HLTH4200 Walden University Epidemiologic Triad Triangle Project When epidemiologists are working to track a disease, the three elements that they focus on

HLTH4200 Walden University Epidemiologic Triad Triangle Project When epidemiologists are working to track a disease, the three elements that they focus on are the agent, the host, and the environment. Following are explanations of each element.

The agent is what causes the disease. The agent is often a virus or bacteria but can also be caused by other agents. In the scenario, described in the Introduction, the agent is the E.coli bacteria.

The host refers to those who are contracting the disease. The host doesn’t necessarily become sick. Hosts can serve as carriers of the disease who do not show outward signs or symptoms.

Finally, the environment refers to the external factors that support or cause the disease to spread. In the E. coli scenario, the lettuce became infected either at the farm or during transport; the lettuce was sold to the distributor and then to Sam’s Sandwich trucks; and people ate the lettuce on these sandwiches.

Each of these steps is important to tracking the disease, and epidemiologists work diligently to trace and report each of the steps to prevent further transmission of the disease.

The following is an example of an epidemiologic triad.

Agent: Salmonella bacteria
Keep in mind that agents can be biologic (e.g., bacteria or viruses), chemical (e.g., poisons or alcohol), physical (e.g., trauma or radiation), or nutritional (e.g., a lack or excess of essential nutrients).
Host factors: Individuals who are particularly vulnerable (e.g., the very young or very old and immunocompromised individuals).
Note that, in general, host characteristics can include age, sex, race, religion, customs, occupation, genetic factors, other health factors, and immunologic status.
Environmental factors: Contaminated kitchen surfaces or utensils, undercooking of contaminated food items, or contaminated chicken.
Environmental factors can include temperature, crowding, noise, pollution, food, and radiation.

Changes in one factor in the epidemiological triad can influence the occurrence of disease by increasing or decreasing a person’s risk for disease. Consider how variations in each factor, shown in the example, can influence the manifestation of disease. Refer to pages 492–500 in your Friis and Sellers (2014) textbook for further explanation.

In this Discussion, you will apply the epidemiologic triad to a disease of your choice to gain a better understanding of both the model and the disease.

To prepare?for this Discussion:

Access and review the Epidemiological Triad Learning Interaction.

Select an infectious disease from the list proved in List of Infectious Diseases document for Week 1 Discussion.

Review the Week 1 “Ebola Virus Disease in the Light of Epidemiological Triad” (Kaur, Sachdeva, Jha, & Sulania, 2017) resource. Consider how the epidemiologic triad/triangle can be applied to your selected disease.

Consider how variations in each factor shown in the example from the textbook can influence the manifestation of the disease. Refer to pages 492–500, in your textbook, for further explanation.

BY DAY 4

Post a comprehensive explanation of the following:

Identify the disease you selected.
Provide an example of an agent that is associated with the infectious disease that you selected.
Discuss ?at least three? examples of environmental factors that contribute to the likelihood of transmission of the agent to an individual for the disease you have selected.
Discuss?at least three? examples of host factors that contribute to the likelihood of transmission of the agent to an individual for the disease you have selected.

Use complete sentences in writing your Discussion post, cite your sources, and include references in APA format. Ensure that your in-text citations and reference list are in APA format List of Infectious Diseases for Week 1 Discussion
1. Acute flaccid myelitis (AFM; polio-like disease)
2. Anthrax
3. Botulism
4. Chlamydia
5. Cholera
6. Cryptosporidiosis
7. Dengue virus infections
8. Ebola virus disease
9. Gonorrhea
10. Hantavirus
11. Hepatitis A (foodborne)
12. HIV infection (AIDS has been reclassified as HIV Stage III)
13. Influenza
14. Legionellosis
15. Leptospirosis
16. Lyme disease
17. Measles
18. Meningococcal disease
19. Mumps
20. Pertussis
21. Plague
22. Poliomyelitis
23. Shiga toxin-producing Escherichia coli (foodborne)
24. Syphilis
25. Tuberculosis
26. West Nile virus
27. Yellow Fever
28. Zika virus disease
Food-Borne Outbreak
Background
An outbreak (epidemic) of gastroenteritis occurred in Greenport, a suburban neighborhood, on the
evening of April 28. A total of 95 people went to the emergency departments of the three local
hospitals during that evening. No more cases were reported afterward. These patients complained
of headache, fever, nausea, vomiting and diarrhea. The disease was severe enough in 25 patients to
require hospitalization for rehydration. Gastroenteritis outbreaks like this are usually caused by the
consumption of a contaminated meal. Meal contamination can often be caused by pathogenic
viruses or bacteria. Acute outbreaks are often produced by toxins from bacteria such as
Staphylococcus spp., Clostridium perfringens, Salmonella spp. and Vibrio cholerae. Norovirus
strains are also common causes of acute outbreaks.
Outbreak Investigation
The local health department was notified of a potential food-borne outbreak of gastroenteritis in
Greenport, and the epidemic team, including an epidemiologist, a microbiology technician and a
nurse, visited the local hospitals to interview the attending physicians, the patients and some of
their relatives. Some stool samples were obtained from patients for microbiologic identification of
the causative agent. The epidemic team knew these types of outbreak usually occur in a very short
time period that lasts no more than a few hours or one to two days after people ingest a
contaminated meal.
Epidemic investigators gather data to define the distribution of the disease by time (onset time and
epidemic curve), place (potential places where the implicated meal was served, such as cafeterias,
restaurants and picnics) and person (the distribution of the disease by age, gender and food items
eaten). The findings of the initial investigation included the following information.
The distribution of the disease by person (age and gender) was found as follows:
Gastroenteritis Outbreak Findings by Person, Case Distribution by Age and Gender
Age Group
0-5
6-10
11 and older
Total by Gender
Females
No. % Female (in age group)
1
44
8
Males
No. % Male (in age group)
1
37
4
Total
No. %
Please calculate the totals for each column and row and their corresponding percentages to try to
determine if there are any important differences by age or by gender. For the column under female
and male, you will be calculating the percentage of female and male cases in that age group out of
the total number of cases for that age group. For example, if there were 4 female cases in the first
age group and a total of 6 cases (both female/male), then the percentage of female cases in that age
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group is 66.67%. For the last column (total), you will divide the number of cases in each age group
by the total number of cases (all age groups) and multiply by 100 to get the percentage.
This task is carried out to investigate if there are any high-risk groups and if the age and gender
distribution can give some clues about the source of the outbreak. Discuss the age group and
gender with the highest proportion of cases.
Construct an Epidemic Curve (use Excel; please review the document entitled, “Constructing an
Epidemic Curve Using Excel” to practice). Put the times in the A column of the spreadsheet and
the number of cases in the B column. Then click to insert a column (bar) chart. Insert the
chart on the last page of this document.
Case distribution (by times):
8:00pm
1
11:00pm
17
8:30pm
1
11:30pm
9
9:00pm
5
12:00am
8
9:30pm
8
12:30am
7
10:00pm
12
1:00am
5
10:30pm
20
1:30am
2
Your epidemic curve shows the onset time of illness in the 95 patients involved in the outbreak.
The epidemic team studied the curve and recognized that this was a typical single (point) source
acute outbreak. The team also could see that the onset of symptoms in all patients occurred during
a six-hour period. Given the symptoms mentioned above and the epidemic curve, the epidemic
team concluded that this type of epidemic usually corresponds to intoxication or food poisoning
and that the potentially implicated meal was probably served and consumed within a period of a
few hours before the onset of the symptoms. Therefore, the epidemic team investigated the places
where affected persons, their relatives and neighbors ate that day (April 28). The following table
shows the team’s findings. Note: Often, during interviews, more ill persons will emerge (who did
not seek medical attention and may/may not be part of this outbreak).
Gastroenteritis Outbreak Findings by Place
Place
Local
cafeteria
People
Who
Attended
Number Ill
from those
who
attended
210
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10
Attack
Rate (%)
People
Who Did
Not Attend
Number Ill
from those
who did
not attend
160
8
Attack
Rate (%)
Relative
Risk
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Place
People
Who
Attended
Number Ill
from those
who
attended
Attack
Rate (%)
People
Who Did
Not Attend
Number Ill
from those
who did
not attend
Local
restaurant
250
8
126
4
Lions Club
luncheon
480
20
194
8
Elementary
school
cafeteria
245
76
495
19
Attack
Rate (%)
Relative
Risk
Please calculate the attack rates (multiply your answer by 100 to get the AR%) by place to try to
determine where the contaminated meal was served. For each place compare attack rates (AR) for
those who attended with attack rates for those who did not, by using the relative risk (i.e., RR =
AR in attendees/AR in nonattendees). Round all answers to the hundredths (i.e, 2.23 vs 2.2).
Relative Risk is not a percentage, so only use % to denote ARs. You will calculate RRs for place
and then food items. So, if one of the places above had an RR of 3.92, your interpretation of the
RR would be that “those who ate at [name of place] had nearly 4 times the risk of gastroenteritis”.
If any of the RRs are well below 1.0, that would mean the location or food was protective of
gastroenteritis ~ meaning those who ate at a certain location or ate an item were less likely to be ill.
For example, if an RR for a food was 0.32, you could state that “those who ate that food were 68%
less likely to have gastroenteritis”. You find the % by subtracting the lower RR from 1.0.
Interpret your findings from the above table.
Once the implicated place was determined, the investigation centered on the food. The following
table includes the food items served in that place on April 28:
Gastroenteritis Outbreak Findings by Person
Ate the Food Item
Did Not Eat the Food Item
Food Item
Total
No. Ill
Attack
Rate (%)
Total
No. Ill
Beef burritos
150
12
230
19
Tossed salad
98
60
297
13
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Attack
Rate (%)
Relative
Risk
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Ate the Food Item
Did Not Eat the Food Item
Food Item
Total
No. Ill
Attack
Rate (%)
Total
No. Ill
Cheeseburger
250
21
131
20
Ice cream
175
19
203
22
Fruit cocktail
88
52
290
23
Baked potato
139
9
243
33
Attack
Rate (%)
Relative
Risk
Important note: None of the kitchen personnel were ill. The names of the kitchen personnel and
their participation in the food preparation are as follows: Manuel prepared the beef burritos and the
potatoes, John prepared the salad and the fruit, Sally served all dishes except the ice cream, and
Jane prepared the cheeseburgers and served the ice cream. The ice cream was a commercial brand
and was bought at a nearby supermarket.
Please calculate the attack rates per 100 (noted as a percentage) by food item to try to determine
the one that was probably contaminated. Compare attack rates (AR) for those who ate the food
item with attack rates for those who did not eat the food item, by using the relative risk (i.e., RR =
AR in those who ate the food/AR in those who did not eat the food). Round your answers to the
hundredths (i.e, 2.23 vs 2.2). Relative Risk is not a percentage, so only use % to denote ARs.
Interpret your findings below.
Given that the epidemic team worked fast enough and the implicated meal(s) was (were)
identified before all food leftovers were discarded, food samples from some meal leftovers were
taken to the laboratory. In addition, stool samples were taken from the kitchen personnel who
prepared or handled each different food item. The laboratory confirmed that Salmonella toxin was
present in some of the food samples and that one of the kitchen personnel of that place had the
same Salmonella species. Furthermore, the Salmonella species found in the food and the kitchen
worker was the same species found in stool samples of the patients. Please discuss these findings
and identify the kitchen worker possibly responsible for the outbreak.
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To determine which food item(s) are responsible, is it enough to just calculate the ARs for
those who ate the food items? Why or why not? (Give a thorough response)
Insert Epidemic Curve on this page.
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Attack Rates & Attack Rate Ratio (Relative Risk)
Relative Risk Example
Escherichia coli 0157:H7 has been classified as a new emerging infection. This
serotype of E. coli is different from previously identified E. coli strains and propagates
slowly, which makes it difficult to detect. Outbreaks of infection have caused death in a
few cases and serious illness in vast numbers of cases exposed to it, especially children.
E. coli outbreaks have been identified in the western U.S., tied to a single fast-food
restaurant chain, especially in Washington state, Las Vegas, and California.
A Little League baseball organization decided to have a season-end barbecue.
The hamburger was furnished by a local private butcher shop. While butchering a steer,
one of the butchers accidentally nicked the large intestine, and some of the animal’s feces
got into the parts ground into hamburger.
It was a nice day, a family affair, with a large turnout of 275 persons – 172 males
and 103 females – attending the barbecue. There were 55 people who were part of the
Little League who did not attend the barbecue. The total number of children and family
members affiliated with the Little League was 330 people.
At the barbecue, two separate grills were used to cook the hamburgers. Two of
the fathers volunteered to do the cooking. One father, Mr. Smith, heard many children
complaining about being hungry, so he wanted to get their burgers to them as fast as he
could. Mr. Smith liked his meat rare, so he seared the extra-thick hamburger patties on
one side, flipped them over, and seared them on the other, heating up the meat quite well
but not really cooking them all the way through. He failed to make the center of the
hamburger reach the required 155 degrees F – proven to be the safe cooking temperature.
The second father, Mr. Cooke, liked his hamburgers well done, but not burned. He held
them to the grill with the spatula each time, squeezing out the juice and helping the meat
cook more. He checked each patty, to ensure that he was cooking the burgers well done,
by opening each one with the corner of the spatula to see that each patty was not pink in
the middle.
Late the next day, on Sunday, several different children from several different
families ended up at the ER of the local hospital, all with similar symptoms of fever,
pain, malaise, stomachache, and bloody diarrhea. After 7 children, all with the same
symptoms, were presented at the ER, the local public health department and
communicable disease epidemiologist were notified.
Several physicians also called the department of public health to report serious
diarrhea cases, all of which had bloody stools with the diarrhea. Laboratory results of
samples collected from the cases showed that the pathogen was Escherichia coli
0157:H7.
In the epidemiological investigation, it was found that, of those who were sick, 46
boys, 22 men, 14 girls, and 16 women got their hamburger patties from Mr. Smith,
whereas 6 boys, 4 men, 4 girls, and 2 women got their patties from Mr. Cooke. It was
discovered that 123 people in all got their hamburgers from Mr. Cooke and 152 from Mr.
Smith. Relative risk was to be determined by the epidemiologist for the risk of eating
© 2019 Laureate Education, Inc.
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hamburgers cooked by Mr. Smith as compared to those cooked by Mr. Cooke. In order
to determine relative risk, a matrix was developed by the epidemiologist.
Diseased
Not Diseased
Totals
Mr. Smith
a = 98
b = 54
a + b = 152
Mr. Cooke
c = 16
d = 107
c + d = 123
Totals
a + c = 114
b + d = 161
a+b+c+d = 275
(total pop. At risk)
To calculate the risk ratio of the E. coli outbreak and cases of illness resulting
from the cooking of Mr. Smith and Mr. Cooke, you calculate the risk of getting ill for
those who ate Mr. Smith’s cooking versus risk for those who ate burgers cooked by Mr.
Cooke (these are Attack Rates).
Risk of illness from Mr. Smith = a / a + b = 98 / 152 = .645 x 100 or 64.5%
(64.5% risk of getting ill by eating Mr. Smith’s cooking)
Risk of illness from Mr. Cooke = c / c + d = 16 / 123 = .130 x 100 or 13.0%
(13% risk of getting ill by eating Mr. Cooke’s cooking)
To calculate the attack rate ratio (relative risk) for Mr. Smith (0.645) versus Mr.
Cooke (0.13), the following steps are taken. First, to assess the ratio of risk, the AR% for
those who were exposed is placed in the numerator, and the AR% for those who were not
exposed is placed in the denominator. Thus, the formula is:
Relative risk = Risk ratio = .645/.13 = 4.96
The risk of getting E. coli at the Little League barbecue by eating Mr. Smith’s
cooking is 4.96 – very high compared to that for Mr. Cooke’s cooking. Thus, for every 1
person who gets sick from eating Mr. Cooke’s cooking, approximately 5 will get sick
from eating Mr. Smith’s cooking.
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Constructing an Epidemic Curve Using Excel
This step-by-step guide is for a simple Epidemic Curve using Excel. This example will use the
cases and dates of a Hepatitis A outbreak. Please practice using this information to construct an
Epidemic Curve with Excel.
Step 1. Input the cases and dates of onset into an Excel spreadsheet.
Column A (date)
April 2
April 26
May 1
May 4
May 6
May 8
May 10
May 12
May 16
May 18
May 20
May 22
May 26
May 30
Column B (# of cases that day)
1
1
4
10
6
8
10
15
10
2
1
1
1
1
Step 2. Select all the cells with data (right-click on A1 and drag down
to B14)
Step 3. Click on Insert on the top menu
Step 4. Click on Insert Column or Bar Chart (2-D Column)
Step 5. The Column Chart / Graph will appear on your spreadsheet.
Step 6. Check to make sure all cases are on the graph and on the right dates. Click on the
‘Chart Title’ to change the heading.
Step 7. Right click on the graph and select ‘Copy’. You can now paste the graph into
another document.
Attack Rates & Attack Rate Ratio (Relative Risk)
Relative Risk Example
Escherichia coli 0157:H7 has been classified as a new emerging infection. This
serotype of E. coli is different from previously identified E. coli strains and propagates
slowly, which makes it difficult to detect. Outbreaks of infection have caused death in a
few cases and serious illness in vast numbers of cases exposed to it, especially children.
E. coli outbreaks have been identified in the western U.S., tied to a single fast-food
restaurant chain, especially in Washington state, Las Vegas, and California.
A Little League baseball organization decided to have a season-end barbecue.
The hamburger was furnished by a local private butcher shop. While butchering a steer,
one of the butchers accidentally nicked the large intestine, and some of the animal’s feces
got into the parts ground into hamburger.
It was a nice day, a family affair, with a large turnout of 275 persons – 172 males
and 103 females – attending the barbecue. There were 55 people who were part of the
Little League who did not attend the barbecue. The total number of children and family
members affiliated with the Little League was 330 people.
At the barbecue, two separate grills were used to cook the hamburgers. Two of
the fathers volunteered to do the cooking. One father, Mr. Smith, heard many children
complaining about being hungry, so he wanted to get their burgers to them as fast as he
could. Mr. Smith liked his meat rare, so he seared the extra-thick hamburger patties on
one side, flipped them over, and seared them on the other, heating up the meat quite well
but not really cooking them all the way through. He failed to make the center of the
hamburger reach the required 155 degrees F – proven to be the safe cooking temperature.
The second father, Mr. Cooke, liked his hamburgers well done, but not burned. He held
them to the grill with the spatula each time, squeezing out the juice and helping the meat
cook more. He checked each patty, to ensure that he was cooking the burgers well done,
by opening each one with the corner of the spatula to see that each patty was not pink in
the middle.
Late the next day, on Sunday, several different children from several different
families ended up at the ER of the local hospital, all with similar symptoms of fever,
pain, malaise, stomachache, and bloody diarrhea. After 7 children, all with the same
symptoms, were presented at the ER, the local public health department and
communicable disease epidemiologist were notified.
Several physicians also called the department of public health to report serious
diarrhea cases, all of which had bloody stools with the diarrhea. Laboratory results of
samples collected from the cases showed that the pathogen was Escherichia coli
0157:H7.
In the epidemiological investigation, it was found that, of those who were sick, 46
boys, 22 men, 14 girls, and 16 women got their hamburger patties from Mr. Smith,
whereas 6 boys, 4 men, 4 girls, and 2 women got their patties from Mr. Cooke. It was
discovered that 123 people in all got their hamburgers from Mr. Cooke and 152 from Mr.
Smith. Relative risk was to be determined by the epidemiologist for the risk of eating
© 2019 Laureate Education, Inc.
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hamburgers cooked by Mr. Smith as compared to those cooked by Mr. Cooke. In order
to determine relative risk, a matrix was developed by the epidemiologist.
Diseased
Not Diseased
Totals
Mr. Smith
a = 98
b = 54
a + b = 152
Mr. Cooke
c = 16
d = 107
c + d = 123
Totals
a + c = 114
b + d = 161
a+b+c+d = 275
(total pop. At risk)
To calculate the risk ratio of the E. coli outbreak and cases of illness resulting
from the cooking of Mr. Smith and Mr. Cooke, you calculate the risk of getting ill for
those who ate Mr. Smith’s cooking versus risk for those who ate burgers cooked by Mr.
Cooke (these are Attack Rates).
Risk of illness from Mr. Smith = a / a + b = 98 / 152 = .645 x 100 or 64.5%
(64.5% risk of getting ill by eating Mr. Smith’s cooking)
Risk of illness from Mr. Cooke = c / c + d = 16 / 123 = .130 x 100 or 13.0%
(13% risk of getting ill by eating Mr. Cooke’s cooking)
To calculate the attack rate ratio (relative risk) for Mr. Smith (0.645) versus Mr.
Cooke (0.13), the following steps are taken. First, to assess the ratio of risk, the AR% for
those who were exposed is placed in the numerator, and the AR% for those who were not
exposed is placed in the denominator. Thus, the formula is:
Relativ…
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