Gastroenteritis Outbreak (2).docx

Running head: GASTROENTERITIS OUTBREAK

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Investigation into an Outbreak of Gastroenteritis at a Canadian Cottage Retreat Your Name Subject and Section Professor’s Name March 22, 2019

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Introduction Epidemics are one of the most dreaded occurrences in the history of mankind. Due to its scope and effects, worldwide epidemics such as the bubonic plague have killed millions of people and resulted great economic repercussions to countries that they have affected. This severity of its effects is one of the reason why the field of medical science have devoted a specialized field only for the study, prevention, and cure of such occurrences. Included in this field is the study of how certain viruses, pathogens, and bacteria evolve against the current treatments that humans utilize against potential outbreaks In line with this, this study would focus on understanding how epidemics spread within a contained population. In the case presented, a gastroenteritis outbreak has spread among attendees of a business conference in a luxury resort. Assuming the role of a medical practitioner, the author of this study would try to determine the possible causes, vehicle, and effects of the said outbreak. All in all, the author believes that by looking closely at the different pieces of evidences available, a plan of action can then be created to prevent the further spread of such disease.

The Case As stated earlier, the case at hand is about spread of a gastroenteritis among the attendees of a business conference. The venue where the spread is believed to have started was an al-inclusive and private resort that serves regular meals for the guests based on the time table of the activities. Unfortunately, the spread of such disease has led to the hospitalization of about 30 individuals where one has tragically died. Among the symptoms that the guests had experienced include severe stomach cramps, diarrhea, and blood in the stool. Since there is similarity between their symptoms, despite the fact that the attendees have come from different areas across Canada, then it could be presumed that the symptoms have started since arrival. Lastly, it was said that the last patient that exhibited symptoms have been admitted by August 9th, which was 10 days after their arrival. In order to make sure that a potential spread could be recognized, the case definition for this study is that “Any individual that has cramps, diarrhea, bloody stool or has been hospitalized since July 30th not obviously due to a previous condition”. Bearing these facts into mind, an analysis of such spread can be done.

Case Analysis Time In the case, it could be seen that there was a 10-day period between the arrival of the guests and the date where the last patient has been admitted. Most gastroenteritis viruses have an incubation period of 24-48 hours, while that of norovirus is about 18-72 hours (VictoriaStateGovernment, n.d.). On the one hand, since the first patients showed symptoms of the illness 2 days after their arrival (August 1), then this suggests that the virus was contracted on the day of their arrival or the day prior the first appearance of the symptoms. On the other hand, since the last showing of symptoms occurred 10 days after, then it is possible that the last exposure was on the 7th to 9th day, following aforementioned incubation periods of the viruses (Figure 1). Epidemic Curve Another way of understanding the spread of the epidemic would be through the epidemic curve. An epidemic curve is simply the “visual display of the onset of illness among cases associated with an outbreak” (Center for Disease Control and Prevention, n.d.). Based on the data provided on the number of people afflicted with the disease, a table and an epi curve could be constructed as follows.

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Figure 2 – Epidemic Curve The Epi curve shown above portrays the spread of the disease among attendees of the conference. It could be noted that most of the symptoms (n = 6) have presented themselves during August 3, from 12 NN to 12 MN. The spread has then subsided until August 5 12 NN to 12 MN. After then, the spread continued sporadically, until August 9 where the last patient was admitted in the local hospital. Considering that the number of reported patients have peaked during August 3 – PM, then the possibilities for the meals and other exposures to be the source of the epidemic are as follows: Possible Exposures and Agents Cucumber Sushi

Time of Exposure (i.e., when it is served) July 30; AM

Possible microorganisms

Average Incubation Date

Resulting Time for Exposure

a. Campylobacte r b. Clostridium perfringens c. E.coli O157H7 d. Salmonella a. E.coli O157H7

a. 2-5 days b. 6-24 hours c. 3-4 days d. 7 hours

a. August 1 AM to August 4 AM b. July 30 AM to August 1 PM c. August 2 AM to August 3 AM d. July 30 PM a. August 2 PM to August 3 PM

a. E. coli b. Shigellosis c. norovirus

a. 3-4 days b. 1-3 days c. 12 – 48 hours

a. August 3 AM to August 4 AM b. August 1 to August 4 c. July 31 to August 2

a. 3- 30 days

a. August 3 to August 31

Sweet potato tacos or burgers Swimming race in the lake

July 30; 6 PM

Scavenger hunt in the woods Chicken Caesar Salad

July 31

a. Borrelia burgdorferi

July 31; AM

a. Campylobacter b. Clostridium perfringens c. E.coli O157H7 d. Salmonella

July 31

a. 3-4 days

a. 2-5 days b. 6-24 hours c. 3-4 days

a. August 2 AM to August 5 AM b. July 31 AM to August 1 AM c. August 4 AM to August 5 AM

GASTROENTERITIS OUTBREAK e. Staphylococcus aureus

Cauliflower curry

July 31; PM

a. Clostridium perfringens b. Bacillus cereus toxicosis (emetictype)

Pasta with Basil Pesto

July 31; PM

E.coli O157

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d. July 31 PM e. July 31 PM

a. August 1 AM to August 1 PM b. July 31 PM to August 1 AM

a. August 3 PM to August 4 PM

The graph above would show different answers to the questions at hand. First, the characteristic of the curve as well as the number of people afflicted would suggest that this is indeed an epidemic. Aside from this, but looking at the peaks and the troughs of the epi curve itself, one could see that this is a kind of ‘point-source outbreak’. Generally speaking, in a point source outbreak, “persons are exposed over a brief time to the same source, such as a single meal or an event” (Center for Disease Control and Prevention, n.d.). This results to a graph with one single peak, and smooth curve on both sides showing onset of the diseases on one side and the gradual tapering of the cases on the other. Accordingly, this shows that there is no propagation (person-to-person) contamination that is happening between the patients. As compared to point-source outbreaks, propagation would show a “curve shape of progressively taller peaks”, which is not the case in the graph provided above. Person In assessing the spread of an epidemic, another factor that must be taken into consideration is the demographic data of those who are afflicted with the disease. This includes age and gender, among other factors. However, considering that our sample population is only limited to adults, due to the nature of the said conference, the demographic factors that would be considered are only gender and age (25 – 60 years old). The following sections would determine if there’s correlation between the said factors and the spread of the disease through the use of tabular representations and odd ratios. Gender In analyzing demographic factors, it is important to determine whether there is a specific correlation between gender and illness. Doing so would help rule out as to whether the disease is sexrelated or not. Aside from this, looking at these facts would also help the practitioner to determine the manner of transmission by isolating possible mediums (or vehicles) of exposure (i.e., water in the women’s comfort room). To determine whether there is a relationship between these two variables, a table below is provided (Table 2 and 3). At first glance, data in table 2 would show that the number of females who were afflicted of the disease is lower as compared to the males. However, due to the greater total number of former attendees, it is important to view the differences in terms of percentages. Accordingly, Table 3 provides the differences in percentages between males and females who contracted the diseases relative to their groups. It shows that there are no significant differences between the two gender groups, which can help us remove it from the possible mediums of transmission for the disease at hand. ILL Column Labels Row Labels N Y Total F 11 16 27 M 9 14 23

GASTROENTERITIS OUTBREAK Total Row Labels F M Grand Total

Y 16 14 30

Percentage 59% 61%

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50

Odds Ratio: OR = (11/9) / (16/14) = (1.22) / (1.14) OR = 1.07

Based on the odd ratio calculated above (1.07 or 107%), it could be seen that the likeliness of one gender to contract the disease is 7% higher than the other. However, this is not significant enough to rule out that gender is a strong force in the determination of the spread of the disease. Age Table 2 below would show that relative percentages of the people who contracted the disease based on age. The author has initially enumerated the ages of the attendees to serve as the categories. After this, the number of those afflicted (n=30) were then counted and recorded to the corresponding category where they belong. As could be seen from the resulting table, about 10% of the total people who were afflicted with the illness was 53 years of age. Aside from that, no other patterns were apparent from the sample population. Age Y Percentage Age Y Percentage Age Y Percentage 25 1 3.3% 39 2 6.7% 51 0.0% 27 1 3.3% 40 1 3.3% 52 1 3.3% 28 1 3.3% 41 1 3.3% 53 3 10.0% 29 0.0% 42 2 6.7% 54 1 3.3% 30 2 6.7% 43 0.0% 55 1 3.3% 32 1 3.3% 44 1 3.3% 56 0.0% 33 2 6.7% 45 1 3.3% 57 1 3.3% 35 0.0% 46 0.0% 59 1 3.3% 36 1 3.3% 47 1 3.3% 60 1 3.3% 37 1 3.3% 48 0.0% Total 33.3% 30 38 0.0% 50 2 6.7%

Cryptosporidium Aside from the possibility of contracting the disease from food, it is also possible that the virus (or bacteria) that caused the epidemic could have used the water in the lake as a medium. This is because most of the attendees have went swimming during the duration of their conference. However, upon looking at the table below (Table 4), the number of attendees who did not swim yet contracted the disease (n = 17) exceeds those who swim (n =13). Count of ILL Column Labels Odds Ratio: Swim N Y Total OR = (11/9) / (17/13) N 11 17 28 = (1.22) / (1.31) Y 9 13 22 OR = 0.93 Total 20 30 50 The computation for the odds ratio between swimming and contracting the disease showed a result of 0.93. Accordingly, this shows that one odd (swimming or not) has a 7% lower chance of leading

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to the disease as compared to the other. Similarly, this odd is not sufficient enough to rule out that swimming is the cause of the outbreak. Lyme Disease Since the attendees have also gone on a scavenger hunt in tall grass, it is also possible that the disease that they have contracted is Lyme Disease. Lyme disease is “caused by the bacterium Borrelia burgdorferiand is transmitted to humans through the bite of infected blacklegged ticks” (Center for Disease Control and Prevention, 2018). The possibility for such is strengthened considering that among those who joined the scavenger hunt (n=33), 20 has contracted the disease while 13 did not. However, it must also be noted that Lyme disease is not contagious between persons. Thus, this raises the question as to why 10 attendees have contracted the disease despite them not joining the said activity. ILL Column Labels Odds Ratio: Hunt N Y Total OR = (7/13) / (10/20) N 7 10 17 = (0.54) / (0.5) Y 13 20 33 OR = 1.08 Total 20 30 50 Just like the previous exposures and elements that have been discussed above, the odds ratio for Lyme disease and the symptoms are low (1.08). Particularly, the resulting odd ratio suggest that the other factor only has 8% higher probability as compared to the other. Symptoms Symptom Profile Disease Diarrhea Cramps Hospital

Frequency (Y) 26 28 11

Percentage (n=30) Disease 87% Blood 93% Dead 37%

Frequency Percentage (Y) (n=30) 17 57% 2 7%

Table 8, would show the particular symptom profile of the patients who had afflicted the disease. Although, there are differences between the symptoms diarrhea, cramps, and bloody stool, these three are the most common among all the patients who contracted the disease. Median Incubation Period The epi curve would show the sudden increase and gradual decrease of the outbreak at hand. From this, the median incubation period of the virus or pathogen could be deduced. Accordingly, the results show that Period between the hypothesized exposure and the outbreak of the disease coincides with each other.

Conclusion Based on the table provided above, two different possible causes for the disease was isolated. These are (1) Campylobacter and (2) shigellosis. On the one hand, this is because the start of their incubation period coincides with the minimum time needed, relative to the first case presented. On the other hand, these two also satisfies the maximum time needed to reach their “maximum incubation period”, which could be seen at the end of the curve.

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References Center for Disease Control and Prevention. (2018, December 21). Lyme Disease. Retrieved from CDC.gov: https://www.cdc.gov/lyme/index.html Center for Disease Control and Prevention. (n.d.). Epi Curve. Retrieved from CDC.gov: https://www.cdc.gov/training/QuickLearns/createepi/1.html Center for Disease Control and Prevention. (n.d.). Using an Epi Curve to Determine Mode of Spread. Retrieved from CDC.gov: https://www.cdc.gov/training/QuickLearns/epimode/ VictoriaStateGovernment. (n.d.). Viral gastroenteritis (not rotavirus). Retrieved from VictoriaStateGovernment.Gov: https://www2.health.vic.gov.au/public-health/infectiousdiseases/disease-information-advice/viral-gastroenteritis-not-rotavirus

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Appendix Possible Exposures and Agents Cucumber Sushi

Possible microorganisms

Reasons for elimination

a. Campylobacter b. Clostridium perfringens c. E.coli O157H7 d. Salmonella

Sweet potato tacos or burgers Swimming race in the lake

a. E.coli O157H7

Scavenger hunt in the woods

a. Borrelia burgdorferi

Chicken Caesar Salad

a. Campylobacter b. Clostridium perfringens c. E.coli O157H7 d. Salmonella e. Staphylococcus aureus

Cauliflower curry

a. Clostridium perfringens b. Bacillus cereus toxicosis (emetictype) a. E.coli O157

a. Campylobacter is a possible agent b. Possibility of Clostridium Perfringens as the virus causing the disease is eliminated because the ‘resulting outbreak expected’ (July 30 AM to August 1 PM) does not match the outbreak in the epi curve c. Possibility of the outbreak being caused by E coli on the sushi is eliminated because its incubation period is only supposed to be between Aug 2 to Aug 3, whereas the outbreak happened from Aug 1 PM to Aug 5 PM d. Possibility of Salmonella being the main cause is also eliminated as the ‘resulting outbreak expected’ is July 30 a. Eliminated since the resulting outbreak expected is both later and earlier than the outbreak period. a. Any possibilities of the disease being contracted from swimming in the lake is eliminated due to the low ‘odds ratio’ (0.93) provided in the previous section b. Admitted c. Eliminated due to incubation periods. a. Any possibilities of the disease being contracted from scavenger hunt is eliminated due to the low ‘odds ratio’ (1.08) provided in the previous section a. Eliminated because expected outbreak does not coincide with the real time period b. Expected outbreak is a lot earlier than what appeared, thereby eliminating it c. Eliminated since expected outbreak should be much latter than what happned d. Eliminated since expected incubation period is July 31 e. Eliminated since expected incubation period is July 31 c. Eliminated because expected incubation period is much earlier d. Eliminated because expected incubation period is much earlier

Pasta with Basil Pesto

a. E. coli b. Shigellosis c. norovirus

b. Eliminated since incubation period does not coincide

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