Modelling the first wave of COVID-19 in India.

Estimating the burden of COVID-19 in India is difficult because the extent to which cases and deaths have been undercounted is hard to assess. Here, we use a 9-component, age-stratified, contact-structured epidemiological compartmental model, which we call the INDSCI-SIM model, to analyse the first wave of COVID-19 spread in India. We use INDSCI-SIM, together with Bayesian methods, to obtain optimal fits to daily reported cases and deaths across the span of the first wave of the Indian pandemic, over the period Jan 30, 2020 to Feb 15, 2021. We account for lock-downs and other non-pharmaceutical interventions (NPIs), an overall increase in testing as a function of time, the under-counting of cases and deaths, and a range of age-specific infection-fatality ratios. We first use our model to describe data from all individual districts of the state of Karnataka, benchmarking our calculations using data from serological surveys. We then extend this approach to aggregated data for Karnataka state. We model the progress of the pandemic across the cities of Delhi, Mumbai, Pune, Bengaluru and Chennai, and then for India as a whole. We estimate that deaths were undercounted by a factor between 2 and 5 across the span of the first wave, converging on 2.2 as a representative multiplier that accounts for the urban-rural gradient. We also estimate an overall under-counting of cases by a factor of between 20 and 25 towards the end of the first wave. Our estimates of the infection fatality ratio (IFR) are in the range 0.05-0.15, broadly consistent with previous estimates but substantially lower than values that have been estimated for other LMIC countries. We find that approximately 35% of India had been infected overall by the end of the first wave, results broadly consistent with those from serosurveys. These results contribute to the understanding of the long-term trajectory of COVID-19 in India.

Association of national and regional lockdowns with COVID-19 infection rates in Pune, India.

Assessing the impact of lockdowns on COVID-19 incidence may provide important lessons for management of pandemic in resource-limited settings. We examined growth of incident confirmed COVID-19 patients before, during and after lockdowns during the first wave in Pune city that reported the largest COVID-19 burden at the peak of the pandemic. Using anonymized individual-level data captured by Pune's public health surveillance program between February 1st and September 15th 2020, we assessed weekly incident COVID-19 patients, infection rates, and epidemic curves by lockdown status (overall and by sex, age, and population density) and modelled the natural epidemic using the compartmental model. Effect of lockdown on incident patients was assessed using multilevel Poisson regression. We used geospatial mapping to characterize regional spread. Of 241,629 persons tested for SARS-CoV-2, 64,526 (26%) were positive, contributing to an overall rate of COVID-19 disease of 267·0 (95% CI 265·3-268·8) per 1000 persons. The median age of COVID-19 patients was 36 (interquartile range [IQR] 25-50) years, 36,180 (56%) were male, and 9414 (15%) were children < 18 years. Epidemic curves and geospatial mapping showed delayed peak of the patients by approximately 8 weeks during the lockdowns as compared to modelled natural epidemic. Compared to a subsequent unlocking period, incident COVID-19 patients were 43% lower (IRR 0·57, 95% CI 0·53-0·62) during India's nationwide lockdown and were 22% lower (IRR 0·78, 95% CI 0.73-0.84) during Pune's regional lockdown and was uniform across age groups and population densities. Both national and regional lockdowns slowed the COVID-19 infection rates in population dense, urban region in India, underscoring its impact on COVID-19 control efforts.

Anisotropic transport and optical birefringence of triclinic bulk and monolayer NbX2Y2(X = S, Se and Y = Cl, Br, I).

A systematic analysis of the electronic, thermoelectric and optical properties of triclinic van der Waal's solids NbX2Y2(X = S, Se and Y = Cl, Br, I) is carried out within the framework of density functional theory for bulk and monolayer. The investigated compounds are semiconductors in bulk and monolayer, with band gap values ranging from 1.1 to 1.8 eV. We observed huge anisotropy in the electrical conductivity with the in-plane conductivity being 40 times higher than out-of-plane conductivity in NbS2I2. The observed high power factor and low thermal conductivity in NbX2Y2render these compounds as potential thermoelectric materials. In addition, the calculated optical properties such as refractive index and absorption coefficient reveal the optical anisotropy. We have calculated birefringence for all the studied compounds and a large value of 0.313 is observed for NbSe2I2. The monolayer electronic properties indicate the presence of anomalous quantum confinement. The giant birefringence along with promosing monolayer properties are the highlights of present work which might fetch future device applications in both bulk as well as monolayer.

Theoretical investigation of planar square carbon allotrope and its hydrogenation.

Using density functional theory we investigate a novel carbon allotrope 'SqC': a square planar material that can be more than tetracoordinated. Carbon atoms in this 2D square Bravais lattice form an unusual five-center four-electron bond with neighboring four carbon atoms (tetracoordination). Such an electron-deficient bonding leaves an empty orbital which enables penta- or hexa-coordinated carbon atom. Indeed, our simulations demonstrate such penta- and hexa-coordinated configurations upon partial and complete hydrogenation, respectively. Surprisingly, in all the forms SqC shows the metallic character. SqC has the binding energy of 6.7 eV and it also satisfies the Born stability criteria. Yet our phonon calculations show that it may only be considered as quasi-stable.

Efficient treatment of solvation shells in 3D molecular theory of solvation.

We developed a technique to decrease memory requirements when solving the integral equations of three-dimensional (3D) molecular theory of solvation, a.k.a. 3D reference interaction site model (3D-RISM), using the modified direct inversion in the iterative subspace (MDIIS) numerical method of generalized minimal residual type. The latter provides robust convergence, in particular, for charged systems and electrolyte solutions with strong associative effects for which damped iterations do not converge. The MDIIS solver (typically, with 2 × 10 iterative vectors of argument and residual for fast convergence) treats the solute excluded volume (core), while handling the solvation shells in the 3D box with two vectors coupled with MDIIS iteratively and incorporating the electrostatic asymptotics outside the box analytically. For solvated systems from small to large macromolecules and solid-liquid interfaces, this results in 6- to 16-fold memory reduction and corresponding CPU load decrease in MDIIS. We illustrated the new technique on solvated systems of chemical and biomolecular relevance with different dimensionality, both in ambient water and aqueous electrolyte solution, by solving the 3D-RISM equations with the Kovalenko-Hirata (KH) closure, and the hypernetted chain (HNC) closure where convergent. This core-shell-asymptotics technique coupling MDIIS for the excluded volume core with iteration of the solvation shells converges as efficiently as MDIIS for the whole 3D box and yields the solvation structure and thermodynamics without loss of accuracy. Although being of benefit for solutes of any size, this memory reduction becomes critical in 3D-RISM calculations for large solvated systems, such as macromolecules in solution with ions, ligands, and other cofactors.

A systematic study of electronic structure from graphene to graphane.

While graphene is a semi-metal, a recently synthesized hydrogenated graphene called graphane is an insulator. We have probed the transformation of graphene upon hydrogenation to graphane within the framework of density functional theory. By analysing the electronic structure for 18 different hydrogen concentrations, we bring out some novel features of this transition. Our results show that the hydrogenation favours clustered configurations leading to the formation of compact islands. The analysis of the charge density and electron localization function (ELF) indicates that, as hydrogen coverage increases, the semi-metal turns into a metal, showing a delocalized charge density, then transforms into an insulator. The metallic phase is spatially inhomogeneous in the sense it contains islands of insulating regions formed by hydrogenated carbon atoms and metallic channels formed by contiguous bare carbon atoms. It turns out that it is possible to pattern the graphene sheet to tune the electronic structure. For example, removal of hydrogen atoms along the diagonal of the unit cell, yielding an armchair pattern at the edge, gives rise to a bandgap of 1.4 eV. We also show that a weak ferromagnetic state exists even for a large hydrogen coverage whenever there is a sublattice imbalance in the presence of an odd number of hydrogen atoms.