Infectious Disease EpidemiologySharyn Orton, Ph.D.
American Red Cross, Rockville, MDSuggested reading:Modern Infectious Disease Epidemiology (1994) by Johan GieseckeModern Epidemiology (1998) by Kenneth Rothman and Sander Greenland
My interest in infectious disease epidemiology stems from my 20+ years as a Medical Technologist. An advanced degree in Epidemiology and Biostatistics has enabled me to better understand the dynamics and power of infectious disease epidemics, as well as the important differences from diseases caused by “non” infectious agents.
Learning/Performance Objectives
1. Understand the unique differences between infectious and “non”- infectious disease epidemiology.
2. Understand the terminology.
3. Be able to calculate sensitivity, specificity, predictive values and transmission probabilities.
Features unique to infectious diseases:
1. A case may also be a source.
2. People may be immune.
3. A case may be a source without being recognized.
4. There is often a need for urgency.
5. Preventive measures often have good scientific basis.
Outcomes of exposure
1. No infection
2. Clinical infection resulting in death, immunity, carrier or non-immunity
3. Sub-clinical infection resulting in immunity, carrier or non-immunity
4. Carrier
Definitions:
1. Incidence
2. Prevalence
3. Attack rate
4. Primary/secondary cases
5. Case fatality rate or ratio
6. Virulence
Definitions continued:
7. Mortality
8. Reproductive rate
9. Vector
10. Transmission routes
11. Reservoir vs source
12. Zoonosis
Definitions continued:
13. Incubation period
14. Serial interval
15. Infectious period
16. Latent period
17. Epidemic
Mathematical Models for Epidemics
Person to person spread relies on the reproduction rate, which is the average number of people infected by one case.
This is influenced by the attack rate of disease, the frequency of contact, the duration of infectivity and the immune status of the population.
Outbreak Analysis
Early analysis:
Person: who is the case?
Place: where was the case infected?
Time: when was the case infected?
Outbreak Analysis continued
Epidemic Curve
1. Plot the date on the horizontal axis.
2. Plot the number of cases on the vertical axis.
3. Determine if the outbreak is point source, continuous or person to person.
Outbreak Analysis continued
Check the geography.
Check the age and sex.
Factors Affecting Surveillance
Outbreak discovery
Outbreak analysis
Validity of notification data
Notification delays
Information feedback
Sources of data
Factors Affecting Infectivity
Dose and route
Immunity
Co-factors
Subclinical infection
Seroepidemiology
Used for:
1. Description of seroprevalence in populations
2. Follow incidence by estimation from changes using multiple samples from a population
Seroepidemiology continued
Importance of case and control classification:
Use of a gold standard reference.
Use of clinical diagnosis.
Seroepidemiology continued
Sensitivity
Specificity
Positive predictive value
Negative predictive value
Pre-test probability of disease
Contact Patterns
Use graphs or matrices to describe the network of contacts.
Study the networks by interviewing the cases about their contacts.
Study the contact structure.
Transmission Probability Ratio
TPR is a measure of risk of transmission from infected to susceptible individuals during a contact.
For any given type of contact or agent, an estimate of the effect of a covariate on susceptibility, infectiousness or both can be made.
TPR continued
TPR of differing types of contacts, infectious agents, infection routes or strains can be calculated.
There are 4 types of transmission probabilities (tp).
Binomial Transmission Probabilities
Used when susceptibles make more than one potentially infectious contact.
The maximum likelihood estimate of the tp under the binomial model=
# of susceptibles who become infected
total number of contacts with infectives
Study Designs
Cross-sectional: risk or prevalence ratio
Case control: odds ratio
Cohort: relative risk
Survival analysis
Study Issues
Confounding
Bias
Misclassification
Interaction
Epidemiology of vaccination
Direct: immunity by infection or vaccination
Indirect: herd immunity
Vaccine efficacy (%) =Iu-Iv/Iu x 100
Conclusion
Infectious and “non”-infectious disease epidemiology have important differences due to the inherently different nature of the risk factors (biological agent i.e. virus, bacteria vs chemical, environmental or genetic).
It is important to understand and consider these differences when conducting infectious disease research.