Dynamics of eastern equine encephalitis virus during the 2019 outbreak in the Northeast United States.
Northeastern USA
eastern equine encephalitis
mosquito modeling
outbreak prediction
phylodynamics
virus evolution
Journal
Current biology : CB
ISSN: 1879-0445
Titre abrégé: Curr Biol
Pays: England
ID NLM: 9107782
Informations de publication
Date de publication:
19 06 2023
19 06 2023
Historique:
received:
09
03
2023
revised:
04
05
2023
accepted:
19
05
2023
pmc-release:
19
06
2024
medline:
22
6
2023
pubmed:
10
6
2023
entrez:
9
6
2023
Statut:
ppublish
Résumé
Eastern equine encephalitis virus (EEEV) causes a rare but severe disease in horses and humans and is maintained in an enzootic transmission cycle between songbirds and Culiseta melanura mosquitoes. In 2019, the largest EEEV outbreak in the United States for more than 50 years occurred, centered in the Northeast. To explore the dynamics of the outbreak, we sequenced 80 isolates of EEEV and combined them with existing genomic data. We found that, similar to previous years, cases were driven by multiple independent but short-lived virus introductions into the Northeast from Florida. Once in the Northeast, we found that Massachusetts was important for regional spread. We found no evidence of any changes in viral, human, or bird factors which would explain the increase in cases in 2019, although the ecology of EEEV is complex and further data is required to explore these in more detail. By using detailed mosquito surveillance data collected by Massachusetts and Connecticut, however, we found that the abundance of Cs. melanura was exceptionally high in 2019, as was the EEEV infection rate. We employed these mosquito data to build a negative binomial regression model and applied it to estimate early season risks of human or horse cases. We found that the month of first detection of EEEV in mosquito surveillance data and vector index (abundance multiplied by infection rate) were predictive of cases later in the season. We therefore highlight the importance of mosquito surveillance programs as an integral part of public health and disease control.
Identifiants
pubmed: 37295427
pii: S0960-9822(23)00679-6
doi: 10.1016/j.cub.2023.05.047
pmc: PMC10316540
mid: NIHMS1907424
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
2515-2527.e6Subventions
Organisme : NIAID NIH HHS
ID : DP2 AI176740
Pays : United States
Organisme : NCEZID CDC HHS
ID : U01 CK000509
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no conflicts of interest related to this work.
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