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Home / Equine Research Bank / PLoS One / Multi-season transmission model of Eastern Equine Encephalit...
PloS one2022; 17(8); e0272130; doi: 10.1371/journal.pone.0272130

Multi-season transmission model of Eastern Equine Encephalitis.

Abstract: Eastern Equine Encephalitis (EEE) is an arbovirus that, while it has been known to exist since the 1930's, recently had a spike in cases. This increased prevalence is particularly concerning due to the severity of the disease with 1 in 3 symptomatic patients dying. The cause of this peak is currently unknown but could be due to changes in climate, the virus itself, or host behavior. In this paper we propose a novel multi-season deterministic model of EEE spread and its stochastic counterpart. Models were parameterized using a dataset from the Florida Department of Health with sixteen years of sentinel chicken seroconversion rates. The different roles of the enzootic and bridge mosquito vectors were explored. As expected, enzootic mosquitoes like Culiseta melanura were more important for EEE persistence, while bridge vectors were implicated in the disease burden in humans. These models were used to explore hypothetical viral mutations and host behavior changes, including increased infectivity, vertical transmission, and host feeding preferences. Results showed that changes in the enzootic vector transmission increased cases among birds more drastically than equivalent changes in the bridge vector. Additionally, a 5% difference in the bridge vector's bird feeding preference can increase cumulative dead-end host infections more than 20-fold. Taken together, this suggests changes in many parts of the transmission cycle can augment cases in birds, but the bridge vectors feeding preference acts as a valve limiting the enzootic circulation from its impact on dead-end hosts, such as humans. Our what-if scenario analysis reveals and measures possible threats regarding EEE and relevant environmental changes and hypothetically suggests how to prevent potential damage to public health and the equine economy.
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Publication Date: 2022-08-17 PubMed ID: 35976903PubMed Central: PMC9385034DOI: 10.1371/journal.pone.0272130Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This study conceptualizes and tests a novel mathematical model to understand the spread of Eastern Equine Encephalitis (EEE), a severe and often deadly virus. Results from the model shed light on the roles different types of mosquitoes play in EEE transmission and how changes in virus behavior could potentially lead to more cases in humans and birds.

Background

  • Eastern Equine Encephalitis (EEE) is a virus transmitted by mosquitoes. Its grim mortality rate, killing one in three symptomatic patients, is troubling, especially in the wake of a recent surge in cases.
  • The reason behind this surge in cases isn’t clear but potential factors include changes in climate, the virus itself or host behavior.
  • The purpose of this research was to better understand the virus’s spread through a novel multi-season deterministic model and its stochastic counterpart, using data accumulated over sixteen years from the Florida Department of Health.

Roles of Different Mosquitoes in Spreading EEE

  • The researchers developed models to investigate the roles enzootic (animal-infecting) and bridge (both bird and human-infecting) mosquito vectors play in the spread of the EEE.
  • Enzootic mosquitoes like Culiseta melanura were found to be more essential for the virus’s persistence, whilst the bridge vectors were more linked with the disease burden in humans.

Investigating Hypothetical Scenarios

  • The researchers simulated scenarios involving viral mutations and changes in host behavior and observed increases in infectivity, vertical transmission, and host feeding preferences.
  • Results revealed that changes in the enzootic vector transmission augmented cases among birds more substantially than equivalent alterations in the bridge vector.
  • The researchers also discovered that small differences, of about 5%, in the bridge vector’s preference for feeding on birds, could fuel a more than 20-fold increase in cumulative infections in dead-end hosts (those who cannot further transmit the infection), including humans.

Conclusion and Implications

  • The outcomes pointed out that changes in various parts of the EEE transmission cycle can increase cases in birds, but the feeding preference of bridge vectors can limit the disease’s spread to humans.
  • The study’s findings serve as an early warning system, flagging possible dangers associated with EEE and environmental changes, and offering preventative strategies to protect public health and the equine economy.

Cite This Article

APA
Petrucciani A, Yu G, Ventresca M. (2022). Multi-season transmission model of Eastern Equine Encephalitis. PLoS One, 17(8), e0272130. https://doi.org/10.1371/journal.pone.0272130

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 17
Issue: 8
Pages: e0272130
PII: e0272130

Researcher Affiliations

Petrucciani, Alexa
  • Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, United States of America.
Yu, Geonsik
  • School of Industrial Engineering, Purdue University, West Lafayette, Indiana, United States of America.
Ventresca, Mario
  • School of Industrial Engineering, Purdue University, West Lafayette, Indiana, United States of America.
  • Purdue Institute for Inflammation, Immunology, and Infectious Diseases, Purdue University, West Lafayette, Indiana, United States of America.

MeSH Terms

  • Animals
  • Chickens
  • Culicidae
  • Encephalitis Virus, Eastern Equine
  • Encephalomyelitis, Eastern Equine / epidemiology
  • Encephalomyelitis, Eastern Equine / veterinary
  • Encephalomyelitis, Equine
  • Horses
  • Humans
  • Insect Vectors
  • Seasons

Conflict of Interest Statement

The authors have declared that no competing interests exist.

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