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OBJECTIVE@#To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model.@*METHODS@#The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals' distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC).@*RESULTS@#The study results indicated that SARIMA model (4,1,4)(0,1,0) in general and SARIMA model (4,1,4)(0,1,1) in below and above 15 years age groups could appropriately predict the disease trend in the study area. Moreover, temperature with a three-month delay (lag3) increased the disease trend, rainfall with a four-month delay (lag4) decreased the disease trend, and rainfall with a nine-month delay (lag9) increased the disease trend.@*CONCLUSIONS@#Based on the results, leishmaniasis follows a descending trend in the study area in case drought condition continues, SARIMA models can suitably measure the disease trend, and the disease follows a seasonal trend.
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Objective To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Methods The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals’ distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). Results The study results indicated that SARIMA model (4,1,4)(0,1,0)
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Objective To assess the spatiotemporal trait of cutaneous leishmaniasis (CL) in Fars province, Iran. Methods Spatiotemporal cluster analysis was conducted retrospectively to find spatiotemporal clusters of CL cases. Time-series data were recorded from 29 201 cases in Fars province, Iran from 2010 to 2015, which were used to verify if the cases were distributed randomly over time and place. Then, subgroup analysis was applied to find significant sub-clusters within large clusters. Spatiotemporal permutation scans statistics in addition to subgroup analysis were implemented using SaTScan software. Results This study resulted in statistically significant spatiotemporal clusters of CL (P < 0.05). The most likely cluster contained 350 cases from 1 July 2010 to 30 November 2010. Besides, 5 secondary clusters were detected in different periods of time. Finally, statistically significant sub-clusters were found within the three large clusters (P < 0.05). Conclusions Transmission of CL followed spatiotemporal pattern in Fars province, Iran. This can have an important effect on future studies on prediction and prevention of CL.
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Background: Cutaneous Leishmaniasis [CL] is endemic in many parts of Iran. This study was conducted to investigate the fauna and some biologic factors of sand flies and detect CL vector[s] in Kharameh district which is one of the most important foci of the disease in Fars province, southern Iran
Methods: To identify the fauna, a total of 1549 sand flies were collected from April 2014 to March 2015. To determine the monthly activity, sand flies were collected from indoor and outdoor areas of the lowland and the highland regions
Results: Ten species of phlebotomine [four Phlebotomus spp. And six Sergentomyia spp.] were identified and Phlebotomus papatasi was the dominant species [53.45%]. To determine the sand flies naturally infected by Leishmania spp., 188 female sand flies [145 P. papatasi, 29 P. sergenti, and 14 P. alexandri] were subjected to polymerase chain reaction [PCR] assay. Two [13.16%] specimens of P. papatasi were found to be positive for Leishmania major
Conclusions: To the best of our knowledge, this is the first PCR detection of L. major within naturally infected P. Papatasis and fly as the main vector in this region of south Iran
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Background: Gastrointestinal tract cancer [GI.C] is one of the common cancers in world-wide. The incidence rate of it is different in various geographical regions. This study was performed to assess spatial clusters of the occurrence of GI.C in Fars Province
Methods: In this cross sectional study, the new cases were 4569 cases from 2001 to 2009. The crude incidence rates were standardized based on world population for both sexes. The spatial analysis was conducted using the geographical information systems. We used the local Indicators of spatial association measure, in order to identify local spatial clusters
Results: From a total of the new cases, 62.8% cases were male. The most common GI.Cs were stomach and colorectal cancer in men and women respectively. The significant cluster patterns were discovered from 2002 to 2007. The common type of spatial clustering was a high-high cluster, that to indicate from North-west to South-east of Fars Province
Conclusions: Analysis of the geographical distribution of GI.C will provide opportunities for policymakers for applying preventive measures. Furthermore, it could be helpful for researchers for future epidemiological studies for investigation of etiological agents in regions with significant spatial clustering of high incidence of cancer
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Cancer is a major health problem in the developing countries. Variations of its incidence rate among geographical areas are due to various contributing factors. This study was performed to assess the spatial patterns of cancer incidence in the Fars Province, based on cancer registry data and to determine geographical clusters. In this cross sectional study, the new cases of cancer were recorded from 2001 to 2009. Crude incidence rate was estimated based on age groups and sex in the counties of the Fars Province. Age standardized incidence rates [ASR] per 100,000 was calculated in each year. Spatial autocorrelation analysis was performed in measuring the geographic patterns and clusters using geographic information system [GIS]. Also, comparisons were made between ASRs in each county. A total of 28, 411 new cases were diagnosed with cancer during 2001-2009 in the Fars Province, 55.5% of which were men. The average age was 61.6 +/- 0.5 years. The highest ASR was observed in Shiraz, which is the largest county in Fars. The Moran's Index of cancer was significantly clustered in 2004, 2005, and 2006 in total, men, and women. The type of spatial clustering was high-high cluster, that to indicate from north-west to south-east of Fars Province. Analysis of the spatial distribution of cancer shows significant differences from year to year and between different areas. However, a clear spatial autocorrelation is observed, which can be of great interest and importance to researchers for future epidemiological studies, and to policymakers for applying preventive measures
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Humans , Female , Male , Cross-Sectional Studies , Spatial Analysis , Geographic Information SystemsABSTRACT
The burden of non-communicable diseases is rising globally. The present study was carried out to examine the relationship between different anthropometric indices and blood pressure in the Iranian population. A cross-sectional descriptive study was conducted on 3916 subjects including 1976 males and 1940 females, aged 15-64 years from a healthy population in Shiraz, IR Iran. Anthropometric variables of each person including weight, height, waist circumference [WC], waist to height ratio [WHR] and body mass index [BMI] were calculated along with measuring systolic and diastolic blood pressures [BP]. The relationship between blood pressure and different anthropometric variables was determined in both genders. The mean +/- SD systolic blood pressures were 123.9 +/- 20.0 and 121.2 +/- 17.7 mmHg while the mean diastolic blood pressures were 78.3 +/- 11.9 and 77.4 +/- 12.9 mmHg in men and women respectively [P<0.001]. The prevalence of hypertension in men [23.8%] was significantly more than that of women [21.1%]. Mean systolic and diastolic blood pressures increased with age and BMI in both genders. Anthropometric indices showed a positive association with systolic and diastolic blood pressures. The BMI and WC showed a strong association with systolic and diastolic blood pressure. The suggested lower cut-off values of the anthropometric indicators will cover maximum of the population with higher odds of having hypertension and may help reduce the levels of populations mean blood pressure