An integrated discrete event simulation and particle swarm optimisation model for optimising efficiency of cancer diagnosis pathways

The National Health Service (NHS) constitution sets out minimum standards for rights of access of patients to NHS services. The ‘Faster Diagnosis Standard’ (FDS) states that 75% of patients should be told whether they have a diagnosis of cancer or not within 28 days of an urgent GP referral. Timely diagnosis and treatment lead to improved outcomes for cancer patients, however, compliance with these standards has recently been challenged, particularly in the context of operational pressures and resource constraints relating to the COVID-19 pandemic. In order to minimise diagnostic delays, the National Physical Laboratory in collaboration with the Royal Free London (RFL) NHS Foundation Trust address this problem by treating it as a formal resource optimisation, aiming to minimise the number of patients who breach the FDS. We use discrete event simulation and particle swarm optimisation to identify areas for improving the efficiency of cancer diagnosis at the RFL. We highlight capacity-demand mismatches in the current cancer diagnosis pathways at the RFL, including imaging and endoscopy investigations. This is due to the volume of patients requiring these investigations to meet the 28-day FDS target. We find that increasing resources in one area alone does not fully solve the problem. By looking at the system as a whole we identify areas for improvement which will have system-wide impact even though individually they do not necessarily seem significant. The outcomes and impact of this project have the potential to make a valuable impact on shaping future hospital activity.

The Impact of COVID-19 on Mental Health Services in Scotland, UK.

There is a global emergency in relation to mental health (MH) and healthcare. In the UK each year, 1 in 4 people will experience MH problems. Healthcare services are increasingly oversubscribed, and COVID-19 has deepened the healthcare gap. We investigated the effect of COVID-19 on waiting times for MH services in Scotland. We used national registers of MH services provided by Public Health Scotland. The results show that waiting times for adults and children increased drastically during the pandemic. This was seen nationally and across most of the administrative regions of Scotland. We find, however, that child and adolescent services were comparatively less impacted by the pandemic than adult services. This is potentially due to prioritisation of paediatric patients, or due to an increasing demand on adult services triggered by the pandemic itself.

Differential Functional Responses of Neutrophil Subsets in Severe COVID-19 Patients.

Neutrophils play a significant role in determining disease severity following SARS-CoV-2 infection. Gene and protein expression defines several neutrophil clusters in COVID-19, including the emergence of low density neutrophils (LDN) that are associated with severe disease. The functional capabilities of these neutrophil clusters and correlation with gene and protein expression are unknown. To define host defense and immunosuppressive functions of normal density neutrophils (NDN) and LDN from COVID-19 patients, we recruited 64 patients with severe COVID-19 and 26 healthy donors (HD). Phagocytosis, respiratory burst activity, degranulation, neutrophil extracellular trap (NET) formation, and T-cell suppression in those neutrophil subsets were measured. NDN from severe/critical COVID-19 patients showed evidence of priming with enhanced phagocytosis, respiratory burst activity, and degranulation of secretory vesicles and gelatinase and specific granules, while NET formation was similar to HD NDN. COVID LDN response was impaired except for enhanced NET formation. A subset of COVID LDN with intermediate CD16 expression (CD16Int LDN) promoted T cell proliferation to a level similar to HD NDN, while COVID NDN and the CD16Hi LDN failed to stimulate T-cell activation. All 3 COVID-19 neutrophil populations suppressed stimulation of IFN-γ production, compared to HD NDN. We conclude that NDN and LDN from COVID-19 patients possess complementary functional capabilities that may act cooperatively to determine disease severity. We predict that global neutrophil responses that induce COVID-19 ARDS will vary depending on the proportion of neutrophil subsets.

A specific low-density neutrophil population correlates with hypercoagulation and disease severity in hospitalized COVID-19 patients.

SARS coronavirus 2 (SARS-CoV-2) is a novel viral pathogen that causes a clinical disease called coronavirus disease 2019 (COVID-19). Although most COVID-19 cases are asymptomatic or involve mild upper respiratory tract symptoms, a significant number of patients develop severe or critical disease. Patients with severe COVID-19 commonly present with viral pneumonia that may progress to life-threatening acute respiratory distress syndrome (ARDS). Patients with COVID-19 are also predisposed to venous and arterial thromboses that are associated with a poorer prognosis. The present study identified the emergence of a low-density inflammatory neutrophil (LDN) population expressing intermediate levels of CD16 (CD16Int) in patients with COVID-19. These cells demonstrated proinflammatory gene signatures, activated platelets, spontaneously formed neutrophil extracellular traps, and enhanced phagocytic capacity and cytokine production. Strikingly, CD16Int neutrophils were also the major immune cells within the bronchoalveolar lavage fluid, exhibiting increased CXCR3 but loss of CD44 and CD38 expression. The percentage of circulating CD16Int LDNs was associated with D-dimer, ferritin, and systemic IL-6 and TNF-α levels and changed over time with altered disease status. Our data suggest that the CD16Int LDN subset contributes to COVID-19-associated coagulopathy, systemic inflammation, and ARDS. The frequency of that LDN subset in the circulation could serve as an adjunct clinical marker to monitor disease status and progression.