arXiv subjects

Kushagra Tiwari

Publications and source records attributed to Kushagra Tiwari.

4 recordsLinked to original sources

arXiv2026

Socio-Spatial Patterns of Suicide Mortality in the United States

Suicide causes more than 49,000 deaths annually in the United States, 55% involving firearms. Suicide mortality varies substantially across US counties, but the role of large-scale social networks remains underexplored. We combine county-level suicide mortality data for 2010-2022 with the Facebook Social Connectedness Index (SCI) and measures of exposure to Extreme Risk Protection Orders (ERPOs). In population-weighted two-way fixed effects models adjusting for sociodemographic and economic characteristics, COVID-19, drug-overdose and alcohol-related mortality, poor mental health days, state firearm policies, and geographical proximity, a one-standard-deviation increase in the SCI-weighted suicide mortality rate of socially connected counties was associated with 2.47 additional deaths per 100,000 residents in the focal county (95% CI [0.97, 4.00]). A one-standard-deviation increase in ERPO social exposure was associated with 0.266 fewer deaths per 100,000 (coefficient -0.266; 95% CI [-0.403, -0.128]) after adjustment for geographical proximity and state-by-year fixed effects. The social-proximity association persisted under alternative neighborhood definitions and spatial-error models, and subgroup analyses showed heterogeneity by age. These findings show that both suicide mortality and the lower mortality associated with exposure to firearm-restriction policies are patterned along inter-county social ties beyond what is explained by geographical proximity alone.

stat.AP↗

arXiv2026

Tuning Cross-stream Lift in Viscoelastic Shear: Distinct Hydrodynamic Signatures of Force-bearing and Force-free Mechanisms

We investigate the lift and drag corrections acting on a particle suspended in a planar viscoelastic shear flow when the particle is tuned to translate relative to the flow by an external mechanism. A cross-stream lift force arises when particle is driven in streamwise direction; we find that the nature of the driving mechanism dictates the lift direction: force-bearing mechanisms (such as gravity acting on non-neutrally buoyant particles) and force-free mechanisms (such as electrophoresis) generate lift forces of opposite sign. By explicitly deriving the first-order fields and stresses, we demonstrate that this reversal originates from distinct hydrodynamic disturbances induced by each mechanism, which produce qualitatively different polymeric stress distributions. This analytical result is further verified through an independent derivation using the reciprocal theorem. Further, we find that driving the particle in the gradient direction gives rise to a streamwise drag correction that is of the same sign for both mechanisms. Beyond microfluidic particle manipulation, these results have broader implications for understanding the locomotion of microswimmers in viscoelastic shear flows, where distinct force-free propulsion mechanisms are expected to generate unique force and torque modifications.

physics.flu-dyn↗

arXiv2025

On the influence of electrolytic gradient orientation on phoretic transport in dead-end pores

Electrolytic diffusiophoresis refers to directional migration of colloids due to interfacial forces that develop in response to local electrolytic concentration ($c$) gradients. This physicochemical transport provides an efficient alternative in numerous microscale applications where advection-induced transport is infeasible. Phoretic withdrawal and injection in dead-end pores can be controlled by orienting salt gradients into or out of the pore; however, the extent to which this orientation influences spatiotemporal transport patterns is not thoroughly explored. In this study, we find that it has a significant influence: colloidal withdrawal in solute-out mode ($β=c_\infty/c_{\text{pore}}<1$) is faster and shallower, whereas the solute-in mode enables deeper withdrawal. Similarly, solute-out injection features rapidly propagating wavefronts, whereas the solute-in mode ($β>1$) promotes uniform and gradual injection. Each mode's transport is found to evolve and persist over different time scales. We characterize the performance of these modes and find that while persistence of the solute-out mode strengthens with a growing electrolytic gradient [$\sim \ln(β^{-0.4})$], solute-in mode diminishes and eventually its persistence is insensitive to $β$. We also incorporate the variable mobility model to examine the impact of large zeta potentials, which intensifies the transport of solute-out mode further and weakens the solute-in mode. Additionally, we investigate how osmotic flows of the two modes affect injection and withdrawal patterns. We find that osmosis-induced mixing can counterintuitively inhibit injection effectiveness in solute-out mode. These insights bring attention to the distinctions between different phoretic transport modes and contribute to the rational design and setup of electrolytic gradients in numerous microscale applications.

cond-mat.soft↗

arXiv2024

Measuring Network Dynamics of Opioid Overdose Deaths in the United States

The US opioid overdose epidemic has been a major public health concern in recent decades. There has been increasing recognition that its etiology is rooted in part in the social contexts that mediate substance use and access; however, reliable statistical measures of social influence are lacking in the literature. We use Facebook's social connectedness index (SCI) as a proxy for real-life social networks across diverse spatial regions that help quantify social connectivity across different spatial units. This is a measure of the relative probability of connections between localities that offers a unique lens to understand the effects of social networks on health outcomes. We use SCI to develop a variable, called "deaths in social proximity", to measure the influence of social networks on opioid overdose deaths (OODs) in US counties. Our results show a statistically significant effect size for deaths in social proximity on OODs in counties in the United States, controlling for spatial proximity, as well as demographic and clinical covariates. The effect size of standardized deaths in social proximity in our cluster-robust linear regression model indicates that a one-standard-deviation increase, equal to 11.70 more deaths per 100,000 population in the social proximity of ego counties in the contiguous United States, is associated with thirteen more deaths per 100,000 population in ego counties. To further validate our findings, we performed a series of robustness checks using a network autocorrelation model to account for social network effects, a spatial autocorrelation model to capture spatial dependencies, and a two-way fixed-effect model to control for unobserved spatial and time-invariant characteristics. These checks consistently provide statistically robust evidence of positive social influence on OODs in US counties.

cs.SI↗