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PUB 540 Oswego Outbreak Case Study

Part 2

In the epidemiological study, the outbreak of diseases depend on various factors. In other
words, disease can be caused by different forms of infections that are either occurring naturally
in the environment of manmade. Measuring the outbreak of diseases involves the collection and
analysis of data to understand the risk factors. Data are always collected from the respondents on
various possible causes of the disease outbreaks. There are different methods that can be applied
in the process of data analysis to determine the accuracy of the data analysis outcomes.
Contingency table is one of the best approach of analyzing and interpreting the cause of a disease
(Aygören-Pürsün et al., 2018). Before engaging in the use of contingency table, there is always
the need to determine the frequencies and to understand different aspects of the data for accurate
outcomes (Carcillo et al., 2017). Investigation of the disease outbreaks involved different
procedures which has to be successfully followed. Every step ought to be covered to ensure the
accurate prediction can be made. In the above case, the first step involved in the disease outbreak
is the identification of the possible. The second step involved the identification of the food
products and the kinds of pathogens that cause that spread or the disease outbreak. The
investigation processes should also involve the possible agents involved in the spread of the
disease among the populations.
In the above case study, there was the analysis of disease outbreaks from the food
products (Roche et al., 2015). Some of the food products that were presented include cabbage,
Jello, mashed potatoes, cakes, coffee, milk, fruit salad etc. The data was collected at different
dates and the respondent were asked whether they consumed the food product. The interview
was a “Yes” or “No” answer.

From the analysis, there was the determination of the attack rate and the attack rate ratio.
The outcomes were determined from the responses obtained from the clients. From the ratios
obtained in the process of analysis, the above scenario meets the definition of a disease outbreak
(Panisello et al., 2016). The contingency tables presented clearly summarize the relationship that
exist between the categorical variables that have been presented. The variables have been shown
simultaneously (Tomza‐Marciniak et al., 2018). The steps required to investigate the disease
outbreak involves the collection of data, which has already been presented in the Microsoft
Excel. After the process of data collection, there was the determination or the calculation of risk
ratios (Geng et al., 2017). The above computation was done for each of the food item presented
in the table. The outcomes was presented in Oswego Line Listing Workbook. The frequencies
presented in the table, Oswego Attack Rate Table was used to determine the attack rates and the
attack rate ratios through the application of the Excel formulas (Saghafian et al. 2018). From the
given risk ratios, there is a clear indication that the above criterion meets the definition of the
disease (Kateri, 2015). The above steps aided in the investigation of the Oswego event through
the presentation, analysis and interpretation of the data.
For each information to be successful, there was careful analysis and presentation of data.
Also, the processes of data collection were accurate and this led to the successful outcomes. The
disease outbreak was facilitate of a means of transmission (Saghafian et al., 2018). In this case,
the rout of transmission was through ingestion of pathogenic organisms that came from the
contaminated food (Kent et al., 2017). The food contamination is often attributed to the exudes
or faces which are transmitted by different agents. In the above case study, the contaminated
food was consumed which led to the transfer of the disease into the body which later caused

There are different control measures that can be taken into consideration in the above
case (Sevá et al., 2017). Maintaining cleanliness is one of the best approach in controlling the
disease outbreak. Recalling food product is another best approach that can be undertaken to
control the spread of the disease. These are primary prevention measures that ought to be
undertaken to manage the disease outbreak.

Discuss the Possible Agents(S) Responsible For the Outbreak

The possible agents responsible for cause of the disease outbreak is the pathogens found
in the food items presented above. Disease outbreak is often caused by the infection that can
transmitted from one person to the other when there is contact. In the above case, the disease
outbreak was caused by the transfer of pathogens from the food products. The outbreak also
occurred as a result of exposure to chemicals found in the food materials. There could also be
exposure to radioactive chemicals. With the above factors, there was high possibility of rapid
transfer of diseases from one person who consumed the food material to the other.
Graph 1.

Epidemic Curve

From graph 1, the epidemiological curve indicates the measurements involving all the
food components involved in the study process. The curve shows a sharp increase in the number
of infections by the food products.
Graph 2

In graph 2 the curve shows the number of participants measured against the variable, spinach. In
other words. The epidemiological curve shows that there is low chances of disease outbreak for
those who consumed spinach.


Graph 3

In epidemiological curve 3, the trend shows that there is little chances of occurrence in the
Graph 4

The curve in graph 4 shows the participants versus the variable Jello. The curve indicates that
there is little chances in the disease outbreak when Jello is consumed.


Aygören-Pürsün, E., Magerl, M., Maetzel, A., & Maurer, M. (2018). Epidemiology of
Bradykinin-mediated angioedema: a systematic investigation of epidemiological
studies. Orphanet journal of rare diseases, 13(1), 73. Retrieved from:
Carcillo, J. A., Sward, K., Halstead, E. S., Telford, R., Jimenez-Bacardi, A., Shakoory, B., … &
Hall, M. (2017). A systemic inflammation mortality risk assessment contingency table for
severe sepsis. Pediatric critical care medicine: a journal of the Society of Critical Care
Medicine and the World Federation of Pediatric Intensive and Critical Care
Societies, 18(2), 143. Retrieved from: 10.1097/PCC.0000000000001029
Geng, J., Xu, J., Nie, W., Peng, S., Zhang, C., & Luo, X. (2017). Regression analysis of major
parameters affecting the intensity of coal and gas outbursts in laboratory. International
Journal of Mining Science and Technology, 27(2), 327-332. Retrieved from:
Kateri, M. (2015). Contingency table analysis. Methods and implementation using R (First
edition). Aachen, Germany: Editorial Advisory Booard. Retrieved from:
Kent, P., Boyle, E., Keating, J. L., Albert, H. B., & Hartvigsen, J. (2017). Four hundred or more
participants needed for stable contingency table estimates of clinical prediction rule
performance. Journal of clinical epidemiology, 82, 137-148. Retrieved from:
Panisello, P. J., Rooney, R., Quantick, P. C., & Stanwell-Smith, R. (2016). Application of
foodborne disease outbreak data in the development and maintenance of HACCP

systems. International Journal of Food Microbiology, 59(3), 221-234. Retrieved from:
Roche, S. E., Garner, M. G., Wicks, R. M., East, I. J., & de Witte, K. (2015). How do resources
influence control measures during a simulated outbreak of foot and mouth disease in
Australia?. Preventive Veterinary Medicine, 113(4), 436-446. Retrieved from:
Saghafian, F., Malmir, H., Saneei, P., Milajerdi, A., Larijani, B., & Esmaillzadeh, A. (2018).
Fruit and vegetable consumption and risk of depression: accumulative evidence from an
updated systematic review and meta-analysis of epidemiological studies. British journal
of nutrition, 119(10), 1087-1101. Retrieved from:
Sevá, A. D. P., Martcheva, M., Tuncer, N., Fontana, I., Carrillo, E., Moreno, J., & Keesling, J.
(2017). Efficacies of prevention and control measures applied during an outbreak in
Southwest Madrid, Spain. PloS one, 12(10), e0186372. Retrieved from:
Tomza‐Marciniak, A., Stępkowska, P., Kuba, J., & Pilarczyk, B. (2018). Effect of bisphenol A
on reproductive processes: a review of in vitro, in vivo and epidemiological
studies. Journal of Applied Toxicology, 38(1), 51-80. Retrieved from:

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