucellosis, cholera and other marker diseases,
many of which are zoonotic
 Open-source EIDSS can support national epidemiological e-surveillance systems for both
human and veterinary disease
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10. References
 Esmagambetova, Aizhan; Kazakov, Stanislav; Burdakov, Alexey; Ospanov, Kenes;
Kyraubaev, Kakimzhan; Sansyzbaev, Erlan; Sadovskaya, Veronika; Ukharov,
Andrey (2014). Accuracy of EIDSS Software Prognosis on CCHF Natural Foci Activity
in Kazakhstan. Edward Mensah (ed.), Online Journal of Public Health Informatics, Vol
6, No 1 (2014), OJPHI, USA.
 Burdakov, Alexey; Wahl, Tom; Oukharov, Andrey; Bekshin, Zhandarbek; Kazakov,
Stanislav; Grigorev, Uriy (2014). Strengthening national One Health disease
surveillance with open-source EIDSS. Eskild Petersen (ed.), International Journal of
Infectious Diseases, April 2014, Volume 21, Supplement 1, Page 274, Elsevier Inc.,
USA.
 Burdakov, Alexey; Oukharov, Andrey; Wahl, Tom (2012). Transforming national
human and veterinary disease surveillance systems from paper into integrated
electronic form in the FSU countries. Eskild Petersen (ed.), International Journal of
Infectious Diseases, June 2012, Volume 16, Supplement 1, Pages e123–e124,
Elsevier Inc., USA.
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11. Acknowledgement
 Presentation and research was co-sponsored by Black & Veatch
 Open Source EIDSS development and implementation is funded by
the Defense Threat Reduction Agency (DTRA) of the U.S. DoD
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12. Q&A
 Contact the authors
 Alexey Burdakov burdakovav@bv.com
 Stanislav Kazakov kz2kazakov@mail.ru
 Aizhan Esmagambetova yesmagambetovai@gmail.com
 Andrey Ukharov oukharov@bv.com
 Damir Kopzhasarov damir_aslanovi4@mail.ru
 Open for collaboration
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