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1.
Asian Pacific Journal of Tropical Biomedicine ; (12): 232-239, 2019.
Article in Chinese | WPRIM | ID: wpr-950357

ABSTRACT

Objective: To establish an early warning system for cutaneous leishmaniasis in Fars province, Iran in 2016. Methods: Time-series data were recorded from 29 201 cutaneous leishmaniasis cases in 25 cities of Fars province from 2010 to 2015 and were used to fit and predict the cases using time-series models. Different models were compared via Akaike information criterion/Bayesian information criterion statistics, residual analysis, autocorrelation function, and partial autocorrelation function sample/model. To decide on an outbreak, four endemic scores were evaluated including mean, median, mean + 2 standard deviations, and median + interquartile range of the past five years. Patients whose symptoms of cutaneous leishmaniasis began from 1 January 2010 to 31 December 2015 were included, and there were no exclusion criteria. Results: Regarding four statistically significant endemic values, four different cutaneous leishmaniasis space-time outbreaks were detected in 2016. The accuracy of all four endemic values was statistically significant (P<0.05). Conclusions: This study presents a protocol to set early warning systems regarding time and space features of cutaneous leishmaniasis in four steps: (i) to define endemic values based on which we could verify if there is an outbreak, (ii) to set different time-series models to forecast cutaneous leishmaniasis in future, (iii) to compare the forecasts with endemic values and decide on space-time outbreaks, and (iv) to set an alarm to health managers.

2.
Asian Pacific Journal of Tropical Biomedicine ; (12): 359-364, 2019.
Article in Chinese | WPRIM | ID: wpr-950338

ABSTRACT

Objective: To determine the endemic values of cutaneous leishmaniasis in different cities of Fars province, Iran. Methods: Totally, 29 201 cases registered from 2010 to 2015 in Iranian Fars province were selected, and the endemic values of cutaneous leishmaniasis were determined by retrospective clusters derived from spatiotemporal permutation modeling on a time-series design. The accuracy of the values was assessed using receiver operating characteristic (ROC) curve. SPSS version 22, ArcGIS, and ITSM 2002 software tools were used for analysis. Results: Nine statistically significant retrospective clusters (P<0.05) resulted in finding seven significant and accurate endemic values (P<0.1). These valid endemic scores were generalized to the other 18 cities based on 6 different climates in the province. Conclusions: Retrospectively detected clusters with the help of ROC curve analysis could help determine cutaneous leishmaniasis endemic values which are essential for future prediction and prevention policies in the area.

3.
Asian Pacific Journal of Tropical Biomedicine ; (12): 478-484, 2018.
Article in Chinese | WPRIM | ID: wpr-950408

ABSTRACT

Objective: To determine whether permutation scan statistics was more efficient in finding prospective spatial-temporal outbreaks for cutaneous leishmaniasis (CL) or for malaria in Fars province, Iran in 2016. Methods: Using time-series data including 29 177 CL cases recorded during 2010-2015 and 357 malaria cases recorded during 2010-2015, CL and malaria cases were predicted in 2016. Predicted cases were used to verify if they followed uniform distribution over time and space using space-time analysis. To testify the uniformity of distributions, permutation scan statistics was applied prospectively to detect statistically significant and non-significant outbreaks. Finally, the findings were compared to determine whether permutation scan statistics worked better for CL or for malaria in the area. Prospective permutation scan modeling was performed using SatScan software. Results: A total of 5 359 CL and 23 malaria cases were predicted in 2016 using time-series models. Applied time-series models were well-fitted regarding auto correlation function, partial auto correlation function sample/model, and residual analysis criteria (P

4.
Journal of Health Sciences and Surveillance System. 2015; 3 (4): 160-164
in English | IMEMR | ID: emr-174644

ABSTRACT

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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