一项由荟萃分析指导的抽样计划，用于估计印度全国10种人兽共患病和4种跨界动物疫病的流行率。
完整摘要 · 中文译文
背景与目的：自然因素和人为因素均会影响人畜共患病和跨境动物疫病（TADs）的出现、维持和传播。此类疾病的监测依赖于建立基线流行率数据，而这需要科学严谨的数据收集计划。本研究旨在建立一个稳健的计划，用于估计印度10种人畜共患病（布鲁氏菌病、结核病、Q热、恙虫病、日本脑炎、克里米亚-刚果出血热、囊尾蚴病、隐孢子虫病、李斯特菌病、沙门氏菌病）和4种跨境动物疫病（猪流感、猪繁殖与呼吸障碍病、 lumpy skin disease、非洲猪瘟）的流行率。 方法：基于按照PRISMA指南进行的系统综述和荟萃分析，使用随机效应模型，并通过I2统计量估计初步流行率来量化异质性，同时纳入待采用检测方法的预定灵敏度和特异度值，使用内部开发的流行病学计算器，以95%置信水平生成两阶段分层随机监测计划，并以村庄作为印度不同邦目标动物种群的分层变量。 结果：14种疾病的合并流行率估计值范围为4%至30%（相应的荟萃分析估计值中报告了95%置信区间）。基于这些合并流行率估计值，为印度生成了一项村级监测计划，包括2，018个村庄的34，975份样本。 结论：这是首个在同一平台下针对多种疾病、基于荟萃分析且科学严谨的抽样方案。该方案有助于开展稳健的患病率研究，可作为监测对印度构成威胁的人畜共患病和跨境动物疾病（TADs）的有效工具。
完整摘要 · 英文原文
BACKGROUND AND OBJECTIVES: Both natural and anthropogenic factors impact the emergence, sustenance, and spread of zoonotic diseases and Transboundary Animal Diseases (TADs). Surveillance of such diseases depends on establishing baseline prevalence data, which necessitates a scientifically rigorous plan for data collection. This study aimed to establish a robust plan for estimating the prevalence of 10 zoonotic diseases (brucellosis, tuberculosis, Q-fever, scrub typhus, Japanese encephalitis, Crimean-Congo haemorrhagic fever, cysticercosis, cryptosporidiosis, listeriosis, salmonellosis) and four TADs (swine influenza, porcine reproductive and respiratory disease, lumpy skin disease, African swine fever) in India. METHODS: Based on a systematic review and meta-analysis conducted in accordance with PRISMA Guidelines, using random effects model with heterogeneity quantified by the I2 statistics estimate of preliminary prevalence rates, and incorporating predetermined sensitivity and specificity values for the assays to be employed, a two-stage stratified random surveillance plan was generated with 95% confidence level, using an in-house developed epi-calculator, with the village as the stratification variable for the targeted animal species in different states of India. RESULTS: The pooled prevalence estimates of the 14 diseases ranged from 4 to 30% (95% confidence intervals reported in the corresponding meta-analysis estimates). Based on these pooled prevalence estimates, a village-level surveillance plan comprising 34,975 samples across 2,018 villages was generated for India. CONCLUSION: This is the first scientifically rigorous meta-analysis-based sampling plan under one platform for many diseases. This could facilitate a robust prevalence study, which could serve as an effective tool for monitoring zoonotic diseases and TADs that are a threat to India.