Essays on Spatial Econometrics Application in Study of Conflict and Economic Activity

Spatial interaction and the locational structure between observations as well as availability of satellite derived data has meant a richer and more exhaustive exploration of topics relevant in development topics, particularly in areas of subnational economic activity and conflict. This research leverages thus spatial econometric techniques to dynamically decompose impacts from socio-economic determinants on conflict incidence (with setting in Sub-Saharan Africa). Later I also present a statistical framework (based on extension of Henderson’s approach (2012)) to augment official income figures at district / county level with multiple satellite derived signals, with specific context given to developing countries. In the first chapter, I look at the relationship and interplay between conflict intensity, foreign aid (in the form of geocoded World Bank Aid allocations) and economic activity (proxied by Sum of Lights, SOL, as gathered from satellite night lights sources), at the sub-national (provincial) level in Sub-Saharan Africa over 2000-13, using a Panel Vector Autoregression approach based on a multi-stage Continuous Updated Estimator GMM estimation strategy, and incorporating spatial effects amongst the concerned variables as well as in the model disturbances. I then decompose the derived impulse responses from this system into spatial direct and indirect responses. As per the findings, conflict intensity reacts (largely) positively to negative shocks in economic activity and World Bank Aid, with evidence of persistent spillover effects stemming from these aforementioned shocks. In the second chapter, following on from the first chapter, I specifically look at the impact of income inequality, derived from the spatial distribution of night lights raster and population raster data, on conflict incidence in Sub-Saharan Africa, using a Spatial Exponential Feedback Model approach (as opposed to the more standard Linear Feedback Model in the literature), based on Empirical Likelihood estimation. I also derive spatial direct and indirect impacts from changes in inequality, with direct responses fully dying away within 5 years while indirect response has an extent of in-built persistence. Thus, this chapter adds to the existing literature on conflict and income inequality by exploring the spatial dimension of the dynamics at play. Lastly, in the third chapter, a modified statistical method is presented, based on Henderson et al. (2012) where he looked at augmenting official national income growth measures by using satellite data on night lights. In the approach as presented here, a Method of Moments approach is introduced so as use multiple satellite signals, in addition to night lights, to augment income growth data at sub-national level. The two other signals are spread of non-vegetative cover and urban land cover data (derived from European Space Agency Climate Change Initiative Land Cover raster products). Three countries were studied with this approach: India, Indonesia and the U.S

Improving Dose-Response Correlations for Locally Advanced NSCLC Patients Treated with IMRT or PSPT

The standard of care for locally advanced non-small cell lung cancer (NSCLC) is concurrent chemo-radiotherapy. Despite recent advancements in radiation delivery methods, the median survival time of NSCLC patients remains below 28 months. Higher tumor dose has been found to increase survival but also a higher rate of radiation pneumonitis (RP) that affects breathing capability. In fear of such toxicity, less-aggressive treatment plans are often clinically preferred, leading to metastasis and recurrence. Therefore, accurate RP prediction is crucial to ensure tumor coverage to improve treatment outcome. Current models have associated RP with increased dose but with limited accuracy as they lack spatial correlation between accurate dose representation and quantitative RP representation. These models represent lung tissue damage with radiation dose distribution planned pre-treatment, which assumes a fixed patient geometry and inevitably renders imprecise dose delivery due to intra-fractional breathing motion and inter-fractional anatomy response. Additionally, current models employ whole-lung dose metrics as the contributing factor to RP as a qualitative, binary outcome but these global dose metrics discard microscopic, voxel-(3D pixel)-level information and prevent spatial correlations with quantitative RP representation. To tackle these limitations, we developed advanced deformable image registration (DIR) techniques that registered corresponding anatomical voxels between images for tracking and accumulating dose throughout treatment. DIR also enabled voxel-level dose-response correlation when CT image density change (IDC) was used to quantify RP. We hypothesized that more accurate estimates of biologically effective dose distributions actually delivered, achieved through (a) dose accumulation using deformable registration of weekly 4DCT images acquired over the course or radiotherapy and (b) the incorporation of variable relative biological effectiveness (RBE), would lead to statistically and clinically significant improvement in the correlation of RP with biologically effective dose distributions. Our work resulted in a robust intra-4DCT and inter-4DCT DIR workflow, with the accuracy meeting AAPM TG-132 recommendations for clinical implementation of DIR. The automated DIR workflow allowed us to develop a fully automated 4DCT-based dose accumulation pipeline in RayStation (RaySearch Laboratories, Stockholm, Sweden). With a sample of 67 IMRT patients, our results showed that the accumulated dose was statistically different than the planned dose across the entire cohort with an average MLD increase of ~1 Gy and clinically different for individual patients where 16% resulted in difference in the score of the normal tissue complication probability (NTCP) using an established, clinically used model, which could qualify the patients for treatment planning re-evaluation. Lastly, we associated dose difference with accuracy difference by establishing and comparing voxel-level dose-IDC correlations and concluded that the accumulated dose better described the localized damage, thereby a closer representation of the delivered dose. Using the same dose-response correlation strategy, we plotted the dose-IDC relationships for both photon patients (N = 51) and proton patients (N = 67), we measured the variable proton RBE values to be 3.07–1.27 from 9–52 Gy proton voxels. With the measured RBE values, we fitted an established variable proton RBE model with pseudo-R2 of 0.98. Therefore, our results led to statistically and clinically significant improvement in the correlation of RP with accumulated and biologically effective dose distributions and demonstrated the potential of incorporating the effect of anatomical change and biological damage in RP prediction models

A Systems Approach for River and River Basin Restoration

Communities increasingly find that the water quality, water levels, or some other resource indicator in their river basins do not meet their expectations. This discrepancy between the desired and actual state of the resource leads to efforts in river basin restoration. River basins are complex systems, and too often, restoration efforts are ineffective due to a lack of understanding of the purpose of the system, defined by the system structure and function. The river basin structure includes stocks (e.g., water level or quality), inflows (e.g., precipitation or fertilization), outflows (e.g., evaporation or runoff), and positive and negative feedback loops with delays in responsiveness, all of which function to change or stabilize the state of the system (e.g., the stock of interest, such as water level or quality). External drivers on this structure, together with goals and rules, contribute to how a river basin functions. This book reviews several new research projects to identify and rank the twelve most effective leverage points to address discrepancies between the desired and actual state of the river basin system. This book demonstrates that river basin restoration is most likely to succeed when we change paradigms rather than try to change the system elements, as the paradigm will establish the system goals, structure, rules, delays, and parameters

Theranostics of the Brain

Glioblastoma is a heterogeneous disease such that the receptors expressed vary based on tumor location. Working with Nemucore Medical Innovations, Inc., theranostic nanoemulsions were designed and manufactured to combat Glioblastoma and other brain diseases. Engineered targeting ligands incorporated in the nanoemulsions assisted in delivery to specific regions. Magnetic Resonance Imaging determined the bio-distribution in healthy rats across the Blood-Brain Barrier. Statistical analysis was completed with T1 MRI data for 174 defined regions. A 3-dimensional heat map program was created to integrate MRI imaging and statistical analysis. In conclusion, data demonstrates targeting ligands on the nanoemulsions alter pharmacodynamics in rat brains, shown by a fully integrated imaging system