Microbiology Case Study E. Coli
The increase in cases could be because of a mix up between artificial or real increases. It is important to characterize the reasons for the increase as artificial increases, which are only perceived, versus real increases. Essentially an artificial increase would include such incidents of stools seeing increased culturing. This artificial increase can also be cause by new developments in the testing procedures of the laboratory, where in the past the lab did not fully isolate the microorganism efficiently. Additionally, changes in the population, contamination of cultures, or any possible errors in the data entry process could have resulted in an artificial increase. Yet, real increases are much different. This could result in a large growth in the population size, more people in the population who are at a higher risk of infection, increases of infection in random contexts, or by chance, and finally an increase infection cases due to a known outbreak.
Question 1 B
In order to help determine which of the previous explanations the cause is most likely, it will be important to examine the procedures with lab and surveillance staff can be examined in order to identify any potential issues. Any potential changes in local lab staff or the procedures used by lab staff might signify an artificial cause in the increase, including changes in diagnosing or reporting practices by the physicians in question. Additionally, if it has been documented that there were issues with culturing stool that might also be an artificial cause. Changes in the population or case characteristics might also shed more light on the nature of the cause.
Pulsed Field Gel Electrophoresis, also known as PFGE, can show similar banding patterns including up to one band difference. Thus, if one were to follow this logic, numbers 2, 3, 4, 6, and 7 are not able to be properly distinguished and thus can be seen as being similar. Only number 4 is isolated by a difference in one band.
There are a number of advantages and disadvantages to this case definition. One advantage is the notion that confirmation by the lab will help increase the degree of specificity, therefore increasing the ability to determine which cases fall into this particular context. Other cases, that may be unrelated to the outbreak, can then be dismissed, which ultimately help reduce misclassification that would only serve to confuse lab staff as they search for the source of the infection. Yet, there are some clear disadvantages too. Essentially, having t o have a lab confirmation may not include potential victims of the outbreak that never went to see a doctor. Additionally, patients who did go to a doctor, but were not properly cultured or tested with PFGE methods may also be excluded. This would eventually decrease the ability of the lab to understand the true nature of case characteristics. Moreover, by such strict limitations, lab officials may not be able to account for cases of visitors to Michigan who became infected and then left. This limits the ability to understand how the outbreak may have been spread to other regions.
Essentially, the male to female ratio was similar in most cases seen in the 1997 FoodNet database. Infection was much higher in younger individuals and showed a decline as the age of individuals increased. However, the cases in Michigan showed a different trend. Adult females tended to have the highest rates of infection, especially between 29 and 50 years of age. This ultimately suggests that the infection was caused by products more geared towards younger and middle aged women.
There are a number of questions that could be used to help determine possible sources of infection. Questions should be drafted asking about all the clinical details of the infection, including the date it began, how bad symptoms have gotten, and how long it lasted. Demographic information and healthcare availability should also be included. Additionally, questions regarding food and consumption history in the last seven days, both at home and out at restaurants, would be helpful. Along with any incidences suggesting exposure to other sick individuals in the last week. Exposure to other elements, like farm animals or foreign countries should also be asked. In order to provide a thorough data set to help lead to a hypothesis, individuals with different demographic characteristics should be interviewed.
According to the data, over ten counties have shown cases to be included in this outbreak. There were no common events or activities that significantly stood out, thus it can be determined that there is a wide distribution of the contaminating factor. Moreover, the onset of symptoms tends to be over a month. As such, it can be concluded that either a product with a long shelf life was contaminated, or that there was a continuous contamination of products over a period of time. The average person infected was a 31-year-old female, with is not typical for most E. coli outbreaks, but is similar to Salmonella cases seen in contaminated sprouts or lettuce. Therefore, a tentative hypothesis could assume it is contaminated lettuce or sprouts causing the outbreak.
Question 8 a
All individuals chosen for controls should match the average demographic characteristics of the highest number of infected people, but who have not been infected themselves. Thus, they should have a high risk for the disease based on potential exposure due to similar demographic and geographical characteristics, yet they do not show common symptoms.
Typically, age and gender may not be the best matches because they are broad categories. Yet, based on the average number of those infected having age and gender characteristics in common, they are a good match for this particular case. Based on the wide distribution of the outbreak, categorizing based on neighborhood or relationships would not work. Age and gender helps increase the statistically efficiency of understanding the nature of the outbreak best.
There are a number of methods which might be able to help identify controls. First, there are neighborhood controls, which consist of both home visits and reverse telephone directory services. The advantages of this method are that there are similar exposures and an overall increased notion that controls will participate because of the high risk in their neighborhood. Yet, some disadvantages include an increased level of difficulty in regards to finding the most appropriate age and gender controls willing to participate. Overmatching might also occur, as neighbors and friends typically share products that they like with one another. Finally, it extends the hours needed to work by investigators, as most people work during the day time. There is also the method of random digit dialing. This is when investigators randomly select telephone numbers. The advantages here are that they do not need to provide identifying elements for potential controls. Such a method may produce controls that are much more representative of their communities. However, there are also disadvantages here. Many calls might be needed before the best age-gender matches are found. Additionally, time might be wasted in calls that go to commercial businesses or that are disconnected.
It is best to look at the events and activities in the week prior to the onset of the illness. E. coli has a 3 to 8 day incubation period. As such, seven days prior to symptoms should be an appropriate time period for examining potential exposures. Rather than using 8 days, which might throw off patients, a week is more digestible to most participants and thus more fruitful to the investigation.
There are a number of possible explanations for the association between the illness and the sprouts. First, there is always chance. Second, a selection bias shows that individuals exposed to alfalfa sprouts were more likely to show a diagnosis. True association is another potential explanation, along with confounding elements, where the eating alfalfa sprouts was more associated with another type of food item, like a salad or sandwich. There is also information bias, where individuals diagnosed have a greater memory of eating sprouts than the controls.
These individuals could have had the chance of cross contamination. Some may have had other food items, like a salad or sandwich, and did not realize they were eating alfalfa sprouts. The sprouts may have been in the same bowl or plate, and not even eaten by the individual. Additionally, those who actually did not eat sprouts may have been infected by a secondary source, like with contact by another infected individual.
It is important to determine whether or not there is enough evidence to suggest that sprouts were the true cause. For this case, it was clear to investigators that sprouts were the cause. Yet, they did not have enough specific information to determine which brand or farmers' sprouts to implement a recall. As such, additional studies were necessary to determine the more specific cause of the outbreak. A tracebook going back…