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印度卡纳塔克邦优化牲畜炭疽疫苗接种策略的综合时空及风险因素洞察

Comprehensive Spatial-Temporal and Risk Factor Insights for Optimizing Livestock Anthrax Vaccination Strategies in Karnataka, India.

作者信息

Anandakumar Jayashree, Suresh Kuralayanapalya Puttahonnappa, Patil Archana Veeranagouda, Jagadeesh Chethan A, Bylaiah Sushma, Patil Sharanagouda S, Hemadri Divakar

机构信息

ICAR-National Institute of Veterinary Epidemiology & Disease Informatics, Bengaluru 560064, Karnataka, India.

M S Ramaiah Institute of Technology, Bengaluru 560054, Karnataka, India.

出版信息

Vaccines (Basel). 2024 Sep 22;12(9):1081. doi: 10.3390/vaccines12091081.

Abstract

Anthrax, a zoonotic disease affecting both livestock and humans globally, is caused by The objectives of this study were the following: (1) to identify environmental risk factors for anthrax and use this information to develop an improved predictive risk map, and (2) to estimate spatial variation in basic reproduction number (Ro) and herd immunity threshold at the village level, which can be used to optimize vaccination policies within high-risk regions. Based on the anthrax incidences from 2000-2023 and vaccine administration figures between 2008 and 2022 in Karnataka, this study depicted spatiotemporal pattern analysis to derive a risk map employing machine learning algorithms and estimate Ro and herd immunity threshold for better vaccination coverage. Risk factors considered were key meteorological, remote sensing, soil, and geographical parameters. Spatial autocorrelation and SaTScan analysis revealed the presence of hotspots and clusters predominantly in the southern, central, and uppermost northern districts of Karnataka and temporal cluster distribution between June and September. Factors significantly associated with anthrax were air temperature, surface pressure, land surface temperature (LST), enhanced vegetation index (EVI), potential evapotranspiration (PET), soil temperature, soil moisture, pH, available potassium, sulphur, and boron, elevation, and proximity to waterbodies and waterways. Ensemble technique with random forest and classification tree models were used to improve the prediction accuracy of anthrax. High-risk areas are expected in villages in the southern, central, and extreme northern districts of Karnataka. The estimated Ro revealed 11 high-risk districts with Ro > 1.50 and respective herd immunity thresholds ranging from 11.24% to 55.47%, and the assessment of vaccination coverage at the 70%, 80%, and 90% vaccine efficacy levels, all serving for need-based strategic vaccine allocation. A comparison analysis of vaccinations administered and vaccination coverage estimated in this study is used to illustrate difference in the supply and vaccine force. The findings from the present study may support in planning preventive interventions, resource allocation, especially of vaccines, and other control strategies against anthrax across Karnataka, specifically focusing on predicted high-risk regions.

摘要

炭疽是一种人畜共患病,在全球范围内影响着牲畜和人类,由……引起。本研究的目标如下:(1)识别炭疽的环境风险因素,并利用这些信息绘制改进的预测风险地图;(2)估计村庄层面基本繁殖数(Ro)和群体免疫阈值的空间变化,这可用于优化高风险地区的疫苗接种政策。基于卡纳塔克邦2000 - 2023年的炭疽发病率以及2008年至2022年的疫苗接种数据,本研究进行了时空模式分析,以利用机器学习算法绘制风险地图,并估计Ro和群体免疫阈值,以实现更好的疫苗接种覆盖率。考虑的风险因素包括关键气象、遥感、土壤和地理参数。空间自相关和时空扫描分析显示,热点和聚集主要存在于卡纳塔克邦南部、中部和最北部地区,且在6月至9月间存在时间聚集分布。与炭疽显著相关的因素包括气温、地面压力、陆地表面温度(LST)、增强植被指数(EVI)、潜在蒸散(PET)、土壤温度、土壤湿度、pH值、有效钾、硫和硼、海拔以及与水体和水道的距离。采用随机森林和分类树模型的集成技术提高炭疽预测的准确性。预计卡纳塔克邦南部、中部和极北部地区的村庄为高风险地区。估计的Ro显示有11个高风险地区Ro > 1.50,各自的群体免疫阈值在11.24%至55.47%之间,并在70%、80%和90%的疫苗效力水平下评估疫苗接种覆盖率,所有这些都用于基于需求的战略疫苗分配。本研究中接种疫苗情况与估计的疫苗接种覆盖率的比较分析用于说明供应和疫苗效力的差异。本研究结果可能有助于规划预防性干预措施、资源分配,特别是疫苗资源分配,以及卡纳塔克邦针对炭疽的其他控制策略,尤其侧重于预测的高风险地区。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a669/11435676/db354b73b4d8/vaccines-12-01081-g001.jpg

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