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| − | <b><a style="color:black; text-decoration: none; line-height:1.1;"href="#target1">Measurements</a></b>
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| − | <b><a style="color:black; text-decoration: none; line-height:1.1;" href="#target3">Sensitivity and Specificity</a></b>
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| − | ADD ChromeQ and App overview and results
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| − | <div id="subheading2"><b>Threshold</b></div>
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| − | Our app, Color Q, generates a relative percentage value, which is calculated from the color variance from a control sample. However, we need to determine what relative percentage value, or threshold, constitutes as a positive test result because a water sample could have a very low concentration, which would not make those who drink it at risk for contraction.
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| − | The infectivity rate for Cholera varies from 104 to 1011 bacterium ingested, depending on the strain and conditions of the host [3]. In order to be health protective, we want a negative result to mean that there is less than 10³ bacterium ingested per person from a water source. Therefore, our threshold is 10³ bacterium per two liters of water, the average water intake per day. For our biosensor, a 100 ml water sample is taken, so for a positive test, there must be 50 bacterium in the sample, with some variability due to the uneven spread of cholera in a water source.
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| − | Then to determine the relative percentage value for a positive test, we will carry out our biosensor protocol on water samples with known concentrations of Cholera. The samples would be triplicates of concentrations of 0, 25,40, 50, 60 and 100 cholera cells per 100ml to see the change in the relative percentage value with differing concentrations. After using our software, we would average the relative percentage value for the samples with a concentration of 40, 50, 60 cholera cells to receive a threshold value. If a sample in the field meets or exceeds the value determined, it would be a positive sample.
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| − | <div id="subheading2"><b>Sensitivity and Specificity</b></div>
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| − | Sensitivity and specificity give insight into the accuracy of disease detection tests. Sensitivity is defined as the percentage of positive test results where it is confirmed that Cholera is present (true positives) out of all of the positive samples, true positives and false negatives [1]. Specificity is the percentage of negative test results that are confirmed to have no Cholera present (true negatives) out of all the negative samples, true negatives and false positives [1]. To find these percentages, we must have another reliable detection method that we will compare our results to. According to the CDC, growing a culture of the sample is the gold standard for Cholera detection [2]. Therefore, we will culture the water sample as well as test our biosensor cells and compare the results to find our test’s accuracy. The results from the culture will be the ‘truth’ of whether the sample really has Cholera or not. Therefore, if the culture is positive and our test’s results are positive, it is a true positive, but if the culture is negative and our results are positive, it is a false positive, and it is the same for true negatives and false negatives. [1]
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| − | <th>Cholera Present</th>
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| − | <th>No Cholera Present</th>
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| − | <th>Positive Test</th>
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| − | <th>True Positive</th>
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| − | <th>False Positive</th>
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| − | <th>Negative Test</th>
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| − | <th>False Negative</th>
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| − | <th>True Negative</th>
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| − | Once the data collection is completed, there are two formulas to calculate sensitivity and specitivity.
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| − | <li>Sensitivity= true positives/(true positives + false negatives) x 100 [1]</li>
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| − | <li>Specificity=true negatives/(true negatives + false positives) x 100 [1]</li>
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| − | </ul>
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| − | The purpose of our biosensor is to detect Cholera at the source to prevent contraction. Therefore, we are more invested in a high sensitivity rather than specificity. With a higher sensitivity, it is more likely to have false positives, but it is safer to have false positives and take precaution than to have false negatives and contract the disease.
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| | [4] Bjerketorp, J., Håkansson, S., Belkin, S., & Jansson, J. K. (2006, February). Advances in preservation methods: Keeping biosensor microorganisms alive and active. Retrieved October 8, 2018, from https://www.ncbi.nlm.nih.gov/pubmed/16368231 | | [4] Bjerketorp, J., Håkansson, S., Belkin, S., & Jansson, J. K. (2006, February). Advances in preservation methods: Keeping biosensor microorganisms alive and active. Retrieved October 8, 2018, from https://www.ncbi.nlm.nih.gov/pubmed/16368231 |
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References
[1] 10.3 - Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value. (2018). Retrieved October 8, 2018, from https://onlinecourses.science.psu.edu/stat507/node/71/
[2] Cholera - Vibrio cholerae infection. (2018, July 20). Retrieved from https://www.cdc.gov/cholera/diagnosis.html
[3] Nelson, E. J., Harris, J. B., Morris, J. G., Calderwood, S. B., & Camilli, A. (2009, October). Cholera transmission: The host, pathogen and bacteriophage dynamic. Retrieved October 8, 2018, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3842031/
[4] Bjerketorp, J., Håkansson, S., Belkin, S., & Jansson, J. K. (2006, February). Advances in preservation methods: Keeping biosensor microorganisms alive and active. Retrieved October 8, 2018, from https://www.ncbi.nlm.nih.gov/pubmed/16368231
