Assessing Zika Virus Transmission Within Households During an Outbreak in Martinique, 2015–2016

Cousien, Anthony; Abel, Sylvie; Monthieux, Alice; Andronico, Alessio; Calmont, Isabelle; Cervantes, Minerva; Césaire, Raymond; Gallian, Pierre; Lamballerie, Xavier de; Laouénan, Cédric; Najioullah, Fatiha; Pierre-François, Sandrine; Pircher, Mathilde; Salje, Henrik; Bosch, Quirine Astrid ten; Cabie, André; Cauchemez, Simon

doi:10.1093/aje/kwz091

Cited by 9 publications

(12 citation statements)

References 35 publications

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“…In contrast to our analysis, studies from other islands found substantially higher seroprevalence estimates, including 73% in Yap in 2007 [ 5 ], 49% in French Polynesia in 2013–2014 [ 10 ], and 42%–50% in Martinique in 2015 [ 7 , 31 ]. The differences in the estimated underlying infection burdens may be in part due to heterogeneity in exposure to infection even within an island population, as seen in early dengue serosurveys in Puerto Rico and municipality-level estimates for ZIKV infection rates [ 27 ].…”

Section: Discussioncontrasting

confidence: 99%

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

et al. 2021

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Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barré Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.

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Section: Discussioncontrasting

confidence: 99%

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

et al. 2021

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“…In contrast to our analysis, studies from other islands found substantially higher seroprevalence estimates, including 73% in Yap in 2007 (5), 49% in French Polynesia in 2013–2014 (10), and 42%–50% in Martinique in 2015 (7,34). The differences in the estimated underlying infection burdens may be in part due to heterogeneity in exposure to infection even within an island population, as seen in early dengue serosurveys in Puerto Rico and municipality-level estimates for ZIKV infection rates (33).…”

Section: Discussioncontrasting

confidence: 99%

“…During the ZIKV epidemic, a household-based cluster investigation of 367 participants from 19 clusters found that ZIKV seroprevalence ranged from 0-57% (4). An estimate based on blood donors alone was 21% (95% confidence interval: 18-24%) (32) while an integrated approach similar to ours estimated an infection rate of 32% (95% CrI: 29-35%) (33).…”

Section: Discussionmentioning

confidence: 68%

“…week 33), when an estimated 120-140 weekly incident infections occurred per 10,000 people.In contrast to our analysis, studies from other islands found substantially higher seroprevalence estimates, including 73% in Yap in 2007 (5), 49% in French Polynesia in 2013-2014(10), and 42%-50% in Martinique in 2015(7,34). The differences in the estimated underlying infection burdens may be in part due to heterogeneity in exposure to infection even within an island population, as seen in early dengue serosurveys in Puerto Rico and municipality-level estimates for ZIKV infection rates(33). Invasion patterns, but nature drive some spatial heterogeneity which can influence longer-term transmission dynamics, since areas with high immunity may limit transmission to areas with low immunity.…”

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confidence: 99%

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Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

Quandelacy¹,

Healy²,

Greening³

et al. 2020

Preprint

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Emerging epidemics are challenging to track. Only a subset of cases is recognized and reported, as seen with the Zika virus (ZIKV) epidemic where large proportions of infection were asymptomatic. However, multiple imperfect indicators of infection provide an opportunity to estimate the underlying incidence of infection. We developed a modeling approach that integrates a generic Time-series Susceptible-Infected-Recovered epidemic model with assumptions about reporting biases in a Bayesian framework and applied it to the 2016 Zika epidemic in Puerto Rico using three indicators: suspected arboviral cases, suspected Zika-associated Guillain-Barre Syndrome cases, and blood bank data. Using this combination of surveillance data, we estimated the peak of the epidemic occurred during the week of August 15, 2016 (the 33rd week of year), and 120 to 140 (50% credible interval [CrI], 95% CrI: 97 to 170) weekly infections per 10,000 population occurred at the peak. By the end of 2016, we estimated that approximately 890,000 (95% CrI: 660,000 to 1,100,000) individuals were infected in 2016 (26%, 95% CrI: 19% to 33%, of the population infected). Utilizing multiple indicators offers the opportunity for real-time and retrospective situational awareness to support epidemic preparedness and response.

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“…Our findings are generally congruent with other studies aiming to understand arboviral epidemics. For example, it was estimated that within-household transmission only accounted for 22% of all ZIKV infections detected during an outbreak in Martinique in 2016, using data collected from a household transmission study, blood-donor seroprevalence studies, and laboratory-testing results among pregnant women with Zika-like illness [32] . Spatiotemporal modelling of data collected from the 2008-2009 dengue epidemic in Cairns, Australia, suggested that more than 50% of potential exposure locations were non-residential [33] .…”

Section: Discussionmentioning

confidence: 99%

Viral genome-based Zika virus transmission dynamics in a paediatric cohort during the 2016 Nicaragua epidemic

et al. 2021

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Background: Nicaragua experienced a large Zika epidemic in 2016, with up to 50% of the population in Managua infected. With the domesticated Aedes aegypti mosquito as its vector, it is widely assumed that Zika virus transmission occurs within the household and/or via human mobility. We investigated these assumptions by using viral genomes to trace Zika transmission spatially. Methods: We analysed serum samples from 119 paediatric Zika cases participating in the long-standing Paediatric Dengue Cohort Study in Managua, which was expanded to include Zika in 2015. An optimal spanning directed tree was constructed by minimizing the differences in viral sequence diversity composition between patient nodes, where low-frequency variants were used to increase the resolution of the inferred Zika outbreak dynamics. Findings: Out of the 18 houses where pairwise difference in sample collection dates among all the household members was within 30 days, we only found two where viruses from individuals within the same household were up to 10 th -most closely linked to each other genetically. We also identified a substantial number of transmission events involving long geographical distances (n=30), as well as potential super-spreading events in the estimated transmission tree. Interpretation: Our finding highlights that community transmission, often involving long geographical distances, played a much more important role in epidemic spread than within-household transmission.

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Assessing Zika Virus Transmission Within Households During an Outbreak in Martinique, 2015–2016

Cited by 9 publications

References 35 publications

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

Estimating incidence of infection from diverse data sources: Zika virus in Puerto Rico, 2016

Viral genome-based Zika virus transmission dynamics in a paediatric cohort during the 2016 Nicaragua epidemic

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