人类接触行为实证研究综述

介绍了当前已有的针对人类接触行为模式的实证研究,总结各研究中一致发现的普适规律,如人类接触行为具有高度同配性、特定社会场合下的接触网络具有典型的小世界特性以及接触时间分布呈幂律特性等,这些规律的发现可以指导传染病动力学建模、复杂网络、流行病学等领域的相关研究。

TransCode:Uncovering COVID-19 transmission patterns via deep learning

Background The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale,especially in densely populated regions.In this study,we aim to discover such fine-scale transmission patterns via deep learning.Methods We introduce the notion of TransCode to characterize fine-scale spatiotemporal transmission patterns of COVID-19 caused by metapopulation mobility and contact behaviors.First,in Hong Kong,China,we construct the mobility trajectories of confirmed cases using their visiting records.Then we estimate the transmissibility of individual cases in different locations based on their temporal infectiousness distribution.Integrating the spatial and temporal information,we represent the TransCode via spatiotemporal transmission networks.Further,we propose a deep transfer learning model to adapt the TransCode of Hong Kong,China to achieve fine-scale transmission characterization and risk prediction in six densely populated metropolises:New York City,San Francisco,Toronto,London,Berlin,and Tokyo,where fine-scale data are limited.All the data used in this study are publicly available.Results The TransCode of Hong Kong,China derived from the spatial transmission information and temporal infectiousness distribution of individual cases reveals the transmission patterns(e.g.,the imported and exported transmission intensities)at the district and constituency levels during different COVID-19 outbreaks waves.By adapting the TransCode of Hong Kong,China to other data-limited densely populated metropolises,the proposed method outperforms other representative methods by more than 10%in terms of the prediction accuracy of the disease dynamics(i.e.,the trend of case numbers),and the fine-scale spatiotemporal transmission patterns in these metropolises could also be well captured due to some shared intrinsically common patterns of human mobility and contact behaviors at the metapopulation level.Conclusions The fine-scale transmission patterns due to the metapopulation level mobility(e.g.,travel across different districts)and contact behaviors(e.g.,gathering in social-economic centers)are one of the main contributors to the rapid spread of the virus.Characterization of the fine-scale transmission patterns using the TransCode will facilitate the development of tailor-made intervention strategies to effectively contain disease transmission in the targeted regions.

云南省2008年HIV感染者/艾滋病患者的高危行为接触者追踪分析

多年来,云南省主要通过在高危人群和重点人群中开展监测、检测、自愿咨询检测等手段发现HIV感染者/艾滋病患者（HIV/AIDS）,全省2008年共检测样本2 015 840人份,平均阳性率为0.6%.

云南省德宏州新报告艾滋病病毒感染者溯源调查

目的对新报告HIV感染者的高危接触者进行逐级追踪调查和HIV检测（溯源调查），评价其作为一种艾滋病检测和防控策略的有效性和可行性。方法对云南省德宏州2008年8—10月新报告的HIV感染者335例及其高危接触者（接触者）进行溯源调查。结果将335例中的309例以及从接触者中发现的148例HIV感染者纳入本次溯源调查。累计报告接触者3395人，其中有联系信息的接触者704人（20．7％）；704人中成功追踪调查361人（51．3％）；其中67．6％（244／361）为HIV感染情况不详；有83．2％（203／244）接受HIV检测，新检出HIV阳性56例，阳性检出率为27．6％（56／203）。HIV感染者的配偶有联系信息的比例和追踪调查率分别为68．8％（280／407）、68．2％（191／280）；远高于商业性伴1．2％（24／1978）、16．7％（4／24），非商业非配偶性伴37．3％（202／542）、22．3％（45／202），以及共用针具者34．1％（140／410）、56．4％（79／140）。结论溯源调查新检出的HIV阳性率高；但是对商业性伴和非商业非配偶性伴的追踪调查存在难度；开展溯源调查有助于发现更多的HIV感染者、掌握和控制艾滋病疫情。