EPIDEMIOLOGY. Countering the Zika epidemic in Latin America.
EPIDEMIOLOGY. Countering the Zika epidemic in Latin America.
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DOI：
10.1126/science.aag0219
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发表时间：
2016-07-22
期刊：
影响因子：
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通讯作者：
Lessler J
中科院分区：
文献类型：
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作者：
Ferguson NM;Cucunubá ZM;Dorigatti I;Nedjati-Gilani GL;Donnelly CA;Basáñez MG;Nouvellet P;Lessler J
随着寨卡病毒感染与小头畸形和其他严重先天性畸形之间存在因果关系的证据越来越多（1），世界卫生组织（WHO）于2016年2月宣布拉丁美洲寨卡疫情为国际关注的突发公共卫生事件（2）。传播的绝对速度（图1和补充材料[SM]）使制定有效的公共卫生对策具有挑战性。立即采取的政策应对措施包括加强病媒控制（3）和建议少数国家推迟怀孕（4），随后世卫组织于2016年6月向所有受影响国家提出了扩大建议。这些都有优点，但效果可能有限（5），并且可能会产生对抗性相互作用。需要更全面地了解疫情的动态和驱动因素，以评估寨卡病毒造成的长期风险并确定干预措施的优先次序。三个关键因素决定了新感染在未感染人群中传播的规模和速度以及长期流行的风险。第一个是传染的可传播性，其特征是繁殖数，R-由典型的指示病例引起的继发感染的平均数（R< 1停止流行）。我们提供了受影响的拉丁美洲国家监测数据的时变R估计值（图1和SM）。国家一级的趋势掩盖了国家以下各级的巨大异质性（见SM），这可能反映了病媒生境质量的地理差异以及气候驱动的病媒密度和能力的变化（6）。
As evidence for a causal link between Zika infection and microcephaly and other serious congenital anomalies grew (1), the World Health Organization (WHO) declared the Latin American Zika epidemic a public health emergency of international concern in February 2016 (2). The sheer speed of spread (Fig. 1 and Supplementary Material [SM]) has made formulating an effective public health response challenging. Immediate policy responses have included enhanced vector control (3) and advice to delay pregnancy in a few countries (4), followed by an extended recommendation to all affected countries by WHO in June 2016. These have merits, but are likely to have limited effectiveness (5) and may interact antagonistically. A fuller understanding of the dynamics and drivers of the epidemic is needed to assess longer-term risks posed by Zika and prioritize interventions.Three key factors determine the scale and speed of spread of an emerging infection in a naïve population and the risk of longer-term endemicity. The first is the transmissibility of the infection, characterised by the reproduction number, R–the average number of secondary infections caused by a typical index case (R< 1 stops an epidemic). We provide time-varying estimates of R for affected Latin American countries where surveillance data are available (Fig. 1 and SM). Trends at the country level hide substantial subnational heterogeneity (see SM), likely reflecting geographic variation in vector habitat quality and climate-driven variation in vector density and competence (6).