Temporal Modeling of Crimean-Congo Hemorrhagic Fever in Iran

Introduction : This study was aimed to investigate the effects of risk factors, and environmental and climatic factors a ffecting the occurrence of Crimean-Congo hemorrhagic fever (CCHF) in Iran. We used temporal modeling to predict the future occurrence of the disease in the country . Methods : We analyzed the data of 165 CCHF patients from all over Iran (e xcept the districts Zabol and Zahedan in Eastern Iran ) during 2000 to 2006. In this study, 130 districts with at least one reported case patient, and 780 districts with no reported case patient, as the control group, were included in the model. Logistic regression was used to design the temporal model of the disease at the district-month level nationwide with the purpose of predicting the occurrence of CCHF disease with in one month in a district. Results: The designed model indicated that the history of previous reports of the disease in a district increased the risk of further reports of the disease (odds ratio: 2.53 (95% CI: 1.61, 3.97), (P ‌ <0.001)). Moreover, w ith each one-million increase in the urban population, the odds of a report of the disease increased 20% (P ‌ =0.003). The odds of the occurrence of the disease were reduced by 9% w ith the increase in e ach degree of latitude (P ‌ =0.028). The odds of the occurrence of the disease increased 6.25 times w ith the increase in e ach kilometer of altitude (P ‌ <0.001). T he disease had a decreasing s ecular trend so that the occurrence of the disease was reduced by 10 ‌ % each year (P ‌ =0.008). Conclusion : Our findings showed that based on the history of CCHF in districts, and population and geographical features, hot zones may be defined with some acceptable accuracy. J Med Microbiol Infec Dis, 2014, 1 (2): 7 pages.