Assessing the spatial-temporal risks of SARS-CoV-2 infection for healthcare-workers in the hospital using behavioural indices from routine data

The COVID-19 pandemic has emphasised the need to rapidly assess infection risks for healthcare workers within the hospital environment. Using data from the first year of the pandemic, we investigated whether an individuals COVID-19 test result was associated with behavioural markers derived from routinely collected hospital data two weeks prior to a test. The temporal and spatial context of behaviours were important, with the highest risks of infection during the first wave, for staff in contact with a greater number of patients and those with greater levels of activity on floors handling the majority of COVID-19 patients. Infection risks were higher for BAME staff and individuals working more shifts. Night shifts presented higher risks of infection between waves of COVID-19 patients. Our results demonstrate the epidemiological relevance of deriving markers of staff behaviour from electronic records, which extend beyond COVID-19 with applications for other communicable diseases and in supporting pandemic preparedness.

Using routinely collected hospital data to investigate healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic

Movement and contacts are central to the transmission of infectious diseases and, within the hospital setting, healthcare worker (HCW) mobility and their contact with patients play an important role in the spread of nosocomial disease. Yet data relating to HCW behaviours associated with mobility and contacts in the healthcare environment are often limited. This paper proposes a framework for integrating several electronic data sources routinely-collected by modern hospitals, to enable the measurement of HCW behaviours relevant to the transmission of infections. Using data from a London teaching hospital during the COVID-19 pandemic, we demonstrate how, at an aggregate level, electronic medical records (EMRs) and door access logs can be used to establish changes in HCW mobility and patient contacts. In addition, to show the utility of these data sources in supporting infection prevention and control (IPC), we investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs). Average daily rates of patient contacts are computed and found to be higher throughout the pandemic compared to that pre-pandemic, while the average daily rates of HCW mobility remained stable until the second wave, where they surpassed pre-pandemic levels. The response of HCW behaviour to the pandemic was not equal between floors, whereby the highest increases in patient contacts and mobility were on floors handling the majority of COVID-19 patients. The first wave of COVID-19 patients resulted in changes to the flow of HCWs between floors, but the interconnectivity between COVID-19 and non COVID-19 wards was evident throughout the pandemic. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting, whereby indirect contact rates between COVID-19 positive and negative patients were lowest during peaks in COVID-19 hospital admissions. We propose that IPC practitioners use these routinely collected data on HCW behaviour to support infection control activities and to help better protect hospital staff and patients from nosocomial outbreaks of communicable diseases.

Pre-existing and de novo humoral immunity to SARS-CoV-2 in humans

Several related human coronaviruses (HCoVs) are endemic in the human population, causing mild respiratory infections1. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiologic agent of Coronavirus disease 2019 (COVID-19), is a recent zoonotic infection that has quickly reached pandemic proportions2,3. Zoonotic introduction of novel coronaviruses is thought to occur in the absence of pre-existing immunity in the target human population. Using diverse assays for detection of antibodies reactive with the SARS-CoV-2 spike (S) glycoprotein, we demonstrate the presence of pre-existing humoral immunity in uninfected and unexposed humans to the new coronavirus. SARS-CoV-2 S-reactive antibodies were readily detectable by a sensitive flow cytometry-based method in SARS-CoV-2-uninfected individuals and were particularly prevalent in children and adolescents. These were predominantly of the IgG class and targeted the S2 subunit. In contrast, SARS-CoV-2 infection induced higher titres of SARS-CoV-2 S-reactive IgG antibodies, targeting both the S1 and S2 subunits, as well as concomitant IgM and IgA antibodies, lasting throughout the observation period of 6 weeks since symptoms onset. SARS-CoV-2-uninfected donor sera also variably reacted with SARS-CoV-2 S and nucleoprotein (N), but not with the S1 subunit or the receptor binding domain (RBD) of S on standard enzyme immunoassays. Notably, SARS-CoV-2-uninfected donor sera exhibited specific neutralising activity against SARS-CoV-2 and SARS-CoV-2 S pseudotypes, according to levels of SARS-CoV-2 S-binding IgG and with efficiencies comparable to those of COVID-19 patient sera. Distinguishing pre-existing and de novo antibody responses to SARS-CoV-2 will be critical for our understanding of susceptibility to and the natural course of SARS-CoV-2 infection.