M Karami Jooshin , H Izanloo, A Saghafipour, F Rezaei, M Asadi Ghalhari ,
Volume 14, Issue 4 (Vol.14, No.4, 2019)
Abstract
Background and Objectives: Cholera is one of the communicable diseases that should be reported immediately as a public health threat. This study was conducted to study the probable risk factors of cholera outbreak in Qom, central Iran, during 2017.
Methods: In a case-control study, 37 cholera patients diagnosed based on para - clinical tests and 37 control samples were evaluated. Charts, frequency tables, regression logistic, Chi-square and t-test in SPSS software ver.25 were used for data analysis.
Results: The causative agent in the Qom cholera outbreak was Vibrio cholerae serotype Inaba. Most of the patients (54%) were in the age range 21-40 years. Most of the cholera cases were males (87%), Iranians (81%), and school or college students (30%). The peak of the epidemic occurred in the third week of November 2017, coinciding with a religious event. Nearly half of the patients were identified at the cross-border surveillance centers. The most important risk factors for the outbreak were a history of travel to Iraq in order to attend the Arbaeen religious event (95%), (OR=75, P-value<0.001), and a history of consuming unreliable foods and water (94% and 50%, (OR=66, CI=8-410, P-value=0.00 and OR=11, CI=2.7-46)), respectively.
Conclusion: Cross-border surveillance of cholera in common borders with Iraq, especially in the Arbaeen religious event, played a vital role in identifying patients suspected of cholera. The surveillance of communicable diseases should be strengthened when entering and leaving the Arbaeen event.
M Javanbakht, M Argani, K Ezimand, A Saghafipour,
Volume 17, Issue 1 (Vol 17,No.1, Spring 2021 2021)
Abstract
Background and Objectives: Environmental conditions in different geographical areas provide a basis for the spread of some diseases. Cutaneous leishmaniasis is a serious threat to public health and is one of the arthropod-borne diseases. The prevalence and distribution of this disease is affected by environmental and climatic factors. The aim of this study was to model the Spatio-temporal variations in the incidence rate of this disease based on environmental and ecological criteria.
Methods: The northeast of Iran was selected as the study area. The data used in this study included vegetation, surface temperature, precipitation, evapotranspiration, soil moisture, digital elevation model and sunny hours. The artificial neural network method was used to model the spatio-temporal changes of cutaneous leishmaniasis.
Results: Spatial variations in the incidence of the disease had a north-south trend and decreased from north to south. In addition, two foci were identified in the medium altitude areas in North and South Khorasan provinces. Temporal variations in the incidence of disease in the study period showed that the incidence rate decreased in the two identified foci from 2011 to 2016.
Conclusion: The modeling results showed that the estimated regression coefficient was 0.92 for neural network based on all three types of data (training, validation, test) indicating good quality of constructed neural network. In addition, sensitivity analysis results showed that sunny hours and soil moisture were the most important factors in the model function.
