Publication Type

Journal Article

Version

publishedVersion

Publication Date

3-2017

Abstract

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.

Keywords

Co-infection, cutaneous leishmaniasis, malaria, negative binomial, overdispersion, spatio-temporal, time series

Discipline

Econometrics | Medicine and Health Sciences

Research Areas

Econometrics

Publication

Epidemiology and Infection

Volume

145

Issue

4

First Page

685

Last Page

700

ISSN

0950-2688

Identifier

10.1017/S0950268816002764

Publisher

Cambridge University Press

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1017/S0950268816002764

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