ABSTRACT
Since the first reports of hepatitis of unknown aetiology occurring in UK children, over 1000 cases have been reported worldwide, including 268 cases in the UK, with the majority younger than 6 years old. Using genomic, proteomic and immunohistochemical methods, we undertook extensive investigation of 28 cases and 136 control subjects. In five cases who underwent liver transplantation, we detected high levels of adeno-associated virus 2 (AAV2) in the explanted livers. AAV2 was also detected at high levels in blood from 10/11 non-transplanted cases. Low levels of Adenovirus (HAdV) and Human Herpesvirus 6B (HHV-6B), both of which enable AAV2 lytic replication, were also found in the five explanted livers and blood from 15/17 and 6/9 respectively, of the 23 non-transplant cases tested. In contrast, AAV2 was detected at low titre in 6/100 whole bloods from child controls from cohorts with presence or absence of hepatitis and/or adenovirus infection. Our data show an association of AAV2 at high titre in blood or liver tissue, with unexplained hepatitis in children infected in the recent HAdV-F41 outbreak. We were unable to find evidence by electron microscopy, immunohistochemistry or proteomics of HAdV or AAV2 viral particles or proteins in explanted livers, suggesting that hepatic pathology is not due to direct lytic infection by either virus. The potential that AAV2, although not previously associated with disease, may, together with HAdV-F41 and/or HHV-6, be causally implicated in the outbreak of unexplained hepatitis, requires further investigation.
Subject(s)
Hepatitis , Adenoviridae InfectionsABSTRACT
Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches to reconstruct outbreaks exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is stable among repeated serial samples from the same host, is transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.
Subject(s)
Communicable DiseasesABSTRACT
This paper presents preliminary summary results from a longitudinal study of participants in seven U.S. states during the COVID-19 pandemic. In addition to standard socio-economic characteristics, we collect data on various economic preference parameters: time, risk, and social preferences, and risk perception biases. We pay special attention to predictors that are both important drivers of social distancing and are potentially malleable and susceptible to policy levers. We note three important findings: (1) demographic characteristics exert the largest influence on social distancing measures and mask-wearing, (2) we show that individual risk perception and cognitive biases exert a critical role in influencing the decision to adopt social distancing measures, (3) we identify important demographic groups that are most susceptible to changing their social distancing behaviors. These findings can help inform the design of policy interventions regarding targeting specific demographic groups, which can help reduce the transmission speed of the COVID-19 virus. ( JEL I11, I12, I18, D81, D91, D62, D64)
Subject(s)
COVID-19ABSTRACT
This paper presents preliminary summary results from a longitudinal study of participants in seven U.S. states during the COVID-19 pandemic. In addition to standard socio-economic characteristics, we collect data on various economic preference parameters: time, risk, and social preferences, and risk perception biases. We pay special attention to predictors that are both important drivers of social distancing and are potentially malleable and susceptible to policy levers.We note three important findings: (1) demographic characteristics exert the largest influence on social distancing measures and mask-wearing, (2) we show that individual risk perception and cognitive biases exert a critical role in influencing the decision to adopt social distancing measures, (3) we identify important demographic groups that are most susceptible to changing their social distancing behaviors. These findings can help inform the design of policy interventions regarding targeting specific demographic groups, which can help reduce the transmission speed of the COVID-19 virus.
Subject(s)
COVID-19ABSTRACT
This paper presents preliminary summary results from a longitudinal study of participants in seven U.S. states during the COVID-19 pandemic. In addition to standard socio-economic characteristics, we collect data on various economic preference parameters: time, risk, and social preferences, and risk perception biases. We pay special attention to predictors that are both important drivers of social distancing and are potentially malleable and susceptible to policy levers. We note three important findings: (1) demographic characteristics exert the largest influence on social distancing measures and mask-wearing, (2) we show that individual risk perception and cognitive biases exert a critical role in influencing the decision to adopt social distancing measures, (3) we identify important demographic groups that are most susceptible to changing their social distancing behaviors. These findings can help inform the design of policy interventions regarding targeting specific demographic groups, which can help reduce the transmission speed of the COVID-19 virus.