Findings suggest that a network-based strategy for self-test distribution is a promising intervention to increase testing uptake and reduce undiagnosed infections among AAMSM and LMSM.
Nosocomial transmission of SARS-CoV-2 is a key concern, and evaluating the effect of testing and infection prevention and control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical English hospital, we estimate that between 9 March 2020 and 17 July 2020 approximately 20% of infections in inpatients, and 73% of infections in healthcare workers (HCWs) were due to nosocomial transmission. Model results suggest that placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 35%. Periodic testing of HCWs has a smaller effect on the number of hospital-acquired COVID-19 cases in patients, but reduces infection in HCWs by as much as 37% and results in only a small proportion of staff absences (approx. 0.3% per day). This is considerably less than the 20–25% of staff that have been reported to be absent from work owing to suspected COVID-19 and self-isolation. Model-based evaluations of interventions, informed by data collected so far, can help to inform policy as the pandemic progresses and help prevent transmission in the vulnerable hospital population.
This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.
Nosocomial transmission of SARS-CoV-2 is a key concern and evaluating the effect of testing and infection prevention control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical UK hospital, we predict that approximately 20% of infections in inpatients, and 89% of infections in HCWs were due to nosocomial transmission. Placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 80%. Periodic testing of HCWs has a smaller effect on the patient-burden of COVID-19 but would considerably reduce infection in HCWs by as much as 64% and result in only a small proportion of staff absences (approximately 1% per day). This is considerably fewer than currently observed due to suspected COVID-19 and self-isolation.
This mixed-methods study used qualitative interviews to explore discrepancies between self-reported HIV care and treatment-related behaviors and the presence of antiretroviral medications (ARVs) in a population-based survey in South Africa. ARV analytes were identified among 18% of those reporting HIV-negative status and 18% of those reporting not being on ART. Among participants reporting diagnosis over a year prior, 19% reported multiple HIV tests in the past year. Qualitative results indicated that participant misunderstandings about their care and treatment played a substantial role in reporting inaccuracies. Participants conflated the term HIV test with CD4 and viral load testing, and confusion with terminology was compounded by recall difficulties. Data entry errors likely also played a role. Frequent discrepancies between biomarkers and self-reported data were more likely due to poor understanding of care and treatment and biomedical terminology than intentional misreporting. Results indicate a need for improving patient-provider communication, in addition to incorporating objective measures of treatment and care behaviors such as ARV analytes, to reduce inaccuracies.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.