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Hidden heterogeneity and its influence on dengue vaccination impact

The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) exper...

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Autores principales: Walters, Magdalene, Perkins, T. Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558830/
https://www.ncbi.nlm.nih.gov/pubmed/33102984
http://dx.doi.org/10.1016/j.idm.2020.09.008
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author Walters, Magdalene
Perkins, T. Alex
author_facet Walters, Magdalene
Perkins, T. Alex
author_sort Walters, Magdalene
collection PubMed
description The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) experience an elevated risk of severe disease in response to their first DENV infection subsequent to vaccination. As a result of these findings, guidelines for use of CYD-TDV now require serological screening prior to vaccination to establish that an individual does not fall into this high-risk category. These complications mean that the public health impact of CYD-TDV vaccination is expected to be higher in areas with higher transmission. One important practical difficulty with tailoring vaccination policy to local transmission contexts is that DENV transmission is spatially heterogeneous, even at the scale of neighborhoods or blocks within a city. This raises the question of whether models based on data that average over spatial heterogeneity in transmission could fail to capture important aspects of CYD-TDV impact in spatially heterogeneous populations. We explored this question with a deterministic model of DENV transmission and CYD-TDV vaccination in a population comprised of two communities with differing transmission intensities. Compared to the full model, a version of the model based on the average of the two communities failed to capture benefits of targeting the intervention to the high-transmission community, which resulted in greater impact in both communities than we observed under even coverage. In addition, the model based on the average of the two communities substantially overestimated impact among vaccinated individuals in the low-transmission community. In the event that the specificity of serological screening is not high, this result suggests that models that ignore spatial heterogeneity could overlook the potential for harm to this segment of the population.
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spelling pubmed-75588302020-10-23 Hidden heterogeneity and its influence on dengue vaccination impact Walters, Magdalene Perkins, T. Alex Infect Dis Model Vector-borne Disease Modelling; Edited by Dr. Patrick Leighton, Dr. Nicholas Ogden, Dr. Jianhong Wu The CYD-TDV vaccine was recently developed to combat dengue, a mosquito-borne viral disease that afflicts millions of people each year throughout the tropical and subtropical world. Its rollout has been complicated by recent findings that vaccinees with no prior exposure to dengue virus (DENV) experience an elevated risk of severe disease in response to their first DENV infection subsequent to vaccination. As a result of these findings, guidelines for use of CYD-TDV now require serological screening prior to vaccination to establish that an individual does not fall into this high-risk category. These complications mean that the public health impact of CYD-TDV vaccination is expected to be higher in areas with higher transmission. One important practical difficulty with tailoring vaccination policy to local transmission contexts is that DENV transmission is spatially heterogeneous, even at the scale of neighborhoods or blocks within a city. This raises the question of whether models based on data that average over spatial heterogeneity in transmission could fail to capture important aspects of CYD-TDV impact in spatially heterogeneous populations. We explored this question with a deterministic model of DENV transmission and CYD-TDV vaccination in a population comprised of two communities with differing transmission intensities. Compared to the full model, a version of the model based on the average of the two communities failed to capture benefits of targeting the intervention to the high-transmission community, which resulted in greater impact in both communities than we observed under even coverage. In addition, the model based on the average of the two communities substantially overestimated impact among vaccinated individuals in the low-transmission community. In the event that the specificity of serological screening is not high, this result suggests that models that ignore spatial heterogeneity could overlook the potential for harm to this segment of the population. KeAi Publishing 2020-10-01 /pmc/articles/PMC7558830/ /pubmed/33102984 http://dx.doi.org/10.1016/j.idm.2020.09.008 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Vector-borne Disease Modelling; Edited by Dr. Patrick Leighton, Dr. Nicholas Ogden, Dr. Jianhong Wu
Walters, Magdalene
Perkins, T. Alex
Hidden heterogeneity and its influence on dengue vaccination impact
title Hidden heterogeneity and its influence on dengue vaccination impact
title_full Hidden heterogeneity and its influence on dengue vaccination impact
title_fullStr Hidden heterogeneity and its influence on dengue vaccination impact
title_full_unstemmed Hidden heterogeneity and its influence on dengue vaccination impact
title_short Hidden heterogeneity and its influence on dengue vaccination impact
title_sort hidden heterogeneity and its influence on dengue vaccination impact
topic Vector-borne Disease Modelling; Edited by Dr. Patrick Leighton, Dr. Nicholas Ogden, Dr. Jianhong Wu
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7558830/
https://www.ncbi.nlm.nih.gov/pubmed/33102984
http://dx.doi.org/10.1016/j.idm.2020.09.008
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