Spatial and temporal invasion dynamics of the 2014-2017 Zika and chikungunya epidemics in Colombia.
Spatial and temporal invasion dynamics of the 2014-2017 Zika and chikungunya epidemics in Colombia.
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DOI：
10.1371/journal.pcbi.1009174
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发表时间：
2021-07
影响因子：
4.3
通讯作者：
Donnelly CA
中科院分区：
文献类型：
--
作者：
Charniga K;Cucunubá ZM;Mercado M;Prieto F;Ospina M;Nouvellet P;Donnelly CA
寨卡病毒（ZIKV）和基孔肯雅病毒（CHIKV）最近被引入美洲，导致重大疾病负担。了解其在国家以下一级的时空动态是为今后的流行病监测和准备提供信息的关键。我们分析了2014-2017年流行期间约105，000例寨卡病毒病和412，000例基孔肯雅热疑似和实验室确诊病例的匿名行列表数据。我们首先确定了每个城市入侵的一周。在1，122个城市中，288个城市符合ZIKV的流行入侵标准，338个城市符合CHIKV的流行入侵标准。我们使用线性和逻辑回归模型分析了入侵的风险因素。我们还估计，这两次流行病的地理起源位于哥伦比亚北部的巴兰基利亚。我们评估了这两种病毒的空间和时间入侵动态，以分析城市之间的传播，使用一套（i）重力模型，（ii）Stouffer的排名模型，和（iii）辐射模型与两种类型的距离度量，地理距离和城市之间的旅行时间。入侵风险是最好的重力模型时，占地理距离和中间水平的密度依赖;斯托弗的排名模型与地理距离表现同样出色。虽然在流行病开始时发生了一些长距离入侵事件，但重力模型估计的距离功率为1.7（95%CrI：1.5-2.0），这表明空间传播主要是由短距离传播驱动的。联合拟合模型突出了流行病之间的相似性，当允许虫媒病毒之间的传播强度不同时，联合拟合模型优于单独模型。然而，ZIKV的传播速度比CHIKV快得多。了解传染病在空间和时间上的传播对于做好准备、设计干预措施和阐明传播机制至关重要。我们分析了来自50多万例报告病例的人类病例数据，以调查最近寨卡病毒（ZIKV）和基孔肯雅病毒（CHIKV）在哥伦比亚流行的传播情况。这两种病毒都传入了哥伦比亚北方。我们发现，重力模型和Stouffer的排名模型最好的描述传输和传输主要发生在短距离。我们的研究结果突出了哥伦比亚ZIKV和CHIKV流行之间的相似性和关键差异，可用于预测未来的流行浪潮，并优先考虑城市进行积极监测和有针对性的干预。
Zika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014–2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKV and 338 cities by CHIKV. We analyzed risk factors for invasion using linear and logistic regression models. We also estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. We assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities using a suite of (i) gravity models, (ii) Stouffer’s rank models, and (iii) radiation models with two types of distance metrics, geographic distance and travel time between cities. Invasion risk was best captured by a gravity model when accounting for geographic distance and intermediate levels of density dependence; Stouffer’s rank model with geographic distance performed similarly well. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5–2.0) from the gravity models suggests that spatial spread was primarily driven by short-distance transmission. Similarities between the epidemics were highlighted by jointly fitted models, which were preferred over individual models when the transmission intensity was allowed to vary across arboviruses. However, ZIKV spread considerably faster than CHIKV. Understanding the spread of infectious diseases across space and time is critical for preparedness, designing interventions, and elucidating mechanisms underlying transmission. We analyzed human case data from over 500,000 reported cases to investigate the spread of the recent Zika virus (ZIKV) and chikungunya virus (CHIKV) epidemics in Colombia. Both viruses were introduced into northern Colombia. We found that gravity models and Stouffer’s rank models best described transmission and that transmission mainly occurred over short distances. Our results highlight similarities and key differences between the ZIKV and CHIKV epidemics in Colombia, which can be used to anticipate future epidemic waves and prioritize cities for active surveillance and targeted interventions.
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影响因子：
3.8
作者：
Gardner LM;Bóta A;Gangavarapu K;Kraemer MUG;Grubaugh ND
通讯作者：
Grubaugh ND
DOI：
10.7705/biomedica.v37i1.2915
发表时间：
2017-01-01
期刊：
Biomédica
影响因子：
--
作者：
Carvajal, Carlos;Pacheco, Carlos;Jaimes, Fabián
通讯作者：
Jaimes, Fabián
影响因子：
5.2
作者：
Bertuzzo, E.;Mari, L.;Rinaldo, A.
通讯作者：
Rinaldo, A.
DOI：
10.1068/a160529
发表时间：
1984-01-01
期刊：
ENVIRONMENT AND PLANNING A
影响因子：
--
作者：
FOTHERINGHAM, AS
通讯作者：
FOTHERINGHAM, AS
影响因子：
9.2
作者：
Barrett ADT
通讯作者：
Barrett ADT