Nelofar Kureshi

@article{nokey,

title = {Longitudinal Trends of Depression in Traumatic Brain Injury: The Role of Individual Heterogeneity in Clinical Prediction},

author = {Nelofar Kureshi and David B. Clarke and Abraham Nunes and Cindy Feng and Syed Sibte Raza Abidi },

doi = {https://doi.org/10.1007/s11469-026-01668-6},

year  = {2026},

date = {2026-05-08},

journal = {International Journal of Mental Health and Addiction},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Investigating the influence of socioeconomic deprivation on spatial patterns of traumatic brain injuries through Bayesian spatial modeling},

author = {Nelofar Kureshi and Syed Sibte Raza Abidi and David B. Clarke and Weiping Zeng and Cindy Feng},

doi = {https://doi.org/10.1007/s10708-024-11239-8},

year  = {2024},

date = {2024-11-01},

journal = {GeoJournal},

volume = {89},

number = {238},

issue = {6},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Risk stratification of new-onset psychiatric disorders using clinically distinct traumatic brain injury phenotypes},

author = {Nelofar Kureshi and Abraham Nunes and Cindy Feng and David B Clarke and Syed Sibte Raza Abidi},

doi = {https://doi.org/10.1186/s13690-024-01346-w},

year  = {2024},

date = {2024-08-02},

journal = {Archives of Public Health},

volume = {82},

issue = {1},

pages = {116},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Spatial hotspots and sociodemographic profiles associated with traumatic brain injury in Nova Scotia},

author = {Nelofar Kureshi and Syed Sibte Raza Abidi and David B Clarke and Weiping Zeng and Cindy Feng},

doi = {https://doi.org/10.1089/neu.2023.0257},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-01},

journal = {Journal of neurotrauma},

volume = {41},

issue = {7-8},

pages = {844-861},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Spatial Hotspots and Sociodemographic Profiles Associated with Traumatic Brain Injury in Nova Scotia},

author = {Nelofar Kureshi and Syed Sibte Raza Abidi and David B Clarke and Weiping Zeng and Cindy Feng},

doi = {10.1089/neu.2023.0257},

year  = {2023},

date = {2023-12-04},

urldate = {2023-12-04},

journal = {Journal of Neurotrauma},

abstract = {Traumatic brain injury (TBI) is a leading cause of death and disability, primarily caused by falls and motor vehicle collisions. While many TBIs are preventable, there is a notable lack of studies exploring the association of geographically defined TBI hotspots with social deprivation. Geographic information systems (GIS) can be used to identify at-risk neighborhoods (hotspots) for targeted interventions. This study aims to determine the spatial distribution of TBI by major causes and to explore the sociodemographic and economic characteristics of TBI hotspots and coldspots in Nova Scotia. Patient data for TBIs from 2003 to 2019 were obtained from the Nova Scotia Trauma Registry. Residential postal codes were geocoded and assigned to Dissemination Areas (DA). Area-based risk factors and deprivation status (residential instability [RI], economic dependency [ED], ethnocultural composition [EC], and situational vulnerability [SV]) from the national census data were linked to DAs. Spatial autocorrelation was assessed using Moran’s I, and hotspot analysis was performed using Getis-Ord Gi* statistic. Differences in risk factors between hot and cold spots were evaluated using the Mann-Whitney U-test for numerical variables and the Chi-square test or Fisher’s Exact test for categorical variables. A total of 5394 TBI patients were eligible for inclusion in the study. The distribution of hotspots for falls exhibited no significant difference between urban and rural areas (p=0.71). Conversely, hotspots related to violence were predominantly urban (p=0.001), while hotspots for motor vehicle collisions (MVCs) were mostly rural (p<0.001). Distinct dimensions of deprivation were associated with falls, MVC, and violent hotspots. Fall hotspots were significantly associated with areas characterized by higher RI (p <0.001) and greater ethnocultural diversity (p <0.001). Conversely, the same domains exhibited an inverse relationship with MVC hotspots; areas with low RI and ethnic homogeneity displayed a higher proportion of MVC hotspots. ED and SV exhibited a strong gradient with MVC hotspots; the most deprived quintiles displayed the highest proportion of MVC hotspots compared to coldspots (ED; p = 0.002, SV; p < 0.001). Areas with the highest levels of ethnocultural diversity were found to have a significantly higher proportion of violence-related hotspots compared to coldspots (p = 0.005). This study offers two significant contributions to spatial epidemiology. Firstly, it demonstrates the distribution of TBI hotspots by major injury causes using the smallest available geographical unit. Secondly, we disentangle the various pathways through which deprivation impacts the risk of main mechanisms of TBI. These findings provide valuable insights for public health officials to design targeted injury prevention strategies in high-risk areas.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}