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1.
PLoS One ; 18(4): e0284512, 2023.
Article in English | MEDLINE | ID: covidwho-2305727

ABSTRACT

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 individual's 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.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics , Routinely Collected Health Data , SARS-CoV-2 , Personnel, Hospital , Health Personnel , Hospitals
2.
Commun Med (Lond) ; 2(1): 165, 2022 Dec 23.
Article in English | MEDLINE | ID: covidwho-2186122

ABSTRACT

BACKGROUND: Insights into behaviours relevant to the transmission of infections are extremely valuable for epidemiological investigations. Healthcare worker (HCW) mobility and patient contacts within the hospital can contribute to nosocomial outbreaks, yet data on these behaviours are often limited. METHODS: Using electronic medical records and door access logs from a London teaching hospital during the COVID-19 pandemic, we derive indicators for HCW mobility and patient contacts at an aggregate level. We assess the spatial-temporal variations in HCW behaviour and, to demonstrate the utility of these behavioural markers, 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). RESULTS: Fluctuations in HCW mobility and patient contacts were identified during the pandemic, with the most prominent changes in behaviour on floors handling the majority of COVID-19 patients. The connectivity between floors was disrupted by the pandemic and, while this stabilised after the first wave, the interconnectivity of COVID-19 and non-COVID-19 wards always featured. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting in response to the number of COVID-19 patients in the hospital. CONCLUSIONS: Routinely collected electronic records in the healthcare environment provide a means to rapidly assess and investigate behaviour change in the HCW population, and can support evidence based infection prevention and control activities. Integrating frameworks like ours into routine practice will empower decision makers and improve pandemic preparedness by providing tools to help curtail nosocomial outbreaks of communicable diseases.


Movement of healthcare workers and their patient contacts can contribute to outbreaks of infection in the healthcare environment. We use electronic medical records and door access logs from a London hospital to derive indicators for staff behaviour during the COVID-19 pandemic. Changes in staff behaviour were most prominent on floors handling the majority of COVID-19 patients. We also show how the flow of staff between COVID-19 and non-COVID-19 wards continued throughout the pandemic, but find evidence that indirect contact between COVID-19 positive and negative patients reduced as COVID-19 prevalence increased. We suggest these routinely collected data on HCW behaviour should be used to support decision makers in activities to help curtail disease outbreaks in healthcare settings.

3.
Sci Rep ; 11(1): 22871, 2021 11 25.
Article in English | MEDLINE | ID: covidwho-1537332

ABSTRACT

The COVID-19 pandemic has posed novel risks related to the indoor mixing of individuals from different households and challenged policymakers to adequately regulate this behaviour. While in many cases household visits are necessary for the purpose of social care, they have been linked to broadening community transmission of the virus. In this study we propose a novel, privacy-preserving framework for the measurement of household visitation at national and regional scales, making use of passively collected mobility data. We implement this approach in England from January 2020 to May 2021. The measures expose significant spatial and temporal variation in household visitation patterns, impacted by both national and regional lockdown policies, and the rollout of the vaccination programme. The findings point to complex social processes unfolding differently over space and time, likely informed by variations in policy adherence, vaccine relaxation, and regional interventions.


Subject(s)
COVID-19/psychology , Communicable Disease Control/methods , Social Support/psychology , COVID-19/prevention & control , Communicable Disease Control/trends , England , Family Characteristics , Health Policy/trends , Humans , Immunization Programs/methods , Models, Statistical , Models, Theoretical , Pandemics , Physical Distancing , Public Policy/trends , SARS-CoV-2/pathogenicity , Social Interaction/classification , Social Support/methods , Vaccines
4.
Nat Med ; 26(8): 1183-1192, 2020 08.
Article in English | MEDLINE | ID: covidwho-704642

ABSTRACT

Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases.


Subject(s)
Coronavirus Infections/prevention & control , Pandemics/statistics & numerical data , Pneumonia, Viral/prevention & control , Population Surveillance , Public Health/statistics & numerical data , Betacoronavirus/pathogenicity , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Humans , Machine Learning , Natural Language Processing , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Privacy , SARS-CoV-2
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