Recent analysis of early COVID-19 data from China showed that the number of confirmed cases followed a subexponential power-law increase, with a growth exponent of around 2.2 (Maier and Brockmann, ...2020). The power-law behavior was attributed to a combination of effective containment and mitigation measures employed as well as behavioral changes by the population. In this work, we report a random walk Monte Carlo simulation study of proximity-based infection spread. Control interventions such as lockdown measures and mobility restrictions are incorporated in the simulations through a single parameter, the size of each step in the random walk process. The step size l is taken to be a multiple of 〈r〉, which is the average separation between individuals. Three temporal growth regimes (quadratic, intermediate power-law and exponential) are shown to emerge naturally from our simulations. For l=〈r〉, we get intermediate power-law growth exponents that are in general agreement with available data from China. On the other hand, we obtain a quadratic growth for smaller step sizes l≲〈r〉∕2, while for large l the growth is found to be exponential. We further performed a comparative case study of early fatality data (under varying levels of lockdown conditions) from three other countries, India, Brazil and South Africa. We show that reasonable agreement with these data can be obtained by incorporating small-world-like connections in our simulations.
•Two-dimensional random walk Monte Carlo simulations are used to investigate COVID-19 infection spread through contact interactions.•Our simulations are shown to make reasonably accurate predictions ...of secondary and tertiary waves of COVID-19 infections.•The proposed model is intuitive and easy to access compared to other conventional approaches.•The ab initio nature of this work promises a better understanding of infectious disease outbreaks.
Phenomenological and deterministic models are often used for the estimation of transmission parameters in an epidemic and for the prediction of its growth trajectory. Such analyses are usually based on single peak outbreak dynamics. In light of the present COVID-19 pandemic, there is a pressing need to better understand observed epidemic growth with multiple peak structures, preferably using first-principles methods. Along the lines of our previous work Physica A 574, 126014 (2021), here we apply 2D random-walk Monte Carlo calculations to better understand COVID-19 spread through contact interactions. Lockdown scenarios and all other control interventions are imposed through mobility restrictions and a regulation of the infection rate within the stochastically interacting population. The susceptible, infected and recovered populations are tracked over time, with daily infection rates obtained without recourse to the solution of differential equations.
The simulations were carried out for population densities corresponding to four countries, India, Serbia, South Africa and USA. In all cases our results capture the observed infection growth rates. More importantly, the simulation model is shown to predict secondary and tertiary waves of infections with reasonable accuracy. This predictive nature of multiple wave structures provides a simple and effective tool that may be useful in planning mitigation strategies during the present pandemic.
Recent work showed that the temporal growth of the novel coronavirus disease (COVID-19) follows a sub-exponential power-law scaling whenever effective control interventions are in place. Taking this ...into consideration, we present a new phenomenological logistic model that is well-suited for such power-law epidemic growth.
We empirically develop the logistic growth model using simple scaling arguments, known boundary conditions and a comparison with available data from four countries, Belgium, China, Denmark and Germany, where (arguably) effective containment measures were put in place during the first wave of the pandemic. A non-linear least-squares minimization algorithm is used to map the parameter space and make optimal predictions.
Unlike other logistic growth models, our presented model is shown to consistently make accurate predictions of peak heights, peak locations and cumulative saturation values for incomplete epidemic growth curves. We further show that the power-law growth model also works reasonably well when containment and lock down strategies are not as stringent as they were during the first wave of infections in 2020. On the basis of this agreement, the model was used to forecast COVID-19 fatalities for the third wave in South Africa, which was in progress during the time of this work.
We anticipate that our presented model will be useful for a similar forecasting of COVID-19 induced infections/deaths in other regions as well as other cases of infectious disease outbreaks, particularly when power-law scaling is observed.
•Early COVID-19 data from the first wave of infections in 2020 showed sub-exponential power-law growth behavior.•The power-law scaling was attributed to effective containment and mitigation strategies, and reproduced reasonably well by two-dimensional random walk Monte Carlo simulations.•Here we empirically develop a new logistic growth model (LGM) that is well suited to describe such power-law growth.•The power-law model is compared with other LGMs. It is shown to be rather robust, making consistently accurate out-of-sample predictions for COVID-19 fatality data from five different countries.
Renal involvement in non-Hodgkin lymphoma (NHL) has myriad of morphological features. We discuss an unusual case who presented as acute pyelonephritis (leucocytosis and acute kidney injury), ovarian ...mass and compressive myelopathy finally diagnosed as Non Hodgkins Lymphoma.
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The Tsallis
q
-statistics have been incorporated in the Weibull model of particle production, in the form of
q
-Weibull distribution, to describe the transverse momentum (
p
T
) distribution of ...charged hadrons at mid-rapidity, measured at RHIC and LHC energies. The
q
-Weibull distribution is found to describe the observed
p
T
distributions over all ranges of measured
p
T
. Below 2.2 GeV/c, while going from peripheral to central collisions, the parameter
q
is found to decrease systematically towards unity, indicating an evolution from a non-equilibrated system in peripheral collisions, towards a more thermalized system in central collisions. However, the trend is reversed in the all inclusive
p
T
regime. This can be attributed to an increase in relative contribution of hard pQCD processes in central collisions. The
λ
-parameter is found to be associated with the mean
p
T
or the collective expansion velocity of the produced hadrons, which shows an expected increase with centrality of collisions. The
k
parameter is observed to increase with the onset of hard QCD scatterings, initial fluctuations, and other processes leading to non-equilibrium conditions.
For the development of advanced polymer nanocomposite processability, high-quality and cost-efficiency plays a crucial role which combines mechanical robustness with functional electrochemical ...properties. In this study, we fabricated the epoxy/graphene nanocomposite (EGNC) with different wt% ratio of graphene nanoplatelets (GNPs). The EGNCs were fabricated through a solution mixing process and used it as an electrode to enhance electrochemical properties. The GNPs and EGNCs characterized using XRD, Raman spectroscopy, ATR FT-IR, and FE-SEM for the structural conformation and surface morphological study. The electrochemical analysis results show significant improvement in the specific capacitance in the EGNC samples as compared to the blank epoxy film. Specific capacitance 17.74 Fg
−1
was recorded at 10 mVs
−1
scan rate in 1.0 M KOH electrolyte solution for the 1.0 wt% EGNC film by cyclic voltammetry analysis. The Galvanostatic charge–discharge and Ragone plots also show mended results by the addition of GNPs.
Recently some of us used a random-walk Monte Carlo simulation approach to study the spread of COVID-19. The calculations were reasonably successful in describing secondary and tertiary waves of ...infection, in countries such as the USA, India, South Africa and Serbia. However, they failed to predict the observed third wave for India. In this work we present a more complete set of simulations for India, that take into consideration two aspects that were not incorporated previously. These include the stochastic movement of an erstwhile protected fraction of the population, and the reinfection of some recovered individuals because of their exposure to a new variant of the SARS-CoV-2 virus. The extended simulations now show the third COVID-19 wave for India that was missing in the earlier calculations. They also suggest an additional fourth wave, which was indeed observed during approximately the same time period as the model prediction.
Muga silk nanoparticles (MSNP) were synthesized using a microwave‐assisted radiolysis method. The effect of microwave on the Muga protein secondary structures was analyzed. The evolution of the ...secondary structure from random coils to the β‐sheets was determined by using FTIR, circular dichroism and X‐ray diffraction techniques. The results showed that Muga silk fibroin protein contained the primary structure in silk‐I state. When the protein was irradiated with microwave, nanoparticle synthesis was possible having silk‐II state imparting crystallinity. The silk nanoparticles were characterized by a particle size analyzer and found to be of ~240 nm in size. The optical properties of these nanoparticles were studied by UV–vis. spectroscopy and photoluminescence. For studying thermal properties, differential scanning calorimetry was performed that revealed early glass transition, which could be attributed to the presence of water and proteins. It also revealed that nanoparticles are thermally stable. Such studies are important for understanding more about the MSNP and would be beneficial for their further wide applications.
Schematic illustration of conversion of random coil to β‐sheets.
We report on the formation of UV emitting Si nanoclusters (NCs) in Si, using a two stage Au implantation technique. These Si NCs, with an average size of 2 nm, show photoluminescence at room ...temperature, over a narrow band of about 100 meV with a peak of emission near 3.3 eV. With emission lifetimes in the range of 1.5-2.5 ns, the transitions seem to come from excitonic recombinations across a quasi-direct gap. Since the structures are below the surface, there is no adverse effect of oxidation resulting in a shift in emission wavelength. On the other hand, an annealing at 500 °C has been found to result in a significant increase in the emission intensity. This is due to localized plasmon induced electric field enhancement in Au nano-islands in the vicinity.
The current measures to control foot-and-mouth disease (FMD) include vaccination, movement control and slaughter of infected or susceptible animals. One of the difficulties in controlling FMD by ...vaccination arises due to the substantial diversity found among the seven serotypes of FMD virus (FMDV) and the strains within these serotypes. Therefore, vaccination using a single vaccine strain may not fully cross-protect against all strains within that serotype, and therefore selection of appropriate vaccines requires serological comparison of the field virus and potential vaccine viruses using relationship coefficients (r1 values). Limitations of this approach are that antigenic relationships among field viruses are not addressed, as comparisons are only with potential vaccine virus. Furthermore, inherent variation among vaccine sera may impair reproducibility of one-way relationship scores. Here, we used antigenic cartography to quantify and visualize the antigenic relationships among FMD serotype A viruses, aiming to improve the understanding of FMDV antigenic evolution and the scope and reliability of vaccine matching. Our results suggest that predicting antigenic difference using genetic sequence alone or by geographical location is not currently reliable. We found co-circulating lineages in one region that were genetically similar but antigenically distinct. Nevertheless, by comparing antigenic distances measured from the antigenic maps with the full capsid (P1) sequence, we identified a specific amino acid substitution associated with an antigenic mismatch among field viruses and a commonly used prototype vaccine strain, A22/IRQ/24/64.
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