key: cord-0768974-yya6a7pe
authors: Lamers, Susanna L.; Nolan, David J.; LaFleur, Tessa M.; Lain, Benjamin N.; Moot, Samual R.; Huston, Christopher R.; Neilsen, Chad D.; Feehan, Amy K.; Miele, Lucio; Rose, Rebecca
title: SARS-CoV-2 genomic surveillance as an evidence-based infection control approach in an offshore petroleum employee population
date: 2022-05-20
journal: Am J Infect Control
DOI: 10.1016/j.ajic.2022.05.008
sha: 6bf990bef27230d3b909618fc2b65e06a234ab64
doc_id: 768974
cord_uid: yya6a7pe

OBJECTIVES: . Industrial hygienists (IH) in the oil and gas business instituted an extraordinary number of safety protocols to limit spread of SARS-CoV-2 onto offshore platforms in the Gulf of Mexico. We used genomic surveillance to provide actionable information concerning the efficacy of their efforts. METHODS: . Over six months, employees at a single company were serology and PCR tested during a 1-5 day pre-deployment quarantine and when post-deployment symptoms were reported. From each positive test (n=49), SARS-CoV-2 genomes were sequenced. Phylogenetic analysis was used to investigate the epidemiology of transmissions. RESULTS: . Genomic surveillance confirmed two viral strains were infecting 18 offshore workers. Genomic data combined with epidemiological data suggested that a change in quarantine protocols contributed to these outbreaks. A pre-deployment outbreak involved a WHO variant of interest (Theta) that had infected four international workers. Two additional pre-deployment clusters of infections were identified. CONCLUSIONS: . Our findings support that IH quarantine/testing protocols limited viral transmissions, halted offshore outbreaks, and stopped the spread of a variant of interest. The study demonstrates how genomic data can be used understand viral transmission dynamics in employee populations and evaluate safety protocols in the offshore oil and gas industry.

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has presented many industries with new and complex challenges, particularly for industrial hygiene (IH) and occupational health and safety (OHS) professionals who assess and manage the risk of SARS-CoV-2 spread in the workplace (1) . SARS-CoV-2 is an especially pernicious pathogen, as the transmission is primarily airborne, asymptomatic individuals can transmit the virus, and the duration of infectiousness varies among individuals and viral variants (2) (3) (4) (5) . Studies suggest that the shortest and longest incubation period is estimated to be 2 and 14 days respectively. The median incubation period is estimated to be 4.91-7.54 days (6, 7) .

Individuals with long incubation periods occur more often in the elderly, are less symptomatic, and are less likely to transmit the virus (8) . It is estimated that 59% of infections come from asymptomatic transmissions, 35% from pre-symptomatic, and 24% from individuals that never develop symptoms (3) .

These factors pose uniquely challenging issues for the oil and gas industry, where SARS-CoV-2 infections have major consequences for workers on offshore platforms. Confined workspaces enable the virus to quickly spread among employees, who are highly mobile and travel internationally (9) . Increased infection rates may result in skeleton crews managing complex and dangerous machinery, which intensifies the risk for on-the-job injuries or chemical spills (10) . Furthermore, flights for remote medical evacuation and diagnostic testing crews greatly increase the risks of injury (11, 12) and the financial burden on the industry (13) . Given the essential nature of the oil and gas industry, and the significant financial and safety interests in limiting spread and mitigating outbreaks, the impact of COVID-19 on offshore platforms could have a devastating effect if left unabated.

Pathogen whole genome sequencing (WGS) can modernize the work of IH and OHS professionals by providing objective information about how pathogens spread in the workplace.

Because WGS objectively shows when transmission occurs, it can elucidate the effectiveness of methods used to reduce viral transmission including airflow systems, social distancing, contactless delivery systems. Furthermore WGS provide information concerning the impact of different viral variants on pathogenesis, transmissibility, and vaccine efficacy. The COVID-19 pandemic has been particularly transformative by driving home the power of WGS, and genomic surveillance is increasingly used in infection control and prevention in hospitals as well as by public health entities (14) (15) (16) (17) (18) (19) (20) (21) . However, WGS has yet to be widely adopted by other high-risk industries where there is potential to improve workplace safety.

In early 2021, an oil and gas company with offshore platforms in the Gulf of Mexico enlisted the services of a molecular biology research lab to implement genomic surveillance of SARS-CoV-2. The IH department of the company already employed extensive COVID-19 prevention protocols which were designed to identify individuals infected with SARS-CoV-2 prior to deployment to offshore platforms, reduce transmissions to co-workers and their families, and lessen the risk of depression or death. Pre-deployment procedures included multi-day hotelbased quarantines, surface disinfection, and serological and PCR-based testing prior to worker deployment. However even with these protective measures, an offshore COVID-19 outbreak involving 18 workers led the IH department to initiate genomic surveillance to determine if a source or sources could be identified. Subsequently, the IH department implemented WGS of SARS-CoV-2 as a standard operating procedure for ongoing monitoring of pre-and postdeployment employee safety policies during the evolving pandemic. Here we report our findings during five months of observation.

Employees and contractors for the company generally resided across Gulf Coast communities; however some employees reside in a variety of national and international locations.

Unsupervised quarantines were initiated early in the pandemic to reduce the interactions of employees with the broader population. Also, as PCR tests are more accurate 2-3 days-postinfection, a short quarantine would improve the likelihood that COVID-19 positive individuals would be identified prior to offshore deployment. Quarantines took place at one of four hotels where employees were instructed to remain in their rooms except for mealtimes. Food was catered from outside restaurants and employees had the option to eat with other employees outside or go back to their rooms. Presumably some interaction with hotel staff occurred.

At the start of this study, the length of quarantine at Hotel B was two weeks. The length of the quarantine at Hotel A had recently changed to only one day following a negative serology and PCR test. Testing protocols were administered prior to deployment for the majority of the population, however, there were occasions that necessitated individuals deployed to rigs without tests, for example, healthcare workers or individuals responding to other emergency situations.

This study involved individuals that deployed to one of four offshore platforms. The employee population base incorporated approximately 300-400 individuals across four platforms. The information we obtained for most individuals included quarantine hotel, platform designation, and in some cases, contracting company. During the 2019-2020 pandemic, employees typically deployed for three weeks.

A case management system was used to document cases, symptoms, and actions taken in association with any COVID-19 positive case. Prior to deployment offshore, employees were quarantined at one of several hotels for up to 7 days. During that time, employees were given a serology test (see details below), which detects antibodies to the virus, and a reversetranscription quantitative PCR testing (RT-qPCR) test, which detects viral RNA associated with an active infection (Figure 1 ). The timing of these tests varied as the pandemic evolved. If an employee was serology-negative and PCR-negative, they exited quarantine and were deployed offshore. If an employee had a previous infection but had finished a home-based selfquarantine, they were typically serology-positive and PCR-negative, so they were cleared for deployment (22) . Serology-negative and PCR-positive employees were isolated, interviewed to identify other employees that they may have come into contact with, and given follow-up care instructions prior to sending home. The leftover testing sample in viral transport media (VTM) was shipped for sequencing.

Once deployed to the offshore platform, employees who presented with COVID-19 symptoms were isolated and a nasopharyngeal swab in VTM was shipped for RT-qPCR testing. If positive, diagnostic teams were flown to the platform and the entire available population was retested. All positive cases were medevacked from the platform for a 10-day inland quarantine. Some individuals could have been missed during offshore testing efforts due to the nature of the industry and travel across platforms in the employee and contractor population.

Serology tests were used to identify the presence of IgG and/or IgM antibodies. The Rapid ICT POS (Aytu BioScience) serology test was used, which is performed via a finger stick, provides results in 15 minutes. Nasopharyngeal swabs were collected in VTM and shipped overnight to a diagnostic testing laboratory. The diagnostic laboratory performed RT-qPCR on extracted viral RNA using FDA Emergency Use Authorization (EUA) approved assays for SARS-CoV-2 S, N and Orf1ab genes, based on Applied Biosystems TaqMan 2019 nCOV assays, and a human control using the manufacturer's protocol. In some cases, BioFire® Respiratory 2.1 (RP2.1) Panel was also used for SARS-CoV-2 detection.

Left-over VTM samples that were positive for SARS-CoV-2 were de-identified and sent to BioInfoExperts for further studies (http://www.bioinfox.com). The total number of samples received included the initial 19 pre-and post-deployment cases from the first suspected outbreak, as well as an additional 30 samples from individuals who tested positive over the next 5 months. Some of these samples were from individuals who had previously tested positive, completed a quarantine, and tested positive again. These samples were classified as "remnant positives," which are likely non-infectious (23); however, in two of these cases we were able to generate a full viral genome. Metadata collected for each de-identified employee included hotelquarantine start date, testing date and result, and date and location of platform deployment.

This study was performed under WCG IRB #1-1455346-1.

SARS-CoV-2 sequencing methods were based on the ARTIC network nCoV-2019 V3 primer scheme using two multiplexed primer pools to create overlapping 400 bp amplicon fragments in two PCR reactions. A detailed version of this protocol can be found here: https://andersenlab.com/secrets/protocols/. Briefly, viral RNA was extracted using the Quick-RNA Viral Kit (Zymo Research) according to the manufacturer's instructions using 400uL VTM from the nasopharyngeal swabs. SARS-CoV-2 RNA was reverse transcribed with SuperScript IV (Invitrogen). The virus cDNA was amplified in two multiplexed PCR reactions (one reaction per ARTIC network primer pool) using Q5 DNA High-fidelity Polymerase (New England Biolabs).

Following an AMPureXP bead (Beckman Coulter) purification of the combined PCR products, the amplicons were diluted, and libraries were prepared using NEBNext Ultra II DNA Library Prep Kits (New England Biolabs). The libraries were purified with AMPureXP beads and quantified using the Qubit High Sensitivity DNA assay kit (Invitrogen) and Tapestation D5000 tape (Agilent). Libraries were normalized and pooled in equimolar amounts at 2 nM. The 2 nM library pool was sequenced with the Illumina MiSeq using a MiSeq reagent kit V3 600 cycles (Illumina).

Raw data from 49 samples were processed on the FoxSeq ® v.4.0 (FoxSeq LLC) analytical pipeline, which automated the following steps: for each sample, raw reads were filtered using Trimmomatic (24) based on read length and mapped to the SARS-CoV-2 reference genome (NC045512.2/Wuhan-Hu-1/2019) using Bowtie2 (25) . Mapping quality statistics were generated using picard (http://broadinstitute.github.io/picard). Bases were called for each position using bcftools mpileup (https://github.com/samtools/bcftools) and filtered if the depth was <50 and/or the frequency of either the reference or the alternative allele was <80%. A consensus sequence was generated for each sample using bcftools consensus. Pango lineages (26) were assigned using Pangolin 3.06 with the PangoLEARN algorithm (https://github.com/cov-lineages/pangolin).

Genetic distances were calculated using dnadist in the ape package in R. Results from analytical pipeline, including sequence quality, pangolin lineage, and distance clustering was delivered automatically in a web-based password-protected portal, which provided evidence of outbreaks to IH personnel in <2 weeks. For outbreak confirmation, maximum-likelihood phylogenetic trees were inferred using IQTREE v2 (27) and visualized using FigTree v1.5. 

We generated near-full length SARS-CoV-2 genome sequences for all PCR-positive samples (n=49). On average, the mean coverage for all genomes was ~13K, with >97% of all sites having at least 20x coverage.

To identify genetically related infections, we inferred a phylogenetic tree of high-coverage viral genomes. We defined an "Outbreak" as: 1) sequences that grouped together on the tree with high support (>70%); 2) sequences were separated by <2 mutations on average; and 3) outbreaks contained >2 individuals. We also classified sequences into Pango lineages, which is a widely used naming system for describing geographic origin and spread of SARS-CoV-2 variants (28) We found evidence for three potential distinct and genetically related outbreaks (Figure 2) . However, the genetic distance among sequences was >2 mutations.

We examined the quarantine and testing history of cases, and together with the genetic information, we constructed a timeline of the early platform outbreaks (Outbreak #1 an #2), which were identified over four days (Figure 3 ).

Outbreak #1 contained the initial person who reported the onset of COVID-19 symptoms (Day 0). This outbreak consisted of five individuals who had quarantined at Hotel A, all that were deployed to the same platform. While the deployment dates varied, their pre-deployment testing routine was the same: a RT-qPCR and a serology test was administered during quarantine, and if they were PCR-negative (typically results have a <24-hour turn-around), they were deployed one day later. Three individuals, including the index case, were deployed only three days prior to the first onset of symptoms. Three of these five individuals eventually reported symptoms on the offshore platform (BIE018, BIE025, and BIE024) and the others were asymptomatic at the time of testing.

Outbreak #2 consisted of 13 individuals on the same platform as outbreak #1. Of these, six individuals quarantined at Hotel A, where dates of testing and deployment varied; however, the procedure always involved a negative serology and PCR test. The other seven people in Outbreak #2 quarantined at Hotel B, where the seven individuals shared the exact same timeline of a negative serological test, a PCR-negative test 3 days later, and deployment two days after the negative PCR test and confirmation of zero symptoms. Individuals at Hotel B always arrived at the hotel and were deployed at the same time, this limiting exposure to additional employees through the 'revolving door' observed at Hotel A. On the platform, only one person in Outbreak #2 was mildly symptomatic with congestion (BIE021), which the individual believed was due to allergies. One of the asymptomatic individuals was seropositive (BIE016) at day 2.

While genetic data cannot identify the index case in either outbreak #1 or #2, it is likely that at least two employees that had quarantined at Hotel A were incubating the two viral strains (B. 1.2 and B.1.234) prior to deployment. All 18 employees tested positive over 4 days, which, based on an average incubation period, would suggest that they were exposed at a similar time.

Furthermore, five individuals at Hotel A (BIE025, BIE034, BIE027, BIE021, and BIE026) tested positive within the 14 day maximum incubation time and three of these cases boarded the platform within the median incubation period. All employees that quarantined at hotel B had deployed 15 days prior to testing positive, which is outside of a long incubation period.

Furthermore, ten out of eleven employees that were serology tested during the outbreaks, were serology negative, suggesting a relatively recent infection. Because of the variable presentation of COVID-19, it is unclear exactly how many people were incubating the virus prior to deployment, but the data strongly suggest that many employees were infected offshore.

Outbreak #3 occurred four months later and consisted of a group of foreign contractors who entered Louisiana through the New Orleans International Airport. These individuals tested negative before traveling to the US and none reporting symptoms. Two days after arriving to the US, they travelled to the Gulf Coast for quarantine, were re-tested, and all were confirmed as COVID-19-positive. Sequencing revealed that they were all infected with P.3, a relatively rare variant originally identified in the Philippines and designated a "variant of interest" at the time by the World Health Organization. This highlights the capability of WGS to objectively identify related infections and the vulnerability of this particular employee population to introductions of novel SARS-CoV-2 lineages, which could have varied transmission dynamics. These cases were immediately reported to the local department of public health for follow up contact tracing and are described in more detail in a separate publication (29) . Importantly, all of these individuals were identified prior to deployment.

In Cluster #2, sequences from three individuals grouped closely on the tree, although did not technically meet the definition of an outbreak as previously defined. The epidemiological history also suggested that this cluster did not represent a direct work-related transmission ( Table 1) . In late February, BIE077 was symptomatic on a platform, tested positive, and was medevacked to shore to quarantine. BIE097 was first identified as positive eleven days later, and BIE108 was identified as positive in early May. To further investigate this cluster, we performed an additional phylogenetic analysis of all 5.1.1.9 cases in Louisiana (Supplemental Figure 1; n = 188 ). This analysis clearly shows that BIE077 is unrelated to BIE097 and suggests a distant relationship of BIE077 and BIE108. It may be that an intermediate, asymptomatic case was not sampled, which could have come from the community.

In this study, we implemented SARS-CoV-2 genomic surveillance as an evidence-based infection control approach in collaboration with an oil and gas company with offshore platforms in the Gulf of Mexico. Louisiana experienced one of the earliest and fastest accelerating COVID-19 outbreaks, coinciding with the Mardi Gras celebrations in February 2020 (15) . The work detailed herein began in January 2021, as our infection rates were subsiding from their previous record peaks and the company IH in the Gulf of Mexico began to ease their quarantine protocols that had been in place for a year. Shortly thereafter, two distinct outbreaks were identified on platforms, suggesting that the reduction of quarantine to 24 hours after a negative test may have played a role. Subsequently, from February to April 2021, positive cases were primarily confined to pre-deployment testing.

We found that an initial suspected cluster of 18 PCR-positive individuals on two platforms over a 5-day period was actually two distinct and separate outbreaks, evidenced by the two separate clades on the phylogenetic tree and two different Pango lineage designations. Several findings might indicate that workers who had a shorter quarantine periods at Hotel A prior to deployment were index cases for both outbreaks. First, during offshore testing, four employees that had quarantined at Hotel A were symptomatic (BIE025, BIE31, BIE24, BIE021) suggesting they had been infected for at least 2 days; employees that quarantined at Hotel B only reported symptoms after removal from the platform, if at all. Second, several studies found that PCR tests are generally accurate at 3-5 days post infection (30, 31) and four of the positive individuals from Hotel A had deployed within this window; Hotel B employees/contractors were deployed for 14 days prior to testing positive. Finally, the single individual that tested positive pre-deployment quarantined at Hotel A; this individual reported no symptoms and was PCR positive/serology negative, indicating an early infection contracted during the pre-deployment quarantine (32) .

The mobile nature of offshore platform work, including medics who bypass testing protocols, likely resulted in some unsampled individuals who may have been involved in transmissions.

Thus, while it appears Hotel A was likely the source, phylogenetic analysis cannot definitively identify an index case. However, the genomic data objectively shows that both outbreaks were limited to 18 individuals because, while additional infections were identified, no new spread of these variants were identified on several platforms that were monitored over the next four months. Without whole genome sequencing, industrial hygienists would be unable to determine if they had stopped a transmission chain, or if it was continuing to disseminate in the worker population.

The pre-deployment outbreak validates that on-going testing can quickly stop the spread of viruses among employees. This outbreak, which was associated with international contractors, highlights the particular risk that offshore platforms face due to the high number of company This study demonstrates the power of genomic surveillance to objectively identify viral transmission in high-risk environments, such as offshore platforms. The genomic data, in combination with employee timelines was used to assess the effectiveness of quarantines and testing protocols. It does appear that longer quarantines were more effective than the quarantines that lasted the length of time it took receive negative test results. While longer quarantines are expensive and frustrating, they may be needed during times of high infection rates. Furthermore, without genomic data, IH have no way of knowing if their plan-of-action stopped a transmission chain, especially with a virus like SARS-CoV-2 that has varied incubation times, varied transmission potential, and varied presentation of symptoms.

Most SARS-CoV-2 surveillance studies by IH or OPH have occurred in healthcare settings; however, this study reveals that genomic data has applications in the unique offshore oil and gas industry for ongoing evaluation concerning the effectiveness of safety protocols. When employees and contractors know that their employer has tools that identify linked cases, they may be more likely to follow mandated safety protocols, which will improve the health of the workers, the industry, and their surrounding communities. Furthermore, the data provides information that public health agencies can use to improve community health. As a whole, the study illustrates the imperative for genomic epidemiologists and industry to collaborate in developing infrastructure and protocols to understand and slow the spread of infectious disease. In either case, these employees are allowed to deploy offshore. Should symptoms appear on the platform, they are immediately retested, and if positive, they are medevacked off the platform and the leftover nasopharyngeal sample in VTM is shipped to molecular biology lab for whole genome sequencing and analysis. 

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