Gaussian process nowcasting: application to COVID-19 mortality reporting

Updating observations of a signal due to the delays in the measurement process is a common problem in signal processing, with prominent examples in a wide range of fields. An important example of this problem is the nowcasting of COVID-19 mortality: given a stream of reported counts of daily deaths, can we correct for the delays in reporting to paint an accurate picture of the present, with uncertainty? Without this correction, raw data will often mislead by suggesting an improving situation. We present a flexible approach using a latent Gaussian process that is capable of describing the changing auto-correlation structure present in the reporting time-delay surface. This approach also yields robust estimates of uncertainty for the estimated nowcasted numbers of deaths. We test assumptions in model specification such as the choice of kernel or hyper priors, and evaluate model performance on a challenging real dataset from Brazil. Our experiments show that Gaussian process nowcasting performs favourably against both comparable methods, and against a small sample of expert human predictions. Our approach has substantial practical utility in disease modelling -- by applying our approach to COVID-19 mortality data from Brazil, where reporting delays are large, we can make informative predictions on important epidemiological quantities such as the current effective reproduction number

Report 46: Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals.

The SARS-CoV-2 Gamma variant spread rapidly across Brazil, causing substantial infection and death waves. We use individual-level patient records following hospitalisation with suspected or confirmed COVID-19 to document the extensive shocks in hospital fatality rates that followed Gamma's spread across 14 state capitals, and in which more than half of hospitalised patients died over sustained time periods. We show that extensive fluctuations in COVID-19 in-hospital fatality rates also existed prior to Gamma's detection, and were largely transient after Gamma's detection, subsiding with hospital demand. Using a Bayesian fatality rate model, we find that the geographic and temporal fluctuations in Brazil's COVID-19 in-hospital fatality rates are primarily associated with geographic inequities and shortages in healthcare capacity. We project that approximately half of Brazil's COVID-19 deaths in hospitals could have been avoided without pre-pandemic geographic inequities and without pandemic healthcare pressure. Our results suggest that investments in healthcare resources, healthcare optimization, and pandemic preparedness are critical to minimize population wide mortality and morbidity caused by highly transmissible and deadly pathogens such as SARS-CoV-2, especially in low- and middle-income countries. NOTE: The following manuscript has appeared as 'Report 46 - Factors driving extensive spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals' at https://spiral.imperial.ac.uk:8443/handle/10044/1/91875 . ONE SENTENCE SUMMARY: COVID-19 in-hospital fatality rates fluctuate dramatically in Brazil, and these fluctuations are primarily associated with geographic inequities and shortages in healthcare capacity

Author correction: spatial and temporal fluctuations in COVID-19 fatality rates in Brazilian hospitals

Correction to: Nature Medicine https://doi.org/10.1038/s41591-022-01807-1, published online 10 May 2022

Next-generation sequencing in childhood disorders

Genetics has been revolutionised by recent technologies. The latest addition to these advances is next-generation sequencing, which is set to transform clinical diagnostics in every branch of medicine. In the research arena this has already been instrumental in identifying hundreds of novel genetic syndromes, making a molecular diagnosis possible for the first time in numerous refractory cases. However, the pace of change has left many clinicians bewildered by new terminology and the implications of next-generation sequencing for their clinical practice. The rapid developments have also left many diagnostic laboratories struggling to implement these new technologies with limited resources. This review explains the basic concepts of next-generation sequencing, gives examples of its role in clinically applied research and examines the challenges of its introduction into clinical practice

Next-generation sequencing in childhood disorders.

Genetics has been revolutionised by recent technologies. The latest addition to these advances is next-generation sequencing, which is set to transform clinical diagnostics in every branch of medicine. In the research arena this has already been instrumental in identifying hundreds of novel genetic syndromes, making a molecular diagnosis possible for the first time in numerous refractory cases. However, the pace of change has left many clinicians bewildered by new terminology and the implications of next-generation sequencing for their clinical practice. The rapid developments have also left many diagnostic laboratories struggling to implement these new technologies with limited resources. This review explains the basic concepts of next-generation sequencing, gives examples of its role in clinically applied research and examines the challenges of its introduction into clinical practice

Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil

Cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Manaus, Brazil, resurged in late 2020 despite previously high levels of infection. Genome sequencing of viruses sampled in Manaus between November 2020 and January 2021 revealed the emergence and circulation of a novel SARS-CoV-2 variant of concern. Lineage P.1 acquired 17 mutations, including a trio in the spike protein (K417T, E484K, and N501Y) associated with increased binding to the human ACE2 (angiotensin-converting enzyme 2) receptor. Molecular clock analysis shows that P.1 emergence occurred around mid-November 2020 and was preceded by a period of faster molecular evolution. Using a two-category dynamical model that integrates genomic and mortality data, we estimate that P.1 may be 1.7- to 2.4-fold more transmissible and that previous (non-P.1) infection provides 54 to 79% of the protection against infection with P.1 that it provides against non-P.1 lineages. Enhanced global genomic surveillance of variants of concern, which may exhibit increased transmissibility and/or immune evasion, is critical to accelerate pandemic responsiveness

Dominant mutations in GRM1 cause spinocerebellar ataxia type 44

The metabotropic glutamate receptor 1 (mGluR1) is abundantly expressed in the mammalian central nervous system, where it regulates intracellular calcium homeostasis in response to excitatory signaling. Here, we describe heterozygous dominant mutations in GRM1, which encodes mGluR1, that are associated with distinct disease phenotypes: gain-of-function missense mutations, linked in two different families to adult-onset cerebellar ataxia, and a de novo truncation mutation resulting in a dominant-negative effect that is associated with juvenile-onset ataxia and intellectual disability. Crucially, the gain-of-function mutations could be pharmacologically modulated in vitro using an existing FDA-approved drug, Nitazoxanide, suggesting a possible avenue for treatment, which is currently unavailable for ataxias.</p

Dominant mutations in GRM1 cause spinocerebellar ataxia type 44

The metabotropic glutamate receptor 1 (mGluR1) is abundantly expressed in the mammalian central nervous system, where it regulates intracellular calcium homeostasis in response to excitatory signaling. Here, we describe heterozygous dominant mutations in GRM1, which encodes mGluR1, that are associated with distinct disease phenotypes: gain-of-function missense mutations, linked in two different families to adult-onset cerebellar ataxia, and a de novo truncation mutation resulting in a dominant-negative effect that is associated with juvenile-onset ataxia and intellectual disability. Crucially, the gain-of-function mutations could be pharmacologically modulated in vitro using an existing FDA-approved drug, Nitazoxanide, suggesting a possible avenue for treatment, which is currently unavailable for ataxias.</p

Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence

The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the current pandemic. Previous estimates have relied on data early in the epidemic, or have not fully accounted for uncertainty in serological test characteristics and delays from onset of infection to seroconversion, death, and antibody waning. After screening 175 studies, we identified 10 representative antibody surveys to obtain updated estimates of the IFR using a modelling framework that addresses the limitations listed above. We inferred serological test specificity from regional variation within serosurveys, which is critical for correctly estimating the cumulative proportion infected when seroprevalence is still low. We find that age-specific IFRs follow an approximately log-linear pattern, with the risk of death doubling approximately every eight years of age. Using these age-specific estimates, we estimate the overall IFR in a typical low-income country, with a population structure skewed towards younger individuals, to be 0.23% (0.14-0.42 95% prediction interval range). In contrast, in a typical high income country, with a greater concentration of elderly individuals, we estimate the overall IFR to be 1.15% (0.78-1.79 95% prediction interval range). We show that accounting for seroreversion, the waning of antibodies leading to a negative serological result, can slightly reduce the IFR among serosurveys conducted several months after the first wave of the outbreak, such as Italy. In contrast, uncertainty in test false positive rates combined with low seroprevalence in some surveys can reconcile apparently low crude fatality ratios with the IFR in other countries. Unbiased estimates of the IFR continue to be critical to policymakers to inform key response decisions. It will be important to continue to monitor the IFR as new treatments are introduced. The code for reproducing these results are available as a R Research Compendium on Github: `mrc-ide/reestimate_covidIFR_analysis`