Eastern equine encephalitis (EEE): a description of the 1989 outbreak, recent epidemiologic trends, and the association of rainfall with EEE occurrence.
- Journal Article
- Animal Health
- Animal Science
- Disease Outbreaks
- Disease Prevalence
- Disease Surveillance
- Disease Transmission
- Eastern Equine Encephalitis
- Environmental Stressors
- Epidemiology
- Equine Diseases
- Equine Health
- Equine Science
- Horses
- Infectious Disease
- Mosquito-borne Diseases
- Predictive Model
- Public Health
- Veterinary Medicine
- Veterinary Science
- Weather
Summary
This research paper discusses an outbreak of Eastern equine encephalitis in 1989, recent trends in the occurrence of the disease, and the potential link between rainfall and the occurrence of the disease. The study also explores the effectiveness of various predictive models in determining disease occurrence based on rainfall data.
Eastern equine encephalitis outbreak in 1989
The research began by discussing an outbreak of Eastern equine encephalitis, a mosquito-transmitted disease that affects both humans and horses. This outbreak, which occurred in 1989, resulted in nine human cases and 196 equine cases. It was predominantly concentrated in coastal Atlantic and Gulf Coast counties.
Epidemiologic trends in recent years
The study then delves into epidemiologic trends over the past two decades. Eastern equine encephalitis incidence and mortality rates have shown a decline compared with previous years. In other words, the study indicates that the number of new cases as well as the number of deaths due to EEE have decreased in more recent years.
Connection between rainfall and the occurrence of EEE
The researchers also analyzed rainfall patterns in areas where human EEE cases had been reported between 1983 and 1989. They identified a correlation between the occurrence of human cases and higher-than-average rainfall. This relationship seemed to be stronger when data was considered from local weather stations as opposed to statewide averages.
Effectiveness of predictive models
The authors evaluated various predictive models, all of which attempted to anticipate the occurrence of EEE based on rainfall data. The most accurate models were those tailored to northern states. However, the accuracy (or sensitivity) and specificity of these models varied. Regardless of model type, none provided a positive predictive value, a measure of how likely a positive result will correctly identify a case of the disease, of more than 50%. This means that the predictive models performed no better than chance at correctly predicting EEE occurrence based on rainfall data.
Cite This Article
Publication
Researcher Affiliations
- Division of Vector-Borne Infectious Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado.
MeSH Terms
- Adolescent
- Adult
- Age Factors
- Aged
- Animals
- Child
- Disease Outbreaks / veterinary
- Encephalomyelitis, Equine / complications
- Encephalomyelitis, Equine / epidemiology
- Encephalomyelitis, Equine / veterinary
- Female
- Horse Diseases / epidemiology
- Horses
- Humans
- Incidence
- Infant
- Male
- Mid-Atlantic Region / epidemiology
- Middle Aged
- Predictive Value of Tests
- Rain
- Southeastern United States / epidemiology
Citations
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