Introduce About page

This commit is contained in:
Gabriella Azzopardi 2021-05-11 10:20:47 +00:00 committed by Philip James Elson
parent 60568aab35
commit 77f52a8087
6 changed files with 146 additions and 3 deletions

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@ -127,6 +127,18 @@ class LandingPage(BaseRequestHandler):
self.finish(report)
class AboutPage(BaseRequestHandler):
def get(self):
template_environment = self.settings["template_environment"]
template = template_environment.get_template("about.html.j2")
report = template.render(
user=self.current_user,
active_page="about",
text_blocks=template_environment.globals['common_text']
)
self.finish(report)
class CalculatorForm(BaseRequestHandler):
def get(self):
template = self.settings["template_environment"].get_template(
@ -171,6 +183,7 @@ def make_app(
urls: typing.Any = [
(r'/?', LandingPage),
(r'/_c/(.*)', CompressedCalculatorFormInputs),
(r'/about', AboutPage),
(r'/static/(.*)', StaticFileHandler, {'path': static_dir}),
(prefix + r'/?', CalculatorForm),
(prefix + r'/report', ConcentrationModel),

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@ -0,0 +1,55 @@
{% extends "page.html.j2" %}
{% block contents %}
<h1>Airborne Transmission of SARS-CoV-2</h1><br>
Currently, the existing public health measures point to the importance of proper building and environmental engineering control measures, such as proper Indoor Air Quality (IAQ).
This pandemic clearly raised increased awareness on airborne transmission of respiratory viruses in indoor settings.
Out of the main modes of viral transmission, the airborne route of SARS-CoV-2 seems to have a significant importance to the spread of COVID-19 infections world-wide, hence proper guidance to building engineers or facility managers, on how to prevent on-site transmission, is essential.<br>
For information on the Airborne Transmission of SARS-CoV-2, feel free to check out the HSE Seminar: <a href=https://cds.cern.ch/record/2743403>https://cds.cern.ch/record/2743403</a>.<br>
Slides available in <a href=https://indico.cern.ch/event/968258>https://indico.cern.ch/event/968258/</a>.
<h1>What is CARA?</h1><br>
CARA stands for COVID Airborne Risk Assessment and was developed in the spring of 2020 to better understand and quantify the risk of long-range airborne spread of SARS-CoV-2 virus in workplaces. CARA comes with different applications that allow more or less flexibility in the input parameters:
<ul>
<li><a href='/calculator'>CARA calculator app</a></li>
<li><a href='/expert-app'>CARA expert app</a></li>
</ul>
The mathematical and physical model simulate the long-range airborne spread of SARS-CoV-2 virus in a finite volume, assuming a homogenous mixture, and estimates the risk of COVID-19 infection therein. The results DO NOT include short-range airborne exposure (where the physical distance plays a factor) nor the other known modes of SARS-CoV-2 transmission. Hence, the output from this model is only valid when the other recommended public health & safety instructions are observed, such as adequate physical distancing, good hand hygiene and other barrier measures.<br>
<p>The methodology, mathematical equations and parameters of the model are described here: <a href="https://edms.cern.ch/ui/file/2566402/1/CARA_Deterministic_parameters_2020.pdf">https://edms.cern.ch/ui/file/2566402/1/CARA_Deterministic_parameters_2020.pdf</a>.</p>
The model used is based on scientific publications relating to airborne transmission of infectious diseases, virology, epidemiology and aerosol science. It can be used to compare the effectiveness of different airborne-related risk mitigation measures.
The tool helps assess the potential dose of infectious airborne viruses in indoor gatherings, with people seated, standing, moving around, while breathing, speaking or shouting/singing. The model is based on the Wells-Riley model of aerosol disease transmission, which assumes a fixed value for the average infectious dose. The dose-response models for respiratory diseases is more accurate, although since this parameter for SARS-CoV-2 is not known so far, the Wells-Riley method is recommended in the health science community (see <a href="#references_block">References</a>).
The methodology of the model is divided into three parts:
<ol>
<li>Estimating the emission rate of infectious viruses.</li>
<li>Modeling the concentration evolution of viruses within a given volume and consequent inhalation dose during the exposure time.</li>
<li>Estimating the probability of a COVID-19 infection, the expected number of new cases arising from the transmission event and the basic reproduction rate (R0).</li>
</ol>
Parts #1 and #3 are mainly based on methods published in scientific papers (see <a href="#references_block">References</a>), and cover the medical aspects, which is not the core competencies of the authors. The heart and soul of CARA lies within the Part #2 and the concentration modelling, which is based on a mass-balance differential equation solved for a constant emission rate and time-dependent exchange rate (e.g. natural ventilation flow rate). Other aspects, e.g., the biological decay of the virus in the air, gravitational settlement of the aerosols, mechanical supply of fresh air, effect of HEPA filtration, among others, are also included.<br>
<h1>What is the aim of CARA?</h1><br>
Although the user is able to calculate the infection probability of a stand-alone event with a pre-defined set of protection measures, the main utility of CARA is to compare the relative impact of different measures and/or combination of measure. For example:
<ul>
<li>Compare keeping a window slightly open vs one or two windows open entirely</li>
<li>Compare opening one entire window every 2h for 10 min vs keeping half a window open all day</li>
<li>Compare the effect of an FFP2 with respect to a Type I surgical mask</li>
<li>Adapt the maximum occupancy considering the effect of HEPA filters</li>
<li>Etc…</li>
</ul>
<h1>Authors:</h1><br>
{{ text_blocks['Authors'] }}
<h1>Acknowledgements:</h1><br>
{{ text_blocks['Acknowledgements'] }}
<a id="references_block" style="color:#2f4858"><h1>References:</h1></a><br>
{{ text_blocks['References'] }}
<div class="text-component text-component-page clearfix"></div>
<br>
</div>
{% endblock contents %}

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## Authors
<h4>Andre Henriques<sup>1</sup>, Marco Andreini<sup>1</sup>, Gabriella Azzopardi<sup>2</sup>, James Devine<sup>3</sup>, Philip Elson<sup>4</sup>, Nicolas Mounet<sup>2</sup>, Markus Kongstein Rognlien<sup>2</sup>, Nicola Tarocco<sup>5</sup></h4><br>
<sup>1</sup>HSE Unit, Occupational Health & Safety Group, CERN<br>
<sup>2</sup>Beams Department, Accelerators and Beam Physics Group, CERN<br>
<sup>3</sup>Experimental Physics Department, Safety Office, CERN<br>
<sup>4</sup>Beams Department, Controls Group, CERN<br>
<sup>5</sup>Information Technology Department, Collaboration, Devices & Applications Group, CERN<br>
## Acknowledgements
We wish to thank CERNs HSE Unit, Beams Department, Experimental Physics Department, Information Technology Department, Industry, Procurement and Knowledge Transfer Department and International Relations Sector for their support to the study. Thanks to Doris Forkel-Wirth, Benoit Delille, Walid Fadel, Olga Beltramello, Letizia Di Giulio, Evelyne Dho, Wayne Salter, Benoit Salvant and colleagues from the COVID working group for providing expert advice and extensively testing the model. Finally, we wish to thank Fabienne Landua and the design service for preparing the illustrations and Alessandro Raimondo, Ana Padua and Manuela Cirilli from the Knowledge Transfer Group for their continuous support. Our compliments towards the work and research performed by world leading scientists in this domain: Prof. Manuel Gameiro, Prof. Shelly Miller, Prof. Linsey Marr, Prof. Jose Jimenez, Dr. Lidia Morawska, Prof Yuguo Li et al. their scientific contribution was indispensable for this project.
## References
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[2] Jimenez, J. (2020), Summary of the Evidence For and Against the Routes of Transmission of SARS-CoV-2. https://tinyurl.com/aerosol-pros-cons.<br>
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[22] Shen Y, Li C, Dong H, et al. Community Outbreak Investigation of SARS-CoV-2 Transmission Among Bus Riders in Eastern China. JAMA Intern Med. Published online September 01, 2020. doi:10.1001/jamainternmed.2020.5225.<br>
[23] Park S, Kim Y, Yi S, et al. Coronavirus Disease Outbreak in Call Center, South Korea. Emerging Infectious Diseases. 2020;26(8):1666-1670. doi:10.3201/eid2608.201274.<br>
[24] Liu, Y., Ning, Z., Chen, Y. et al. Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature (2020). 10.1038/s41586-020-2271-3.<br>
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[26] Gao, X., Li, Y. and Leung, G.M., 2009. Ventilation control of indoor transmission of airborne diseases in an urban community. Indoor and Built Environment , 18(3), pp.205 -218.<br>
[27] Zhu S, Jenkins S, Addo K, et al. Ventilation and laboratory confirmed acute respiratory infection (ARI) rates in college residence halls in College Park, Maryland. Environment International. 2020;137:105537. doi:10.1016/j.envint.2020.105537.<br>
[28] Perry J.L., et al. Submicron and Nanoparticulate Matter Removal by HEPA-Rated Media Filters and Packed Beds of Granular Materials. NASA/TM—2016218224.<br>
[29] Julian W. Tang, et al. (2009) A schlieren optical study of the human cough with and without wearing masks for aerosol infection control J . R. Soc. Interface.6S727S736. 10.1098/rsif.2009.0295.focus.<br>
[30] Buonanno, G., et al. (2020) “Estimation of airborne viral emission: Quanta emission rate of SARS-CoV-2 for infetion risk assessment”, https://doi.org/10.1016/j.envint.2020.105794.<br>
[31] Buonanno, G., et al. (2020) “Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications ”, https://doi.org/10.1016/j.envint.2020.106112.<br>
[32] Gammaitoni, L. et al. (1997) “Using a mathematical model to evaluate the efficacy of TB control measures.”, Emerg. Infect. Dis. (1997), pp. 335-342, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2627642.<br>
[33] Huang, J.T., et al. (2007) “Evaluation of the Efficiency of Medical Masks and the Creation of New Medical Masks.”, J. Int. Medical Research, 35: 213 223, https://doi.org/10.1177/147323000703500205.<br>
[34] Morawska, L. et al. (2009), “Size distribution and sites of origin of droplets expelled from the human respiratory tract during expiratory activities”, J. Aerosol Science, 256-269, https://doi.org/10.1016/j.jaerosci.2008.11.002.<br>
[35] Riley, E.C., et al. (1978), “Airborne spread of measles in a suburban elementary school.”, Am. J. Epidemiol. 107, 421432, https://doi.org/10.1093/oxfordjournals.aje.a112560.<br>
[36] Sze To, G.N., Chao, C.Y.H. (2010). “Review and comparison between the Wells-Riley and dose-response approaches to risk assessment of infectious respiratory diseases.” Indoor Air 20, 216. https://doi.org/10.1111/j.1600-0668.2009.00621.x.<br>
[37] Wells, W.F., (1934). “On airborne infection: study II. Droplets and Droplet nuclei.” Am. J. Epidemiol. 20, 611618. https://doi.org/10.1093/oxfordjournals.aje.a118097.<br>
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[40] WHO. Avoid the three Cs Be aware of different levels of risk in different settings. https://www.who.int/images/default-source/wpro/countries/malaysia/infographics/three-3cs/final-avoid-the-3-cs-poster.tmb-1920v.jpg?sfvrsn=638335c1_1.<br>
[41] Miller, S. Germicidal Ultraviolet Light (Radiation) for Reducing Disease Transmission. https://shellym80304.files.wordpress.com/2020/05/isiaq-guv-2-compiled.pdf
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[46] Li, Yuguo (2020). SARS-CoV-2 airborne transmission is opportunistic and ventilation works. University of Hong Kong. COVID-19 zoom conference. https://www.hku.hk/f/upload/21292/HKU%20Covid-19%20Zoom%20conference.pdf.<br>
[47] Marr, L. (2020). Aerosol and Transmission of Respiratory Viruses 101, Airborne Transmission of SARS-CoV-2: A Virtual Workshop. https://www.nationalacademies.org/event/08-26-2020/airborne-transmission-of-sars-cov-2-a-virtual-workshop?s=09 .<br>
[48] Morawska, L. (2006). Droplet fate in indoor environments, or can we prevent the spread of infection?. Indoor Air, Volume: 16, Issue: 5, Pages: 335-347, doi:10.1111/j.1600-0668.2006.00432.x.<br>
[49] Marr, L.C., Tang, J.W., Van Mullekom, J., et al., 2019, Mechanistic insights into the effect of humidity on airborne influenza virus survival, transmission and incidence, J Roy Soc Interface. https://doi.org/10.1098/rsif.2018.0298.<br>
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<p>
CARA is a risk assessment tool developed to model the concentration of viruses in enclosed spaces, in order to inform space-management decisions.
It does this by simulating the long-range airborne spread SARS-CoV-2 virus in a finite volume, assuming homogenous mixing, and it estimates the risk of COVID-19 infection therein.
Please see the <a href="https://gitlab.cern.ch/cara/cara/-/blob/master/README.md">about</a> page for more details on the methodology, assumptions and limitations of CARA.
Please see the <a href="/about">About</a> page for more details on the methodology, assumptions and limitations of CARA.
</p>
<p>
The full CARA source code can be accessed freely under an Apache 2.0 open source license from our <a href="https://gitlab.cern.ch/cara/cara">code repository</a>.

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</a>
</li>
</li>
<li>
<a href="/about" class="{{ "is-active" if "about" == active_page else "" }}">
About
</a>
</li>
</ul>
</div>
</div>

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@ -31,7 +31,6 @@ async def test_user_guide(http_server_client):
assert resp.code == 200
@pytest.mark.xfail(reason="about page not yet implemented")
async def test_about(http_server_client):
resp = await http_server_client.fetch('/about')
assert resp.code == 200