mteb/CovidQA huggingface dataset:
Overall, 48Á0% of our cases were positive for respiratory virus infections, which resembled the latest study in the same city. 21 A similar incidence rate has been obtained in neighboring regions 13, 22 and other cities such as Rome 23 and Milan, 24 but it was different from other studies. [10] [11] [12] In China, the overall positive rate reported varied from 27Á3 to 74Á8% depending on different areas and detection methods. 15, 16, [25] [26] [27] [28] [29] [30] [31] The rate of respiratory viral infections varied worldwide, and many factors such as geographic distribu-tion, study design and detection protocols could lead to these variations. 1, 7, 8, 32 In our study, leukocyte count was used as an indicator of inclusion criteria and it probably affected the positive rate. Viruses not considered in the study, for example coronaviruses, would underestimate the positive rate. Most studies showed that RSV or HRV was the most prevalent viruses in children with viral respiratory tract
infection. 1 In this study, IAV was the most frequently detected respiratory virus, followed by RSV and HRV. IAV (H1N1) outbreak in 2009 could explain this shift. Data showed that about 60% of IAV infections were detected during the outbreak period. Studies showed that the H1N1 outbreak could change viral distribution patterns. 24, 29, 33 Regardless of the IAV (H1N1) outbreak, RSV and HRV were the two most common viral pathogens in ARTIs, which was consistent with most previous studies. 1, 10, 15, 16, 22, [25] [26] [27] [28] [29] Our study further confirmed the importance of RSV and HRV in children with ARTIs, especially in children < 4 years of age. 10, 14, 23 Our results also showed that 12Á7% of viral pathogens detected were PIV1 and PIV3, which implied that PIVs played an important role in children with ARTIs. Similar findings were obtained in the studies conducted in Shanghai, 14, 34 Changsha, 26 Harbin, 30 Hong Kong 13 and Rome. 23 The prevalence of PIV3 was twofold higher than
that of PIV1, particularly in infants, which was similar with other reports, 25, 26, 30, 35 implying that infants could be more vulnerable to infection with PIV3 than PIV1.
HMPV has been proven to be one of the main viral pathogens responsible for ARTIs in children. 5 The positive rate found in the study was consistent with previously published results. 10, 36, 37 In China, the infection rate of HMPV varied from 3Á2 to 10Á6%. 22, 26, 28, 29, 31 The seasonality of HMPV in this study was mainly from March to May, similar to that in Hong Kong, 36 but different from other places. 5, 37 In our study, 4Á9% of cases were positive for BOV, which coincided with 5Á0% in Hong Kong 38 and higher than Guangzhou 39 and eastern Guangdong. 22 Our result suggested that BOV might be present throughout the year with no seasonal distribution. However, seasonal distribution was noted from September to February in Hong Kong 38 and May and June in Guangzhou. 39 The use of multiple PCR made it possible to simultaneously detect a broad spectrum of viruses with excellent sensitivity, at the same time, with increased viral detection rate and co-infection rate for ARTIs. 12,40
Among our positive cases, co-infection rate was 31Á1%, which was similar to 27Á9% reported by Do et al. 10 Co-infection rate reported elsewhere varied widely from 25Á4 to 47Á9%. 40 The relatively lower co-infection rates ranging from 0Á24 to 26Á9% were reported in the studies conducted in various cities of China. 22, [25] [26] [27] [28] [29] [30] [31] In most of these studies, immunofluorescence kits were used to test a lower number of respiratory viruses. It was worth to note that in the study by Peng et al. 32 in Wuhan, China, 69Á5% of co-infection rate was reported with immunofluorescence kit. These variations might be attributed to geographic differences, diagnostic methods for viral agents and study design. 12, 32, 34, 41, 42 Pathogens in those negative patients need to be further investigated as only ten common and newly identified viruses were included in our study, which might underestimate positive rate or coinfection rate. It was notable that the correlation between
co-infection rate and positive rate was not observed.
Of multiple infections, dual infection was predominant in this study whether or not considering the IAV (H1N1) outbreak in 2009, which was consistent with previous studies. 28, 32, 42, 43 Similar with the studies conducted in the cities of Guangzhou and Wuhan, China, 28, 29 our study showed that IAV, RSV and HRV were the main viruses involved in multiple infections. High co-infection rate between these three viruses could be explained from the overlap of their seasonal distributions. A variety of predominant multiple infection patterns between respiratory viruses were observed in different studies. 12, 32, 42, 43 For example, it was shown in Martin et al.'s study 43 that ADV and coronaviruses were the most common co-infection pattern.
Our study showed that RSV and HRV were the two most viruses involved in multiple infection, followed by IAV and PIVs, regardless of IAV infection in the H1N1 outbreak period. It was difficult to explain the variations of coinfection patterns based only on seasonal distribution. A recent study suggested that co-infection patterns were not random and certain pathogens had higher frequency of coinfection. 41 As molecular assays only detect nucleic acid and positive result does not mean the presence of the pathogen, when studying co-infection patterns of respiratory viruses, the ability to differentiate the real causative pathogens needs to be solved first. Viral load detection could provide some clues for solving this issue. 43, 44 Although high co-infection rates have been reported in various studies, the associations among multiple infections, hospitalization rate and severity of ARTIs were still not clear with inconsistent results in different studies. 42, 43, 45 Our data suggested
that multiple infection had less association with the severity of disease, consistent with Peng et al.'s study. 32 The relationship between co-infection rates and age group was also investigated in our study, and little correlation was observed. Several previous studies observed that co-infection rates were more frequent in a certain age group, but results were varied. 32, 43 In contrast to temperate region, where most viruses had winter-spring seasonality, the respiratory viral infections in tropical and subtropical regions appeared mainly to be spring-summer seasonality. 9 In this study, due to the high detection rate and similar seasonality of RSV, HRV, IAV, PIV and HMPV, an overall spring-summer seasonality of viral respiratory infections in children was concluded. Studies conducted in Hong Kong showed that a clear seasonal peak was from April to September, 36, 46 with a longer duration than our study. The overall seasonality in this study was also different from the studies
conducted in northern or central cities of China, in which the seasonality of most viruses presented in autumn-winter and/or winter-spring. 15, [25] [26] [27] 30 The winter-spring seasonality was also observed in Guangzhou, a city about 150 kilometers north of Shenzhen. 28 Different seasonal onset and duration were observed in various studies conducted in (sub-) tropical regions. In these studies, ambient temperature, humidity and rainfall were widely used to explain these differences in seasonality, but inconsistent results were observed. 9, 46, 47 Although most studies demonstrated that the seasonality of viral respiratory infections was correlated with increased rainfall, effects of climate factors such as humidity and temperature on the seasonality were complex and interactive. 9, 46, 48 The study areas have four indistinct seasons, and the coldest month usually emerges in January (average 12°C). During the period from March to May, the weather featured warm ambient temperature
(average 18-25°C), high relative humidity (average 85%-90%) and increasing rainfall. These meteorological conditions were perhaps conducive to viral survival. 9, 48 In addition, intensive temperature fluctuations during seasonal alternation could increase the susceptibility to infections. 49 As reported in other studies in temperate, tropical and subtropical regions, viral infection rates in children population showed an inverse correlation with age, with younger individuals experiencing higher viral infection rates. 3, 4, 6, 9, 24 Our results suggested that children younger than 4 years of age, particularly <6 months, were at higher risk of hospitalization for ARTIs, compared with older children. This was particularly substantiated in RSV infection. Our presumption was supported by other studies. 14,25-28 Of course, this speculation needed to be validated by the population-based study. The findings reported elsewhere suggested that more males than females were affected by ARTIs,
which were not observed in our study.
Notably, our study occurred over a span of 3 years, which included the IAV (H1N1) outbreak in 2009. The impact of the outbreak on the results should be considered. Data showed that the detection rate of IAV increased significantly and co-infection rate during outbreak months was much higher than average co-infection rate. Unfortunately, we did not type these influenza strains based on the original study design. It was most likely that these strains contributed to the relatively high proportion of IAV. Relatively higher single and multiple infections of RSV, HRV and PIVs were also observed during the outbreak of IAV. Increased susceptible population and awareness, intensive testing and altered patient and physician behavior could lead to these increases. These factors could partly explain the relatively high proportion of pneumonia cases in the study. Furthermore, studies showed that the outbreak of IAV (H1N1) could increase the risk of other viral infections such as RSV and HRV. 24,
33 Other limitations also existed in this study. First, molecular methods allowed the detection of only viral nucleic acid even without virus replication, which complicates the interpretation of positive detection results. Second, the subtype identification of some common respiratory viruses such as IAV and HRV was not performed in our study, particularly during the IAV (H1N1) outbreak in 2009.
In summary, despite those aforementioned limitations, this three consecutive years' surveillance would provide a basic profile of the spectrum, seasonality, age and gender distribution, co-infection patterns as well as clinical association of viral respiratory infections in hospitalized children in the study sites. It could help the prediction, prevention and control of ARTIs in children.
Spread from the Sink to the Patient: In Situ Study Using Green Fluorescent Protein (GFP)-Expressing Escherichia coli To Model Bacterial Dispersion from Hand-Washing Sink-Trap Reservoirs

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5377511/

SHA: 615071c8c959f24857b1bad521cc432b59719bfb

Authors: Kotay, Shireen; Chai, Weidong; Guilford, William; Barry, Katie; Mathers, Amy J.
Date: 2017-03-31
DOI: 10.1128/aem.03327-16
License: cc-by
Abstract: There have been an increasing number of reports implicating Gammaproteobacteria as often carrying genes of drug resistance from colonized sink traps to vulnerable hospitalized patients. However, the mechanism of transmission from the wastewater of the sink P-trap to patients remains poorly understood. Herein we report the use of a designated hand-washing sink lab gallery to model dispersion of green fluorescent protein (GFP)-expressing Escherichia coli from sink wastewater to the surrounding environment. We found no dispersion of GFP-expressing E. coli directly from the P-trap to the sink basin or surrounding countertop with coincident water flow from a faucet. However, when the GFP-expressing E. coli cells were allowed to mature in the P-trap under conditions similar to those in a hospital environment, a GFP-expressing E. coli-containing putative biofilm extended upward over 7 days to reach the strainer. This subsequently resulted in droplet dispersion to the surrounding
areas (<30 in.) during faucet operation. We also demonstrated that P-trap colonization could occur by retrograde transmission along a common pipe. We postulate that the organisms mobilize up to the strainer from the P-trap, resulting in droplet dispersion rather than dispersion directly from the P-trap. This work helps to further define the mode of transmission of bacteria from a P-trap reservoir to a vulnerable hospitalized patient. IMPORTANCE Many recent reports demonstrate that sink drain pipes become colonized with highly consequential multidrug-resistant bacteria, which then results in hospital-acquired infections. However, the mechanism of dispersal of bacteria from the sink to patients has not been fully elucidated. Through establishment of a unique sink gallery, this work found that a staged mode of transmission involving biofilm growth from the lower pipe to the sink strainer and subsequent splatter to the bowl and surrounding area occurs rather than splatter directly from
the water in the lower pipe. We have also demonstrated that bacterial transmission can occur via connections in wastewater plumbing to neighboring sinks. This work helps to more clearly define the mechanism and risk of transmission from a wastewater source to hospitalized patients in a world with increasingly antibiotic-resistant bacteria that can thrive in wastewater environments and cause infections in vulnerable patients.
Text: D espite early reports (1) (2) (3) (4) (5) , the premise that hand-wash sink traps can act as reservoirs of bacteria that cause nosocomial infections has been frequently overlooked. There has recently been an alarming increase in sink-related outbreaks worldwide, with many reports establishing an observational link (6) (7) (8) (9) (10) (11) (12) (13) . A sink often operates as an open conduit to wastewater in a patient care area that is often in the same room as the patient.
Health care establishments often invest in desperate interventions to deal with nosocomial outbreaks. The preferred method for addressing most of the environmentrelated transmission is to employ enhanced cleaning using chemical and physical agents (14, 15) . Unfortunately, routine approaches are inefficient in completely eliminating drug-resistant Gammaproteobacteria in an inaccessible microbiologically active area such as a sink trap (6, (16) (17) (18) (19) (20) . The wet, humid, and relatively protected environment in a sink trap favors the formation of rich stable microbial communities (16, 21, 22) . These communities will be exposed to liquids and waste that are discarded in a sink and may include antimicrobials, discarded beverages, soap, presumably pathogenic bacteria from health care workers' hands, and other items. In short, sink traps could serve as a breeding ground for opportunistic and highly antimicrobial-resistant bacteria that cannot be easily cleaned or removed (23)
(24) (25) (26) (27) (28) .
There are many reports of a genetic association between pathogens found in sink traps and those found in patients (29, 30) . However, surprisingly little work has been done to understand the microscale transmission dynamics. It was previously demonstrated using a suspension of fluorescent particles (Glo Germ; Glo Germ Co., Moab, UT) that material injected into the P-trap gets dispersed around a hand-washing sink (6) . This result however has not been replicated hitherto in the follow-up studies. Dispersion has never been investigated with living organisms. Ultimately, many details remain unaddressed surrounding the spread of Enterobacteriaceae in sink-trap wastewater systems: (i) can organisms grow retrograde from the P-trap water to the sink strainer, (ii) can organisms spread from one sink to another along the internal surfaces of pipes with shared drainage systems, and (iii) which portion of a colonized drain pipe results in dispersion into the sink bowl during a hand-washing
event? We aim to better understand the dispersion dynamics of Gammaproteobacteria living in the wastewater of a sink strainer and P-trap into an area where patients and health care workers could be exposed. To study this dynamic, we used a surrogate organism that could be easily tracked while remaining in the Enterobacteriaceae family, where some of the most concerning threats in antimicrobial resistance are developing (30) .
Growth and colonization of GFP-expressing E. coli in the P-trap. In the first 14 days following the installation of the P-trap with established green fluorescent protein (GFP)-expressing Escherichia coli and just water running from the faucet, GFPexpressing E. coli was not detected in the tailpipe beyond 1.5 in. above the liquid level in the P-trap. GFP-expressing E. coli, however, was found to be viable in the P-trap without any nutrients added. A nutrient regimen was then instituted to understand the influence of nutrients on mobility and upward growth. The addition of tryptic soy broth (TSB) promoted GFP-expressing E. coli growth as early as day 1, with growth observed in the tailpipe 2 in. above the liquid surface in the P-trap (Table 1) . On day 7, the strainer (ϳ8 in. above the liquid in the P-trap) was found to be colonized with GFP-expressing E. coli. This translates to an average growth rate of 1 in./day along the length of the tailpipe with the addition of nutrients and
without faucet operation. GFP-expressing E. coli was not detected in the faucet water.
Sink-to-sink transmission of bacteria. In these experiments, a flanking sink (sink 5) was the only P-trap inoculated with GFP-expressing E. coli and therefore was the sole source for transmission to the connected sinks. Starting with a lower inoculum concentration (10 3 CFU/ml) in sink 5, on day 7, GFP-expressing E. coli was detected in the sink 2 and sink 3 P-traps (Fig. 1a) . With inoculum concentrations of 10 6 CFU/ml and Ͼ10 10 CFU/ml in sink 5, all of the sink P-traps in the sink gallery with the exception of sink 1 were found to be colonized with GFP-expressing E. coli after 7 days (Fig. 1b and  c) . Faucet water and aerators tested negative for GFP-expressing E. coli. Irrespective of the starting inoculum concentration, on day 7 the highest level of colonization was recorded in the sink 3 P-trap. After day 7, when the nutrient regimen (described previously) was followed for an additional 7 days in each of the sinks in the sink gallery with an inoculum concentration of Ͼ10 10
CFU/ml, GFP-expressing E. coli was detected in the strainers of sinks 2 and 3 on day 14. This finding validated the upward growth and growth rate in the tailpipe when nutrients were added. Nonfluorescent colonies were occasionally observed in the P-trap water samples collected from the sinks, which were subsequently identified to be Pseudomonas sp. or Stenotrophomonas maltophilia, and fluorescent colonies were confirmed to be E. coli.
Dispersion of microspheres from sinks. In the first dispersion experiment, when fluorescent microspheres were inoculated into the offset drain tailpiece only 4 in. below the strainer, no microspheres were detected on the polyester sheets placed on the counter space.

However, when the sink bowl was coated with the microspheres, polyester sheets overlaid on the counter space captured the dispersed microspheres caused by the faucet operation. Dispersion was observed on almost all zones of the sink counter space (Fig. 2) . Relatively higher levels of dispersion were observed along the major and minor axes of the elliptical sink bowl (zones 2, 5, 6, 9, 11, and 12) . Anterior corners of the sink counter space (zones 4 and 7), which were most distant from the impact of water in the sink bowl, received the lowest dispersion.
Dispersion of GFP-expressing E. coli from sinks. Initially the P-trap alone was inoculated with GFP-expressing E. coli and carefully installed, keeping the tailpipe and strainer free of GFP-expressing E. coli before operating the faucets. No fluorescent CFU were observed on the plates placed on the counter or attached to the bowl surface after faucet operation. Similarly, no fluorescent CFU were detected when GFPexpressing E. coli was inoculated into the offset drain tailpiece only 4 in. below the strainer. Interestingly, when there was conspicuous water backup over the strainer as a result of a higher water flow rate from the faucet than the drainage rate from the P-trap, dispersal was detected on the plates attached to the bowl surface.
The dispersion pattern recorded when the sink bowl was coated with GFPexpressing E. coli was comparable to the pattern recorded when the sink bowl was coated with fluorescent microspheres (Fig. 2) . Dispersion was significantly higher along the axes (zones 6, 9, 11, and 12) and lower at the corners of the sink counter space (zones 4, 7, and 10).

In contrast, dispersion of GFP-expressing E. coli caused by the faucet operation was much more extensive when the strainer was allowed to be colonized with GFPexpressing E. coli prior to the dispersion experiment. In addition to the sink counter space, we measured dispersion to the sink bowl, faucet, faucet handles, splatter shields, and the extended counter surface. Dispersion of GFP-expressing E. coli was highest on the plates attached to the sink bowl (Fig. 3b) . Further, dispersion was greater along the 

Ϫ" and "ϩ" denote the absence and presence of GFP-expressing E. coli, respectively.
minor axis of the sink bowl (Fig. 3b , zones B3, B4, and B10) than along the major axis of the sink bowl, associated with a shorter distance from the strike point of the faucet water to the bowl along this axis. The next highest CFU count from the dispersal was recorded on the counter area near the faucets (Fig. 3a , zones 12 and 11). A similar pattern of higher dispersion near the faucets and lower dispersion at the corners of the counter space (Fig. 3a , zones 4, 7, and 10) was also observed using microspheres. Dispersion was also recorded in other zones of the counter space, on the Plexiglas splatter shields, faucets, faucet handles, and extended surface (Fig. 3c ). There were no GFP-expressing E. coli CFU recorded on plates placed beyond 30 in. from the strainer, demarcating the range of dispersion under these experimental conditions. Table 2 gives a summary of the total distribution loads recorded using fluorescent microspheres and GFP-expressing E. coli across each experiment.
The loads of dispersion on the sink counter were comparable when the sink bowl was coated with microspheres or GFP-expressing E. coli before the faucet operation. Although the dispersion load on the sink counter was lower when the sink strainer was colonized, it is interesting to note that the sink bowl received the highest dispersion.
To mimic dispersion in a hospital setting, we first investigated whether GFPexpressing E. coli would establish consistent colonization in a sink trap as many other Gammaproteobacteria implicated in nosocomial outbreaks have done (6, 28) . Many recent reports demonstrate that P-traps become colonized with highly consequential Gammaproteobacteria, which then results in nosocomial transmission (29, 31, 32) . The retained water in a sink P-trap is present to provide a water barrier to prevent off-gassing of sewer smell, but it may inadvertently provide favorable conditions for pathogenic and opportunistic antibiotic-resistant microorganisms to survive and develop resilient biofilms (3, 33) . However, the mechanism of dispersal of the bacteria in the P-trap to patients or the surrounding health care area had not been fully elucidated. We began with the hypothesis that the bacteria originate from the P-trap via droplet creation when the water from the faucet hits the P-trap water, thus
contaminating the sink bowl and the surrounding area. The finding supporting this theory had been previously reported using Glo Germ particles (6) . However, in the present study with careful attention to avoid strainer and tail piece contamination, the dispersal directly from the sink P-trap with either microspheres or GFP-expressing E. coli could not be reproduced as previously reported (6) .