A study into the validation of ATP testing devices for integrated cleanliness monitoring within healthcare settings

There is a problem in hospital cleaning. There is currently no scientific monitoring method that provides timely and reliable assurance that harmful bacteria have been removed by the cleaning processes. This PhD investigates the validation of commercially available testing devices intended for the rapid detection of adenosine triphosphate (ATP), which may provide a quantitative surrogate estimate of surface cleanliness based on ATP measurements. The findings indicate that ATP testing devices, despite problems with scaling and imprecision, provide immediacy in readings which enables the incorporation of ATP testing into an improved and integrated cleanliness monitoring process for applications within healthcare settings

A suggested sampling algorithm for use with ATP testing in cleanliness measurement

Introduction: Rapid Adenosine Triphosphate (ATP) testing is becoming a commonly used method to measure cleanliness on reusable medical devices and healthcare environmental surfaces. Unfortunately, ATP testing devices suffer from inherent variability from a number of sources including imprecision in ATP measurement. Method: This paper proposes a new sampling algorithm which reduces the impact of inherent variability and thus improves decision making when using ATP testing. Conclusion: This algorithm can be applied across a variety of applications to provide more reliable data on measurable cleanliness standards for both medical devices and environmental surfaces. Formal trials using the new ATP sampling algorithm are required

Using a simplified ATP algorithm to improve data reliability and improve cleanliness standards for surface and medical device hygiene

Background: An algorithm has been improved to mitigate variability in cleanliness measurements of various surfaces using rapid Adenosine Triphosphate (ATP) testing. A cleaning intervention step (CIS) verifies the cleanability of those surfaces. Methods: ATP testing was performed on surfaces which were pre-approved as “clean” and ready for re-use. Adjacent (duplicate) ATP sampling was undertaken on 421 environmental surfaces, medical devices and other implements. The CIS was conducted on 270 surfaces using an aseptic technique and disposable cleaning wipes. Results: The two initial ATP results were plotted against each other with a 100 RLU threshold grading the results as clean (2x 100RLU) or equivocal (1x 100RLU). Of the surfaces sampled, 68.5 % were clean (288/421), 13.5 % were dirty (57/421) and 18 % were equivocal (76/421). The duplicate testing demonstrated a false negative rate of 10 % (44/421) where the first swab was 100 RLU. For the equivocal group, the gap between the two swabs was >100 RLU for 7.5 % of surfaces (33/421). The CIS was conducted on 270 of the surfaces tested and showed that cleaning could be improved (P=<0.001) on 88.5 % of surfaces (239/270). Conclusion: The simplified ATP testing algorithm provides real-time discrimination between surface cleanliness levels and improved certainty over surface hygiene. The duplicate swab sampling approach mitigates uncontrolled variability in the results and the CIS provides a nuanced understanding of the measurable cleanliness of any surface

Conditions under which glutathione disrupts the biofilms and improves antibiotic efficacy of both ESKAPE and NON-ESKAPE species

Bacterial antibiotic resistance has increased in recent decades, raising concerns in hospital and community settings. Novel, innovative strategies are needed to eradicate bacteria, particularly within biofilms, and diminish the likelihood of recurrence. In this study, we investigated whether glutathione (GSH) can act as a biofilm disruptor, and enhance antibiotic effectiveness against various bacterial pathogens. Biological levels (10 mM) of GSH did not have a significant effect in inhibiting growth or disrupting the biofilm in four out of six species tested. However, exposure to 30 mM GSH showed >50% decrease in growth for all bacterial species, with almost 100% inhibition of Streptococcus pyogenes and an average of 94–52% inhibition for Escherichia coli, Methicillin-resistant Staphylococcus aureus (MRSA) and Methicillin-sensitive S. aureus (MSSA) and multi-drug resistant Acinetobacter baumannii (MRAB) isolates, respectively. Klebsiella pneumoniae and Enterobacter sp. isolates were however, highly resistant to 30 mM GSH. With respect to biofilm viability, all species exhibited a >50% decrease in viability with 30 mM GSH, with confocal imaging showing considerable change in the biofilm architecture of MRAB isolates. The mechanism of GSH-mediated biofilm disruption is possibly due to a concentration-dependent increase in GSH acidity that triggers cleaving of the matrix components. Enzymatic treatment of MRAB revealed that eDNA and polysaccharides are essential for biofilm stability and eDNA removal enhanced amikacin efficiency. Combination of GSH, amikacin and DNase-I showed the greatest reduction in MRAB biofilm viability. Additionally, GSH alone and in combination with amikacin fostered human fibroblast cell (HFF-1) growth and confluence while inhibiting MRAB adhesion and colonization

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society

Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission

Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16–20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p