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Research Article · Open access · Published 18 October 2014

EPIDEMIOLOGICAL STUDY: LABORATORY DATA MINING IN SOUTH OF JORDAN

Hani Nawafleh1, Amir M. Al Hroob1, Mariam M. Kawafha2 & Khalil I Altaif1

American Journal of Infectious Diseases, Volume 10, Issue 3, pp. 137–141 · doi.org/10.3844/ajidsp.2014.137.141

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Abstract

Introduction: To determine the prevalence of parasitic infection among the population of Ma’an governorate. Methodology: A retrospective data mining of retrieved and analysis laboratory stool specimens records of patients seen in Ma’an Hospital (in different specialties) during the period 1st January 2009 to 31 December 2009 were carried out for the detection of intestinal parasites. Results:-1999 Stool samples were examined; 338 were positive samples (16.9%). The highest incidence of intestinal parasites was during summer months (June -October) and the lowest was during winter months (December-January). Six different parasitic species were detected. The highest frequency was among adult males and females higher than children. Amoebiasis and Giardiasis (80.7% and 15.7%.respectively) were the commonest species detected while Entrobius. vermicularis (0.9%), Strongyloides. Stercoralis (0.6%) and hookworms (0.9%) were the least common. Conclusion:- Intestinal parasite is not a major public health problem in Ma’an governorate. Nevertheless a comprehensive health education program, improvements to environmental sanitation should be developed to keep this health problem under control and activate the role of community nursing to raise community health awareness. Furthermore, a wider survey should be conducted in different health centers in the governorate to obtain a better epidemiological picture of parasitic infection in this region.

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Nawafleh, H., Hroob, A. M. A., Kawafha, M. M. & Altaif, K. I. (2014). EPIDEMIOLOGICAL STUDY: LABORATORY DATA MINING IN SOUTH OF JORDAN. American Journal of Infectious Diseases, 10(3), 137–141. https://doi.org/10.3844/ajidsp.2014.137.141

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EPIDEMIOLOGICAL STUDY: LABORATORY DATA MINING IN SOUTH OF JORDANAmerican Journal of Infectious Diseases · Volume 10, Issue 3 · pp. 137–141 · CC BY 3.0Download