Modelling the impact of hybrid immunity on future COVID-19 epidemic waves.

BACKGROUND: Since the emergence of SARS-CoV-2 (COVID-19), there have been multiple waves of infection and multiple rounds of vaccination rollouts. Both prior infection and vaccination can prevent future infection and reduce severity of outcomes, combining to form hybrid immunity against COVID-19 at the individual and population level. Here, we explore how different combinations of hybrid immunity affect the size and severity of near-future Omicron waves. METHODS: To investigate the role of hybrid immunity, we use an agent-based model of COVID-19 transmission with waning immunity to simulate outbreaks in populations with varied past attack rates and past vaccine coverages, basing the demographics and past histories on the World Health Organization Western Pacific Region. RESULTS: We find that if the past infection immunity is high but vaccination levels are low, then the secondary outbreak with the same variant can occur within a few months after the first outbreak; meanwhile, high vaccination levels can suppress near-term outbreaks and delay the second wave. Additionally, hybrid immunity has limited impact on future COVID-19 waves with immune-escape variants. CONCLUSIONS: Enhanced understanding of the interplay between infection and vaccine exposure can aid anticipation of future epidemic activity due to current and emergent variants, including the likely impact of responsive vaccine interventions.

Mathematical models of Plasmodium vivax transmission: A scoping review.

Plasmodium vivax is one of the most geographically widespread malaria parasites in the world, primarily found across South-East Asia, Latin America, and parts of Africa. One of the significant characteristics of the P. vivax parasite is its ability to remain dormant in the human liver as hypnozoites and subsequently reactivate after the initial infection (i.e. relapse infections). Mathematical modelling approaches have been widely applied to understand P. vivax dynamics and predict the impact of intervention outcomes. Models that capture P. vivax dynamics differ from those that capture P. falciparum dynamics, as they must account for relapses caused by the activation of hypnozoites. In this article, we provide a scoping review of mathematical models that capture P. vivax transmission dynamics published between January 1988 and May 2023. The primary objective of this work is to provide a comprehensive summary of the mathematical models and techniques used to model P. vivax dynamics. In doing so, we aim to assist researchers working on mathematical epidemiology, disease transmission, and other aspects of P. vivax malaria by highlighting best practices in currently published models and highlighting where further model development is required. We categorise P. vivax models according to whether a deterministic or agent-based approach was used. We provide an overview of the different strategies used to incorporate the parasite's biology, use of multiple scales (within-host and population-level), superinfection, immunity, and treatment interventions. In most of the published literature, the rationale for different modelling approaches was driven by the research question at hand. Some models focus on the parasites' complicated biology, while others incorporate simplified assumptions to avoid model complexity. Overall, the existing literature on mathematical models for P. vivax encompasses various aspects of the parasite's dynamics. We recommend that future research should focus on refining how key aspects of P. vivax dynamics are modelled, including spatial heterogeneity in exposure risk and heterogeneity in susceptibility to infection, the accumulation of hypnozoite variation, the interaction between P. falciparum and P. vivax, acquisition of immunity, and recovery under superinfection.

Rapid prototyping of models for COVID-19 outbreak detection in workplaces.

Early case detection is critical to preventing onward transmission of COVID-19 by enabling prompt isolation of index infections, and identification and quarantining of contacts. Timeliness and completeness of ascertainment depend on the surveillance strategy employed. This paper presents modelling used to inform workplace testing strategies for the Australian government in early 2021. We use rapid prototype modelling to quickly investigate the effectiveness of testing strategies to aid decision making. Models are developed with a focus on providing relevant results to policy makers, and these models are continually updated and improved as new questions are posed. Developed to support the implementation of testing strategies in high risk workplace settings in Australia, our modelling explores the effects of test frequency and sensitivity on outbreak detection. We start with an exponential growth model, which demonstrates how outbreak detection changes depending on growth rate, test frequency and sensitivity. From the exponential model, we learn that low sensitivity tests can produce high probabilities of detection when testing occurs frequently. We then develop a more complex Agent Based Model, which was used to test the robustness of the results from the exponential model, and extend it to include intermittent workplace scheduling. These models help our fundamental understanding of disease detectability through routine surveillance in workplaces and evaluate the impact of testing strategies and workplace characteristics on the effectiveness of surveillance. This analysis highlights the risks of particular work patterns while also identifying key testing strategies to best improve outbreak detection in high risk workplaces.

Individual variation in vaccine immune response can produce bimodal distributions of protection.

The ability for vaccines to protect against infectious diseases varies among individuals, but computational models employed to inform policy typically do not account for this variation. Here we examine this issue: we implement a model of vaccine efficacy developed in the context of SARS-CoV-2 in order to evaluate the general implications of modelling correlates of protection on the individual level. Due to high levels of variation in immune response, the distributions of individual-level protection emerging from this model tend to be highly dispersed, and are often bimodal. We describe the specification of the model, provide an intuitive parameterisation, and comment on its general robustness. We show that the model can be viewed as an intermediate between the typical approaches that consider the mode of vaccine action to be either "all-or-nothing" or "leaky". Our view based on this analysis is that individual variation in correlates of protection is an important consideration that may be crucial to designing and implementing models for estimating population-level impacts of vaccination programs.

COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting.

Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19-free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission. This transition is articulated in the national 're-opening' plan released in July 2021. Here, we report on the dynamic modelling study that directly informed policies within the national re-opening plan including the identification of priority age groups for vaccination, target vaccine coverage thresholds and the anticipated requirements for continued public health measures-assuming circulation of the Delta SARS-CoV-2 variant. Our findings demonstrated that adult vaccine coverage needed to be at least 60% to minimize public health and clinical impacts following the establishment of community transmission. They also supported the need for continued application of test-trace-isolate-quarantine and social measures during the vaccine roll-out phase and beyond.

Fitting potential energy and induced dipole surfaces of the van der Waals complex CH4-N2 using non-product quadrature grids.

We present an extensive study of the five-dimensional potential energy and induced dipole surfaces of the CH4-N2 complex assuming rigid-rotor approximation. Within the supermolecular approach, ab initio calculations of the interaction energies and dipoles were carried out at the CCSD(T)-F12 and CCSD(T) levels of theory using the correlation-consistent aug-cc-pVTZ basis set, respectively. Both potential energy and induced dipole surfaces inherit the symmetry of the molecular system and transform under the A1+ and A2+ irreducible representations of the molecular symmetry group G48, respectively. One can take advantage of the symmetry when fitting the surfaces; first, when constructing angular basis functions and second, when selecting the grid points. The approach to the construction of scalar and vectorial basis functions exploiting the eigenfunction method [Q. Chen, J. Ping and F. Wang, Group Representation Theory for Physicists, World Scientific, 2nd edn, 2002] is developed. We explore the use of Sobolev-type quadrature grids as building blocks of robust quadrature rules adapted to the symmetry of the molecular system. Temperature variations of the cross second virial coefficient and first classical spectral moments of the rototranslational collision-induced band were derived. A reasonable agreement between calculated values and experimental data was found attesting to the high quality of constructed surfaces.

Early analysis of the Australian COVID-19 epidemic.

As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).

Use of the complete basis set limit for computing highly accurate ab initio dipole moments.

Calculating dipole moments with high-order basis sets is generally only possible for the light molecules, such as water. A simple, yet highly effective strategy of obtaining high-order dipoles with small, computationally less expensive basis sets is described. Using the finite field method for computing dipoles, energies calculated with small basis sets can be extrapolated to produce dipoles that are comparable to those obtained in high order calculations. The method reduces computational resources by approximately 50% (allowing the calculation of reliable dipole moments for larger molecules) and simultaneously improves the agreement with experimentally measured infrared transition intensities. For atmospherically important molecules, which are typically too large to consider the use of large basis sets, this procedure will provide the necessary means of improving calculated spectral intensities by several percent.

A highly accurate ab initio dipole moment surface for the ground electronic state of water vapour for spectra extending into the ultraviolet.

A new global and highly accurate ab initio dipole moment surface (DMS) for water vapour is presented. This DMS is based on a set of 17 628 multi-reference configuration interaction data points that were calculated with the aug-cc-pCV6Z basis set with the Douglas-Kroll-Hess Hamiltonian; tests are performed at several other levels of ab initio theory. This new "CKAPTEN" DMS improves agreement with recent experimental measurements compared with previous models that poorly predicted some bands in the infrared while also maintaining or improving on the agreement for all remaining strong lines. For high overtones located in both the visible and the near ultraviolet regions, our predicted intensities all lie within 10% of recent atmospheric observations. A crossing of energy levels in the ν1 fundamental and 2ν2 states is seen to offset transition intensities in the ν1 fundamental band; residual inaccuracies within the potential energy surface used is the cause of this problem.