State-wide genomic epidemiology investigations of COVID-19 in healthcare workers in 2020 Victoria, Australia: Qualitative thematic analysis to provide insights for future pandemic preparedness

Watt, Anneliese; Sherry, Norelle L; Andersson, Patiyan; Lane, Courtney R; Johnson, Sandra; Wilmot, Mathilda; Horan, Kristy; Sait, Michelle; Ballard, Susan A; Crachi, Christina; Beck, Dianne J.; Marshall, Caroline; Kainer, Marion; Stuart, Rhonda L.; McGrath, Christian; Kwong, Jason C; Bass, Pauline; Kelley, Peter; Crowe, Amy; Guy, Stephen; Macesic, Nenad; Smith, Karen; Williamson, Deborah A; Seemann, Torsten; Howden, Benjamin P

doi:10.1016/j.lanwpc.2022.100487

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…They also found that booster protection remained largely stable for at least 16 weeks after vaccination [32] . Moreover, staff-to-staff and staff-to-patient transmission is a major driver of SARS-CoV-2 dissemination in healthcare facilities [33] , [34] , [35] . Real-life data found significantly lower SARS-CoV-2 viral loads in upper respiratory tract during the first five symptomatic days in boosted patients with Omicron breakthrough infections compared to unvaccinated infected patients [36] .…”

Section: Discussionmentioning

confidence: 99%

Association between COVID-19 vaccination status, time elapsed since the last vaccine dose, morbidity, and absenteeism among healthcare personnel: A prospective, multicenter study

Maltezou¹,

Gamaletsou²,

Koukou³

et al. 2022

Vaccine

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Section: Discussionmentioning

confidence: 99%

Association between COVID-19 vaccination status, time elapsed since the last vaccine dose, morbidity, and absenteeism among healthcare personnel: A prospective, multicenter study

Maltezou¹,

Gamaletsou²,

Koukou³

et al. 2022

Vaccine

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“…Genomic epidemiology draws together bioinformatic analysis from pathogen genomic sequences and epidemiological data to provide context and support to inferences of transmission. Synthesis of genomic and epidemiological data is required to perform these inferences, however this can be challenging given the complexity of the underlying data [4]. These challenges can be compounded when genomic and epidemiological investigations are conducted by discrete organisations (for example public health laboratories and local public health services respectively) with different information contexts and objectives.…”

mentioning

confidence: 99%

Combined visualization of genomic and epidemiological data for outbreaks

Suster,

Watt,

Wang

et al. 2024

Preprint

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In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new 'phylepic' visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

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