School

School of Health Sciences and Human Performance

Department

Health Promotion and Physical Education

Abstract

The halfway point of each semester amplifies factors including weakened immune systems, due to stress from midterm exams and lack of sleep, and increased commingling amongst student populations. This is the perfect formula that leads to a potential rise in communicable diseases amongst college students. Leading up to midterms and mid-semester breaks, students tend to populate the indoor community spaces due to the cold climate of Ithaca, NY and the high volume of coursework that needs to be completed. The Center for Health Sciences (CHS) computer lab is a commonly populated area on the Ithaca College campus due to the printing resources offered and its proximity to a commonly used lunch space, the CHS Café. Due to course load spikes during mid-semester, students are potentially more inclined to stay on campus regardless of their health status, working in shared spaces, leading to a rise of transmission of communicable disease. Previously, scientists Ross and Neufeld assessed biogeography and microbial variability on university campuses utilizing the 16srRNA gene analysis method. 16srRNA is a universal microbial gene commonly used to identify organisms based on signature sequences. Their study provided evidence supporting flourishing biodiversity of microorganisms related to increased interaction between students, faculty, and staff on university campuses (Ross, Neufeld, 2015). They suggested that an increase in microbial variability on university campuses may correlate to increased infection among student and staff populations. Based on this data, we propose that microbial variability will be higher during midterms week and will be decreased in the week subsequent due to reduced stress and student traffic. Previous conducted studies during Spring 2019 and Fall 2019 aimed to identify and quantify the effect of microbial variability and load in relation to student traffic. Microbial variability was assessed via aseptic swabbing protocol previously described by Chase et al. with some modifications (Chase et al, 2016). Swabbing of these surfaces took place during the middle of midterm exam week and the first day following mid-term break at three different time points (9:00AM, 1:00PM, & 4:00PM). Sterile cotton swabs were immersed in sterile distilled water and swiped onto selected surfaces, including Dell and Mac spacebars and mouses, to collect microbial samples. Samples were immediately swiped onto plates containing Mueller Hinton microbiological growth media, followed by 48-hour incubation at 37 degrees Celsius. Following incubation, microbial growth was assessed macroscopically by colony morphology and microscopically via Gram Stain. We hypothesized that timing of the biogeographical assessment affects the microbial variability outcomes due to high volumes of student traffic. Specifically, the expectation was to detect a greater microbial variability on commonly utilized surfaces during both midterm exam weeks than if these surfaces were assessed immediately following midterm exam breaks. Additionally, variability and load were predicted to increase throughout each day as student traffic progressed. In comparison to research conducted during Spring 2019, further observation was conducted to assess microbial load and variability regarding different computer materials in these community spaces. Mac and Dell computers were assessed to determine differences in variability on computer type. However, it was found that microbial variability and load are higher following midterm exam breaks. Data collected were analyzed and provided evidence of less microbial diversity during midterm week of both semesters. Due to the high prevalence of Gram-Negative species found following swabbing and staining, we can infer that many of these species are potentially pathogenic. This in conjunction with the highest microbial load and variability found at the start of the day during Fall 2019, suggests that computers need to be included in regular disinfection and cleaning processes, to reduce microbial load and variability, and potentially reducing bacterial and fungal transmission. These observations have possible implications in many public settings, especially educational institutions. These data show that current sanitation methods might not be effective at microbial removal to outpace microbial resistance and could put more students at risk of infection. To further support our findings future work would include longitudinal surveying of individuals who use the computer lab to track their infection rates while continued swabbing; to provide evidence in support that microbial load and variability in the lab may be linked to infection.

References:

Chase J., Fouquier J., Zare M, Sonderegger D. L., Knight R., Kelley S. T., Siegel J., Caporaso J.G. (2016). Geography and location are the primary drivers of office microbiome composition. mSystems, 1(2):e00022-16. doi:10.1128/mSystems.00022-16

Ross, A. A., & Neufeld, J. D. (2015). Microbial biogeography of a university campus. Microbiome,3(1). doi:10.1186/s40168-015-0135-0

Document Type

Poster

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Microbial Variability in Relation to Student Traffic and the Prevalence of Illness

The halfway point of each semester amplifies factors including weakened immune systems, due to stress from midterm exams and lack of sleep, and increased commingling amongst student populations. This is the perfect formula that leads to a potential rise in communicable diseases amongst college students. Leading up to midterms and mid-semester breaks, students tend to populate the indoor community spaces due to the cold climate of Ithaca, NY and the high volume of coursework that needs to be completed. The Center for Health Sciences (CHS) computer lab is a commonly populated area on the Ithaca College campus due to the printing resources offered and its proximity to a commonly used lunch space, the CHS Café. Due to course load spikes during mid-semester, students are potentially more inclined to stay on campus regardless of their health status, working in shared spaces, leading to a rise of transmission of communicable disease. Previously, scientists Ross and Neufeld assessed biogeography and microbial variability on university campuses utilizing the 16srRNA gene analysis method. 16srRNA is a universal microbial gene commonly used to identify organisms based on signature sequences. Their study provided evidence supporting flourishing biodiversity of microorganisms related to increased interaction between students, faculty, and staff on university campuses (Ross, Neufeld, 2015). They suggested that an increase in microbial variability on university campuses may correlate to increased infection among student and staff populations. Based on this data, we propose that microbial variability will be higher during midterms week and will be decreased in the week subsequent due to reduced stress and student traffic. Previous conducted studies during Spring 2019 and Fall 2019 aimed to identify and quantify the effect of microbial variability and load in relation to student traffic. Microbial variability was assessed via aseptic swabbing protocol previously described by Chase et al. with some modifications (Chase et al, 2016). Swabbing of these surfaces took place during the middle of midterm exam week and the first day following mid-term break at three different time points (9:00AM, 1:00PM, & 4:00PM). Sterile cotton swabs were immersed in sterile distilled water and swiped onto selected surfaces, including Dell and Mac spacebars and mouses, to collect microbial samples. Samples were immediately swiped onto plates containing Mueller Hinton microbiological growth media, followed by 48-hour incubation at 37 degrees Celsius. Following incubation, microbial growth was assessed macroscopically by colony morphology and microscopically via Gram Stain. We hypothesized that timing of the biogeographical assessment affects the microbial variability outcomes due to high volumes of student traffic. Specifically, the expectation was to detect a greater microbial variability on commonly utilized surfaces during both midterm exam weeks than if these surfaces were assessed immediately following midterm exam breaks. Additionally, variability and load were predicted to increase throughout each day as student traffic progressed. In comparison to research conducted during Spring 2019, further observation was conducted to assess microbial load and variability regarding different computer materials in these community spaces. Mac and Dell computers were assessed to determine differences in variability on computer type. However, it was found that microbial variability and load are higher following midterm exam breaks. Data collected were analyzed and provided evidence of less microbial diversity during midterm week of both semesters. Due to the high prevalence of Gram-Negative species found following swabbing and staining, we can infer that many of these species are potentially pathogenic. This in conjunction with the highest microbial load and variability found at the start of the day during Fall 2019, suggests that computers need to be included in regular disinfection and cleaning processes, to reduce microbial load and variability, and potentially reducing bacterial and fungal transmission. These observations have possible implications in many public settings, especially educational institutions. These data show that current sanitation methods might not be effective at microbial removal to outpace microbial resistance and could put more students at risk of infection. To further support our findings future work would include longitudinal surveying of individuals who use the computer lab to track their infection rates while continued swabbing; to provide evidence in support that microbial load and variability in the lab may be linked to infection.

References:

Chase J., Fouquier J., Zare M, Sonderegger D. L., Knight R., Kelley S. T., Siegel J., Caporaso J.G. (2016). Geography and location are the primary drivers of office microbiome composition. mSystems, 1(2):e00022-16. doi:10.1128/mSystems.00022-16

Ross, A. A., & Neufeld, J. D. (2015). Microbial biogeography of a university campus. Microbiome,3(1). doi:10.1186/s40168-015-0135-0