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Predicting Malaria Transmission Risk in Endemic Areas of Iran: A Multilevel Modeling Using Climate and Socioeconomic Indicators Publisher



Sheikhzadeh K1 ; Haghdoost AA1 ; Bahrampour A1, 2 ; Raeisi A3 ; Zolala F1 ; Farzadfar F4 ; Kasaeian A5 ; Parsaeian M4, 6
Authors
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Authors Affiliations
  1. 1. Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
  2. 2. Department of Biostatistics and Epidemiology, Faculty of Health, Kerman University of Medical Sciences, Kerman, Iran
  3. 3. Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Hematology-Oncology and Stem Cell Transplantation Research Center, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Source: Iranian Red Crescent Medical Journal Published:2017


Abstract

Background: Over the past years, the malaria elimination program has considerably decreased the malaria indigenous cases and confined their incidence to the southeastern areas of Iran encompassing 28 less developed counties with favorable transmission conditions. Objectives: The aim of the study was to investigate the effects of climatic and socioeconomic indicators on malaria transmission and to predict malaria transmission risk until 2025 for all the southeastern endemic counties in Iran. Methods: The aggregated data from indigenous malaria cases, as well as, climatic and socioeconomic indicators of malaria endemic areas were collected on the monthly basis from each county between 2005 and 2015. The collected variables were, then, estimated until 2025 using time series analysis. Considering the nature of these data, two different multilevel models were implemented for vivax and falciparum based on the socioeconomic variable that was used. Finally, applying two different models, two sets of estimates were obtained for malaria transmission risk in each county. Results: The annual decline of malaria transmission was estimated to be 17% based on model 1, and 25% based on the model 2 for vivax (P < 0.001). These estimates were 13% and 21% for falciparum (P < 0.001), respectively. For every increased unit in the wealth index, malaria transmission for vivax and falciparum decreased by 33% (P = 0.001) and 12% (P = 0.54), respectively. Also, for every increase in the mean years of schooling, the transmission decreased by 65% (P < 0.001) and 57% (P = 0.001) for vivax and falciparum. Conclusions: The results of this study, using climatic variables along with socioeconomic variables, indicated the obvious influence of socioeconomic status improvement on decreasing malaria transmission. According to the results, malaria transmission risk will considerably diminish in the next few years. The pattern of malaria transmission decline was consistent with the declining trend of malaria incidence which will move from the west to the east and from the north to the south in the years to come. The transmission risk for falciparum was considerably lower than that of vivax and the endemic areas of falciparum move towards 0 faster than vivax. © 2017, Iranian Red Crescent Medical Journal.