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基于 ARIMA 模型的沙赫鲁德皮肤利什曼病发病率的时间序列分析。

Time series analysis of cutaneous leishmaniasis incidence in Shahroud based on ARIMA model.

机构信息

Student Research Committee, School of Public Health, Shahroud University of Medical Sciences, Shahroud, Iran.

Student Research Committee, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran.

出版信息

BMC Public Health. 2023 Jun 20;23(1):1190. doi: 10.1186/s12889-023-16121-9.


DOI:10.1186/s12889-023-16121-9
PMID:37340451
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10283195/
Abstract

BACKGROUND: Leishmaniasis is a zoonotic disease and Iran is one of the ten countries with has the highest estimated cases of leishmaniasis. This study aimed to determine the time trend of cutaneous leishmaniasis (CL) incidence using the ARIMA model in Shahroud County, Semnan, Iran. METHODS: In this study, 725 patients with leishmaniasis were selected in the Health Centers of Shahroud during 2009-2020. Demographic characteristics including; history of traveling, history of leishmaniasis, co-morbidity of other family members, history of treatment, underlying disease, and diagnostic measures were collected using the patients' information listed in the Health Ministry portal. The Box-Jenkins approach was applied to fit the SARIMA model for CL incidence from 2009 to 2020. All statistical analyses were done by using Minitab software version 14. RESULTS: The mean age of patients was 28.2 ± 21.3 years. The highest and lowest annual incidence of leishmaniasis were in 2018 and 2017, respectively. The average ten-year incidence was 132 per 100,000 population. The highest and lowest incidence of the disease were 592 and 195 for 100,000 population in the years 2011 and 2017, respectively. The best model was SARIMA (3,1,1) (0,1,2) (AIC: 324.3, BIC: 317.7 and RMSE: 0.167). CONCLUSIONS: This study suggested that time series models would be useful tools for predicting cutaneous leishmaniasis incidence trends; therefore, the SARIMA model could be used in planning public health programs. It will predict the course of the disease in the coming years and run the solutions to reduce the cases of the disease.

摘要

背景:利什曼病是一种人畜共患病,伊朗是估计有最高利什曼病病例的十个国家之一。本研究旨在使用 ARIMA 模型确定伊朗塞姆南省沙赫鲁德县皮肤利什曼病(CL)发病率的时间趋势。

方法:在这项研究中,选择了 2009 年至 2020 年期间沙赫鲁德卫生中心的 725 例利什曼病患者。使用卫生部门户列出的患者信息,收集人口统计学特征,包括:旅行史、利什曼病史、其他家庭成员的合并症、治疗史、潜在疾病和诊断措施。应用 Box-Jenkins 方法拟合 2009 年至 2020 年 CL 发病率的 SARIMA 模型。所有统计分析均使用 Minitab 软件版本 14 进行。

结果:患者的平均年龄为 28.2±21.3 岁。利什曼病的最高和最低年发病率分别出现在 2018 年和 2017 年。平均十年发病率为每 10 万人 132 例。发病率最高和最低的年份分别为 2011 年和 2017 年,每 10 万人分别为 592 例和 195 例。最佳模型为 SARIMA(3,1,1)(0,1,2)(AIC:324.3,BIC:317.7 和 RMSE:0.167)。

结论:本研究表明,时间序列模型将是预测皮肤利什曼病发病率趋势的有用工具;因此,SARIMA 模型可用于规划公共卫生计划。它将预测未来几年疾病的进程,并提出解决方案来减少疾病的发生。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb1/10283195/860a81a829c2/12889_2023_16121_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb1/10283195/d25fa0481fb0/12889_2023_16121_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb1/10283195/860a81a829c2/12889_2023_16121_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb1/10283195/d25fa0481fb0/12889_2023_16121_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bb1/10283195/860a81a829c2/12889_2023_16121_Fig2_HTML.jpg

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Time series analysis of cutaneous leishmaniasis incidence in Shahroud based on ARIMA model.

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引用本文的文献

[1]
Effect of flood on the cutaneous leishmaniasis incidence in northeast of Iran: an interrupted time series study.

BMC Infect Dis. 2025-1-3

[2]
Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.

Environ Health Prev Med. 2023

本文引用的文献

[1]
The epidemiology of cutaneous leishmaniasis in Golestan Province, Iran: A cross-sectional study of 8-years.

Parasite Epidemiol Control. 2019-3-7

[2]
Leishmaniasis among neighbouring endemic countries in the Eastern Mediterranean, African and European regions.

East Mediterr Health J. 2019-3-19

[3]
Leishmaniasis.

Lancet. 2018-8-17

[4]
Risk factors for anthroponotic cutaneous leishmaniasis in unresponsive and responsive patients in a major focus, southeast of Iran.

PLoS One. 2018-2-7

[5]
Spatial and temporal trends of visceral leishmaniasis by mesoregion in a southeastern state of Brazil, 2002-2013.

PLoS Negl Trop Dis. 2017-10-6

[6]
A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran, Iran.

Environ Sci Pollut Res Int. 2017-6

[7]
Forecasting the number of zoonotic cutaneous leishmaniasis cases in south of Fars province, Iran using seasonal ARIMA time series method.

Asian Pac J Trop Med. 2017-1

[8]
Spatial Analyses of the Relation between Rodent's Active Burrows and Incidence of Zoonotic Cutaneous Leishmaniasis in Golestan Province, Northeastern of Iran.

J Arthropod Borne Dis. 2016-10-4

[9]
Assessing Incidence Patterns and Risk Factors for Cutaneous Leishmaniasis in Peshawar Region, Khyber Pakhtunkhwa, Pakistan.

J Parasitol. 2016-10

[10]
Dynamic Relations between Incidence of Zoonotic Cutaneous Leishmaniasis and Climatic Factors in Golestan Province, Iran.

J Arthropod Borne Dis. 2015-3-11

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