mteb/CovidQA huggingface dataset:
After the CT examination, the technologist browses the images quickly. If the CT appearance is
typical of lung infection, the technologist immediately reports it to the chest radiologist on duty
and asks the patient to wait in the CT examination room. If the chest radiologist does not
suspect COVID-19 infection, the patient can leave the CT examination room. If the chest
radiologist does suspect COVID-19 infection, the technologist immediately reports it to the
EMICT and sends the patient to the fever tent. The floor and equipment in the CT examination
room are disinfected according to regulations, and air disinfection is conducted for 30 min
before examining other patients. These CT scanners are considered noncontaminated (not
fever-CTs) after these sterilization procedures.
Fever-DR examination procedure
10
The COVID-19 guideline of the NHC does not recommend chest DR because its ability in
diagnosing COVID-19 is limited. At our hospital, we only use mobile DR units to provide
bedside examination for critically ill patients. The technologist operating the mobile DR
wears personal protective equipment according to the three-level protection standard and
sterilizes the mobile DR according to the ward management requirements as described below.
Equipment and environment disinfection procedures
Routine disinfection procedure [9]
1) Object surface disinfection: Object surface is wiped with 1000mg/L chlorine-containing
disinfectant, wipe twice with 75% ethanol for non-corrosion resistance, once /4 hours.
2) Equipment disinfection: The equipment in the contaminated area are wiped with
2000mg/L chlorine-containing disinfectant. The DR and CT gantry in the contaminated
area are wiped with 75% ethanol. The equipment in the buffer area is wiped with
500-1000mg/L chlorine-containing disinfectant or alcohol-containing disposable
disinfectant wipes twice a day.
3) Air disinfection: Turning off all central air conditioners to prevent air contamination with
each other. Polluted area: open the door for ventilation, each time more than 30 minutes,
once /4 hours; The air sterilizer is continuously sterilized or the ultraviolet ray is
continuously used in the unmanned state for 60 minutes, four times a day, remembered to
close the inner shielding door when air disinfection. Other ambient air is sprayed with
1000mg/L chlorine-containing disinfectant and ventilated twice a day
4) Ground disinfection: The ground is wiped with 1000mg/L chlorine-containing
disinfectant, once /4 hours.
5) When contaminated, disinfect at any time. In case of visible contamination, disposable
absorbent materials should be used first to completely remove the pollutants, and then a
cloth soaked with 2000mg/L chlorine-containing disinfectant should be used for 30
minutes before wiping.
11
Fever-CT disinfection procedures after examination
In addition to the above, disinfect the examination bed and ground with chlorinated disinfectant
containing 2000mg/L [10].
Noncontaminated CT disinfection procedures after suspected COVID-19 case examination
In addition to the above routine disinfection procedure, air disinfection is conducted for 30 min
before examining other patients.
Results
From January 21, 2020 when screening for epidemiological history or symptoms
suspicious for COVID-19, to March 9, 2020, our hospital screened a total of 7,203 individuals
and confirmed 24 cases of COVID-19. Of these, 3,083 people underwent fever-CT
examinations. Including the initial examination and reexamination, the total number of fever
CT examination numbered 3,340. The fever-CT scanned a patient approximately every 21.5
minutes. As a result of our precautions, none of the staff of the radiology department developed
symptoms suspicious for COVID-19. The fever-CT technologist, with the highest probability
of exposure, remains PCR negative.
Discussion
It has been 17 years since the severe acute respiratory syndrome (SARS) epidemic, the last
national spread of severe infectious disease, broke out. Currently, the Chinese people are
panicking again. The speed and extent by which COVID-19 has spread in 2 months are
12
unprecedented, beyond those of SARS, and this has been aided by its contagious nature and
rapid spread via droplets and contact. The droplet mode of transmission means that a person can
be infected easily by means of casual contact or even fomites on contaminated environmental
surfaces. Another theory has yet to be proved: aerosol propagation.
How radiology departments respond to any infectious disease outbreak is determined
primarily by the estimated risk of cross-infection to the staff and other patients. Appropriate
precautions taken only by staff in direct contact with patients may be adequate when the risk is
low. The strongest measures need to be implemented to limit the spread of the disease when the
risk is high. With severe infectious diseases such as COVID-19, the highest level of infection
control measures must be implemented; these include providing adequate standard protective
equipment, training staff, and instituting proper emergency plans.
Once a contagious infectious disease has been identified, the EMICT must consider four
main areas of response: data gathering, collaboration, needs assessment, and expert advice [10].
Data gathering includes dissemination of up-to-date case definitions and information about
confirmatory tests to all staff with direct patient contact to allow appropriate barrier precautions
to be taken. All typical and atypical imaging features of the disease should be made known to
all radiologists to assist in recognition of the disease on images and to allow accurate reporting
of these findings. We have stored images of all probable cases of COVID-19 in the PACS so
that these images were readily available for any radiologist to review, and images from
previous imaging studies are also available for comparison.
Collaboration with the radiology departments of other hospitals is very important because
patients may initially present to different centers, depending on geographic location and travel
13
distance. These patients may be few in number at a single hospital, but if data from patients at
several hospitals are available, a more accurate overall understanding of both imaging features
and epidemiology can be achieved. Dissemination of this information to all healthcare facilities
will also lead to early recognition of the disease, and appropriate isolation measures may be
instituted.
The Internet and social media apps, especially WeChat, have been used for distribution of
medical information, and because the exchange of information regarding infectious disease
outbreaks is almost instantaneous, it is an indispensable tool for radiologists. In fact, within a
month of the outbreak, the hospital that received the most infected patients from the source of
the outbreak made a PowerPoint presentation of the CT manifestations of COVID-19, which
was shared via WeChat and disseminated across the country in a very short time. Subsequently,
COVID-19-teaching PowerPoint presentations from various hospitals appeared and were
quickly shared via WeChat.
Our diagnostic process is limited as chest CT along is not diagnostic of COVID-19
because of lack of imaging specificity. But when combined with other epidemiological,
clinical, laboratory and virus nucleic acid information, typical chest CT imaging findings are
helpful for making the diagnosis. In our opinion, the major role of chest CT is to understand the
extent and dynamic evolution of lung lesions induced by COVID-19. The reasons why we
adopted the low-dose chest CT scan protocol are as follows: low-dose chest CT has been
widely used in the screening of early lung cancer. It is well known that many early lung cancers
are ground-glass opacities (GGO), so we believe that low-dose screening is also applicable for
COVID-19. In addition, considering the rapid development of COVID-19, many CT
14
examinations may be conducted in the same individual to monitor disease progress. Low-dose
scanning can reduce the radiation damage to patients.
Although the processes we established minimized the exposure of hospital staff, ancillary
personnel and other patients, it remains limited as follows. Sichuan province is not the center of
the epidemic. The number of patients with COVID-19 whom we have treated has not been
high, and most cases are from other provinces of China. However, we believe that our
experience in management, the reconfiguration of our radiology department, and the workflow
changes implemented in the current COVID-19 situation are useful for other radiology
departments that must prepare for dealing with patients with COVID-19. While no radiology
personnel developed symptoms suspicious for or were confirmed as having COVID-19, there
may be asymptomatic personnel.
REFERENCES
1. National Health Commission of the People’s Republic of China.(2020). March 12: Daily briefing
on novel coronavirus cases in China. Retrieved from
http://en.nhc.gov.cn/2020-03/12/c_77618.htm. Accessed March 11, 2020.
2. World Health Organization. (2020). Coronavirus disease 2019 (COVID-19) Situation Report-52.
Retrieved from
https://www.who.int/docs/default-source/coronaviruse/20200312-sitrep-52-covid-19.pdf?sfvrsn=e
2bfc9c0_2 9. Accessed March 11, 2020.
3. National Health Commission of the People’s Republic of China.(2020). Latest developments in
epidemic control on Feb 15. Retrieved from http://en.nhc.gov.cn/2020-02/16/c_76622. Accessed
March 11, 2020.
15
4. Health Commission of the People’s Republic of China.(2020). The notification of the trial
operation based on the guideline version 6 in the coronavirus disease diagnosis and treatment.
Retrieved from
http://www.nhc.gov.cn/xcs/zhengcwj/202002/8334a8326dd94d329df351d7da8aefc2.shtml.
Accessed March 11, 2020
5. Health Commission of the People’s Republic of China.(2020). The notification of the trial
operation based on the guideline version 6 in the coronavirus disease diagnosis and treatment.
Retrieved from
http://www.nhc.gov.cn/xcs/zhengcwj/202002/8334a8326dd94d329df351d7da8aefc2.shtml.
Accessed March 11, 2020.
6. Health Commission of the People’s Republic of China.(2009). The guideline for pathogens
isolated operations in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/200904/40116.shtml. Accessed March 11, 2020.
7. Health Commission of the People’s Republic of China.(2017). The guideline for prevention and
control of hospital acquired infections of airborne pathogens. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201701/7e0e8fc6725843aabba8f841f2f585d2.shtml. Accessed
March 11, 2020.
8. Health Commission of the People’s Republic of China.(2017). The guideline for prevention and
control of hospital acquired infections of airborne pathogens. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201701/7e0e8fc6725843aabba8f841f2f585d2.shtml. Accessed
March 11, 2020.
9. Health Commission of the People’s Republic of China.(2012). The standardization for
sterilization techniques in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201204/54510.shtml. Accessed March 11, 2020.
10. Health Commission of the People’s Republic of China.(2012). The standardization for
sterilization techniques in hospital. Retrieved from
http://www.nhc.gov.cn/wjw/s9496/201204/54510.shtml. Accessed March 11, 2020.
11. Katona P. Bioterrorism Preparedness: Generic Blueprint for Health Departments, Hospitals, and
Physicians. Infectious Diseases in Clinical Practice. 2002;11(3):115-122. Accessed March 11,
2020.
16
Figure Legends
Figure 1. Diagram of the layout of our radiology department was divided into four areas: contaminated
(shaded in black), semicontaminated (shaded in dark gray), buffer (shaded in light gray), and clean areas
(shaded in white). The contaminated area was separated from other areas by barriers.
Figure 2. Diagram shows CT protocol for suspected and confirmed patients with COVID-19.
Figure 3. Diagram shows CT protocol for regular patients.
Abbreviations:
COVID-19: coronavirus disease 2019
CT: computed tomography
DR: digital radiography
EMICT: emergency management and infection control team
NHC: National Health Commission
PACS: picture archiving and communication system
SARS: severe acute respiratory syndrome
Sentence Summary
With severe infectious diseases such as COVID-19, the highest level of infection control
measures must be implemented, collaboration with the radiology departments of other
hospitals be needed, and social media be employed.
Take-home points
1. To response to a community infection emergency, a special emergency management team
needs to be setup at the departmental level to implement infection containment and
control procedures that continues to allow the imaging examination and imaging
diagnosis of those with suspected infection, and to prevent intra-departmental spreading
of infection (EMICT).
2. Infection control measures, such as reconfiguration of department areas, personal
protection and anti-infection training of all staff, standardized procedures including
contact minimization for chest CT and DR examinations, and timely disinfection of CT
and DR examination rooms, should be implemented properly.
3. If there are more than one scanner in a hospital, only one of them should be assigned to
suspected cases.
Identification of COVID-19 Can be Quicker through Artificial Intelligence framework using a Mobile Phone-Based Survey in the Populations when Cities/Towns Are Under Quarantine

https://doi.org/10.1017/ice.2020.61

SHA: 83c96f2a481be06a5c58552cbad2ca67ce789dc2

Authors: Vazquez, Arni S.R. Srinivasa Rao; Jose A.
Date: 2020
DOI: 10.1017/ice.2020.61
License: cc-by

Abstract: We are proposing to use machine learning algorithms to be able to improve possible case identifications of COVID-19 more quicker when we use a mobile phone-based web survey. This will also reduce the spread in the susceptible populations.
Text: Emerging and novel pathogens are a significant problem for global public health and technology can assist in faster identification of possible cases to bring timely interventions. This is especially true for viral diseases that are easily and readily transmissible and have asymptomatic infectivity periods. The novel Coronavirus (SARSCoV2) described in December 2019 has resulted in major quarantines throughout the world, including major cites, villages and public areas throughout China [1] [2] [3] to prevent further spread. As of February 25 th 2020, the World Health Organization's situational data indicates that there were about 77780 confirmed cases, including 2666 deaths due to COVID-19, including cases in 25 countries [4] . The majority of the deaths reported so far have been in China only [5] .

Organization have issued interim guidelines in order to protect the population, and to attempt to prevent the further spread of COVID-19 from infected individuals [6] .
Since cities and villages throughout China are unable to accommodate such large numbers of infected individuals, and be able to maintain the quarantined. China has built several new hospitals in an attempt to manage the infected individuals [7] . It is imperative that we evaluate novel models in an attempt to control the rapidly spreading virus [8] .
In order to reduce the time to identification of a person under investigation (PUI) for the COVID-19 infection, and the rapid isolation of this individual, we propose to collect the basic travel history along with the more common manifestations using a phone-based online survey. Such collected data can be used to assist in the preliminary screening and early identification of possible COVID-19 infected individuals. Thousands of data points are able to be collected and processed through an artificial intelligence (AI) framework which can ultimately evaluate individuals that may be infected and stratify them into no-risk, minimal-risk, moderate-risk, and high-risk of being infected with the virus. The identification of the high-risk cases can then be quarantined earlier, thus decreasing the chance of spread. Table 1 is inserted here.
See Appendix I for the details on the steps involved in data collection on all the respondents independent of whether or not they think they are infected. The AI algorithm described in Appendix II is to identify possible case identifications and send alerts to the nearest health clinic as well as to the respondent for an immediate health visit, we call this as an "alert for health check recommendation for COVID-2019. In case the respondent is unable to commute to the health center, the health department can then send an alert to a mobile health unit so they can then do doorto-door assessments and even testing for the virus. This generates alert for mobile health check recommendation for 2019-nCoV (MHCRC). If a respondent does not have an immediate risk of having symptoms or signs related to the viral infection, then the AI-based health alert will be sent to the respondent to notify them that there is no current risk of COVID-2019. Figure 1 summarizes the outcomes of data collection
and identification of possible cases. The data recorded in step 5 of the algorithm using signs and symptoms will be collected prior to both the groups who have received alerts HCRC or MHCRC (for possible identification and assessment) and NCRC (for non-identified respondents).
These are explained in steps (iii) and (iv) in the Appendix II. The extended analysis proposed will help to understand if there is any association with different sociodemographic variables and the manifestations such as fever and signs and lower respiratory infections, including cough and SOB in individuals defined as either with and without possible infection.
Applications of AI and deep learning argued to be useful tools in assisting diagnosis and treatment decision making [10] [11] . There were studies which promoted disease detection through AI models [12] [13] [14] [15] . Use of mobile phones [16] [17] [18] [19] and web based portals [20] [21] have been tested successfully in health related data collection. However, one need to apply such techniques in a timely way for faster results. Apart from cost-effectiveness, the proposed modeling will be of great assistance in identifying and controlling when populations are closed due to virus spread. In addition to these, our proposed algorithm can be easily extended to identify individuals who might have any mild symptoms and signs.

We have developed our data collection criteria based on CDC's Flowchart to Identify and Assess 2019 Novel Coronavirus [9] and added additional variables for the extended utility of our efforts in identifying infected and controlling the spread (see Table 1 ).
Let be the outputs recorded during the data collection steps 1 (ii) If the set of identifiers, , for is equal to one of the elements of the set then send HCRC or MHCRC to that respondent, else proceed to the test criteria (iv).

If is equal to one of the elements of the set , for then the respondent will be sent an NCRC alert.

(iv)

If is equal to one of the elements of the set , then the respondent will be sent an NCRC alert.

Comparison of test criteria results of (iii) and (iv) with their corresponding geographic and socio-demographic details will yield further investigations of signs and symptoms Suppose we define two events and using the sets and as below:

: out of responded cases are identified through the algorithm out of have responded to the survey.

The conditional probability of the event given the event , say, is computed as
Overview of the 3rd isirv-Antiviral Group Conference – advances in clinical management

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4280814/

SHA: f7bb1f005066cb4930f83cde4cdc1ff3fe411def

Authors: Hurt, Aeron C; Hui, David S; Hay, Alan; Hayden, Frederick G
Date: 2014-11-15
DOI: 10.1111/irv.12293
License: cc-by

Abstract: This review highlights the main points which emerged from the presentations and discussions at the 3rd isirv-Antiviral Group Conference - advances in clinical management. The conference covered emerging and potentially pandemic influenza viruses and discussed novel/pre-licensure therapeutics and currently approved antivirals and vaccines for the control of influenza. Current data on approved and novel treatments for non-influenza respiratory viruses such as MERS-CoV, respiratory syncytial virus (RSV) and rhinoviruses and the challenges of treating immunocompromised patients with respiratory infections was highlighted.
Text: Recurrent infections by influenza and other respiratory viruses contribute enormously to the burden of human disease and (emergent) sporadic zoonotic infections, such as by influenza H7N9 and H5N1 and Middle East respiratory syndrome (MERS) coronavirus, pose a constant threat of a new global epidemic. Despite extensive knowledge of the viruses and their interaction with the host, there is little in our armoury of vaccines and therapeutics to combat this perpetual onslaught. The 3rd isirv Antiviral Group conference on Influenza and Other Respiratory Virus Infections: Advances in Clinical Management, convened in Tokyo, Japan on 4-6 June 2014, attracted 188 clinicians, public health specialists and medical scientists from 34 countries to present their recent research and discuss various aspects of the impact of respiratory viruses in different patient groups/settings and in different regions of the world. The programme 1 focused on the latest advances in the mitigation and clinical
management of influenza and other respiratory virus disease, and the successful use of antivirals (and vaccines) against seasonal and pandemic influenza, particularly in Japan, as well as the development/assessment of novel antiviral agents. This overview highlights some of the main points which emerged from the presentations (both oral and poster) and associated discussion.
In recent years, an increasing number of cases of novel animal influenza A viruses infecting humans have been reported. These include multiple avian influenza A virus subtypes, in particular H5N1 and H7N9, and swine-origin H3N2v. Reasons for this increase include both social factors, for example, increased human populations living in close proximity to animals and increased surveillance and diagnostic testing. Risk assessment tools have been developed by many authorities around the world (e.g. the European CDC, US CDC, USAID and WHO) to assist in predicting the likelihood that a particular virus will emerge and its associated impact, as well as prioritising the development of candidate human vaccine viruses. 2 These tools allow continual reassessment as new data become available and provide an objective, transparent process with which to make resource allocation and pandemic planning decisions.
In February 2013, China detected the first human cases of H7N9 infection in severely ill patients with pneumonia. 3 As of May 22, 2014 , there have been 446 confirmed H7N9 cases in China resulting in 163 deaths. 4 The cases have occurred mainly during two waves (weeks [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] 2013 and week 40, 2013week 20, 2014) , 4 of which 85% had prior exposure to poultry or contaminated live poultry markets. The median time from poultry exposure to disease onset was 5 days, whereas the median time from illness onset to hospital admission, ARDS development, antiviral therapy and death was 5, 6Á8, 7 and 14 days, respectively. 5 Closure of live poultry markets has markedly reduced the risk of H7N9 infection. Across nine areas in the two most affected provinces in China, modelling analysis estimated that the effectiveness of market closure was 97% (95% CI: 89%, 100%). 6 A retrospective serological study of blood specimens taken in January-May and