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Deutsche Bahn
Working Paper www.deutschebahn.com
June 2020 1 © Deutsche Bahn AG
Preliminary Implications of COVID-19 on Long-
Distance Traffic of Deutsche Bahn
Christian Gravert1, Philipp Nagl2, Hans-Peter Lang3, Fabian Ball2, Anja Schöllmann2, Sabina Jeschke1
1Deutsche Bahn AG, Berlin; 2DB Fernverkehr AG, Frankfurt am Main; 3DB Systemtechnik, Munich
E-mail: philipp.nagl@deutschebahn.com
June 2020
Abstract
This paper summarizes the findings of Deutsche Bahn since the outbreak of the COVID-19
pandemic. The number of observed infections on trains is worldwide very low. This holds
true for both passengers and employees. Relevant influencing factors such as the type of
contact, air exchange rate and air flow can explain the low incidence. Air conditioning
systems with a high air exchange rate and fresh air content as well as vertical air flow seem to
have positive effects. Mask wearing and comprehensive testing of employees in suspected
cases are additional precautionary measures. The focus here is on long-distance passenger
traffic.
Keywords: SARS-CoV-2, incidence, airborne infections, air conditioning, long-distance trains, Wells-Riley equation
1. Introduction
With this document, Deutsche Bahn (DB) wants to
contribute to a better understanding of the infection with the
SARS-CoV-2 virus and in particular address the question of
whether travelling on long-distance trains represents an
increased risk of infection. It is our mission to do everything
that is viable to make rail travel as safe as possible. Hence, we
also document our findings for the expert audience and are
grateful for hints and suggestions to further develop our
protective measures.
As a globally operating enterprise, DB has been dealing
with the “SARS-CoV-2” virus and the disease it causes,
“COVID-19”, since January 2020. Since the outbreak in Italy
in February 2020, efforts were intensified and, in particular,
internal monitoring processes for diseases, measures to protect
customers and employees, and measures to gain systematic
knowledge about the virus were initiated.
This document summarizes the findings of our medical,
technical and operational services.
2. Evaluation of available public transport studies
Measured against the large number of passengers and their
diverse contacts, we see remarkably few infections with
SARS-CoV-2 in trains
1
. To our knowledge, not a single
contact tracing has been identified in Germany and Austria as
having been triggered by an infection on the train journey. One
reason for this may be that contact tracing is more difficult in
this setting than in other settings and it is therefore generally
more difficult to generate evidence. However, since the
beginning of March, improved instruments for detecting
infections in trains and buses have been available. DB had
already added an online tool to its customer website at the
beginning of March for passengers who feared they had
become infected on the train. The German government has
ordered the use of “railway disembarkation cards” in cases of
suspected infection, first for cross-border trains and a little
later also for domestic trains
2
. A follow-up of almost 4,700
proven cases of infection in Austria with regard to the concrete
transmission routes showed “[...] no case histories [...]
[through] the use of public transport” (translated from
German)
3
.
Preliminary Implications of COVID-19 on Long-distance Traffic
2
Own enquiries both with the heads of the medical services
of the railways
4
worldwide and with the pandemic teams of
the UIC-represented (International Union of Railways)
railways
5
also did not yield any indications of proven SARS-
CoV-2 infections in trains. In the study by Luo et al.
6
the
highest incidence was measured with over 10% for contacts
within a household. In public transport, one of the most
frequently identified types of contact, an incidence of only
0.1% was calculated.
These surprisingly low infection rates in public transport
have prompted us to analyze the available literature in greater
depth. On the one hand there are studies on concrete
transmissions (in the literature before 2020 of course only on
pathogens other than SARS-CoV-2) and on the other hand
mathematical-theoretical considerations on the risk of
infection in enclosed spaces, such as vehicles.
Compared to international air and sea travel, long distance
train journeys in Central Europe are rather short with an
average duration of three hours. Infection clusters on cruise
7
and military ships received massive attention in the daily
press. In airplanes, as in trains and buses, transmission seems
to occur only rarely
8
.
A meta-study from 2016
9
was looking at the transmission
of influenza and corona viruses in means of transport,
including train journeys. The authors conclude that there is
little overall evidence in the scientific literature on the
transmission of viruses in trains, although there is certainly a
role for public transport in the spread of infectious diseases in
general.
In London in 2018, a positive correlation between the
length of subway journeys and station stops with the incidence
of flu-like illnesses was identified.
10
. However, other authors
concluded for London that people who regularly use public
transport did not have an increased risk of influenza
infection
11
.
There are first studies on the risk of infection on trains in
the current SARS-CoV-2 pandemic, but most of them are still
in preprint status. Qian et al.
12
investigated over 300 outbreaks
of COVID-19 in China with over 1,200 infected persons. To
classify the outbreaks, they divided them into six categories,
one of which is transport, including train travel. One third
(108) of the identified outbreaks took place in the transport
context, including transmissions in motorized individual
transport, and the Chinese New Year with particularly heavy
travel movements during the period under investigation (end
of December 2019 to end of January 2020). A detailed
breakdown of the distribution within the transport category by
the authors is not available and cannot be derived. An
important aspect addressed by the authors is the supply of
fresh air in closed environments caused by ventilation, which
plays a decisive role in the probability of infection. This will
be discussed in chapter four.
For findings on train traffic from China, the long distances
and associated excessive travel times in these cases must be
considered. Cui et al.
13
describe an outbreak of influenza A
(H1N1) in a train in China in 2009, with a total travel time of
over 40 hours (about 2,500km, 28 stops). A total of 22 cases
of infection could be linked to the train journey, eight of them
among passengers (including the index case), five among the
on-board staff and the rest through subsequent close contact
between infected persons. The authors report that the infection
rate in air-conditioned carriages was lower than in non-air-
conditioned ones. Furthermore, the spatial proximity as well
as the individual travel duration played a decisive role in the
probability of infection. No infections occurred in persons on
board with a stay of less than ten hours, four of the 13
infections occurred during a travel period of 10-30 hours and
the remaining nine infections were only identified for a travel
period of more than 30 hours.
The Wells-Riley equation has been established to calculate
the probability of infection in enclosed spaces
14
,
15
where is the number of infected persons in the room, is the
average respiratory rate of a person, is the duration of stay
or exposure and is the ventilation rate ( and per volume
per unit of time). is Euler’s number. The parameter
describes the quanta, which is the rate of infectious particles
an infected person emits per unit of time. It depends on the
specific pathogen and the intensity of the air emission (e.g.
pure breathing as opposed to speaking or singing). In order to
reduce the risk of infection, the rear part of the above term
must converge towards 1. Thus, the number of infected
persons in the room, the number of emitted infectious
particles, the breathing rate and the duration of exposure have
an increasing effect on the probability of infection. The
ventilation rate has a protective effect. Issarov et al.
16
, as well
as Rudnick and Milton
17
, discuss some limitations of the
widely used Wells-Riley equation, such as the assumption of
stationary conditions. Rudnick and Milton modify the formula
in such a way that it can also be applied under non-stationary
conditions.
In a study by Buonanno, Stabile and Morawska
18
, the
quanta of SARS-CoV-2 is estimated regarding the respective
activity (breathing or speaking, both during rest or light work).
A distinction is also made between natural and mechanical air
exchange, with clear advantages for the latter.
Dai and Zhao
19
conclude that, e.g., when travelling in a
train without physical exertion in the presence of an
(asymptomatic) infected person, the probability of infection is
about 1% for a three-hour stay. A shorter exposure time
reduces the risk of infection accordingly. In their scenarios,
the authors distinguish between the wearing and non-wearing
of a medical surgical mask by all those present, assuming
mask wearing to reduce the risk of infection by a factor of four.
The probability of 1% above implies wearing of masks. Other
Preliminary Implications of COVID-19 on Long-distance Traffic
3
recent studies also underline the positive effect of face masks
while optimizing the circulation of fresh air.
20
,
21
Various authors have examined the role of air conditioning
and ventilation of enclosed spaces in the transmission of
airborne pathogens. A literature review can be found in Liu et
al. 2018
22
. Overall, an air supply distributed as evenly as
possible in the room reduces the risk of infection most
strongly. The ventilation rate in closed rooms is also decisive
with regard to airborne transmission, whereby the highest
possible proportion of outside air is always favorable.
In summary, for train journeys two factors are of essential
importance. (1) minimizing breathing air emissions from
potentially infected persons and (2) maximizing fresh air
circulation in the relevant areas. We will discuss these and
further factors in chapters three and four. Measuring body
temperature to detect previously undiagnosed infections, does
not seem to be very practicable
23
, since the rate of undetected
infections is almost 50% and the false positive rate, i.e. healthy
persons are detected as infected, is also relevant.
A particular hazard in long-distance trains cannot be
deduced from the studies conducted to date, presented in the
literature research. On the contrary, infections in trains, as in
airplanes, are rarely observed.
3. Measures taken to protect passengers and staff
DB AG took measures to protect passengers and staff at an
early stage on the basis of the recommendations of the Robert
Koch Institute, the applicable regulations, the latest scientific
findings and knowledge exchange with foreign partner
railways. For example, as soon as the pandemic began to
spread in Germany in March 2020, the cleaning cycles of
contact surfaces in trains, stations and all DB working areas
were increased. If suspicions are confirmed, trains and
workplaces are disinfected subsequently. In suspected cases of
COVID-19 infection in DB AG trains, a reporting process
with the authorities was established and employees in
customer contact were equipped with two FFP 2 (the
European equivalent to N95) masks. One mask is intended for
the suspected infection as external protection and one mask
for the self-protection of the employee during support.
In order to protect DB AG employees, instructions on
behavior during the corona pandemic have been drawn up for
the various occupational groups and are continuously updated.
In addition, employees are regularly informed about current
developments and measures by means of internal
communication channels specific to each professional group.
The other main measures are the creation of additional lunch
and disposition rooms to ensure sufficient distance in the event
of prolonged contact with the same people, installation of spit
guards and partitions, work in the home office where possible,
provision of disinfectants, wearing of mouth-nose covers for
work where the distance of 1.5 metres cannot be maintained,
introduction of contactless ticketing, and other organizational
measures (e.g. adjustment of shift schedules) to reduce
contacts.
Particularly at the beginning of the pandemic, when no
concrete regulations for mouth and nose cover existed, it was
of central importance that sufficient space was made available
for travellers to feel safe while travelling. For this reason, DB
decided to continue to provide a comprehensive and stable
basic service despite the decline in demand and the travel
restrictions imposed.
In long-distance transport, the train frequency was reduced
by about one quarter from the beginning of March to the
beginning of April, but the coverage was never abandoned. No
further reductions were made after the German government
announced initial easing of the regulations on 15 April 2020.
Based on the development of demand and the successive
lifting of travel restrictions, the frequency was raised again
and the load factor control was adjusted.
Within the context of train occupancy rate control, the
number of reservations is limited in the booking portals so that
there is enough space available throughout the train. For better
orientation, new capacity utilization information has been
introduced in the timetable information system. Travel
connections with an expected load factor of more than half of
the seat capacity are specially marked. For connections with a
presumably very high load factor, ticket reservations will be
restricted. As before, the booking process will continue to
ensure that the train load factor is as uniform as possible.
Despite these measures, the 1.5 m social distancing rule in
trains cannot always be respected as passenger numbers
increase; this also emerges from a joint recommendation of the
public transport industry to resume passenger transport during
the COVID-19 pandemic. For this reason, with the
introduction of the general obligation to wear masks as a
further protective measure, DB has made it compulsory for
employees to wear mouth-nose covers on board trains and
strongly recommended that passengers wear them. Despite the
initial scepticism of experts towards mouth-and-nose masks,
they appear to significantly reduce the risk of infection in
public areas and on trains
24
,
25
.
4. Discussion on the transmission path via air
conditioning systems
According to current knowledge, the virus is mainly
transmitted via droplets that are produced when coughing and
sneezing and are absorbed by the person opposite via the
mucous membranes of the nose, mouth, and possibly the eyes.
It has not yet been conclusively clarified whether droplets are
only able to carry a sufficient amount of virus to be infectious
once they reach a certain size. An overview of this discussion
can be found in a publication of the National Academies of
Sciences, Engineering, and Medicine
26
. Larger droplets (>10
μm) presumably have a higher infection potential, but are less
Preliminary Implications of COVID-19 on Long-distance Traffic
4
relevant for the question of air conditioning systems as they
sink to the surface or to the ground after only about 1-2 m. As
it seems more and more likely that infections can also occur
via aerosols (droplets <10 μm)
27
, two questions arise in
connection with the basic functioning of air conditioning
systems.
1. Can an air flow from the air conditioning system
promote the distribution of droplets (especially
droplets <10 μm)?
28
,
29
2. Can the air recirculation function distribute
SARS-CoV2 through the system?
The way air conditioning in trains, planes and many
buildings works is that a mixture of circulating air and fresh
air is treated (cooled, heated, filtered, dehumidified, etc.) and
fed into the passenger compartment. An essential design
principle for the airflow in the passenger compartment is
minimizing draft sensations for the passengers.
The air in an ICE train (Intercity Express, system of high-
speed trains predominantly running in Germany, with train
generations 1-4) is usually discharged close to the ground over
the entire length of the passenger compartment and then
reintroduced either close to the ground, at the windows or
from the roof (cf. Figure 1). Only the circulating air for
recycling is taken as free air flow at the end of the car. The air
flow is therefore essentially vertical rather than horizontal,
which makes direct distribution of the virus by the airflow
rather unlikely
30
.
A transmission of droplets via air conditioning systems
with recirculation function has not been proven so far due to
the very long ventilation paths, the drying of the air and the
existing filters (filter class G4 in rail traffic, particles >10 μm
are filtered). This is also more likely to be ruled out in a case
study of an outbreak in a restaurant28. Nevertheless, this
question has been investigated in more detail for the DB
facilities.
Long-distance trains have a high air exchange rate per
passenger: a complete air exchange with fresh air in an ICE 4
carriage takes place every 6-8 minutes. Per passenger, sensor-
controlled 15-22 m³/h are supplied. An active air volume
control system, which is regulated by the CO2 content, ensures
that the fresh air supply is regulated depending on the
occupancy of the trains and does not drop below this threshold
even when the trains are fully loaded or in the event of extreme
heat or cold.
For air traffic, the Boeing 737-800 has an air exchange rate
for fresh air of “10-15” per hour
31
. Converted to the volume of
the passenger compartment of approx. 200 m³, this means an
average air exchange in the 737 every 4.8 minutes. Calculated
on the higher number of passengers per m³ in air traffic, this
means with an average load factor of 96% and with 189 seats
(business figures of Ryanair 2019) per passenger between 11
and 17 m³/h fresh air.
The air exchange rate in air and rail traffic is thus
comparable and is significantly higher than in buildings
(especially malls, restaurants or churches)12.
In aircraft, usually finer filter systems (HEPA = High
Efficiency Particulate Air filter) are additionally available.
These are currently only designed for the air circulation and
pressure requirements of air traffic and have not been
technically applicable to land transport so far, since germ-free
outside air can be taken in during flight in the aircraft, which
does not represent a burden for fine filters, whereas the filter
systems on the ground have to cope with the outside air with
pollen and dust. However, in rail traffic, regular stops during
a journey, especially at higher load factors, mean that
additional fresh air is supplied by the passengers getting on
and off the train. This effect has a positive impact, but varies
greatly and is therefore not considered further in this study.
DB is currently examining the use of extended filter systems
for new train generations.
Overall, based on the theoretical findings from the literature
in connection with the actual functioning of air conditioning
systems in ICE trains, it cannot be assumed that this will
increase the risk of infection. On the contrary, due to good
ventilation, a reduction of the risk can be assumed. In
connection with the incremental re-opening of our society, the
population's need for mobility is also increasing. As the
number of vehicles is increasing, we need to answer the
Figure 1: Schematic diagram of air distribution in the ICE, Source: DB AG
Preliminary Implications of COVID-19 on Long-distance Traffic
5
question of whether the measures already taken are
appropriate, sufficient and whether there is need for additional
action.
Therefore, DB has decided to conduct a follow-up project
with the German Aerospace Center (Deutsches Zentrum für
Luft- und Raumfahrt; DLR) in railroad cars by means of
simulation calculations and 1:1 tests, in the laboratory and on
the original vehicle in which basic knowledge about possible
infection paths.
5. Empiricism among the employees of Deutsche
Bahn
5.1 Evaluation of the internal reporting systems
DB has systematically recorded all confirmed COVID-19
cases since the beginning of the pandemic.
Number of
persons
Age 20-66
CoVID-19
positive cases
Age 20-66
Ratio
DB (only Germany)
198,000
326
0,16%
DB FV
17,300
30
0,17%
DB FV Board Service
8,000
17
0,21%
German Population
51,800,000
134,701
0,26%
Table 1. Evaluation of reporting system DB AG for confirmed COVID-
19 cases, status 02.06.2020. DB FV = DB Fernverkehr
It can be seen that the number of infected DB employees,
in relation to the population of their group within the railways,
within long-distance transport and within the train attendant
service, is below the age-corrected proportion of COVID 19
cases in Germany. The train attendant service is of particular
interest because this group of employees was on the trains
during the entire pandemic phase and could therefore have
come into contact with infected passengers.
5.2 Environment of the infection in sick persons in long-
distance transport
As part of the systematic recording of confirmed COVID-
19 cases, the environment in which the COVID-19 infection
occurred was also recorded for the employees of DB
Fernverkehr AG (German for: DB Long-Distance Traffic).
Infection
Environment
No. of cases
train attendant
service
Ratio
No. of cases DB
FV w/o train
attendant service
Ratio
Unknown
8
47%
3
23%
Private
Environment
8
47%
5
38%
Professional
Environment
1
6%
5
38%
Sum
17
100%
13
100%
Table 2. Evaluation of the infection environment of employees of DB
Fernverkehr AG, status 02.06.2020
The evaluation shows that in the area of train attendant
service, the proportion of infections in the professional
environment is significantly lower than the proportion of other
occupational groups of DB Fernverkehr AG and the
proportion of infections in the private environment is higher
than the proportion of other occupational groups. However,
the proportion of cases in the train attendant service in which
the environment of the infection is unknown is higher than in
the other occupational groups. Nevertheless, no increased risk
of infection for employees on board long-distance trains can
be deduced from these figures.
5.3 Study on infection risks and immunity of long-
distance transport employees
Together with the Charité – Universitätsmedizin Berlin,
DB will conduct a study on COVID-19 infection risks in long-
distance transport from the end of June 2020 onwards.
In the study, at least 400 train attendants, 150 train drivers
and 150 maintenance workers at the locations Berlin,
Frankfurt, Hamburg and Munich will be examined for acute
SARS-CoV-2 infections and COVID-19 immunity in three
runs at four-month intervals. By comparing the infections and
immunities in the three occupational groups, findings are to be
gained as to whether
a. train crew on long-distance trains is exposed to a
higher risk of infection with COVID-19 than other
operational occupational groups,
b. there is a significant number of previously
undetected COVID-19 infections at work,
c. further measures must be taken to protect company
employees.
The selection of the test persons is based on a representative
random sample per location and department.
The tests for acute COVID-19 infections are carried out by
PCR nasal/venture swab, the tests for COVID-19 immunity by
an antibody test by blood collection. Medical-epdimiological
risk factors in the test persons are determined by means of a
questionnaire. The scientific evaluation of the tests will be
carried out in completely anonymous form and in compliance
with all data protection requirements.
5.4 COVID-19 findings in the ICE plants in Munich and
Berlin
Two confirmed cases of SARS-CoV-2 were reported at the
Munich ICE plant at the beginning of May 2020. The
immediate team colleagues as well as one person from a
second team with direct contact to employees who tested
positive went into quarantine and had themselves tested. In the
course of this, two further SARS-CoV-2 infections were
detected and a further 20 people were released from duty for
quarantine measures.
Preliminary Implications of COVID-19 on Long-distance Traffic
6
In order to prevent the virus from spreading in the Munich
plant and at the same time uphold production activity and take
account of emerging uncertainties among the workforce, the
plant management decided to carry out a large-scale,
voluntary test offer for the employees of the ICE plant in
Munich. After being contacted by the respective manager, the
employees were able to decide for themselves whether or not
they wanted to take part in the test, which was organized in
cooperation with DB's senior physician and a medical service
provider. The persons to be tested were prioritized on the basis
of their proximity to or contact with the infected persons and
their criticality for the operation of the ICE Munich plant.
The test offer was very well received by the employees and
almost everyone addressed took part in the test. As part of the
test, a total of 212 out of 812 employees were tested for acute
SARS-CoV-2 infection via throat swab (PCR) over a period
of two days. All 212 tests were negative. In the following
week, due to a similar starting situation (two confirmed
infections among employees), 81 employees at the ICE plant
in Berlin-Rummelsburg voluntarily underwent a PCR throat
swab test; here too, all test results were negative.
The results show the effectiveness of the work organization
measures taken to prevent the uncontrolled spread of the virus.
1
Mohr, O., M. Askar, S. Schink, T. Eckmanns, G. Krause,
und G. Poggensee. 2012. “Evidence for Airborne Infectious
Disease Transmission in Public Ground Transport – a
Literature Review”. Eurosurveillance 17 (35): 20255.
https://doi.org/10.2807/ese.17.35.20255-en.
2
General ruling of the German Federal Police of 28 February
2020: Reporting obligations of railway undertakings, file
number 23-23 01 07-0002-0001.
https://www.bundespolizei.de/Web/DE/04Aktuelles/01Meld
ungen/Nohomepage/200305_allgemeinverfuegung_evu_bpol
p.html
3
Österreichische Agentur für Gesundheit und
Ernährungssicherheit GmbH. 2020. „Epidemiologische
Abklärung am Beispiel COVID-19“. Press release. Austrian
Agency for Health and Food Safety GmbH. 20 May 2020.
https://www.ages.at/service/service-
presse/pressemeldungen/epidemiologische-abklaerung-am-
beispiel-covid-19/.
4
Own survey by email to the 34 railway company medical
services associated in the UIMC (International Union of
Railway Medical Services), 22 May 2020
5
Posting in the portal of the COVID-19 Task Force of the
UIC (International Union of Railways)
6
Luo, Lei, Dan Liu, Xin-long Liao, Xian-bo Wu, Qin-long
Jing, Jia-zhen Zheng, Fang-hua Liu, et al. 2020. “Modes of
Contact and Risk of Transmission in COVID-19 among
Especially in comparison to outbreaks in other industries it is
shown that local outbreaks can be contained with appropriate
measures. At the same time, an infection at the workplace
cannot be completely ruled out. For this reason, the consistent
implementation of work organization measures, e.g.
compulsory masks for activities with close personal contact
and adherence to distance regulations, is essential and
mandatory. The procedures in Munich and Berlin have also
shown that rapid testing of a large proportion of the workforce
is an effective means of controlling a local SARS-CoV-2
outbreak and ensuring that production activities proceed.
6. Outlook
The vital question for the handling of COVID-19 over the
coming months for DB is to analyze in detail and improve the
measures taken. We need an understanding of what is sensible
and can be improved and which measures, also in terms of
travelers and employees, turn out to be less effective. We will
also focus on understanding exactly where there are still gaps
in our protection system and how these can be closed if
individual cases become known among employees and
travelers.
Close Contacts.” MedRxiv, March, 2020.03.24.20042606.
https://doi.org/10.1101/2020.03.24.20042606.
7
Moriarty, Leah F. „Public Health Responses to COVID-19
Outbreaks on Cruise Ships — Worldwide, February–March
2020“. MMWR. Morbidity and Mortality Weekly Report 69
(2020). https://doi.org/10.15585/mmwr.mm6912e3.
8
Böhmer, Merle M, Udo Buchholz, Victor M Corman,
Martin Hoch, Katharina Katz, Durdica V Marosevic, Stefanie
Böhm, et al. 2020. “Investigation of a COVID-19 Outbreak
in Germany Resulting from a Single Travel-Associated
Primary Case: A Case Series.” The Lancet Infectious
Diseases, May. https://doi.org/10.1016/S1473-
3099(20)30314-5.
9
Browne, Annie, Sacha St-Onge Ahmad, Charles R. Beck,
und Jonathan S. Nguyen-Van-Tam. 2016. “The Roles of
Transportation and Transportation Hubs in the Propagation
of Influenza and Coronaviruses: A Systematic Review”.
Journal of Travel Medicine 23 (1).
https://doi.org/10.1093/jtm/tav002.
10
Goscé, Lara, und Anders Johansson. 2018. “Analysing the
link between public transport use and airborne transmission:
mobility and contagion in the London underground”.
Environmental Health 17 (1): 84.
https://doi.org/10.1186/s12940-018-0427-5.
11
Adler, Alma J., Ken TD Eames, Sebastian Funk, and W.
John Edmunds. 2014. “Incidence and Risk Factors for
Preliminary Implications of COVID-19 on Long-distance Traffic
7
Influenza-like-Illness in the UK: Online Surveillance Using
Flusurvey.” BMC Infectious Diseases 14 (1): 232.
https://doi.org/10.1186/1471-2334-14-232.
12
Qian, Hua, Te Miao, Li Liu, Xiaohong Zheng, Danting
Luo, und Yuguo Li. 2020. “Indoor Transmission of SARS-
CoV-2”. MedRxiv, April, 2020.04.04.20053058.
https://doi.org/10.1101/2020.04.04.20053058.
13
Cui, Fuqiang, Huiming Luo, Lei Zhou, Dapeng Yin,
Canjun Zheng, Dingming Wang, Jian Gong, u. a. 2011.
“Transmission of Pandemic Influenza A (H1N1) Virus in a
Train in China”. Journal of Epidemiology 21 (4): 271–77.
https://doi.org/10.2188/jea.JE20100119.
14
Furuya, Hiroyuki. 2007. “Risk of Transmission of
Airborne Infection during Train Commute Based on
Mathematical Model.” Environmental Health and Preventive
Medicine 12 (2): 78–83. https://doi.org/10.1265/ehpm.12.78.
15
Noakes, Catherine J., and P. Andrew Sleigh. 2009.
“Mathematical Models for Assessing the Role of Airflow on
the Risk of Airborne Infection in Hospital Wards.” Journal
of the Royal Society Interface 6 (Suppl 6): 791–800.
https://doi.org/10.1098/rsif.2009.0305.focus.
16
Issarow, Chacha M., Nicola Mulder, und Robin Wood.
2015. “Modelling the Risk of Airborne Infectious Disease
Using Exhaled Air”. Journal of Theoretical Biology 372
(Mai): 100–106. https://doi.org/10.1016/j.jtbi.2015.02.010.
17
Rudnick, S. N., und D. K. Milton. 2003. “Risk of indoor
airborne infection transmission estimated from carbon
dioxide concentration”. Indoor air 13 (3): 237–245.
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