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Outbreak Investigation Methods from Mystery to Mastery

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1 Outbreak Investigation Methods from Mystery to Mastery
I is for Investigation Welcome to Session 1 of the I is for Investigation training series from the UNC Center for Public Health Preparedness. Outbreak Investigation Methods from Mystery to Mastery

2 Recognizing an Outbreak
Session I Recognizing an Outbreak This is the first lecture in the series, “Outbreak Investigation Methods: From Mystery to Mastery.” This session will cover recognizing an outbreak.

3 Session Overview Overview of outbreak investigation
Identifying a potential outbreak Verifying the diagnosis and confirming the outbreak Defining and finding cases Orienting data by person, place, and time In this session, we will start with an overview of outbreak investigation, including the basic steps of an investigation, and the process of identifying a potential outbreak. We will then focus on the first steps of investigating a potential outbreak, which are to verify the diagnosis and confirm the outbreak, to define and find additional cases, and then to orient case-patient data by person, place, and time.

4 Learning Objectives Identify steps of an outbreak investigation
Develop a case definition Identify a process for case finding in an outbreak Apply methods used to orient data by person, place, and time Create and interpret epidemic curves The learning objectives for this session are to: Identify steps of an outbreak investigation; Develop and use a case definition; Apply the process of case finding in an outbreak; Identify methods used to orient data by person, place, and time; Create and interpret epidemic curves.

5 Overview of Outbreak Investigation
Let’s begin with an overview of the outbreak investigation process.

6 What is an Outbreak? The occurrence of more cases of a disease than expected for a particular place and time Number of cases Let’s start with a definition. What is an outbreak? An outbreak is the occurrence of more cases of a disease than expected for a particular group of people in a particular place and time. For many diseases, we expect to see a certain number of cases – they are there either all the time, or a few cases come and go now and then. This graph shows the number of cases along the left-hand side, so the height of the blue line indicates the number of cases. Along the bottom we have the days of the month, so as we go across we see the number of cases occurring on each day of the month. For the first 10 or 12 days of the month, we see a fairly constant level of cases. This is shown with the low, bumpy line. If the number of cases increases a great deal more than what we are used to seeing, this is an outbreak. On this graph, we can see the increase in cases in the large peak. Typically, the number of cases in an outbreak will decrease either because of health officials who implement control measures, or because of a natural decrease in cases. The only way we will know if there is an increase or a decrease in the number of cases, and therefore whether an outbreak is happening or declining, is if we plot/graph the number of cases on a regular basis. In general when we see an outbreak is occurring, we will start an investigation into the problem. Expected number of cases Days

7 Basic Steps of an Outbreak Investigation
Verify the diagnosis and confirm the outbreak Define a case and conduct case finding Tabulate and orient data: time, place, person Take immediate control measures Formulate and test hypothesis Plan and execute studies Implement and evaluate control measures Communicate findings Throughout the I is for Investigation series, we will be working with this list of the basic steps of an outbreak investigation. Let’s start by briefly going through the steps. First, we must verify the diagnosis and confirm that there is actually an outbreak occurring. Next, we need to create a preliminary case definition and conduct active case finding. Once we have information from some cases, we need to compile and review it. Then we implement preliminary control measures. After that, we formulate and test a hypothesis, and plan and execute additional studies based on the preliminary results. Finally, we implement and evaluate control measures and communicate our findings. This session will focus on steps 1, 2, and 3.

8 Basic steps provide a model for systematic outbreak investigations
Exceptions to the Rule Basic steps provide a model for systematic outbreak investigations No two outbreaks are alike! Steps of an outbreak could… occur in a different order occur simultaneously be repeated The basic steps from the previous slide are extremely useful when investigating an outbreak; however, it is important to remember that they are only guidelines for how to conduct a systematic outbreak investigation; they are not hard and fast rules. No two outbreaks are alike, and even with years of experience you cannot predict exactly how the events of an outbreak will unfold. Although the steps we just went through were listed sequentially, they could occur in a different order, and they often occur simultaneously or may be repeated as new information is received.

9 Identifying a Potential Outbreak
Let’s start from the very beginning. How do we even know an outbreak might be occurring? Next we will look at some of the ways we can identify a potential outbreak.

10 Outbreak Information Sources
Laboratory-confirmed reports of notifiable diseases Clinician reports of notifiable disease and unusual increases in disease Concerned parent/citizen reports to health department Media Information on possible outbreaks can come from various health sources, including everything from established surveillance sources to informal notifications. There may be an increase in laboratory-confirmed reports or clinician reports of notifiable diseases or unusual increases in disease that indicate there is a problem. For example, an Oklahoma meningococcal disease outbreak that occurred in 2010 was identified among elementary school students after physicians reported the notifiable diagnosis of suspected meningitis to state health officials. Health departments also take calls and reports from parents or other citizens, such as school nurses, daycare providers, and restaurant patrons, who are concerned about an illness in their child or community. Health departments may decide to investigate these reports, particularly if they get multiple reports from different sources. Additionally, the media may also pick up a story on an outbreak or disease problem as a news item that the health department wasn’t otherwise aware of.

11 Gathering Information from Case Reports
Collect: As much information as possible Negative as well as positive information Food history 3 days (72 hrs) to 5 days, if unknown agent Within incubation period, if known agent Exposure sources such as water, people, animals No matter what the source, when a complaint about an illness comes in to the health department, you should always collect as much information as possible from the person reporting an illness the first time contact is made. It might be difficult to contact that person in the future if any additional questions arise. If the complainant cannot provide critical pieces of information, try to find out who may be able to contribute, and contact that person. Be sure to ask the complainant how s/he can be reached in the future and if anyone else has been notified of this problem. It is equally important to collect information on pertinent negatives as well as pertinent positives. For example, if one only records that the person’s symptoms included vomiting and diarrhea, it is difficult to know if that means there was no fever or the information was not collected. If the complaint is about a foodborne illness, collect a complete food history. Regardless of the source, complainants will often associate illness with the last food or meal they consumed (particularly if it was at a commercial establishment). If the etiologic agent is not known, obtain at least a 72-hour food history (i.e., all foods/beverages/meals consumed in the 72 hours prior to onset of illness). For illnesses in which diarrhea is the predominant symptom (as opposed to vomiting), one should collect a 5-day food history because incubation periods for diarrheal diseases tend to be longer. If the etiologic agent is known, ask about foods/beverages/meals eaten within the incubation period for that illness. If more than one person is reported ill, foods/beverages/meals COMMON to all persons will be of particular interest BUT complete food histories for the appropriate time periods should still be collected. Remember that many illnesses that can be acquired through foods may also be acquired through other means such as water, person-to-person contact, and animal-to-person contact. Keep an open mind about possible sources and do not assume that it must be food.

12 Disease Surveillance: Case Report
What questions would you ask an ill person? WHO: age, sex, occupation, any others ill WHAT: physical condition, symptoms, medication, and medical care sought WHEN: when did the affected become ill WHERE: city/school, address, telephone number of ill person(s) WHY/HOW: suspected cause of illness, risk factors, modes of transmission, notes on people who did not become ill As you are taking information from a person reporting a case of illness, keep in mind the vital information to ask: always obtain the “Who, what, when, where, and why” of a potential case. “Who” characteristics include the affected person’s age, sex, occupation, and the characteristics of others who may be ill. The “what” covers the symptoms, the affected person’s physical condition, and whether they have sought medical care. “When” means asking when the affected person became ill, that is, when did symptoms begin? “Where” can be the geographic location or address of where the affected person lives, works, or goes to school. Additionally, you should collect the contact information for the affected person . The ill individual may or may not actually know why or how they became ill. Regardless, it is a good idea to ask them what they think caused their illness so that you can begin to form a list of the suspected cause of the illness or possible risk factors for illness. The individual may be able to tell you whether others who were with them became ill or not. At the conclusion of the discussion with the affected person, thank the person for notifying you of their illness.

13 Disease Surveillance: What Next?
File the report and stop? Investigate further? Once a complaint is received, you need to decide what to do with it. Do you file the report and stop? Or, do you investigate further?

14 Deciding to Investigate
Ideally, all reports of possible outbreaks should be investigated to: Prevent other persons from becoming ill Identify potentially problematic practices Add to the knowledge of infectious diseases Ideally, all reports of possible outbreaks should be investigated to: prevent other persons from becoming ill identify potentially problematic practices in the community that could lead to illness in the future add to our knowledge of infectious diseases

15 Why Investigate? Surveillance detects increases in cases of disease
Characterize the problem Prevention and control Research and answer scientific questions Train epidemiologists Political / legal concerns Outbreak investigations afford a number of opportunities for health department personnel. Initially an investigation is considered when there is an increase in disease over what would be expected at that place and time. Investigation of a newly recognized pathogen or an outbreak of a known pathogen is done to characterize the problem – how many are affected, who is affected, and what is the potential for spread. Investigations may identify preventable risk factors associated with infection leading to possible control measures. For example, epidemiologic investigations have identified consumption of foods such as undercooked hamburgers, unpasteurized apple juice, or alfalfa sprouts linked with E. coli O157:H7 outbreaks. Such outbreak investigation findings may allow consumers to follow precautions to reduce their risk of illness. Outbreak investigations may provide new research insights into the disease even if no new cases are occurring. In 1983, identification of an outbreak of explosive diarrheal illness of unknown etiology associated with consumption of unpasteurized milk led to years of laboratory research into the presumed infectious agent of Brainerd diarrhea. Since that time, a handful of additional outbreaks have occurred, and scientists are still trying to determine what the possible causative agent may be. Although the agent hasn’t been identified, epidemiologists do report that pasteurizing milk and boiling potentially contaminated water (such as well water) are effective preventive measures. Outbreak investigations provide opportunities for training of health department staff in methods of public health investigation and emergency response that are essential in the era of potential bioterrorism events. Finally, investigation of an outbreak may be done because of political pressure to investigate a problem, or to gather evidence for legal proceedings.

16 Maybe You Should Investigate...
If illness is severe (life-threatening) If there are confirmed clusters or large numbers of a similar illness If foodborne illness is from a food handler If illness is associated with commercially- distributed food If there is outside pressure to investigate (media, politicians) Given resource constraints in many health departments, however, it may not be possible to investigate all individual cases or investigate all cases to the same degree. Therefore, public health workers often must choose which instances should receive highest priority for investigation. In general, top priorities include complaints that involve: a life-threatening illness, such as botulism or anthrax a confirmed cluster or large numbers of people with the same illness a food handler or food service establishment a commercially distributed product outside pressure to investigate, such as from the public, the media, or political leaders.

17 Maybe You Shouldn’t Investigate...
If affected persons might not have the same illness If affected persons are not able to provide adequate information for investigation If the diagnosis and/or clinical symptoms are not consistent with the related exposures If there are repeated complaints made by the same individual(s) for which prior investigations revealed no significant findings Clues that a follow-up investigation may not be warranted or is unlikely to be productive might be: If signs/symptoms or confirmed diagnoses among the affected persons suggest they might not have the same illness If affected persons are not able to provide adequate information for investigation, including date and time of onset of illness or symptoms If the confirmed diagnosis and/or clinical symptoms are not consistent with reported exposures If there have been repeated complaints by the same individual(s) with no significant findings upon investigation An important caveat here is not to over-interpret the situation if a complainant refuses to provide contact information. Anonymous complaints are common and do not automatically invalidate a complaint. Complainants often request anonymity.

18 Verifying the Diagnosis and Confirming the Outbreak
Once you have made the decision to investigate, you move into carrying out the steps of an outbreak investigation. In the next section we will look at the first step: Verifying the diagnosis and confirming the outbreak.

19 Verify the Diagnosis Evaluate: Predominant signs and symptoms
Incubation period Duration of symptoms Suspected food Suspected toxin, virus, or bacteria Laboratory testing of stool, blood, or vomitus Verifying the diagnosis means that we identify the diagnoses of individuals and also verify whether different individuals reportedly belonging to the same outbreak actually have the same disease. Usually, we are looking for a specific pathogen that could be causing disease. So how do we determine which pathogen could be causing the outbreak? We can start by evaluating several clues. First, we can evaluate the predominant signs and symptoms of the illness to identify agents that are more or less likely to be the cause of illness. We can look at the incubation period – that is, the amount of time between exposure and onset of illness – and the duration of symptoms, because both will vary with different agents. If there is a food item suspected of causing the illness, that can be evaluated as well, as some foods are more likely to be associated with certain agents – undercooked beef might indicate E. coli, for example, while shellfish might indicate a toxin. Evaluating these clues can tell us whether different individuals have the same disease, and can inform officials about which laboratory tests to conduct. The most definitive way to find the agent is to conduct laboratory testing of clinical specimens such as stool, blood, or vomitus. Once an agent is identified, the laboratory may be able to conduct pulse field gel electrophoresis, or PFGE, to fingerprint the agent to further verify that all case-patients are outbreak-related.

20 Identify the Pathogen Ensure all suspect patients have the same pathogen Identify the potential incubation period for hypothesis generation Can proceed while waiting for laboratory diagnosis Why do we need to identify the pathogen exactly? First, if a number of patients have similar symptoms, the verification process can determine whether these individuals actually have a disease caused by the same pathogen, or different diseases with a similar presentation. Pathogen identification will help identify the potential incubation period and the incubation period can be used to help pinpoint at what time the exposure took place. It is crucial to know the incubation period for generating hypotheses about the source of the illness. Because laboratory results can take time, we do not need to wait for laboratory diagnosis to proceed; sometimes the investigation must move forward before a definitive diagnosis is reached.

21 Verify the Diagnosis Potential reasons for negative laboratory results: Illness could be due to an organism that wasn’t tested for Mishandling of specimen resulting in death of the pathogen (during storage, transport, processing, or culture) Specimens collected too late in the illness What happens if specimens are submitted to the laboratory, but come back with negative results? Of course, a negative test result could indicate the truth, but we must always be skeptical of our data, and consider other possibilities to explain the data. In the case of the laboratory results, there are several potential reasons for negative results. The most straightforward explanation is that the pathogen that was tested for did not cause the illness. The illness could be due to a virus or bacteria not tested for, or due to a different agent such as a fungus or toxin. Sometimes, however, a result may be negative even if the pathogen being tested for DID cause the illness. In these cases, the pathogen is simply not present in the specimen at the time of testing. This could be due to mishandling of the specimen during storage, transport, processing, or culture, resulting in the death of the pathogen. Alternatively, specimens could have been collected too late in the illness, so that the person’s immune response already cleared the pathogen.

22 Defining and Finding Cases
Once a diagnosis has been identified, often accompanied by a verification of the pathogen involved, it is time to move on to the next steps of conducting an outbreak investigation: creating a case definition and finding additional cases.

23 Case Definition A standard set of criteria for deciding whether an individual should be classified as having the disease of interest, including: Clinical criteria (signs, symptoms, and laboratory tests) Person, place, and time criteria To verify the existence of a true outbreak, you must establish that there are a higher number of cases than expected. The first step in doing this is to develop a case definition. A case definition is a standard set of criteria for deciding whether an individual should be classified as having the disease of interest, including: - Clinical criteria such as signs, symptoms, and laboratory tests; and - Person, place, and time criteria

24 Case Definition Can be modified as more data are obtained
Should not include a possible cause of the outbreak The case definition is not set in stone, especially in the early stages of an investigation. The case definition can be modified as more data describing the illness are obtained. It is very important that you do not include any possible causes of the outbreak in the case definition. For example, if we were investigating an outbreak of Legionnaire’s disease and our hypothesis was that spending time in hotel X’s hot tub led to the illness, we would not want to limit the case definition to people who had spent time in the hot tub at hotel X, as we would be excluding the possibility that another exposure was involved before we had enough information to determine whether or not the hot tub at the hotel was the cause.

25 Additional sources may be appropriate, depending on the outbreak.
Case Finding Contact local care providers Contact schools, large businesses Contact state health department / neighboring health departments Ask case-patients if they know of others who are ill Additional sources may be appropriate, depending on the outbreak. Once you have established a case definition, you need to conduct additional case finding. To find additional case-patients, you can contact local care providers, such as physicians or emergency departments, to see if they are seeing increased numbers of patients who meet the case definition. You can also contact schools or large businesses to find out if they are seeing increased absenteeism. It is also a good idea to contact the state health department and neighboring health departments to determine if the potential outbreak spans a wider geographic area. Finally, you can also ask case-patients if they know of others who are ill with similar symptoms. In addition to finding out about existing potential case-patients, you can also request that local care providers and state or neighboring health departments contact you if they see any new case-patients that meet your case definition. Depending on the outbreak, there may be additional sources for finding cases that are appropriate. For example, in an outbreak that appears to be related to a specific restaurant, investigators may get contact information from patrons who paid with a credit card, and follow up to see if they are experiencing symptoms.

26 Orienting Data by Person and Place
Once you have found a number of cases, you must begin looking at the data you have collected on these cases. This leads us to the next step in an outbreak investigation, which is orienting data by person, place, and time.

27 Descriptive Epidemiology
Comprehensively describes the outbreak Person Place Time Line listings Graphs Bar graphs Histograms Measures of central tendency Person, place, and time are the foundational components of descriptive epidemiology, and can be used to comprehensively describe the outbreak. We’ll spend the next few minutes looking at ways to organize and summarize this information. Summarizing descriptive data may be done using one or more of several different methods. Commonly used methods are line listings, bar graphs, and histograms. In addition, statistical methods such as measures of central tendency can be used to summarize data. Let’s look at each of these methods briefly.

28 Line Listing Signs/Symptoms Lab Demographics Case # Report Date
Signs/Symptoms Lab Demographics Case # Report Date Onset Date Physician Diagnosis N V J HAIgM Sex Age 1 10/12/02 10/5/02 Hepatitis A M 37 2 10/4/02 62 3 10/13/02 38 4 10/9/02 NA F 44 5 10/15/02 17 6 10/16/02 10/6/02 43 A line listing is a tool that you can begin using as soon as you begin collecting cases in an apparent outbreak. It allows information regarding time, person, and place to be organized and reviewed quickly. A line listing can be done by hand with pencil and paper or using a software program such as Microsoft Excel or Epi Info. To set up a line listing, create a table in which each row represents a case and each column represents a variable of interest (variables of interest will depend on the nature of the outbreak but should include components of the case definition). New cases should be added to the list as they are identified and all cases should be updated throughout the investigation as new information is obtained. This is an example of a line listing for a Hepatitis A outbreak. It shows the case number (the name of the case is excluded because it is confidential information), the date the illness was reported, the date of symptom onset, the clinical diagnosis, whether the person had symptoms such as nausea, vomiting or jaundice, whether there were positive lab results, and some basic demographics.

29 Bar Graph (Person) Bar graphs allow more rapid processing of information, although less information is summarized at one time. A bar graph shows categorical data with space between the intervals. This is an example of a bar graph showing the number of males and females in each exposure category – note that this is a “person” characteristic. Females are shown in green, males in blue. Those who were exposed to a specific food item are shown on the left, and those who were not exposed are shown on the right. Always remember to include a descriptive title and to label both axes when you create a graph.

30 Histogram (Person) A histogram graphs continuous data with no gaps on the x-axis. This is an example of a histogram showing the age distribution of cases. Age is also a person characteristic.

31 Measures of Central Tendency Mean (Average)
Equals the sum of all values divided by the number of values. Example: Cases: 7,10, 8, 5, 5, 37, 9 years old Mean = ( )/7 Mean = 11.6 years of age Now let’s look at some basic measures of central tendency. The most commonly used measures of central tendency are the mean and median. The mean is simply the arithmetic average. It is calculated by adding up all of the values and then dividing by the number of values. For example, if we wanted to calculate the mean age of seven case-patients in an outbreak investigation who were 7, 10, 8, 5, 5, 37 and 9 years of age we would add these values up (81) and divide by the number of case-patients, 7. The mean, or average age is 11.6 years.

32 Measures of Central Tendency Median (50th percentile)
The value that falls in the middle position when the measurements are ordered from smallest to largest Example: Ages: 7,10, 8, 5, 5, 37, 9 Ages sorted: 5, 5, 7, 8, 9,10, 37 Median age = 8 The median is another measure of central tendency. It is the 50th percentile value. In other words, it is the value in the middle position of a set of measurements ordered from smallest to largest. Using the same example as before, we first rank the ages from youngest to oldest. Since there are so few case patients, it’s easy to see that the middle value is 8. Compared to the mean, the median is less sensitive to extreme values, because these values are not used to calculate the median. In this example the case who is 37 years of age is quite a bit older than the rest of the cases. If you’ll recall, the mean age for these case-patients was The median value, 8, is less because it is not influenced by the value of 37.

33 Calculate a Median Value
If the number of measurements is odd: Median = value with rank (n+1) / 2 n = the number of values Example: 5, 5, 7, 8, 9,10, 37 n = 7 (n+1) / 2 = (7+1) / 2 = 4 The 4th value = 8 Often, there will be too many values to identify the median by sight. In that case there are rules for calculating the median; a slightly different method has to be used if there are an odd number of measurements versus an even number. If the number of values is odd, the median value is the value with rank (n+1)/2, where “n” is the number of values or measurements. In our example, we have 7 values, so “n” is 7. (n+1) = 8, so (n+1) divided by 2=4. We then find the 4th ordered value, which is 8, and this is the median value.

34 Calculate a Median Value
If the number of measurements is even: Median=average of the two values with: rank of n / 2 and rank of (n / 2) + 1 Example 5, 5, 7, 8, 9, 10, 12, 37 n = 8 (8 / 2) = 4, so “8” is the first value (8 / 2) + 1 =5, so “9” is the second value (8 + 9) / 2 = 8.5 The median value = 8.5 If the number of values is even, the median is the value half way between the values with rank (n/2) and (n/2)+1. In other words, it’s the average of the two middle values. Say we have an additional value in our example, so that “n” is now 8. Eight divided by 2 is 4, and the value at the rank of 4 is 8. Therefore “8” is the first value in our calculation. When we add “1” to that value, we have the rank of 5. The value 9 is in the 5th ordered position in our list, so our second value is 9. The average of 8 and 9 is 8.5, so the median value for this list is 8.5.

35 Descriptive Epidemiology: Place
Spot map Shows where cases live, work, spend time If population size varies between locations being compared, use location-specific attack rates instead of number of cases In addition to describing person characteristics of the case-patients in an outbreak, descriptive epidemiology can provide information about the geography of the outbreak. Characterizing the outbreak by place allows the investigator to assess the geographic extent of the situation and may also reveal patterns, such as clusters of cases, that may provide information about the cause or source of the outbreak. A spot map can be used to describe the outbreak “place”. A spot map is simply a map that indicates the location of a case characteristic. For example, a spot map may show where a case lives or works. Individual cases are usually plotted with spot maps. If the populations in the areas being compared differ, it is best to use location-specific attack rates rather than numbers of cases. This will take the size of the location-specific population into account and will allow for comparison of the different areas. We will discuss attack rates later in this presentation.

36 Descriptive Epidemiology: Place
This is an example of a spot map from an outbreak of histoplasmosis in Minnesota. Each dot on the map represents the location where one case-patient in the outbreak lived. Source:

37 Orienting Data by Time Epidemic Curves
Descriptive epidemiology is also used to display time trends. In an outbreak setting, this is most frequently done by the use of epidemic curves.

38 Descriptive Epidemiology: Time
An epidemic curve is when time data are shown as a histogram with the time period of interest shown on the x-axis (the horizontal line) and the number of cases during the corresponding time period on the y-axis (the vertical line). Note that when you generate a histogram, each time interval along the x-axis is spaced in equal intervals. Note that time can also be easily represented using a line graph.

39 Descriptive Epidemiology: Time
An epidemic curve (epi curve) is a graphical depiction of the number of cases of illness by the date of illness onset Can provide information on the outbreak’s: Pattern of spread Magnitude Outliers Time trend Exposure and / or disease incubation period An epidemic curve, or epi curve, is a graphical depiction of the number of outbreak cases by date of illness onset. An epi curve is useful because it can provide information on the outbreak’s Pattern of spread Magnitude Outliers Time trend Exposure and / or disease incubation period Let’s now talk about each of these aspects of an epi curve in more detail.

40 Epi Curve: Pattern of Spread
The overall shape of the epi curve can reveal the type of outbreak (the pattern of spread) Common source Intermittent Continuous Point source Propagated The overall shape of the curve can reveal the type of outbreak – whether it is a common source outbreak or propagated. There are 3 types of common source outbreaks that we may be able to discern from looking at the epi curve: intermittent, continuous, or point source.

41 Common Source Outbreak
People are exposed to a common harmful source Period of exposure may be brief (point source) long (continuous) or intermittent A common source outbreak is one in which people are exposed to a common harmful source. The period of exposure may be brief, long or intermittent.

42 Epi Curve: Common Source Outbreak with Point Source Exposure
This graph is an example of an epi curve for a point source outbreak. A point source outbreak is a type of common source outbreak in which all of the cases are exposed within one incubation period. Note how the graph shows a steep upslope and a comparatively gradual downslope. This shape is characteristic for a point source outbreak. Eating a batch of contaminated food at a social function would be an example of this type of outbreak. Everyone was exposed to the same source, a contaminated food, and the exposure was brief - in this case limited to the social function. Pattern of Spread

43 Epi Curve: Common Source Outbreak with Continuous Exposure
This graph shows an example of an epi curve for a common source outbreak with continuous exposure. In this type of outbreak, the duration of exposure is relatively long and often cases will rise gradually (and possibly plateau, rather than peak) An example of this type of outbreak could be a contaminated well used for drinking water. Pattern of Spread

44 Epi Curve: Common Source Outbreak with Intermittent Exposure
Intermittent exposure often results in an epi curve with irregular peaks that reflect the timing and the extent of exposure This epi curve might illustrate an outbreak in which a food handler who was ill with Hepatitis A only worked on certain days. Cases were exposed to a common source, the food handler, but they were exposed intermittently since the food handler worked only on certain days of the week. Pattern of Spread

45 Epi Curve: Propagated Outbreak
This graph shows an example of an epi curve for a propagated outbreak. A propagated outbreak occurs when there is person-to-person spread. Because of this, propagated epidemics can last longer than common source epidemics, and may lead to multiple waves of infection if secondary and tertiary cases occur. The classic epi curve from a propagated outbreak shows successively taller peaks, distanced one incubation period apart. However, in reality, the epi curve for this type of outbreak may not fit this exact pattern. This type of outbreak could occur, for example, with a disease such as tuberculosis, in which one infected person transmits the disease to several other people who, in turn, infect even more people. Pattern of Spread

46 Epidemic Curves: Magnitude of the Outbreak
An epidemic curve can provide a sense of the magnitude of the outbreak as well. For example, there were 73 cases reported in this point source outbreak, which was also shown in a prior slide. This could be a fairly large outbreak for certain diseases in a small geographical area! Magnitude

47 Epi Curves Provide Information about the Time Trend of an Outbreak
Date of illness onset for the first case Date when the outbreak peaked Date of illness onset for the last case Epi curves also can provide information about the time trend of the outbreak. Considering the date of onset for the first case, the date that the outbreak peaked, and the date of onset for the last case can provide insight into the period of exposure to the risk factor causing the outbreak or the incubation period of the organism causing the outbreak. Number of cases Days

48 Clues from the Epi Curve
Incubation period The time from the moment of exposure to an infectious agent until signs and symptoms of the disease appear Period of exposure Point source outbreak Timeframe during which the exposure likely occurred Epi curves can also be used to estimate two important outbreak characteristics: the probable incubation period and the period of exposure of the causative organism. The incubation period is the time period from the moment of an exposure to an infectious agent until the time that signs and symptoms of the disease appear. The incubation period is characteristic of an infectious agent. For example, the average incubation period for chicken pox is days, and the average incubation period for shiga-toxin producing E coli is 3-4 days. The period of exposure is useful for point source outbreaks, and is the timeframe during which the exposure likely occurred.

49 Using Epi Curves to Estimate the Incubation Period
Use when timing of exposure is known and agent is unknown Estimated incubation period is between Time of suspected exposure Time of peak of epi curve Let’s talk about how to use an epi curve to estimate the incubation period. This is a useful technique when the timing of the presumed exposure is known, epi curves can be used to estimate the incubation period of the infectious agent and, because different agents have different incubation periods, this may facilitate the identification of the causative agent. The estimated incubation period can be determined from an epi curve as the period between the known or hypothesized time of exposure and the peak of the epi curve. In a point source outbreak, the timing from exposure to the peak number of cases will represent the most common, or average, incubation period.

50 Using Epi Curves to Estimate Period of Exposure
Use when incubation period for the disease is known Period of exposure is between Peak of epi curve counting back the average incubation period Earliest case, counting back the minimum incubation period In common source outbreaks involving diseases with known incubation periods, epi curves can help determine the probable period of exposure. This can be done by looking up the average incubation period for the organism and counting back from the peak case the amount of time of the average incubation period. Likewise, you can look up the minimum incubation period for the organism and count back the minimum incubation period from the earliest case on the epi curve. Since this technique is not precise, you may want to widen the identified exposure period by 10% to 20% on either side so as not to miss a potential exposure.

51 Calculating the Exposure Period
Let’s look at an example to put this technique into context. Consider the outbreak of hepatitis A illustrated by the epi curve shown here. The incubation period for hepatitis A ranges from 15 to 50 days, with an average incubation period of days (or roughly one month). Remember to calculate the exposure period, we locate the peak of the epi curve and count back the average incubation period. So first, what is the peak of the outbreak? During this outbreak, the peak of the outbreak occurred on or about October 28th. Second, given that the average incubation period for Hepatitis A is about one month, what date would we arrive at if we count backwards about one month from the outbreak peak? One month earlier would fall during the last few days of September. Note on the graph, where the time period of the average incubation period is marked, falling from about September 30th to the outbreak peak on October 28th. Next, let’s also look at the minimum incubation period of Hepatitis A, counting back from the earliest case. The earliest case occurred on October 20th. The minimum incubation period, as we noted earlier, is 15 days. Subtracting 15 days from October 20th points us to October 5th. Note that this time frame is also marked on the graph. In this situation, we now have a time frame to examine for possible Hepatitis A exposures, and that period is about September 30th to October 5th. In this outbreak, this time period turned out to be the exact period during which there had been a temporary lapse in chlorination of the water supply! Centers for Disease Control. Hepatitis–Alabama. MMWR 1972:21:

52 Creating an Epidemic Curve
Number of cases of disease reported during an outbreak plotted on the y-axis Cases of Disease X in Y Population, Nov-Dec 2012 By this time, you have a good idea of what an epidemic curve looks like and its basic elements. Let’s take a moment to list all the elements you should include when you create an epidemic curve graph. The structure of an epi curve is straight forward. Simply plot the number of cases of disease reported during an outbreak on the y-axis (the vertical line) and the time or date of illness onset on the x-axis (the horizontal line). Also, you should include the pre-epidemic period on the epi curve to show the baseline number of cases. You should include a descriptive title and labeled axes with your epi curve. Pre-epidemic period included to show the baseline number of cases Time or date of illness onset plotted on the x-axis

53 Creating an Epidemic Curve
Descriptive title Cases of Disease X in Y Population, Nov-Dec 2012 Every epidemic curve should include a descriptive title, which means that the disease, the population and/or place, and the time period should be given. Always label the x and y axes. Axis labels

54 Epi Curve X-axis Units Depends upon the incubation period
Begin with a unit one quarter the length of the incubation period Example: 1. Mean incubation period for influenza = 36 hours x ¼ = 9 3. Use 9-hour intervals on the x-axis for an outbreak of influenza lasting several days One of the trickier aspects of creating an epi curve is choosing the unit of time for the x-axis. This choice is usually based on the incubation period of the illness and the time interval of the outbreak. In general, a time unit that is approximately one quarter of the incubation period is usually a good place to start. For example, imagine that we are plotting an influenza outbreak. The mean incubation period for influenza is about 36 hours. To determine our units, we take one-quarter of 36 hours, which is 9 hours. We would then use 9-hour intervals on the x-axis for this outbreak. Keep in mind the entire time period you are considering, however. If the outbreak is over several days, the 9-hour time period will work well. In fact, you might choose 8 hours, just to make it easier to graph 24-hour periods. However, if you are plotting cases that have occurred in a larger outbreak over a month, this time period will quickly become cumbersome, and you will want to consider one or 2-day intervals.

55 Epi Curve X-axis Units For an unknown incubation period
Graph several epi curves with different time units Choose units that best represent the data Units may range from hours to months, depending on the outbreak duration and known or suspected incubation period If the incubation period of the illness (or the illness itself) is not known, several epi curves with different time intervals on the x-axis should be examined to see which x-axis units best represent the data. For most diseases, onset by day is appropriate for the x-axis, but for illnesses with very short incubation periods (for example, Staphylococcus aureus food poisoning) hours of onset may be preferable. Likewise, for diseases with long incubation periods, such as tuberculosis, the best time interval may be days, weeks, or months. Epi Info software allows you to plot by hours, minutes, and even seconds, and by a.m. versus p.m. as needed. If an outbreak endures over several weeks or months, you will also need to consider this in the choice of x-axis units.

56 Example X-axis Considerations
For example, consider these data for the same outbreak displayed by week of onset on the left and day of onset on the right. The graph by day of onset looks quite different and is more informative than the graph by week of onset. For example, the epi curve using the day as the unit of time on the x-axis distributes the cases more evenly and highlights the first identified case patient. X-axis unit of time = 1 week X-axis unit of time = 1 day

57 Session Summary Outbreak Outbreak investigation
The occurrence of more cases of disease than expected for a given place and time Outbreak investigation Decision to investigate depends on several factors Verification of the diagnosis allows for identification of the incubation period and is necessary to hypothesize about the exposure Case definition classifies case-patients related to the outbreak and is used to conduct additional case finding In conclusion of our session on recognizing an outbreak, let’s review some key points. By definition, an outbreak is the occurrence of more cases of a disease than expected for a given place and time. The decision whether or not to investigate an outbreak depends on several factors, including whether a true outbreak can be verified. There are basic steps that can be followed to investigate an outbreak but these steps can be followed in a flexible manner, so the order can change and steps can be skipped or repeated as needed. These steps include verification of the diagnosis, which allows for identification of the incubation period and is necessary for generating hypotheses about the exposure that may have caused the outbreak. A case definition is needed to classify case-patients related to the outbreak and to conduct additional case finding.

58 Session Summary Descriptive epidemiology Measures of central tendency
Characterizes the outbreak by time, place, and person Is essential for hypothesis generation Measures of central tendency Assess distribution of data Include mean and median Epi curves, spot maps, and line listings are ways to summarize time, place, and person elements of descriptive statistics Conducting descriptive epidemiology is a first step in characterizing the outbreak so that possible causes can be identified. Descriptive epidemiology familiarizes the investigator with data about time, place, and person and is essential for hypothesis generation. Measures of central tendency provide a means of assessing the distribution of data. These measures include mean and median. Finally, epi curves, spot maps, and line listings are all ways in which you can summarize and review the time, place, and person elements – respectively – of descriptive statistics. These methods can provide additional information and clues about the cause of the outbreak.

59 References and Resources
Centers for Disease Control and Prevention (1992). Principles of Epidemiology, 2nd ed. Atlanta, GA: Public Health Practice Program Office. Centers for Disease Control and Prevention. Outbreak of Meningococcal Disease Associated with an Elementary School--Oklahoma, March 2010; MMWR April 6, 2012 / 61(13); Centers for Disease Control and Prevention. Brainerd Diarrhea. Division of Bacterial Disease; October FOCUS Workgroup. An Overview of Outbreak Investigations. FOCUS on Field Epidemiology (1):1.

60 References and Resources
FOCUS Workgroup. Anatomy and Physiology of an Outbreak Investigation Team. FOCUS on Field Epidemiology (1):2. Hall, J.A., et al. Epidemiologic profiling: evaluating foodborne outbreaks for which no pathogen was isolated by routine laboratory testing: United States, Epidemiol Infect. 2001;127:381-7 Nelson, A. Embarking on an Outbreak Investigation. FOCUS on Field Epidemiology (1):3. Torok, M. Case Finding and Line Listing: A Guide for Investigators FOCUS on Field Epidemiology (1):4. Torok, M. Epidemic Curves. FOCUS on Field Epidemiology (1):5.


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