A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Insights into the implementation of a whole genome sequencing report form (SRF) to reduce nosocomial SARS-CoV-2 in UK hospitals within an unfolding pandemic: A qualitative process evaluation using normalisation process theory

BACKGROUND

Here we report on a process evaluation conducted as part of a large multisite non-randomised trial of the effectiveness of a novel whole genome sequence report form (SRF) to reduce nosocomial SARS-CoV-2 through changing infection prevention and control (IPC) behaviours during the COVID -19 pandemic. We detail how the SRF was implemented across a heterogeneous purposive sub-sample of hospital trial sites (n=5/14).

METHODS

We conducted in-depth interviews from diverse professional staff (N=39). Deductive and inductive thematic analysis initially explored participants' accounts of implementing the SRF. The resulting themes, concerning the way the SRF was used within sites, were then coded in relation to the key tenets of normalisation process theory (NPT).

RESULTS

Factors that enabled the implementation of the SRF included: elements of the context such as health care professional passion; the existence of whole genome sequencing (WGS) infrastructure; effective communication channels, the creation of new connections across professionals and teams; the integration of SRF-led discussions within pre-existing meetings and the ability of a site to achieve a rapid turnaround time. In contrast, we found factors that constrained the use of the SRF included elements of the context such as the impact of the Alpha-variant overwhelming hospitals. In turn, dealing with COVID-19 breached the limited capacity of infection prevention and control (IPC) to respond to the SRF and ensure its routinisation.

CONCLUSION

We show preliminary support for this SRF being an acceptable, useable and potentially scalable way of enhancing existing IPC activities for viral respiratory infections. However, the context of both the trial and the alpha wave of COVID-19 limit confidence in these insights.

CLINICAL TRIAL NUMBER

https://www.isrctn.com/ISRCTN50212645, Registration date 20/05/2020.

The NOSTRA model: Coherent estimation of infection sources in the case of possible nosocomial transmission

Nosocomial, or hospital-acquired, infections are a key determinant of patient health in healthcare facilities, leading to longer stays and increased mortality. In addition to the direct effects on infected patients, the burden imposed by nosocomial infections impacts both staff and other patients by increasing the load on the healthcare system. The appropriate infection control response may differ depending on whether the infection was acquired in the hospital or the community. For example, nosocomial outbreaks may require ward closures to reduce the risk of onward transmission, whilst this may not be an appropriate response to repeated importations of infections from outside the facility. Unfortunately, it is often unclear whether an infection detected in a healthcare facility is nosocomial, as the time of infection is unobserved. Given this, there is a strong case for the development of models that can integrate multiple datasets available in hospitals to assess whether an infection detected in a hospital is nosocomial. When assessing nosocomiality, it is beneficial to take into account both whether the timing of infection is consistent with hospital acquisition and whether there are any likely candidates within the hospital who could have been the source of the infection. In this work, we developed a Bayesian model which jointly estimates whether a given infection detected in hospital is nosocomial and whether it came from a set of individuals identified as candidates by hospital staff. The model coherently integrates pathogen genetic information, the timings of epidemiological events, such as symptom onset, and location data on the infected patient and candidate infectors. We illustrated this model on a real hospital dataset showing both its output and how the impact of the different data sources on the assessed probabilities are contingent on what other data has been included in the model, and validated the calibration of the predictions against simulated data.

Variable rates of SARS-CoV-2 evolution in chronic infections

An important feature of the evolution of the SARS-CoV-2 virus has been the emergence of highly mutated novel variants, which are characterised by the gain of multiple mutations relative to viruses circulating in the general global population. Cases of chronic viral infection have been suggested as an explanation for this phenomenon, whereby an extended period of infection, with an increased rate of evolution, creates viruses with substantial genetic novelty. However, measuring a rate of evolution during chronic infection is made more difficult by the potential existence of compartmentalisation in the viral population, whereby the viruses in a host form distinct subpopulations. We here describe and apply a novel statistical method to study within-host virus evolution, identifying the minimum number of subpopulations required to explain sequence data observed from cases of chronic infection, and inferring rates for within-host viral evolution. Across nine cases of chronic SARS-CoV-2 infection in hospitalised patients we find that non-trivial population structure is relatively common, with five cases showing evidence of more than one viral population evolving independently within the host. The detection of non-trivial population structure was more common in severely immunocompromised individuals (p = 0.04, Fisher's Exact Test). We find cases of within-host evolution proceeding significantly faster, and significantly slower, than that of the global SARS-CoV-2 population, and of cases in which viral subpopulations in the same host have statistically distinguishable rates of evolution. Non-trivial population structure was associated with high rates of within-host evolution that were systematically underestimated by a more standard inference method.

Evaluating pooled testing for asymptomatic screening of healthcare workers in hospitals

BACKGROUND

There is evidence that during the COVID pandemic, a number of patient and HCW infections were nosocomial. Various measures were put in place to try to reduce these infections including developing asymptomatic PCR (polymerase chain reaction) testing schemes for healthcare workers. Regularly testing all healthcare workers requires many tests while reducing this number by only testing some healthcare workers can result in undetected cases. An efficient way to test as many individuals as possible with a limited testing capacity is to consider pooling multiple samples to be analysed with a single test (known as pooled testing).

METHODS

Two different pooled testing schemes for the asymptomatic testing are evaluated using an individual-based model representing the transmission of SARS-CoV-2 in a 'typical' English hospital. We adapt the modelling to reflect two scenarios: a) a retrospective look at earlier SARS-CoV-2 variants under lockdown or social restrictions, and b) transitioning back to 'normal life' without lockdown and with the omicron variant. The two pooled testing schemes analysed differ in the population that is eligible for testing. In the 'ward' testing scheme only healthcare workers who work on a single ward are eligible and in the 'full' testing scheme all healthcare workers are eligible including those that move across wards. Both pooled schemes are compared against the baseline scheme which tests only symptomatic healthcare workers.

RESULTS

Including a pooled asymptomatic testing scheme is found to have a modest (albeit statistically significant) effect, reducing the total number of nosocomial healthcare worker infections by about 2[Formula: see text] in both the lockdown and non-lockdown setting. However, this reduction must be balanced with the increase in cost and healthcare worker isolations. Both ward and full testing reduce HCW infections similarly but the cost for ward testing is much less. We also consider the use of lateral flow devices (LFDs) for follow-up testing. Considering LFDs reduces cost and time but LFDs have a different error profile to PCR tests.

CONCLUSIONS

Whether a PCR-only or PCR and LFD ward testing scheme is chosen depends on the metrics of most interest to policy makers, the virus prevalence and whether there is a lockdown.

Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana

Malaria results in over 600,000 deaths annually, with the highest burden of deaths in young children living in sub-Saharan Africa. Molecular surveillance can provide important information for malaria control policies, including detection of antimalarial drug resistance. However, genome sequencing capacity in malaria-endemic countries is limited. We designed and implemented an end-to-end workflow to detect Plasmodium falciparum antimalarial resistance markers and diversity in the vaccine target circumsporozoite protein (csp) using nanopore sequencing in Ghana. We analysed 196 clinical samples and showed that our method is rapid, robust, accurate and straightforward to implement. Importantly, our method could be applied to dried blood spot samples, which are readily collected in endemic settings. We report that P. falciparum parasites in Ghana are mostly susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine resistance and no evidence of artemisinin resistance. Multiple single nucleotide polymorphisms were identified in csp, but their significance is uncertain. Our study demonstrates the feasibility of nanopore sequencing for malaria genomic surveillance in endemic countries.

Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review

BACKGROUND

Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses.

AIM

To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission.

METHODS

Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

FINDINGS

In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS.

CONCLUSION

WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

How public health authorities can use pathogen genomics in health protection practice: a consensus-building Delphi study conducted in the United Kingdom

Pathogen sequencing guided understanding of SARS-CoV-2 evolution during the COVID-19 pandemic. Many health systems developed pathogen genomics services to monitor SARS-CoV-2. There are no agreed guidelines about how pathogen genomic information should be used in public health practice. We undertook a modified Delphi study in three rounds to develop expert consensus statements about how genomic information should be used. Our aim was to inform health protection policy, planning and practice. Participants were from organisations that produced or used pathogen genomics information in the United Kingdom. The first round posed questions derived from a rapid literature review. Responses informed statements for the subsequent rounds. Consensus was accepted when 70 % or more of the responses were strongly agree/agree, or 70 % were disagree/strongly disagree on the five-point Likert scale. Consensus was achieved in 26 (96 %) of 27 statements. We grouped the statements into six categories: monitoring the emergence of new variants; understanding the epidemiological context of genomic data; using genomic data in outbreak risk assessment and risk management; prioritising the use of limited sequencing capacity; sequencing service performance; and sequencing service capability. The expert consensus statements will help guide public health authorities and policymakers to integrate pathogen genomics in health protection practice.

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

Understanding 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.