Longini I M, Koopman J S, Monto A S, Fox J P
Am J Epidemiol. 1982 May;115(5):736-51. doi: 10.1093/oxfordjournals.aje.a113356.
A maximum likelihood procedure is given for estimating household and community transmission parameters from observed influenza infection data. The estimator for the household transmission probability is an improvement over the classical secondary attack rate calculations because it factors out community-acquired infections from true secondary infections. The mathematical model used does not require the specification of infection onset times and, therefore, can be used with serologic data which detect asymptomatic infections. Infection data were derived by serology and virus isolation from the Tecumseh Respiratory Illness Study and the Seattle Flu Study for the years 1975-1979. Included were seasons of influenza B and influenza A subtypes H1N1 and H3N2. The transmission characteristics of influenza B and influenza A(H3N2) and A(H1N1) outbreaks during this period are compared. Influenza A(H1N1), A(H3N2) and influenza B are found to be in descending order both in terms of ease of spread in the household and intensity of the epidemic in the community. Children are found to be the main introducers of influenza into households. the degree of estimation error from the misclassification of infected and susceptible individuals is illustrated with a stochastic simulation model. This model simulates the expected number of detected infections at different levels of sensitivity and specificity for the serologic tests used. Other sources of estimation error, such as deviation from the model assumption of uniform community exposure and the possible presence of superspreaders, are also discussed.
给出了一种最大似然法,用于根据观察到的流感感染数据估计家庭和社区传播参数。家庭传播概率的估计方法是对经典二代发病率计算方法的改进,因为它从真正的二代感染中排除了社区获得性感染。所使用的数学模型不需要指定感染发病时间,因此可用于检测无症状感染的血清学数据。感染数据来自1975 - 1979年特库姆塞呼吸道疾病研究和西雅图流感研究的血清学和病毒分离结果。其中包括乙型流感以及甲型H1N1和H3N2亚型流感的流行季节。比较了这一时期乙型流感、甲型H3N2和甲型H1N1流感暴发的传播特征。发现甲型H1N1、甲型H3N2和乙型流感在家庭中的传播难易程度和社区中的流行强度方面均呈递减顺序。发现儿童是流感传入家庭的主要传染源。用随机模拟模型说明了感染和易感个体误分类导致的估计误差程度。该模型模拟了在所用血清学检测的不同灵敏度和特异性水平下预期检测到的感染数量。还讨论了其他估计误差来源,如偏离社区均匀暴露的模型假设以及可能存在的超级传播者。