arXiv subjects

Zeina S. Khan

Publications and source records attributed to Zeina S. Khan.

6 recordsLinked to original sources

arXiv2021

Measuring the Change in European and US COVID-19 Death Rates

By fitting a compartment ODE model for Covid-19 propagation to cumulative case and death data for US states and European countries, we find that the case mortality rate seems to have decreased by at least 80% in most of the US and at least 90% in most of Europe. These are much larger and faster changes than reported in empirical studies, such as the 18% decrease in mortality found for the New York City hospital system from March to August 2020 (Horwitz et al, Trends in Covid-19 risk-adjusted mortality rates, J. Hosp. Med. 2020). Our reported decreases surprisingly do not have strong correlations to other model parameters (such as contact rate) or other standard state/national metrics such as population density, GDP, and median age. Almost all the decreases occurred between mid-April and mid-June, which unexpectedly corresponds to the time when many state and national lockdowns were released resulting in surges of new cases. Several plausible causes for this drop are examined, such as improvements in treatment, face mask wearing, a new virus strain, and potentially changing demographics of infected patients, but none are overwhelmingly convincing given the currently available evidence.

q-bio.PE↗

arXiv2020

US faces endemic Covid-19 infections and deaths; ways to stop the pandemic

A new epidemic model for Covid-19 has been constructed and simulated for eight US states. The coefficients for this model, based on seven coupled differential equations, are carefully evaluated against recorded data on cases and deaths. These projections reveal that Covid-19 will become endemic, spreading for more than two years. If stay-at-home orders are relaxed, most states may experience a secondary peak in 2021. The number of Covid-19 deaths could have been significantly lower in most states that opened up, if lockdowns had been maintained. Additionally, our model predicts that decreasing contact rate by 10%, or increasing testing by approximately 15%, or doubling lockdown compliance (from the current $\sim$ 15%) will eradicate infections in Texas within a year. Applied to the entire US, the predictions based on the current situation indicate about 11 million total infections (including undetected), 8 million cumulative confirmed cases, and 630,000 cumulative deaths by November 1, 2020.

q-bio.PE↗

arXiv2020

A predictive model for Covid-19 spread applied to eight US states

A compartmental epidemic model is proposed to predict the Covid-19 virus spread. It considers: both detected and undetected infected populations, medical quarantine and social sequestration, release from sequestration, plus possible reinfection. The coefficients in the model are evaluated by fitting to empirical data for eight US states: Arizona, California, Florida, Illinois, Louisiana, New Jersey, New York State, and Texas. Together these states make up 43% of the US population; some of these states appear to have handled their initial outbreaks well, while others appear to be emerging hotspots. The evolution of Covid-19 is fairly similar among the states: variations in contact and recovery rates remain below 5%; however, not surprisingly, variations are larger in death rate, reinfection rate, stay-at-home effect, and release rate from sequestration. The results reveal that outbreaks may have been well underway in several states before first detected and that California might have seen more than one influx of the pandemic. Our projections based on the current situation indicate that Covid-19 will become endemic, spreading for more than two years. Should states fully relax stay-at-home orders, most states may experience a secondary peak in 2021. If lockdowns had been kept in place, the number of Covid-19 deaths so far could have been significantly lower in most states that opened up. Additionally, our model predicts that decreasing contact rate by 10%, or increasing testing by approximately 15%, or doubling lockdown compliance (from the current $\sim$ 15% to $\sim$ 30%) will eradicate infections in the state of Texas within a year. Extending our fits for all of the US states, we predict about 11 million total infections (including undetected), 8 million cumulative confirmed cases, and 630,000 cumulative deaths by November 1, 2020.

q-bio.PE↗

arXiv2012

The head leads the body: a curvature-based kinematic description of C. elegans

Caenorhabditis elegans, a free-living soil nematode, propels itself by producing undulatory body motion and displays a rich variety of body shapes and trajectories during its locomotion in complex environments. Here we show that the complex shapes and trajectories of C. elegans have a simple analytical description in curvature representation. Our model is based on the assumption that the curvature wave is generated in the head segment of the worm body and propagates backwards. We have found that a simple harmonic function for the curvature can capture multiple worm shapes during the undulatory movement. The worm body trajectories can be well represented in terms of piecewise sinusoidal curvature with abrupt changes in amplitude, wavevector, and phase.

physics.bio-ph↗

arXiv2005

Pattern scaling in the axial segregation of granular materials in a rotating tube

Granular mixtures frequently segregate by grain size along the axis of partially-filled, horizontal, rotating tubes. When segregation approaches saturation at the surface, a well-defined pattern of bands with wavelength $λ$ emerges. The long-term dynamics of the pattern involves a much slower coarsening process. We characterized the initial saturated wavelength $λ$ as a function of the diameter of the tube $D$ for a filling fraction of 30 %, for $1.9 {\rm cm} \leq D \leq 11.5 {\rm cm}$. We also studied the initial growth-rate of the bands as $D$ varies. We find that $λ/D$ is not constant, but rather increases rapidly for small $D$. The growth-rate of bands decreases with smaller $D$ and segregation is suppressed completely for sufficiently small $D$. These relatively simple features are not captured by any of the existing models of axial segregation.

cond-mat.soft↗

arXiv2004

Subdiffusive axial transport of granular materials in a long drum mixer

Granular mixtures rapidly segregate radially by size when tumbled in a partially filled horizontal drum. The smaller component moves toward the axis of rotation and forms a buried core, which then splits into axial bands. Models have generally assumed that the axial segregation is opposed by diffusion. Using narrow pulses of the smaller component as initial conditions, we have characterized axial transport in the core. We find that the axial advance of the segregated core is well described by a self-similar concentration profile whose width scales as $t^α$, with $α\sim 0.3 < 1/2$. Thus, the process is subdiffusive rather than diffusive as previously assumed. We find that $α$ is nearly independent of the grain type and drum rotation rate within the smoothly streaming regime. We compare our results to two one-dimensional PDE models which contain self-similarity and subdiffusion; a linear fractional diffusion model and the nonlinear porous medium equation.

cond-mat.soft↗