Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection

Malaria and leishmaniasis are among the two most important health problems of many developing countries especially in the Middle East and North Africa. It is common for vector-borne infectious diseases to have similar hotspots which may be attributed to the overlapping ecological distribution of the...

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Main Authors: ADEGBOYE, O. A., AL-SAGHIR, M., LEUNG, Denis H. Y.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/soe_research/1984
https://ink.library.smu.edu.sg/context/soe_research/article/2983/viewcontent/joint_spatial_timeseries_epidemiological_analysis_of_malaria_and_cutaneous_leishmaniasis_infection.pdf
https://ink.library.smu.edu.sg/context/soe_research/article/2983/filename/0/type/additional/viewcontent/S0950268816002764sup001.pdf
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spelling sg-smu-ink.soe_research-29832020-01-20T03:49:15Z Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection ADEGBOYE, O. A. AL-SAGHIR, M. LEUNG, Denis H. Y. Malaria and leishmaniasis are among the two most important health problems of many developing countries especially in the Middle East and North Africa. It is common for vector-borne infectious diseases to have similar hotspots which may be attributed to the overlapping ecological distribution of the vector. Hotspot analyses were conducted to simultaneously detect the location of local hotspots and test their statistical significance. Spatial scan statistics were used to detect and test hotspots of malaria and cutaneous leishmaniasis (CL) in Afghanistan in 2009. A multivariate negative binomial model was used to simultaneously assess the effects of environmental variables on malaria and CL. In addition to the dependency between malaria and CL disease counts, spatial and temporal information were also incorporated in the model. Results indicated that malaria and CL incidence peaked at the same periods. Two hotspots were detected for malaria and three for CL. The findings in the current study show an association between the incidence of malaria and CL in the studied areas of Afghanistan. The incidence of CL disease in a given month is linked with the incidence of malaria in the previous month. Co-existence of malaria and CL within the same geographical area was supported by this study, highlighting the presence and effects of environmental variables such as temperature and precipitation. People living in areas with malaria are at increased risk for leishmaniasis infection. Local healthcare authorities should consider the co-infection problem by recommending systematic malaria screening for all CL patients. 2017-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1984 info:doi/10.1017/S0950268816002764 https://ink.library.smu.edu.sg/context/soe_research/article/2983/viewcontent/joint_spatial_timeseries_epidemiological_analysis_of_malaria_and_cutaneous_leishmaniasis_infection.pdf https://ink.library.smu.edu.sg/context/soe_research/article/2983/filename/0/type/additional/viewcontent/S0950268816002764sup001.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Co-infection cutaneous leishmaniasis malaria negative binomial overdispersion spatio-temporal time series Econometrics Medicine and Health Sciences
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Co-infection
cutaneous leishmaniasis
malaria
negative binomial
overdispersion
spatio-temporal
time series
Econometrics
Medicine and Health Sciences
spellingShingle Co-infection
cutaneous leishmaniasis
malaria
negative binomial
overdispersion
spatio-temporal
time series
Econometrics
Medicine and Health Sciences
ADEGBOYE, O. A.
AL-SAGHIR, M.
LEUNG, Denis H. Y.
Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
description Malaria and leishmaniasis are among the two most important health problems of many developing countries especially in the Middle East and North Africa. It is common for vector-borne infectious diseases to have similar hotspots which may be attributed to the overlapping ecological distribution of the vector. Hotspot analyses were conducted to simultaneously detect the location of local hotspots and test their statistical significance. Spatial scan statistics were used to detect and test hotspots of malaria and cutaneous leishmaniasis (CL) in Afghanistan in 2009. A multivariate negative binomial model was used to simultaneously assess the effects of environmental variables on malaria and CL. In addition to the dependency between malaria and CL disease counts, spatial and temporal information were also incorporated in the model. Results indicated that malaria and CL incidence peaked at the same periods. Two hotspots were detected for malaria and three for CL. The findings in the current study show an association between the incidence of malaria and CL in the studied areas of Afghanistan. The incidence of CL disease in a given month is linked with the incidence of malaria in the previous month. Co-existence of malaria and CL within the same geographical area was supported by this study, highlighting the presence and effects of environmental variables such as temperature and precipitation. People living in areas with malaria are at increased risk for leishmaniasis infection. Local healthcare authorities should consider the co-infection problem by recommending systematic malaria screening for all CL patients.
format text
author ADEGBOYE, O. A.
AL-SAGHIR, M.
LEUNG, Denis H. Y.
author_facet ADEGBOYE, O. A.
AL-SAGHIR, M.
LEUNG, Denis H. Y.
author_sort ADEGBOYE, O. A.
title Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
title_short Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
title_full Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
title_fullStr Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
title_full_unstemmed Joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
title_sort joint spatial time series epidemiological analysis of malaria and cutaneous leishmaniasis infection
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/soe_research/1984
https://ink.library.smu.edu.sg/context/soe_research/article/2983/viewcontent/joint_spatial_timeseries_epidemiological_analysis_of_malaria_and_cutaneous_leishmaniasis_infection.pdf
https://ink.library.smu.edu.sg/context/soe_research/article/2983/filename/0/type/additional/viewcontent/S0950268816002764sup001.pdf
_version_ 1770573489919492096