Application of modern spatio-temporal analysis technologies to identify and visualize patterns of rabies emergence among different animal species in Kazakhstan.

IF 1 4区 医学 Q4 HEALTH CARE SCIENCES & SERVICES Geospatial Health Pub Date : 2024-07-31 DOI:10.4081/gh.2024.1290
Aizada A Mukhanbetkaliyeva, Anar M Kabzhanova, Ablaikhan S Kadyrov, Yersyn Y Mukhanbetkaliyev, Temirlan G Bakishev, Aslan A Bainiyazov, Rakhimtay B Tleulessov, Fedor I Korennoy, Andres M Perez, Sarsenbay K Abdrakhmanov
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Abstract

During the period 2013-2023, 917 cases of rabies among animals were registered in the Republic of Kazakhstan. Out of these, the number of cases in farm animals amounted to 515, in wild animals to 50 and in pets to 352. Data on rabies cases were obtained from the Committee for Veterinary Control and Supervision of Kazakhstan, as well as during expeditionary trips. This research was carried out to demonstrate the use of modern information and communication technologies, geospatial analysis technologies in particular, to identify and visualize spatio-temporal patterns of rabies emergence among different animal species in Kazakhstan. We also aimed to predict an expected number of cases next year based on time series analysis. Applying the 'space-time cube' technique to a time series representingcases from the three categories of animals at the district-level demonstrated a decreasing trend of incidence in most of the country over the study period. We estimated the expected number of rabies cases for 2024 using a random forest model based on the space-time cube in Arc-GIS. This type of model imposes only a few assumptions on the data and is useful when dealing with time series including complicated trends. The forecast showed that in most districts of Kazakhstan, a total of no more than one case of rabies should beexpected, with the exception of certain areas in the North and the East of the country, where the number of cases could reach three. The results of this research may be useful to the veterinary service in mapping the current epidemiological situation and in planning targeted vaccination campaigns among different categories of animals.

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应用现代时空分析技术识别哈萨克斯坦不同动物物种中狂犬病的出现模式并将其可视化。
2013-2023年期间,哈萨克斯坦共和国共登记了917例动物狂犬病病例。其中,农场动物515例,野生动物50例,宠物352例。有关狂犬病病例的数据来自哈萨克斯坦兽医控制和监督委员会以及考察期间。这项研究旨在展示现代信息和通信技术,特别是地理空间分析技术的使用情况,以确定哈萨克斯坦不同动物物种中狂犬病出现的时空模式并将其可视化。我们还旨在根据时间序列分析预测明年的预期病例数。将 "时空立方体 "技术应用于代表地区一级三类动物病例的时间序列,结果表明在研究期间,全国大部分地区的发病率呈下降趋势。我们使用 Arc-GIS 中基于时空立方体的随机森林模型估算了 2024 年狂犬病病例的预期数量。这种模型只需对数据进行少量假设,在处理包括复杂趋势在内的时间序列时非常有用。预测结果显示,在哈萨克斯坦的大多数地区,预计狂犬病病例总数不会超过 1 例,但该国北部和东部的某些地区除外,这些地区的病例数可能达到 3 例。这项研究的结果可能有助于兽医服务部门了解当前的流行病学情况,并计划在不同类别的动物中开展有针对性的疫苗接种活动。
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来源期刊
Geospatial Health
Geospatial Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
2.40
自引率
11.80%
发文量
48
审稿时长
12 months
期刊介绍: The focus of the journal is on all aspects of the application of geographical information systems, remote sensing, global positioning systems, spatial statistics and other geospatial tools in human and veterinary health. The journal publishes two issues per year.
期刊最新文献
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