Spatial clustering of livestock Anthrax events associated with agro-ecological zones in Kenya, 1957-2017.


Journal

BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551

Informations de publication

Date de publication:
18 Feb 2021
Historique:
received: 01 07 2020
accepted: 04 02 2021
entrez: 19 2 2021
pubmed: 20 2 2021
medline: 20 3 2021
Statut: epublish

Résumé

Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957-2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region. Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects. The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country (p < 0.05). Interestingly, cattle were > 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August (P = 0.034) and December (P = 0.061), months that follow long and short rain periods, respectively. Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots.

Sections du résumé

BACKGROUND BACKGROUND
Developing disease risk maps for priority endemic and episodic diseases is becoming increasingly important for more effective disease management, particularly in resource limited countries. For endemic and easily diagnosed diseases such as anthrax, using historical data to identify hotspots and start to define ecological risk factors of its occurrence is a plausible approach. Using 666 livestock anthrax events reported in Kenya over 60 years (1957-2017), we determined the temporal and spatial patterns of the disease as a step towards identifying and characterizing anthrax hotspots in the region.
METHODS METHODS
Data were initially aggregated by administrative unit and later analyzed by agro-ecological zones (AEZ) to reveal anthrax spatio-temporal trends and patterns. Variations in the occurrence of anthrax events were estimated by fitting Poisson generalized linear mixed-effects models to the data with AEZs and calendar months as fixed effects and sub-counties as random effects.
RESULTS RESULTS
The country reported approximately 10 anthrax events annually, with the number increasing to as many as 50 annually by the year 2005. Spatial classification of the events in eight counties that reported the highest numbers revealed spatial clustering in certain administrative sub-counties, with 12% of the sub-counties responsible for over 30% of anthrax events, whereas 36% did not report any anthrax disease over the 60-year period. When segregated by AEZs, there was significantly greater risk of anthrax disease occurring in agro-alpine, high, and medium potential AEZs when compared to the agriculturally low potential arid and semi-arid AEZs of the country (p < 0.05). Interestingly, cattle were > 10 times more likely to be infected by B. anthracis than sheep, goats, or camels. There was lower risk of anthrax events in August (P = 0.034) and December (P = 0.061), months that follow long and short rain periods, respectively.
CONCLUSION CONCLUSIONS
Taken together, these findings suggest existence of certain geographic, ecological, and demographic risk factors that promote B. anthracis persistence and trasmission in the disease hotspots.

Identifiants

pubmed: 33602160
doi: 10.1186/s12879-021-05871-9
pii: 10.1186/s12879-021-05871-9
pmc: PMC7890876
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

191

Subventions

Organisme : Defense Threat Reduction Agency
ID : HDTRA11710043.

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Auteurs

Leonard M Nderitu (LM)

Paul G Allen School for Global Health, Washington State University, Pullman, Washington, USA.
Washington State University Global `Health Program-Kenya, WSU, Nairobi, Kenya.

John Gachohi (J)

Washington State University Global `Health Program-Kenya, WSU, Nairobi, Kenya. john.gachohi@wsu.edu.
School of Public Health, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya. john.gachohi@wsu.edu.

Frederick Otieno (F)

International Livestock Research Institute, Nairobi, Kenya.

Eddy G Mogoa (EG)

University of Nairobi, College of Agriculture and Veterinary Sciences, Nairobi, Kenya, University of Nairobi, Nairobi, Kenya.

Mathew Muturi (M)

International Livestock Research Institute, Nairobi, Kenya.
Kenya Zoonotic Disease Unit, Nairobi, Kenya.

Athman Mwatondo (A)

International Livestock Research Institute, Nairobi, Kenya.
Kenya Zoonotic Disease Unit, Nairobi, Kenya.

Eric M Osoro (EM)

Washington State University Global `Health Program-Kenya, WSU, Nairobi, Kenya.

Isaac Ngere (I)

Washington State University Global `Health Program-Kenya, WSU, Nairobi, Kenya.

Peninah M Munyua (PM)

Division of Global Health Protection, United States Centers for Disease Control and Prevention, Nairobi, Kenya.

Harry Oyas (H)

Kenya Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya.

Obadiah Njagi (O)

Kenya Ministry of Agriculture, Livestock and Fisheries, Nairobi, Kenya.

Eric Lofgren (E)

Paul G Allen School for Global Health, Washington State University, Pullman, Washington, USA.

Thomas Marsh (T)

Paul G Allen School for Global Health, Washington State University, Pullman, Washington, USA.

Marc-Alain Widdowson (MA)

Division of Global Health Protection, United States Centers for Disease Control and Prevention, Nairobi, Kenya.
Institute of Tropical Medicine, Antwerp, Belgium.

Bernard Bett (B)

International Livestock Research Institute, Nairobi, Kenya.

M Kariuki Njenga (MK)

Paul G Allen School for Global Health, Washington State University, Pullman, Washington, USA.
Washington State University Global `Health Program-Kenya, WSU, Nairobi, Kenya.

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Classifications MeSH