泰国禽流感风险的地理空间和时间分析：基于地理信息系统的多标准决策分析方法用于加强监测和控制

IF 3.5 2区农林科学 Q2 INFECTIOUS DISEASES

Transboundary and Emerging Diseases Pub Date : 2024-09-13 DOI:10.1155/2024/6474182

Waratida Sangrat, Weerapong Thanapongtharm, Suwicha Kasemsuwan, Visanu Boonyawiwat, Somchai Sajapitak, Chaithep Poolkhet

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引用次数: 0

摘要

禽流感（AI）是一种严重影响全球家禽生产的病毒性传染病。本研究采用基于地理信息系统（GIS）的多标准决策分析（MCDA）方法，旨在确定与泰国禽流感相关的空间和时间因素。我们发现，禽流感的高风险地区主要集中在该国的中部和北部较低的地区，东北部和南部地区的发生率较低。使用历史疫情数据对模型进行验证后发现，两者的一致性适中（AUC = 0.60，95% CI = 0.58-0.61）。这项研究为规划国家人工智能监测计划和协助疾病预防与控制工作提供了宝贵的见解。利用这种基于地理信息系统的 MCDA，并结合时间风险因素分析，可以提高国家级疾病监测的效率和效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control

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Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control

Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)–based multi-criteria decision analysis (MCDA) approach. We discovered that high-risk areas for AI were primarily concentrated in the central and lower northern regions of the country, with fewer occurrences in the northeastern and southern regions. Model validation using historical outbreak data showed moderate agreement (AUC = 0.60, 95% CI = 0.58–0.61). This study provides valuable insights for planning national AI surveillance programs and aiding in disease prevention and control efforts. The efficiency and effectiveness of disease surveillance at the national level can be improved using this GIS-based MCDA, in conjunction with temporal risk factor analysis.

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来源期刊

Transboundary and Emerging Diseases 农林科学-传染病学

CiteScore

8.90

自引率

9.30%

发文量

350

审稿时长

1 months

期刊介绍： Transboundary and Emerging Diseases brings together in one place the latest research on infectious diseases considered to hold the greatest economic threat to animals and humans worldwide. The journal provides a venue for global research on their diagnosis, prevention and management, and for papers on public health, pathogenesis, epidemiology, statistical modeling, diagnostics, biosecurity issues, genomics, vaccine development and rapid communication of new outbreaks. Papers should include timely research approaches using state-of-the-art technologies. The editors encourage papers adopting a science-based approach on socio-economic and environmental factors influencing the management of the bio-security threat posed by these diseases, including risk analysis and disease spread modeling. Preference will be given to communications focusing on novel science-based approaches to controlling transboundary and emerging diseases. The following topics are generally considered out-of-scope, but decisions are made on a case-by-case basis (for example, studies on cryptic wildlife populations, and those on potential species extinctions): Pathogen discovery: a common pathogen newly recognised in a specific country, or a new pathogen or genetic sequence for which there is little context about — or insights regarding — its emergence or spread. Prevalence estimation surveys and risk factor studies based on survey (rather than longitudinal) methodology, except when such studies are unique. Surveys of knowledge, attitudes and practices are within scope. Diagnostic test development if not accompanied by robust sensitivity and specificity estimation from field studies. Studies focused only on laboratory methods in which relevance to disease emergence and spread is not obvious or can not be inferred (“pure research” type studies). Narrative literature reviews which do not generate new knowledge. Systematic and scoping reviews, and meta-analyses are within scope.