Provincial clustering of malaria in Iran between 2005 and 2014

Objective: To reveal the provincial clustering of malaria in Iran between 2005 and 2014 based on the epidemiologic factors and the climatic indicators affecting the disease. Methods: This was a descriptive-analytical study using malaria and meteorological data from the Malaria Elimination Programme...

Full description

Bibliographic Details
Published in:Asian Pacific Journal of Tropical Medicine
Main Authors: Vahid Moqarabzadeh, Ahmad Ali Enayati, Ahmad Raeisi, Fatemeh Nikpour, Jamshid Yazdani Charati
Format: Article in Journal/Newspaper
Language:English
Published: Wolters Kluwer Medknow Publications 2020
Subjects:
malaria
cluster analysis
iran
Arctic medicine. Tropical medicine
RC955-962
Arctic
Online Access:https://doi.org/10.4103/1995-7645.280223
https://doaj.org/article/83683190c90f4fac9cc0d09ce8c4043a
Description
Summary:Objective: To reveal the provincial clustering of malaria in Iran between 2005 and 2014 based on the epidemiologic factors and the climatic indicators affecting the disease. Methods: This was a descriptive-analytical study using malaria and meteorological data from the Malaria Elimination Programme of the Ministry of Health and Medical Education and National Meteorological Organization. After standardization, the aggregate data was used to produce 10-year means for each province. The data analysis included grouping the provinces with respect to factors using hierarchical clustering method and Kruskal-Wallis test to examine the difference between clusters using SPSS ver.23. Results: The hierarchical clustering stratified the provinces’ in 5 clusters. Kruskal-Wallis H test revealed a significant difference in the incidence rate per 100 000 population (P=0.001), male gender (P=0.001), Iranian nationality (P=0.001), Afghan nationality (P=0.003), Pakistani nationality (P=0.001), urban residence (P=0.006), rural residence (P=0.004), autochthonous cases (P=0.007), average minimum temperature (P=0.001), average maximum temperature (P=0.007), average relative humidity (P=0.011), average pressure level (P=0.038), prevailing wind direction (P=0.023), average wind speed (P=0.031) and average precipitation sum (P=0.002) among the clusters. Conclusions: The results of this study and stratification of the provinces could help health policy makers to better manage malaria by allocating resources accordingly.

Similar Items