A. Rezaianzadeh, M. Zare, M. Aliakbarpoor, H. Faramarzi, M. Ebrahimi
{"title":"Space-Time Cluster Analysis of Malaria in Fars Province-Iran","authors":"A. Rezaianzadeh, M. Zare, M. Aliakbarpoor, H. Faramarzi, M. Ebrahimi","doi":"10.5812/IJI.107238","DOIUrl":null,"url":null,"abstract":"Background: Malaria, a mosquito-borne infection, is caused by protozoan parasites invading the red blood cells of both humans and animals. Iran is an endemic site for malaria with 1 - 10 cases per one million dwellers, in which 90% of cases occur in southern parts of Iran. Objectives: to detect space-time clusters of Malaria in Fars province-Iran during 1/1/2011 and 31/12/2015. Methods: 357 malaria cases were recorded from 19 cities of Fars province. Permutation scan modeling was applied retrospectively to detect the outbreaks of malaria during 1/1/2011 and 31/12/2015. SPSS V. 22, ITSM V. 2002, ArcGIS10, and SaTScan9.4.4 software tools were used. The significance level was considered 0.05. Results: Based on the results of the current study, 5 space-time clusters were discovered for malaria, indicating that malaria followed a time-space trend in the area (P value < 0.05). The Most Likely Cluster (MLC) contained almost 50% (6/12) of all cases during 1/7/2015 and 31/7/2015 in Firoozabad (P < 0.05); however, non-statistically significant clusters were detected which had clinically important information on the canons of the outbreaks. Conclusions: Malaria did not occur uniformly in Fars province during 1/1/2011 and 31/12/2015. Detected space-time clusters could help Public health managers and policymakers dedicating clinical staff and facilities to more needy areas and consequently reduce the rate of disease in the area.","PeriodicalId":13989,"journal":{"name":"International Journal of Infection","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Infection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5812/IJI.107238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Background: Malaria, a mosquito-borne infection, is caused by protozoan parasites invading the red blood cells of both humans and animals. Iran is an endemic site for malaria with 1 - 10 cases per one million dwellers, in which 90% of cases occur in southern parts of Iran. Objectives: to detect space-time clusters of Malaria in Fars province-Iran during 1/1/2011 and 31/12/2015. Methods: 357 malaria cases were recorded from 19 cities of Fars province. Permutation scan modeling was applied retrospectively to detect the outbreaks of malaria during 1/1/2011 and 31/12/2015. SPSS V. 22, ITSM V. 2002, ArcGIS10, and SaTScan9.4.4 software tools were used. The significance level was considered 0.05. Results: Based on the results of the current study, 5 space-time clusters were discovered for malaria, indicating that malaria followed a time-space trend in the area (P value < 0.05). The Most Likely Cluster (MLC) contained almost 50% (6/12) of all cases during 1/7/2015 and 31/7/2015 in Firoozabad (P < 0.05); however, non-statistically significant clusters were detected which had clinically important information on the canons of the outbreaks. Conclusions: Malaria did not occur uniformly in Fars province during 1/1/2011 and 31/12/2015. Detected space-time clusters could help Public health managers and policymakers dedicating clinical staff and facilities to more needy areas and consequently reduce the rate of disease in the area.