Estimation of age-stratified contact rates during the COVID-19 pandemic using a novel inference algorithm

Well parameterised epidemiological models including accurate representation of contacts, are fundamental to controlling epidemics. However, age-stratified contacts are typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here we fit age-stratified models, including re-estimation of relative contact rates between age-classes, to public data describing the 2020-21 COVID-19 outbreak in England. This data includes age-stratified population size, cases, deaths, hospital admissions, and results from the Coronavirus Infection Survey (almost 9000 observations in all). Fitting stochastic compartmental models to such detailed data is extremely challenging, especially considering the large number of model parameters being estimated (over 150). An efficient new inference algorithm ABC-MBP combining existing Approximate Bayesian Computation (ABC) methodology with model-based proposals (MBP) is applied. Modified contact rates are inferred alongside time-varying reproduction numbers that quantify changes in overall transmission due to pandemic response, and age-stratified proportions of asymptomatic cases, hospitalisation rates and deaths. These inferences are robust to a range of assumptions including the values of parameters that cannot be estimated from available data. ABC-MBP is shown to enable reliable joint analysis of complex epidemiological data yielding consistent parametrisation of dynamic transmission models that can inform data-driven public health policy and interventions.

On predicting particle capture rates in aquatic ecosystems

Recent advances in understanding the capture of moving suspended particles in aquatic ecosystems have opened up new possibilities for predicting rates of suspension feeding, larval settlement, seagrass pollination and sediment removal. Drawing on results from both highly-resolved computational fluid dynamics (CFD) simulations and existing experimental data, we quantify the controlling influence of flow velocity, particle size and collector size on rates of contact between suspended particles and biological collectors over the parameter space characterising a diverse range of aquatic ecosystems. As distinct from assumptions in previous modeling studies, the functional relationships describing capture are highly variable. Contact rates can vary in opposing directions in response to changes in collector size, an organism’s size, the size of particles being intercepted (related to diet in the case of suspension feeders), and the flow strength. Contact rates shift from decreasing to increasing with collector diameter when particles become relatively large and there is vortex shedding in the collector wake. And in some ranges of the ecologically relevant parameter space, contact rates do not increase strongly with velocity or particle size. The understanding of these complex dependencies allows us to reformulate some hypotheses of selection pressure on the physiology and ecology of aquatic organisms. We discuss the benefits and limitations of CFD tools in predicting rates of particle capture in aquatic ecosystems. Finally, across the complete parameter space relevant to real aquatic ecosystems, all quantitative estimates of particle capture from our model are provided here.

Multiscale model for forecasting Sabin 2 vaccine virus household and community transmission

Since the global withdrawal of Sabin 2 oral poliovirus vaccine (OPV) from routine immunization, the Global Polio Eradication Initiative (GPEI) has reported multiple circulating vaccine-derived poliovirus type 2 (cVDPV2) outbreaks. Here, we generated an agent-based, mechanistic model designed to assess OPV-related vaccine virus transmission risk in populations with heterogeneous immunity, demography, and social mixing patterns. To showcase the utility of our model, we present a simulation of mOPV2-related Sabin 2 transmission in rural Matlab, Bangladesh based on stool samples collected from infants and their household contacts during an mOPV2 clinical trial. Sabin 2 transmission following the mOPV2 clinical trial was replicated by specifying multiple, heterogeneous contact rates based on household and community membership. Once calibrated, the model generated Matlab-specific insights regarding poliovirus transmission following an accidental point importation or mass vaccination event. We also show that assuming homogeneous contact rates (mass action), as is common of poliovirus forecast models, does not accurately represent the clinical trial and risks overestimating forecasted poliovirus outbreak probability. Our study identifies household and community structure as an important source of transmission heterogeneity when assessing OPV-related transmission risk and provides a calibratable framework for expanding these analyses to other populations. Trial Registration: ClinicalTrials.gov This trial is registered with clinicaltrials.gov, NCT02477046.

Anterior occlusion in shortened dental arches

Objectives The aim of this study was to examine the occlusion of anterior teeth in individuals with shortened dental arch (SDA). Material and methods In a case–control clinical study, 41 individuals with SDA and 41 individuals with complete dental arch (CDA) participated. The CDA control group was matched for age and gender. Testing for occlusal contacts of anterior maxillary teeth was conducted by biting on foil strips (8 µm) with subjectively normal bite force (NBF) and maximal bite force (MBF). The data was analyzed on individual and tooth levels. Results The median rates of anterior maxillary teeth with occlusal contacts were 0.67 (NBF) and 0.83 (MBF) in the SDA group and 0.50 (NBF) and 0.83 (MBF) in the CDA group. Within both groups, the contact rates were significantly higher in MBF. The group difference with NBF was significant. A generalized linear model showed that the odds of an anterior maxillary tooth to have an occlusal contact were greater in the SDA both for NBF with an odds ratio (OR) 2.277 and MBF with an OR 1.691. Conclusions The findings suggest effective compensatory mechanisms relative to the occlusal function in individuals with SDA. Clinical relevance The study delivers further evidence regarding the SDA concept as a viable option in the management of posterior tooth loss.

A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations

We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.

Third doses of COVID-19 vaccines reduce infection and transmission of SARS-CoV-2 and could prevent future surges in some populations

Background Vaccines have greatly reduced the impact of COVID-19 globally. Unfortunately, evidence indicates that immunity wanes following vaccination, especially with the Delta variant (B.1.617.2). Protection against severe disease and death remain high, but protection against milder disease and infection have dropped significantly. A third booster dose of two-dose vaccines has been approved in several countries to individuals at higher risk of severe disease to protect those individuals, but the benefit to boosting immunity in younger healthy individuals and the effects on transmission are less clear. Methods Here we use relationships between neutralizing antibody titers and vaccine protection against infection and transmission, combined with data on waning and boosting of neutralizing antibody titers to examine the impact of a third dose of the Pfizer vaccine on infection and transmission and its impact on the pathogen effective reproductive number Rt. Findings Eight months of waning reduced protection of the Pfizer vaccine against all infections from 80.0% (95% CI: 77% to 83%) to 60.4% (95% CI: 53% to 67%); a third dose (which increased neutralizing antibody titers 25.9- fold relative to levels after 8 months of waning) increased protection to 87.2% (95% CI: 83% to 91%). Increased protection against infection and transmission from third doses reduced Rt by 21% to 66% depending on vaccine coverage and previous infection and reduced Rt below 1 when vaccination coverage was high or contact rates were well below pre-pandemic levels. Interpretation A third dose of the Pfizer vaccine could reduce transmission of SARS-CoV-2, which would reduce infection in unvaccinated individuals and breakthrough infections in vaccinated individuals. While vaccination of unvaccinated individuals, especially in developing countries, would be more effective for reducing disease than providing a third dose to vaccinated individuals, the benefit of a third dose in reducing transmission is sizeable and increases with vaccine coverage and contact rates among individuals.

Social mixing patterns in the UK following the relaxation of COVID-19 pandemic restrictions: a cross-sectional online survey

Background Since 23 March 2020, social distancing measures have been implemented in the UK to reduce SARS-CoV-2 transmission. We conducted a cross-sectional survey to quantify and characterize non-household contact and to identify the effect of shielding and isolating on contact patterns. Methods Through an online questionnaire, the CoCoNet study measured daily interactions and mobility of 5143 participants between 28 July and 14 August 2020. Negative binomial regression modelling identified participant characteristics associated with contact rates. Results The mean rate of non-household contacts per person was 2.9 d-1. Participants attending a workplace (adjusted incidence rate ratio (aIRR) 3.33, 95%CI 3.02 to 3.66), self-employed (aIRR 1.63, 95%CI 1.43 to 1.87) or working in healthcare (aIRR 5.10, 95%CI 4.29 to 6.10) reported significantly higher non-household contact rates than those working from home. Participants self-isolating as a precaution or following Test and Trace instructions had a lower non-household contact rate than those not self-isolating (aIRR 0.58, 95%CI 0.43 to 0.79). We found limited evidence that those shielding had reduced non-household contacts compared to non-shielders. Conclusion The daily rate of non-household interactions remains lower than pre-pandemic levels, suggesting continued adherence to social distancing guidelines. Individuals attending a workplace in-person or employed as healthcare professionals were less likely to maintain social distance and had a higher non-household contact rate, possibly increasing their infection risk. Shielding and self-isolating individuals required greater support to enable them to follow the government guidelines and reduce non-household contact and therefore their risk of infection.

A twelve-month projection to September 2022 of the Covid-19 epidemic in the UK using a Dynamic Causal Model

Objectives Predicting the future UK Covid-19 epidemic allows other countries to compare their epidemic with one unfolding without public health measures except a vaccine programme. Methods A Dynamic Causal Model (DCM) is used to estimate the model parameters of the epidemic such as vaccine effectiveness and increased transmissibility of alpha and delta variants, the vaccine programme roll-out and changes in contact rates. The model predicts the future trends in infections, long-Covid, hospital admissions and deaths. Results Two dose vaccination given to 66% of the UK population prevents transmission following infection by 44%, serious illness by 86% and death by 93%. Despite this, with no other public health measures used, cases will increase from 37 million to 61 million, hospital admission from 536,000 to 684,000 and deaths from 136,000 to 142,000 over twelve months. Discussion Vaccination alone will not control the epidemic. Relaxation of mitigating public health measures carries several risks including overwhelming the health services, the creation of vaccine resistant variants and the economic cost of huge numbers of acute and chronic cases.

Redefining snakebite envenoming as a zoonosis: disease incidence is driven by snake ecology, socioeconomics and anthropogenic impacts

Snakebite is the only WHO-listed, not infectious neglected tropical disease (NTD), although its eco-epidemiology is similar to that of zoonotic infections: envenoming occurs after a vertebrate host contacts a human. Accordingly, snakebite risk represents the interaction between snake and human factors, but their quantification has been limited by data availability. Models of infectious disease transmission are instrumental for the mitigation of NTDs and zoonoses. Here, we represented snake-human interactions with disease transmission models to approximate geospatial estimates of snakebite incidence in Sri Lanka, a global hotspot. Snakebites and envenomings are described by the product of snake and human abundance, mirroring directly transmitted zoonoses. We found that human-snake contact rates vary according to land cover (surrogate of occupation and socioeconomic status), the impacts of humans and climate on snake abundance, and by snake species. Our findings show that redefining snakebite as zoonosis provides a mechanistic eco-epidemiological basis to understand snakebites, and the possible implications of global environmental and demographic change for the burden of snakebite.