A method to reduce ELISA serial dilution assay workload applied to SARS-CoV-2 and seasonal HCoVs

Objectives Assays using ELISA measurements on serially diluted serum samples have been heavily used to measure serum reactivity to SARS-CoV-2 antigens and are widely used in virology and elsewhere in biology. We test a method to reduce the workload of these assays, and measure reactivity of SARS-CoV-2 and HCoV antigens to human serum samples collected before and during the COVID-19 pandemic. Methods We apply Bayesian hierarchical modelling to ELISA measurements of human serum samples against SARS-CoV-2 and HCoV antigens. Results Inflection titers for SARS-CoV-2 full-length spike protein (S1S2), spike protein receptor-binding domain (RBD), and nucleoprotein (N) inferred from three spread-out dilutions correlated with those inferred from eight consecutive dilutions with an R2 value of 0.97 or higher. We confirm existing findings showing a small proportion of pre-pandemic human serum samples contain cross-reactive antibodies to SARS-CoV-2 S1S2 and N, and that SARS-CoV-2 infection increases serum reactivity to the beta-HCoVs OC43 and HKU1 S1S2. Conclusions In serial dilution assays, large savings in resources and/or increases in throughput can be achieved by reducing the number of dilutions measured and using Bayesian hierarchical modelling to infer inflection or endpoint titers. We have released software for conducting these types of analysis.

Data-driven estimate of past and present surface loading over North America: Bayesian Hierarchical Modelling approach applied to GPS and GRACE observations

<p>Glacial Isostatic Adjustment (GIA) and the hydrological cycle are both associated with mass changes, which are observed by GRACE, and vertical land motion (VLM), which is observed by GPS. Hydrology-related VLM results from the instantaneous response of the elastic solid Earth to surface loading by freshwater, whereas GIA-related VLM reveals the long-term response of the visco-elastic Earth mantle to past glacial cycles. Thus, observations of mass changes and VLM are interrelated and GIA and hydrology are difficult to investigate independently. Taking advantage of the differences in the spatio-temporal characteristics of the GIA and hydrology fields, we can separate the respective contributions of each process. In this work, we use a Bayesian Hierarchical Modelling (BHM) approach to provide a new data-driven estimate of GIA and time-evolving hydrology-related VLM for North America. We detail our processing strategy to prepare the input data for the BHM while preserving the content of the original observations. We discuss the separation of GIA and hydrology processes from a statistical and geophysical point of view. Finally, we assess the reliability of our estimates and compare our results to the latest GIA and hydrological models. Specifically, we compare our GIA solution to a forward-model global field, ICE-6G, and a recent GIA estimate developed for North America (Simon et al. 2017). Our time-evolving hydrology field is compared with WaterGAP, a global water balance model. Overall, for both GIA and hydrology, there is a good agreement between our results and the forward models, but we also find differences which possibly highlight deficiencies in these models.</p>

Subnational analysis of the COVID-19 epidemic in Brazil

Brazil is currently reporting the second highest number of COVID-19 deaths in the world. Here we characterise the initial dynamics of COVID-19 across the country and assess the impact of non-pharmaceutical interventions (NPIs) that were implemented using a semi-mechanistic Bayesian hierarchical modelling approach. Our results highlight the significant impact these NPIs had across states, reducing an average R_t >3 to an average of 1.5 by 9-May-2020, but that these interventions failed to reduce R_t <1, congruent with the worsening epidemic Brazil has experienced since. We identify extensive heterogeneity in the epidemic trajectory across Brazil, with the estimated number of days to reach 0.1 % of the state population infected since the first nationally recorded case ranging from 20 days in São Paulo compared to 60 days in Goiás, underscoring the importance of sub-national analyses in understanding asynchronous state-level epidemics underlying the national spread and burden of COVID-19.