Space-time dynamics of a triple epidemic: dengue, chikungunya and Zika clusters in the city of Rio de Janeiro
Space-time dynamics of a triple epidemic: dengue, chikungunya and Zika clusters in the city of Rio de Janeiro
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DOI：
10.1098/rspb.2019.1867
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发表时间：
2019-10-02
影响因子：
4.7
通讯作者：
Carvalho, Marilia Sa
中科院分区：
文献类型：
--
作者：
Freitas, Lais Picinini;Cruz, Oswaldo Goncalves;Carvalho, Marilia Sa
登革热是一种由伊蚊传播的虫媒病毒疾病，几十年来一直在巴西流行。然而，病媒控制战略并没有显著减少疾病负担，也不足以防止基孔肯雅病毒和寨卡病毒进入该国并在该国定居。在里约热内卢市，2015年至2016年期间发现了第一次寨卡和基孔肯雅疫情，与登革热疫情同时发生。了解这些疾病在三重流行情况下的表现，是制定更好的预防和应对暴发干预措施的必要步骤。我们应用扫描统计分析来分别检测每种疾病的时空聚类，并同时检测所有三种疾病的时空聚类。一般而言，在相同的地点和时间段内没有检测到粉虱，这可能是由于病毒对宿主资源的竞争、易感种群的枯竭、不同的传入时间和人类行为的变化（例如，针对特定虫媒病毒病例的增加加强了病媒控制活动）。这三种疾病的同时聚集通常包括人口密度高和社会经济地位低的社区，特别是在城市的北部地区。利用时空集群检测可以及时指导对高风险地点的密集干预，以改善临床诊断和管理，并精确定位病媒控制措施。
Dengue, an arboviral disease transmitted by Aedes mosquitoes, has been endemic in Brazil for decades. However, vector-control strategies have not led to a significant reduction in the disease burden and have not been sufficient to prevent chikungunya and Zika entry and establishment in the country. In Rio de Janeiro city, the first Zika and chikungunya epidemics were detected between 2015 and 2016, coinciding with a dengue epidemic. Understanding the behaviour of these diseases in a triple epidemic scenario is a necessary step for devising better interventions for prevention and out-break response. We applied scan statistics analysis to detect spatio-temporal clustering for each disease separately and for all three simultaneously. In general, dusters were not detected in the same locations and time periods, possibly owing to competition between viruses for host resources, depletion of susceptible population, different introduction times and change in behaviour of the human population (e.g. intensified vector-control activities in response to increasing cases of a particular arbovirus). Simultaneous clusters of the three diseases usually included neighbourhoods with high population density and low socioeconomic status, particularly in the North region of the city. The use of space-time cluster detection can guide intensive interventions to high-risk locations in a timely manner, to improve clinical diagnosis and management, and pinpoint vector-control measures.