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Spatial cluster analysis of human cases of Crimean Congo hemorrhagic fever reported in Pakistan

Overview of attention for article published in Infectious Diseases of Poverty, March 2015
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Title
Spatial cluster analysis of human cases of Crimean Congo hemorrhagic fever reported in Pakistan
Published in
Infectious Diseases of Poverty, March 2015
DOI 10.1186/2049-9957-4-9
Pubmed ID
Authors

Tariq Abbas, Muhammad Younus, Sayyad Aun Muhammad

Abstract

Crimean Congo hemorrhagic fever (CCHF) is a tick-borne viral zoonotic disease that has been reported in almost all geographic regions in Pakistan. The aim of this study was to identify spatial clusters of human cases of CCHF reported in country. Kulldorff's spatial scan statisitc, Anselin's Local Moran's I and Getis Ord Gi* tests were applied on data (i.e. number of laboratory confirmed cases reported from each district during year 2013). The analyses revealed a large multi-district cluster of high CCHF incidence in the uplands of Balochistan province near it border with Afghanistan. The cluster comprised the following districts: Qilla Abdullah; Qilla Saifullah; Loralai, Quetta, Sibi, Chagai, and Mastung. Another cluster was detected in Punjab and included Rawalpindi district and a part of Islamabad. We provide empirical evidence of spatial clustering of human CCHF cases in the country. The districts in the clusters should be given priority in surveillance, control programs, and further research.

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The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 22%
Researcher 10 20%
Student > Master 7 14%
Student > Postgraduate 3 6%
Professor > Associate Professor 3 6%
Other 6 12%
Unknown 11 22%
Readers by discipline Count As %
Medicine and Dentistry 11 22%
Environmental Science 5 10%
Agricultural and Biological Sciences 5 10%
Immunology and Microbiology 3 6%
Veterinary Science and Veterinary Medicine 3 6%
Other 11 22%
Unknown 13 25%