Evidence map›Paper›PMID 30056641›Full record

ArticleEpidemiology and health2018

Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014-2017 using a hierarchical Bayesian method and the spatial scan statistic.

Erfan Ayubi, Mohammad Barati, Arasb Dabbagh Moghaddam, Ali Reza Khoshdel

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Article in Epidemiology and health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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7citing papers in PubMed
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7 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Erfan AyubiModern Epidemiology Research Center, AJA University of Medical Sciences, Tehran, Iran.
Mohammad BaratiInfectious Diseases Research Center, AJA University of Medical Sciences, Tehran, Iran.
Arasb Dabbagh MoghaddamDepartment of Preventive Medicine, Deputy of Health, AJA University of Medical Sciences, Tehran, Iran.
Ali Reza KhoshdelModern Epidemiology Research Center, AJA University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to map the incidence of cutaneous leishmaniasis (CL) in Iranian army units (IAUs) and to identify possible spatial clusters.

methodsThis ecological study investigated incident cases of CL between 2014 and 2017. CL data were extracted from the CL registry maintained by the deputy of health of AJA University of Medical Sciences. The standardized incidence ratio (SIR) of CL was computed with a Besag, York, and Mollié model. The purely spatial scan statistic was employed to detect the most likely highand low-rate clusters and to obtain the observed-to-expected (O/E) ratio for each detected cluster. The statistical significance of the clusters was assessed using the log likelihood ratio (LLR) test and Monte Carlo hypothesis testing.

resultsA total of 1,144 new CL cases occurred in IAUs from 2014 to 2017, with an incidence rate of 260 per 100,000. Isfahan and Khuzestan Provinces were found to have more CL cases than expected in all studied years (SIR>1), while Kermanshah, Kerman, and Fars Provinces were observed to have been high-risk areas in only some years of the study period. The most significant CL cluster was in Kermanshah Province (O/E, 67.88; LLR, 1,200.62; p<0.001), followed by clusters in Isfahan Province (O/E, 6.02; LLR, 513.24; p<0.001) and Khuzestan Province (O/E, 2.35; LLR, 73.71; p<0.001), while low-rate clusters were located in the northeast areas, including Razavi Khorasan, North Khorasan, Semnan, and Golestan Provinces (O/E, 0.03; LLR, 95.11; p<0.001).

conclusionsThis study identified high-risk areas for CL. These findings have public health implications and should be considered when planning control interventions among IAUs.

Indexed as

Bayes TheoremCluster AnalysisHumansIncidenceIranLeishmaniasis, CutaneousMilitary PersonnelModels, StatisticalSpatial AnalysisCutaneous leishmaniasisIranMilitary personnelSpatial analysis

Identifiers

PMID30056641
PMCPMC6186865

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