Prediction of hospital-onset COVID-19 using networks of patient contact: an observational study

PurposePredicting healthcare-acquired infections (HAIs) has the potential to revolutionise the prevention and control of transmissible infections. Existing prediction models for HAIs, however, fail to capture fully the contact-driven nature of infectious diseases. Here, we investigate the epidemiological predictivity of patient contact patterns through a forecasting model for hospital-onset COVID-19 infection (HOCI).Methods & MaterialsOur cohort comprises all patient admissions at a large London NHS Trust between 1/04/2020 and 1/04/2021. For patients, we consider (i) their hospital pathway, (ii) patient contacts, and (iii) date of COVID-19 infection. We consider rolling 14-day windows and forecast patient infection over the subsequent 7 days. Over each window, we construct a patient contact network and compute network features that capture contact centrality. We then combine network features, hospital environmental variables and patient clinical data to predict subsequent infections.ResultsA total of 51,157 patient admissions/episodes were observed during the study. Across all models, we find that contact-network features showed the highest performance (0.91 AUC-ROC). A reduced model with the six most predictive variables was almost as predictive and contained five features from patient contact (including direct contact with and network proximity to infectious cases) and only one environmental variable (length of stay).ConclusionOur results reveal that the number of direct contacts and network proximity to infectious patient(s) are highly predictive of HOCI. Such contact-based risk factors are easily extracted from routinely collected electronic health records providing a highly accessible route to improve personalised disease prognostics in future models.</p

Infantile Sialic Acid Storage Disease: Two Unrelated Inuit Cases Homozygous for a Common Novel SLC17A5 Mutation

Infantile sialic acid storage disease (ISSD) is a lysosomal storage disease characterized by accumulation of covalently unlinked (free) sialic acid in multiple tissues. ISSD and Salla disease (a predominantly neurological disorder) are allelic disorders caused by recessive mutations of a lysosomal anionic monosaccharide transporter, SLC17A5. While Salla disease is common in Finland due to a founder-effect mutation (p.Arg39Cys), ISSD is comparatively rare in all populations studied. Here, we describe the clinical and molecular features of two unrelated Canadian Inuit neonates with a virtually identical presentation of ISSD. Both individuals presented antenatally with fetal hydrops, dying shortly following delivery. Urinary free sialic acid excretion was markedly increased in the one case in which urine could be obtained for testing; postmortem examination showed a picture of widespread lysosomal storage in both. Both children were homozygous for a novel splice site mutation (NM_012434:c.526-2A\u3eG) resulting in skipping of exon 4 and an ensuing frameshift. Analysis of a further 129 pan-Arctic Inuit controls demonstrated a heterozygous carrier rate of 1/129 (~0.4 %) in our sample. Interestingly, lysosomal enzyme studies showed an unexplained ninefold increase in neuraminidase activity, with lesser elevations in the activities of several other lysosomal enzymes. Our results raise the possibility of a common founder mutation presenting as hydrops in this population. Furthermore, if confirmed in subsequent cases, the marked induction of neuraminidase activity seen here may prove useful in the clinical diagnosis of ISSD