1. Principles of Disease Outbreak Investigation

2. Contents Definitions Justification Choosing a goal
Why investigate an outbreak?
Choosing a goal
Control vs. prevention
Performing an investigation
How do I go about this?

3. Basic Definitions

4. What is an Outbreak?
The confirmed presence of disease, clinically expressed or not, in at least one individual in a defined location and during a specified period of time.
It is implied that there is an increase in reported cases or an unusual clustering of cases
Often used synonymously with epidemic

5. Epidemic
Occurrence of a disease or any other health-related event affecting a number of individuals in clear excess of what would be expected for a specific region and period of time
Disease suddenly affecting a large number of individuals in a given region
May cause people to think its more severe
Syn: called epizootic in animals

6. Pandemic
Epidemic that propagates over long distances, through several continents, and that affects a considerable portion of the human population (ie. Influenza)
Syn: Panzootic in animals
Epizootic / Epidemic and Panzootic / Pandemic are now used interchangeably

7. Justification

8. Prevention
Stopping investigation in the here and now, will leave you vulnerable to why and how!

9. Justification - Why bother?
Solving a case or a series of individual cases is not necessarily solving the problem
How do you decide if this is an isolated case or a potential population problem?
Using a standardized approach helps answer big picture questions
What is it? (old or emerging disease?)
Where did it come from? (reservoir)
How is it spreading? (transmission)
How can you control it? (stop spread)
What about future prevention?

10. Why investigate outbreaks?
To describe new diseases
To identify the source of current outbreak
To evaluate existing prevention/control measures
To prevent future outbreaks
Opportunity for research and training
Public relations – “because you have to”
Political concerns – “because you have to”
Legal obligations – “because you have to”

11. Bottom line If you understand the problem you can solve the problem
Study the problem in a standardized manner
Report your findings in a standardized manner
This allows for comparison between outbreaks and for others to benefit from your experience

12. Choosing your goal

13. When should I bother to do a full investigation?
When you don’t know much about the situation you are faced with
When you are facing larger outbreaks
When you are faced with emerging diseases
When you want to understand why preventive measures aren’t working
When you need to concentrate more on control of a disease rather than future prevention

14. Control
Disease control results in the cessation of new cases during the course of a given outbreak
Investigations help identify:
The reservoir
The route of transmission and likelihood of spread
Ideally, what the disease agent is
If treatment/vaccination strategies already exist

15. Prevention
Disease prevention is the protection of a given individual or population against the introduction of disease
Analytical studies such as clinical treatment evaluations or vaccine trials are best done to create prevention strategies
However, outbreak investigations help:
Identify potential strategies
Evaluate existing treatment / vaccine protocols
Identify gaps in information – focus research goals

16. Prioritizing goals
Although immediate control and long term prevention are always important, one may be a higher priority at any given time during an outbreak - investigations are more useful for control efforts than for the creation of ongoing prevention strategies which require clinical trials and analytical studies (outbreak investigations often help formulate hypotheses that must be studied further)

17. Prioritizing goals
To prioritize your efforts, you need to know where the outbreak is in its natural course
Are cases increasing or is the outbreak almost over?
If increasing – goal is to stop the spread
Investigate to control
If decreasing – goal is to prevent future outbreaks
Evaluate prevention strategies

18. To help identify the goal
Three critical pieces of information include the identity of the disease agent, the source/reservoir of the agent and the route of transmission
Answer the following questions and refer to the decision tree:
Is the source known or unknown?
Is the route of transmission known or unknown?
Have we diagnosed the disease agent or are we performing empirical treatment?

19. Relative priority of efforts during an outbreak
Source/Mode of Transmission
Known
Unknown
Causative agent
Control +
Prevention +++
Control +++
Prevention +
Known I II
III IV
Unknown
+++ = highest priority + = lower priority

20. I
When the cause, source and route of transmission of an outbreak are all known, the priority should be to maximize effectiveness of prevention strategies. Outbreak investigations should help you both develop hypotheses about how prevention failed and identify research priorities.
An example of this would be an outbreak of rabies in outdoor cats in Virginia. Even though we don’t inherently expect high rates of rabies in this population, we know the risk is there. Therefore, efforts must be focused on increasing vaccination of cats or discovering why vaccination might have failed.

21. II
When the cause of an outbreak is known, but the source (reservoir) or route of transmission remains unknown, there is still quite a bit of investigation work to be done. In this case, investigation should focus on filling the knowledge gaps in the ecology of the disease to better guide future control and prevention efforts.
An example of this would Ebola virus, an emerging disease that can be diagnosed but whose reservoir is not yet known. Although some routes of transmission are known, zoonotic routes such as the dressing and eating of bush meat are just now being elucidated. This is often the case with emerging infectious diseases.

22. III
When the source and route of transmission is known, but an agent cannot be identified, both control and prevention efforts are important. Even this knowledge is likely the result of earlier investigations, there may be quite a bit of work left to do in order to identify the actual cause. In addition, there are probably no prevention strategies already in place to deal with this issue.
This represents that reality of investigating emerging diseases as they emerge. West Nile virus is a good example. Investigations had already shown that this was likely an arbovirus (arthropod born virus) that was carried by wild birds, but it tool a while for diagnosticians to isolate and identify the virus.

23. IV
When almost nothing is known at the time a new disease is discovered, outbreak investigations are most important. An organized, systematic approach helps create both clinical and diagnostic case definitions, identify risk factors, and formulate hypotheses to target control and prevention strategies
The recognition of a new syndrome of immunocompromised people in the 1980’s resulted in the discovery of HIV. Investigation of a neurologic syndrome of cattle in the UK (BSE) and ongoing investigations of a wasting syndrome (CWD) in deer and elk in the US shed new light on prion diseases, resulting in the discovery that the family of transmissible spongiform encephalopathies can be zoonotic diseases.

24. Why investigate outbreaks?
To describe new diseases
To identify the source of current outbreak
To evaluate existing prevention/control measures
To prevent future outbreaks
Opportunity for research and training
Public relations – “because you have to”
Political concerns – “because you have to”
Legal obligations – “because you have to”

25. Outbreak Investigation

26. Decide to investigate
Once you have decided that an investigation is worth your time and effort, you need an actual method to use. Most of the world follows the outbreak investigation procedures used by the world health organization (WHO) and the centers for disease control and prevention (CDC). For an in-depth look at this refer to the outbreak investigation chapter of the CDC epidemiology manual. There is also a tutorial provided on your disc that you may download (it is on investigating foodborne outbreaks). The methodology is the same, learn the process through whatever makes it easiest.

27. Iterative Process
Outbreak investigation is performed by following a series of steps that involve the collection of information which, once collected, often require you to repeat steps with a new baseline of information. Continuously updating old information to collect new data is therefore an iterative process.

28. For example…
A case definition at the beginning of an outbreak will usually be based upon the most preliminary information such as easily observable clinical signs or easily performed diagnostic tests. As you find out more about the disease and how to diagnose it in a specific spp., the case definition will also involve a ‘gold standard’ diagnostic test. Based upon the new case definition, it will be easier to identify new cases and identify new clinical signs or pathologic diagnoses which will be added to the case definition and allow you to further study the issue…………………..

29. Case definition based upon clinical signs
Find Cases
Case definition based upon clinical signs
Case definition based upon clinical signs and diagnostic results
Lessons learned from initial phase result in more ways to diagnose the disease and ‘gold standard’ diagnostic test
Update Definition

30. Pre-investigation Summary
It is always best to start by summarizing the current situation. This is the same as starting any case description with the signalment and history of the animals and/or group of animals. In addition, you should summarize the environment including housing, diet and other husbandry considerations.

31. Steps of Investigation
Establish case definition
Confirm reported cases
Establish endemic level (background rate) of disease
Establish the existence of an OUTBREAK
Examine descriptive epidemiological features
Generate hypotheses
Test hypotheses
Collect and test environmental samples
Implement control/prevention
COMMUNICATE

32. 1 - Case Definition - clinical
A case definition is a standard set of criteria applied to each individual to decide if he/she/it should be classified as a case or not
Clinical criteria are simple, objective measures such as temperature, fecal quality, behavioral observations that are used to identify suspect cases
It includes a time frame of suspicion such as onset of illness in the past 2 months
It includes definition of place such as at zoo ‘X’ or wildlife park ‘Y’
And it includes exclusion criteria for traits that are NOT in the case definition such as ‘not in reptiles’ or ‘not in a certain age class’ – these are things that you know will rule an animal out
Whatever the criteria, they should be applied consistently and objectively to all animals/people investigated

33. 1 - Case Definition - diagnostic
A diagnostic case definition includes a standard set of tests used to confirm suspect cases. This also includes standard samples to be taken and submitted to the lab (often a standardized lab as well). Confirming suspects is usually done as part of the second iteration through the process once you have verified the diagnosis through laboratory testing. It is important to use this definition to verify all suspect cases identified within the initial clinical sign based investigation

34. 1 - Final Case Definition
A final case definition includes both clinical and diagnostic pieces. It is important to remember that this is an iterative process (will change over time) due to the availability of new information and new diagnostic test validation. For example, the official case definition for West Nile virus was updated every year between 1999 and 2003 in the U.S. by both the CDC and USDA. In addition, there were different definitions for birds, horses and humans each of these years. Each of these was applied to the spp. of interest in the particular year of interest.

35. 2 - Case Confirmation
The goal of verifying the diagnosis of the initial cases is to 1) ensure that the problem has been properly diagnosed and 2) to rule out laboratory error that may result in false positives leading to increased perception that there is an outbreak
You should:
Use the current case definition to scrutinize initial reports or assumed cases
Verify with diagnosticians your assumptions about the quality (Sensitivity/Specificity) of diagnostic tests used
Keep standardized, detailed records of all suspects

36. 2 - Case Confirmation
In reality, many cases don’t exactly fit the case definition, at least for a while. Therefore, it is useful to categorize suspects into categories reflecting levels of confidence (usually, eventual cases move through these groups as diagnostic results become available).
For example, a definite case of WNV includes clinical neurologic signs as well as isolation of the virus and PCR (+) tissues. A probable case of WNV could include clinical signs with confirmed positive serology. While a possible case would entail either clinical signs without diagnostic evidence or a seropositive screen without the presence of clinical signs.

37. 3 - Establish Endemic Levels
It is important to know how many cases are normal in a given population in a given period of time. Establishing endemic levels or normal amounts of cases help establish whether or not an outbreak is occurring (outbreak = current cases > expected).
Outbreaks are usually identified in one of two ways. The best way is through good surveillance and monitoring where constant standardized data is collected to create baselines that are then compared to current data. The more common way is for a clinician to report ‘several cases’ of something new.

38. 3 - Establish Endemic Levels
Establishing endemic levels without surveillance or monitoring data is often difficult and time consuming. Many sources of data are available: health, agricultural or wildlife management authorities may have surveillance data for notifiable diseases; for common conditions there are usually literature reports, hospital summaries, or other demographic information available. If local data are not available, rates may be applied from the closest related data source, or a survey may be conducted to derive estimates. This process usually involves a thorough literature search and communication with numerous types of health authorities.

39. 3 - Establish Endemic Levels
In the captive (or free range) wildlife community you should ask yourself the following questions:
Has this ever been reported in this spp.?
If not, than the first case is a potential outbreak because the expected is zero
If so, how common is it
in this zoo?
in zoos in a given area (state, province, country, continent)
Can this information be turned into a prevalence or rate?
These are good because they allow for comparisons of data over time

40. Prevalence vs. Incidence
Prevalence is the total number of cases or outbreaks of a disease or infection in a specific population at a designated time or during a particular time period
All cases are included (new, old, those that recover during the period of interest)
Incidence is the inclusion of only NEW cases within the given time period
Can be calculated for any time period (monthly, weekly or at a specific point in time [pt. Prevalence])

41. 4 – Is this an outbreak?
Occurrence of more cases than expected in a given area or population over a particular time. This is in contrast to a cluster, an aggregation of cases in a given area or population over a particular time without regard to the number expected. In an outbreak/epidemic, we presume that cases are related to one another or that they have a common cause.

42. Observed > Expected
So what?
Is this a condition for which adequate information exists to make decisions?
Yes – implement control and prevention measures
No – collect more information
Is the problem ongoing?
Yes – continue investigation
No – what can you do to avoid this happening again
Implement preventive measures
Improve existing preventive measures
Do you know how/where/when it started?
Do you know how it spread?
What is the likelihood of it happening again?

43. Observed < Expected
May not be an outbreak….yet
Is the problem ongoing (what is the likelihood that it will become a larger problem)?
Yes – continue investigation
No – maybe this is just an unusual series of cases
This is probably worth writing up as a case series study
Search literature

44. 5 - Descriptive Epidemiology
Collect and organize patient/case data
Characterize patient demographics
species, age, sex, food source, movement, habitat, lifestyle
Epidemic curve
shape of curve - point-source vs.propagated vs. mixed outbreak
Characterize geographically and temporally
Establish rates
incidence, prevalence, morbidity vs. mortality
Determine risk factors

45. Collecting Information (1,2)
Surveys and questionnaires should contain:
Identifying information
Name, ID, spp., housing history
Demographic information
Age, sex
Clinical information
Clinical signs, diagnostic test results
Risk factor information
Exposure to foods, chemicals, toxins, drugs, sick con-specifics
Sources of information
Word questions precisely, define vague terms
Questions should contain a SINGLE idea
No saving space here
Questions should not be open ended

46. Survey Questions Bad question example
Please describe the sick animal’s illness
Too many factors in one question
Questions should not be open-ended
How to fix it: ask specific questions related to the case definition
Did this animal vomit in the past 24 hours? Y/N
Did this animal have diarrhea within two days of suspected illness? Y/N
Where there signs of neurologic abnormality (ie. circling, depression, tremors, ataxia)? Y/N

47. Line Listing (1,2)
Build a table where all information on each case and non case can be summarized
Include clinical, laboratory and pathologic diagnostic information
Include pertinent demographic information
Include a key for all standardized abbreviations

48. Case Series Studies
A case series study is a descriptive summary of a line listing.
It is more informative than a case report because it supports the development of hypotheses that may be tested
Basic descriptive statistics may be derived from these studies (ie. Sample prevalence)
Be careful not to infer too much about the entire population from case reports or case series studies
They can be very useful for organizing information about a potential outbreak

49. Index case = the first case seen
Epidemic Curves (3)
Visual display (histogram) of outbreak’s magnitude and time trend
X-axis is time of onset of illness
Y-axis is number of cases that meet case definition
Unit of time based upon incubation period of disease under investigation
The shape of the curve may suggest how the disease was introduced and how it spread
# Cases
Index case = the first case seen
Week

50. Point (common) Source Epidemic
All cases originate from a single, common cause
Cases occur over expected range of incubation period X
Exposure
Incubation period

51. Continuous Common Source
Like a point source only the peak is wider suggesting prolonged exposure to same agent
ie. a contaminated batch of food that is used for an extended time
Agent is introduced and keeps spreading to other individuals
Tougher to tell incubation period X X X

52. Intermittent Common Source
Exposure to same source at either regular or irregular intervals
This is different than continuous exposure because the agent is reintroduced at different times
ie. receiving separate contaminated feed deliveries from the same producer
Same incubation periods repeated
OR….equivalent incubation periods, but two diseases X X

53. Propagated Epidemic
May have repeat exposure to same source but also have animal-animal or person-person spread
Should have same incubation periods like intermittent common source but increase in overall prevalence over time as greater % of population is affected

54. Mixed Epidemic
Either same disease introduced separately or different diseases with different incubation periods introduced around the same time
Should see two different clinical syndromes if different diseases present X Y

55. Geographic and Temporal Characterization (4)
Summarize by time place and type of individual affected
EpiMap free software from CDC
Birds, Horses, Mosquitoes and Humans

56. Establish Rates (5)
Rate = A ratio that represents the magnitude of change in the occurrence of an event of interest (infection, disease, death) with respect to a population at risk over time
Proportion = a frequency ratio whose numerator is contained in the denominator (a/[a+b])
In epidemiology, rates are often misused and displayed as proportions, the difference will not be addressed here as we show you commonly used rates/proportions (see Thrushfield, Veterinary Epidemiology for a good discussion of this topic)
There are many commonly used ‘rates’ in epidemiology, only basic ones are described here
Important rates:
Mortality, Morbidity, Prevalence, Incidence, Attack Rate

57. Mortality vs. Morbidity
Mortality = frequency of deaths
Mort. rate = Number of deaths divided by the number of individuals at risk in a defined population over a defined period of time
Example: 2.4 deaths per 1,000 giraffe years in the population of North American zoos
Morbidity = state of being diseased, frequency of diseased individuals
Morb. Rate = Number diseased divided by the number of individuals at risk in a defined population over a defined period of time
Example: 40% of all Bali mynahs in North American zoos were diagnosed with atoxoplasmosis between

58. Prevalence vs. Incidence
Prevalence is the total number of cases or outbreaks of a disease or infection in a specific population at a designated time or during a particular time period
All cases are included (new, old, those that recover during the period of interest)
Incidence is the inclusion of only NEW cases within the given time period
Can be calculated for any time period (monthly, weekly or at a specific point in time [pt. Prevalence])

59. Other Rates
Attack Rate = Proportion of individuals at risk that develop disease or become ill
Number ill / Number potentially exposed
Case fatality rate
Number of deaths in given time period Number of diseased individuals in the population during the same time period
Survival Rate = 100% - Case fatality rate

60. Determine Risk Factors (6)
Risk Factor = factor associated with an increase in the probability of occurrence of the out come of interest (death, disease etc.)
Poor ventilation
Introduction of new animals into a herd
Contaminated feed
Exposure to mosquitoes
Immunocompromised condition

61. Risk factors ‘causing’ disease
Risk factors should contribute to the cause of a disease
The cause is usually a combination of multiple risk factors
Although statistical association strongly suggests that a risk factor may cause a particular disease, there are other conditions which should be considered
Evans’s and Hills postulates
Relative risk and odds ratios help define the association between a risk factor and a health outcome

62. Evans’s Postulates of Causation
Prevalence should be higher in those exposed than in those unexposed
Exposure to cause should be higher in diseased than in those healthy
Disease should follow exposure
Host response to exposure should reflect degree of exposure (dose – response)
Response to exposure should be regular or consistent
Experimental reproduction of disease should occur as result of exposure to adequate dose
Elimination of the risk factor should result in a decrease of disease
Modification of the host’s response to the factor should result in a decrease of disease (vaccine, drug treatment)
The relationship between risk factor and disease should make biological sense\
Emerging diseases sometimes do not make sense (ie. Prion diseases)

63. 6 – Generate Hypotheses
Hypotheses should be derived through the evaluation of descriptive information, literature searches, and personal experience. Hypotheses should address the source of the agent, the mode of transmission, and exposures that cause disease. Although empirical decisions will be made in order to control an outbreak, hypotheses should be testable in order validate subjective or empirical decisions. Remember, good hypotheses infer causation and usually make biological sense!

64. 7 - Test Hypotheses Two common ways to test hypotheses
Compare with established facts
Clinical, laboratory, environmental evidence so obviously supports the hypothesis that analytical studies are unnecessary
Use analytical epidemiology
Cases where answers are not obvious and further support is needed to decide evaluate the relationship between risk factors and causation
Goal - assess causal relationship between exposure (risk factor) and disease
Analytical studies
case-control study (not covered here)
prospective cohort study
Both of these studies make use of a comparison group to quantify relationship between exposure and disease

65. Prospective (cohort) Study
Study in small, well-defined population
Survey population for presence/absence of clinical signs (creating ‘ill’ and ‘not ill’ groups) and exposure/non exposure to risk factors
Calculate attack rates for those that were positive for each risk factor and those that were negative for each risk factor
Risk factors with high importance will have:
High attack rates among those exposed to the risk factor
Low attack rates among those not exposed to the item
Compute relative risk ratio’s

66. Example
A suspected food borne outbreak of Salmonella in a zoo’s population of 12 lions is being investigated. Food items are rotated so not all animals had the same ingredients in the past week.
Conduct risk factor exposure survey
Calculate attack rates for exposure and non exposure to each food item (risk factor)
Calculate relative risk for each risk factor / food item
Perform statistical tests of significance to evaluate the possibility that results are due to sample size or ‘chance’

67. 1. Risk factor exposure survey
Conduct a survey for each animal
Design questions with closed answers
Was this animal sick (as defined by case definition)? Yes No
Did this animal consume carnivore chow in the past week? Yes No
Repeat for all other food items / risk factors
Create a summary chart

68. 2. Calculate attack rates
Attack rates should be calculated for both exposed and non exposed groups
Attack rate (exp) = # exposed who were sick total # exposed to the factor
Attack rate (not exp) = # NOT exposed sick total # NOT exposed to the factor
Number of Lions that ate item
Number that did not eat item AR
Ill
Well
Total
Exposed
Not exp
Femur bones 2 8 10 1 3
0.20
0.33
Carnivore chow 9 4
0.11
0.25
Hamburger 5 6 11
0.45
0.50
Hard boiled eggs 7
1.00

69. 3. Calculate relative risk
Calculate for each factor
Relative risk (RR) = Attack rate for those exposed Attack rate for those not exposed
Number of Lions that ate item
Number that did not eat item AR
Rel Risk
Ill
Well
Total
Exposed
Not exp
Femur bones 2 8 10 1 3
0.20
0.33
0.60
Carnivore chow 9 4
0.11
0.25
0.44
Hamburger 5 6 11
0.45
0.50
0.91
Hard boiled eggs 7
1.00
3.00

70. Interpretation
Number of Lions that ate item
Number that did not eat item AR
Rel Risk
Ill
Well
Total
Exposed
Not exp
Femur bones 2 8 10 1 3
0.20
0.33
0.60
Carnivore chow 9 4
0.11
0.25
0.44
Hamburger 5 6 11
0.45
0.50
0.91
Hard boiled eggs 7
1.00
3.00
In this case, any of the food items could have been contaminated with Salmonella. However, it was discovered that the hard boiled eggs were not being thoroughly cooked before they were fed to the animals in order to save time. This information, gathered during the environmental investigation (next slide), combined with a relative risk greater than 1.0, support the conclusion that hard boiled eggs caused the outbreak
RR ~ 1.0, the risk of disease is similar in the exposed and unexposed groups and exposure is not associated with disease
RR < 1.0, the risk of disease is less in the exposed than the unexposed group and exposure could be ‘protective’ if this makes biological sense
RR > 1.0, the risk of disease is greater in the exposed than the unexposed group and exposure could be a risk factor

71. 4. Statistical Significance
The relative risk calculations of an investigation are not statistically significant unless the proper tests (such as chi-square or Fisher exact test) are performed to determine the probability (p-value) that the results were not due to chance alone. If the resulting p-value is smaller than the pre-determined cut-off (usually 0.05), they are said to be ‘statistically significant’ and unlikely to be by chance alone. It is beyond this exercise to teach statistical tests of significance, the references at the end of this tutorial provide in-depth coverage of this topic. Free software from the CDC called ‘StatCalc’ (embedded in EpiInfo 2000 [ provides a simple way to conduct these tests .

72. Epidemiological Triad
Disease spread is a result of the interaction between the host, disease agent and the environment in which they all live
The host is what we are concerned about
HOST
AGENT
Environment
Studying the environment can lead us to why the event occurred
The agent is what we test and treat for

73. 8 - Environmental Investigation
Collect and test environmental samples related to risk factors
food, beverage, waste, bedding, pond, estuary
Positives/negatives do not prove/disprove causation and must be interpreted in light of all results in investigation
Lab error, handling error, insensitive tests
Interpret carefully
Obtain specimens before intervention

74. 9 - Control and Prevention
Target critical control points/weak links in triad
Host immunity (vaccines)
Agent susceptibility (antibiotics, antivirals)
Environmental reservoirs (disinfection, removal of source)
Start empirical treatment when it will do no harm or analysis is obvious
When not obvious, test hypotheses concerning agents and control points
Evaluation of strategies:
Successful interventions result in a change in disease rates
Keep measuring and collecting information throughout entire process

75. Risk Communication
Perception is often reality
With a lack of information, people will act on their assumptions so keep people informed the best you can
Media, friend or foe?
Media training for those most likely to frequently interact creates calm, organized approach
Public relations experts should be consulted
Moral dilemma, the public’s right to know
At what point do you tell a wide audience and how much do you tell them?
Stakeholders
Identify all the different types of people that need to have information and remember to keep them informed
Reports
Standardized report templates prepared ahead of time facilitate communication in times of high stress (like an outbreak)
Publish standardized reports for all relevant stakeholders in appropriate language and in a timely fashion. Publish results/review in scientific literature so that others may learn from your experience

76. References Texts: Veterinary Epidemiology, 2nd Ed. – Thrushfield
Applied Veterinary Epidemiology and the Control of Disease in Populations – Toma, Dufour et al.
Epidemiology, 2nd Ed. – Gordis
Application of Quantitative Methods in Veterinary Epidemiology – Noordhuizen, Frankena et al.
Investigation and Mangement of Disease in Wild Animals – Wobeser
Clinical Epidemiology, 2nd Ed. – Sackett et al.
Tutorials and Software:
Epi Info 2000 and Epi Map 2000 –
Investigating disease outbreaks, a tutorial –
Publication:
Reingold, AL Outbreak Investigation – A perspective. Emerging Infectious Diseases, (4)1.