Ospina Juan, Hincapie-Palacio Doracelly, Ochoa Jesús, Molina Adriana, Rúa Guillermo, Pájaro Dubán, Arrubla Marcela, Almanza Rita, Paredes Marlio, Mubayi Anuj
Eafit University, Medellín, Colombia.
National School of Public Health, 'Héctor Abad Gómez', Epidemiology Group, University of Antioquia, Medellín, Colombia.
Trop Med Int Health. 2017 Oct;22(10):1249-1265. doi: 10.1111/tmi.12924. Epub 2017 Sep 5.
To stratify and understand the potential transmission processes of Zika virus in Colombia, in order to effectively address the efforts on surveillance and disease control.
We compare R of Zika for municipalities based on data from the regional surveillance system of Antioquia, Colombia. The basic reproduction number (R ) and its 95% confidence intervals were estimated from an SIR model with implicit vector dynamics, in terms of recovered individuals in each time unit, using an approximate solution. These parameters were estimated fitting the solution of the model to the daily cumulative frequency of each Zika case according to symptoms onset date relative to the index case reported to the local surveillance system.
R was estimated for 20 municipalities with a median of 30 000 inhabitants, all located less than 2200 m above sea level. The reported cases ranged from 17 to 347 between these municipalities within 4 months (January to April of 2016). The results suggest that 15 municipalities had a high transmission potential (R > 1), whereas in five municipality transmissions were potentially not sustaining (R < 1), although the upper bound of the confidence interval of the R for 3 of these 5 was greater than one, indicating the possibility of an outbreak later on.
The study identified high-risk municipalities (R > 1) and provide a technique to optimise surveillance and control of Zika. Health authorities should promote the collection, analysis, modelling and sharing of anonymous data onto individual cases to estimate R .
对寨卡病毒在哥伦比亚的潜在传播过程进行分层并了解,以便有效开展监测和疾病控制工作。
我们根据哥伦比亚安蒂奥基亚地区监测系统的数据,比较了各城市寨卡病毒的R值。基本再生数(R)及其95%置信区间是通过一个具有隐式病媒动态的SIR模型,以每个时间单位康复个体数量为依据,采用近似解进行估计的。这些参数是通过将模型的解与当地监测系统报告的首例病例症状出现日期相关的各寨卡病例每日累计频率进行拟合来估计的。
对20个平均人口为3万的城市进行了R值估计,这些城市均位于海拔2200米以下。在4个月内(2016年1月至4月),这些城市报告的病例数在17至347例之间。结果表明,15个城市具有高传播潜力(R>1),而5个城市的传播可能无法持续(R<1),尽管这5个城市中有3个城市R值置信区间上限大于1,表明后期可能会爆发疫情。
该研究确定了高风险城市(R>1),并提供了一种优化寨卡病毒监测和控制的技术。卫生当局应推动收集、分析、建模和共享关于个体病例的匿名数据以估计R值。