Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015–2016 ZIKV epidemic

Sun, Kaiyuan; Zhang, Qian; Pastore-Piontti, Ana; Chinazzi, Matteo; Mistry, Dina; Dean, Natalie E.; Rojas, Diana Patricia; Merler, Stefano; Poletti, Piero; Rossi, Luca; Halloran, M. Elizabeth; Longini, Ira M.; Vespignani, Alessandro

doi:10.1186/s12916-018-1185-5

Cited by 11 publications

(13 citation statements)

References 49 publications

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“…Therefore, outside of the southeastern United States, a detected transmission event from an imported case will most likely represent only a sporadic occurrence, with minimal onward transmission even in the absence of local control efforts. These transmission patterns are consistent with previous local transmission patterns of other mosquitoborne flaviviruses in the United States, such as chikungunya and dengue, and with other model estimates (9,32).…”

Section: Discussionsupporting

confidence: 90%

Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States

Mina¹,

Guterman²,

Allen³

et al. 2020

Emerg. Infect. Dis.

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Z ika virus is a flavivirus spread by Aedes mosquitoes that for >60 years remained only an esoteric threat to human health (1). However, the recent Zika epidemic, which erupted in South America in 2015 and became the largest in history, brought the virus to prominence, particularly because infection has been linked to fetal microcephaly and other neurodevelopmental and neurologic sequelae (2). Although no longer classified a global emergency by the World Health Organization (WHO), Zika virus emergence and transmission continues globally, and WHO warns that Zika virus is set to remain as a long-term public health challenge (3). Given the critical importance of preventing Zika virus infections, especially during pregnancy, transmission anywhere requires that nations remain vigilant and informed at local, state, and national levels to prevent and control introduction and onward transmission (4,5). This imperative is especially important for countries such as the United States that simultaneously harbor the Aedes vectors and maintain essentially entirely susceptible populations. Numerous models for the potential emergence of Zika virus in the United States focus largely on the ecologic niche of Aedes mosquitoes (6-10). Projections that simultaneously consider vector dynamics and human demographics, including birth seasonality, to resolve both relative and absolute epidemic risk and potential control measures across space and time throughout the year are more limited. Here we present a stochastic Zika virus compartment model that considers the overlap of vector dynamics and human demographics at the county level in the United States, including Puerto Rico. The model was used to profile the risk for Zika virus transmission, assuming an initial introduction into each county, including trimester-specific fetal exposures for each of the 3,208 counties and municipalities within the United States including Puerto Rico over time and under varying control measures. We tested 3 approaches to controlling Zika virus transmission and assessed their utility in preventing or abrogating Zika virus transmission. These approaches include reducing human-vector contact (i.e.,

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Section: Discussionsupporting

confidence: 90%

Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States

Mina¹,

Guterman²,

Allen³

et al. 2020

Emerg. Infect. Dis.

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“…Examples of these matrices constructed using different assumptions and data are given in figure 3 . Matrices were constructed using human movement data from Twitter [ 32 , 251 , 256 ], air travel [ 239 , 249 , 250 ] or public transportation [ 19 ], using movement models that aimed to replicate human commuting behaviour [ 32 , 241 , 243 , 244 , 246 , 248 , 254 , 255 , 257 ], distance [ 242 ] or using a fixed value based on the type of neighbourhood [ 252 , 253 ]. Two studies estimated people's home and work addresses using mobile phone data and simulated movement between those [ 245 , 247 ], and two simulated the short flight distance of mosquitoes by allowing movement into neighbouring cells [ 240 , 245 ].…”

Section: Resultsmentioning

confidence: 99%

“…There were 21 studies (21/34, 61.8%) included in the review that used a movement matrix within a mechanistic model to account for spatial connectivity [19,32,[239][240][241][242][243][244][245][246][247][248][249][250][251][252][253][254][255][256][257]; all these studies assumed that connectivity arose from either host or vector movement. These models treated subgroups of the host and/or vector populations as nodes in a network with values of the matrix reflecting movement between those nodes.…”

Section: Movement Matricesmentioning

confidence: 99%

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

Lee

Jarvis

Edmunds

et al. 2021

J. R. Soc. Interface.

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Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.

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“…The relationship between arboviral transmission and temperature and rainfall is complex and regionally inconsistent [60]. However, up to a threshold, temperature generally has a positive relationship with Aedes spp.…”

Section: Discussionmentioning

confidence: 99%

El Niño Southern Oscillation, overseas arrivals and imported chikungunya cases in Australia: A time series analysis

Huang¹,

Hu²,

Yakob³

et al. 2019

PLoS Negl Trop Dis

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Background Chikungunya virus (CHIKV) is an emerging mosquito-borne pathogen circulating in tropical and sub-tropical regions. Although autochthonous transmission has not been reported in Australia, there is a potential risk of local CHIKV outbreaks due to the presence of suitable vectors, global trade, frequent international travel and human adaptation to changes in climate. Methodology/Principal findings A time series seasonal decomposition method was used to investigate the seasonality and trend of monthly imported CHIKV cases. This pattern was compared with the seasonality and trend of monthly overseas arrivals. A wavelet coherence analysis was applied to examine the transient relationships between monthly imported CHIKV cases and southern oscillation index (SOI) in time-frequency space. We found that the number and geographical distribution of countries of acquisition for CHIKV in travellers to Australia has increased in recent years. The number of monthly imported CHIKV cases displayed an unstable increased trend compared with a stable linear increased trend in monthly overseas arrivals. Both imported CHIKV cases and overseas arrivals showed substantial seasonality, with the strongest seasonal effects in each January, followed by each October and July. The wavelet coherence analysis identified four significant transient relationships between monthly imported CHIKV cases and 6-month lagged moving average SOI, in the years 2009–2010, 2012, 2014 and 2015–2016. Conclusion/Significance High seasonal peaks of imported CHIKV cases were consistent with the high seasonal peaks of overseas arrivals into Australia. Our analysis also indicates that El Niño Southern Oscillation (ENSO) variation may impact CHIKV epidemics in endemic regions, in turn influencing the pattern of imported cases.

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Quantifying the risk of local Zika virus transmission in the contiguous US during the 2015–2016 ZIKV epidemic

Cited by 11 publications

References 49 publications

Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States

Comprehensive Profiling of Zika Virus Risk with Natural and Artificial Mitigating Strategies, United States

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

El Niño Southern Oscillation, overseas arrivals and imported chikungunya cases in Australia: A time series analysis

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