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Spatiotemporal Frameworks for Infectious Disease Diffusion and Epidemiology
Open AccessArticle

Spatially Correlated Time Series and Ecological Niche Analysis of Cutaneous Leishmaniasis in Afghanistan

1
Department of Mathematics, Physics and Statistics, Qatar University, 2713 Doha, Qatar
2
Department of Information Technology, American University of Nigeria, 640001 Yola, Nigeria
*
Author to whom correspondence should be addressed.
Academic Editor: Peter Congdon
Int. J. Environ. Res. Public Health 2017, 14(3), 309; https://doi.org/10.3390/ijerph14030309
Received: 31 October 2016 / Accepted: 3 March 2017 / Published: 17 March 2017
(This article belongs to the Special Issue Spatio-temporal Frameworks for Infectious Disease Epidemiology)
Leishmaniasis is the third most common vector-borne disease and a very important protozoan infection. Cutaneous leishmaniasis is one of the most common types of leishmaniasis infectious diseases with up to 1.2 million occurrences of new cases each year worldwide. A dynamic transmission multivariate time series model was applied to the data to account for overdispersion and evaluate the effects of three environmental layers as well as seasonality in the data. Furthermore, ecological niche modeling was used to study the geographically suitable conditions for cutaneous leishmaniasis using temperature, precipitation and altitude as environmental layers, together with the leishmaniasis presence data. A retrospective analysis of the cutaneous leishmaniasis spatial data in Afghanistan between 2003 and 2009 indicates a steady increase from 2003 to 2007, a small decrease in 2008, and then another increase in 2009. An upward trend and regularly repeating patterns of highs and lows were observed related to the months of the year, which suggests seasonality effect in the data. Two peaks were observed in the disease occurrence—January to March and September to December—which coincide with the cold period. Ecological niche modelling indicates that precipitation has the greatest contribution to the potential distribution of leishmaniasis. View Full-Text
Keywords: ecological niche model; environment; overdispersion; negative binomial; leishmaniasis; infectious disease ecological niche model; environment; overdispersion; negative binomial; leishmaniasis; infectious disease
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MDPI and ACS Style

Adegboye, O.A.; Adegboye, M. Spatially Correlated Time Series and Ecological Niche Analysis of Cutaneous Leishmaniasis in Afghanistan. Int. J. Environ. Res. Public Health 2017, 14, 309. https://doi.org/10.3390/ijerph14030309

AMA Style

Adegboye OA, Adegboye M. Spatially Correlated Time Series and Ecological Niche Analysis of Cutaneous Leishmaniasis in Afghanistan. International Journal of Environmental Research and Public Health. 2017; 14(3):309. https://doi.org/10.3390/ijerph14030309

Chicago/Turabian Style

Adegboye, Oyelola A.; Adegboye, Majeed. 2017. "Spatially Correlated Time Series and Ecological Niche Analysis of Cutaneous Leishmaniasis in Afghanistan" Int. J. Environ. Res. Public Health 14, no. 3: 309. https://doi.org/10.3390/ijerph14030309

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