Benefit Estimation of Water Quality Improvements in Bagmati River Using Choice Modeling

Environmental Economics and Policy,

Knowledge, Information, and Water Treatment Behavior of Residents in the Kathmandu Valley, Nepal

Access to safe drinking water plays a crucial role in the overall social and economic development of a community. Unsafe water delivered to household taps increases the risks of waterborne diseases and threatens population health. Consumers can adopt a number of averting behaviors such as filtering or boiling their water. While these approaches are effective in reducing the likelihood of contracting a waterborne disease, not all households treat their water. Given this, it is important to develop a better understanding of factors that influence water treatment behavior. In this paper, we examine determinants of water treatment behavior using survey data (N=1200) from Kathmandu, Nepal. In particular, this paper focuses on the impacts of knowledge, exposure to information, and community participation on drinking water treatment behavior. Previous research has found that income, education level, awareness, and exposure to media are major factors that impact the individual-level decision to treat water before using it. We contribute to this literature by explicitly examining how knowledge about waterborne diseases, exposure to water quality information campaigns, and participation in community organizations impact drinking water treatment behavior. The results from probit regression analyses suggest that either a one percentage increase in the knowledge index or community participation index both increase the likelihood of utilizing drinking water treatment methods by about 0.17 percentage points. Households connected to the distribution system are 31 percentage points more likely to treat water compared to those that are not connected to the system. Multinomial results indicate that wealthier households use more than one treatment method

Towards 6G-V2X: Aggregated RF-VLC for Ultra-Reliable and Low-Latency Autonomous Driving

We are witnessing a transition to a new era of mobility where pervasively connected (semi-)autonomous cars will deliver significantly improved safety, traffic efficiency, and travel experiences. A diverse set of advanced vehicular use cases such as platooning, remote driving, and fully autonomous driving will be made possible by building on emerging sixth-generation (6G) wireless networks. Among many disruptive 6G wireless technologies, the principal objective of this paper is to introduce the potential benefits of the hybrid integration of Visible Light Communication (VLC) and Radio Frequency (RF) based Vehicleto- Everything (V2X) communication systems. We examine the impact of interference as well as various meteorological phenomena viz. rain, fog and dry snow, on the proposed Link aggregated (LA) aided hybrid RF-VLC V2X systems. The simulation results suggest that our proposed LA-aided hybrid RF-VLC V2X systems have the potential to achieve a high level of reliability (estimated at approximately 99.999%) and low latency (potentially less than 1 ms) within a range of up to 200 m, even in scenarios affected by interference and adverse meteorological conditions. To stimulate future research in the hybrid RF- VLC V2X area, we also highlight the potential challenges and research directions

Heterogeneous Visible Light and Radio Communication for Improving Safety Message Dissemination at Road Intersection

Visible light communication (VLC) has recently emerged as an affordable and scalable technology supporting very high data rates for short range vehicle-to-vehicle (V2V) communication. In this work, we advocate the use of vehicular-VLC (V-VLC) for basic safety messages (BSMs) dissemination in lieu of conventional vehicular radio frequency (V-RF) communication in road intersection applications, where the reception performance is affected by interference from the concurrent transmissions of other vehicles. We make use of stochastic geometry to characterize the interference from the same lane as well as the perpendicular lane for various network configurations, i.e., standalone V-VLC, stand-alone V-RF and hybrid V-VLC/V-RF network. Specifically, by modelling the interfering vehicles’ locations as a spatial Poisson point process (PPP), we are able to capture a static two-dimensional road geometry as well as the impact of interference due to vehicles clustering in the vicinity of road intersection in terms of outage probability and throughput. In addition to above, the performance of spatial ALOHA and carrier sense multiple access with collision avoidance medium access control (CSMA/CA MAC) protocol for standalone V-VLC, standalone V-RF and hybrid V-VLC/V-RF network configuration for relaying BSMs at road intersection is also compared. The performance metrics such as delay outage rate (DOR) and information outage rate (IOR) are utilized to investigate the impact of latency associated with various network configurations. Our numerical results reveal that our proposed hybrid V-VLC/V-RF leads to significant improvement in terms of outage performance, throughput and latency as compared to stand-alone V-VLC or stand-alone V-RF network

Estimating Population Attribute Values in a Table: “Get Me Started in” Iterative Proportional Fitting

Iterative proportional fitting (IPF) is a technique that can be used to adjust a distribution reported in one data set by totals reported in others. IPF is used to revise tables of data where the information is incomplete, inaccurate, outdated, or a sample. Although widely applied, the IPF methodology is rarely presented in a way that is accessible to nonexpert users. This article fills that gap through discussion of how to operationalize the method and argues that IPF is an accessible and transparent tool that can be applied to a range of data situations in population geography and demography. It offers three case study examples where IPF has been applied to geographical data problems; the data and algorithms are made available to users as supplementary material

Collaborative care model for depression in rural Nepal: A mixed-methods implementation research study

Introduction Despite carrying a disproportionately high burden of depression, patients in low-income countries lack access to effective care. The collaborative care model (CoCM) has robust evidence for clinical effectiveness in improving mental health outcomes. However, evidence from real-world implementation of CoCM is necessary to inform its expansion in low-resource settings. Methods We conducted a 2-year mixed-methods study to assess the implementation and clinical impact of CoCM using the WHO Mental Health Gap Action Programme protocols in a primary care clinic in rural Nepal. We used the Capability Opportunity Motivation-Behaviour (COM-B) implementation research framework to adapt and study the intervention. To assess implementation factors, we qualitatively studied the impact on providers' behaviour to screen, diagnose and treat mental illness. To assess clinical impact, we followed a cohort of 201 patients with moderate to severe depression and determined the proportion of patients who had a substantial clinical response (defined as ≥50% decrease from baseline scores of Patient Health Questionnaire (PHQ) to measure depression) by the end of the study period. Results Providers experienced improved capability (enhanced self-efficacy and knowledge), greater opportunity (via access to counsellors, psychiatrist, medications and diagnostic tests) and increased motivation (developing positive attitudes towards people with mental illness and seeing patients improve) to provide mental healthcare. We observed substantial clinical response in 99 (49%; 95% CI: 42% to 56%) of the 201 cohort patients, with a median seven point (Q1:-9, Q3:-2) decrease in PHQ-9 scores (p<0.0001). Conclusion Using the COM-B framework, we successfully adapted and implemented CoCM in rural Nepal, and found that it enhanced providers' positive perceptions of and engagement in delivering mental healthcare. We observed clinical improvement of depression comparable to controlled trials in high-resource settings. We recommend using implementation research to adapt and evaluate CoCM in other resource-constrained settings to help expand access to high-quality mental healthcare

A Connectivity-Driven Development Strategy for Nepal: From a Landlocked to a Land-Linked State

Nepal's lackluster economic performance during the post-conflict period (that is, after November 2006) has been driven by remittances from the export of labor services and the improved performance of the agricultural sector, which is still very much weather dependent. The authors make the case for a connectivity-driven development strategy for the country. They argue that improved connectivity within Nepal and cross-border connectivity with its neighbors in South Asia, the Association of Southeast Asian Nations (ASEAN), and the People's Republic of China (PRC) that are converting Nepal from a landlocked into a land-linked state, could be important "engines of growth" for the country. It is argued that such a development strategy is not a new one for Nepal as in the past the country was strategically located on the Southwestern Silk Road (SSR). A number of factors have revived the case for making Nepal a land-linked state in Asia. Nepal has adopted a multi-track approach to promoting regional cooperation and integration in connectivity with its neighbors. But a lot more needs to be done, especially in the context of the difficult political situation in the country, and donors have an important role to play in this regard. Ten priority projects to convert Nepal into a land-linked state are identified, but a detailed impact analysis of these projects is beyond the scope of this paper

Do Governance Indicators Explain Development Performance? A Cross-Country Analysis

The central question addressed by this study is whether countries with above-average governance grew faster than countries with below-average governance. Using the World Bank's worldwide governance indicators to measure governance performance, it examines whether a country with governance "surplus" in a given base year (1998) grew faster on average in a subsequent period (1998- 2011) than a country with governance "deficit." Governance is defined in several dimensions, including government effectiveness, political stability, control of corruption and regulatory quality, voice and accountability, and rule of law. The study finds that government effectiveness, political stability, control of corruption and regulatory quality all have a more significant positive impact on country growth performance than voice and accountability and rule of law. Developing Asian countries with a surplus in government effectiveness, regulatory quality and corruption control are observed to grow faster than those with a deficit in these indicators - up to 2 percentage points annually, while Middle East and North African countries with a surplus in political stability, government effectiveness, and corruption control are observed to grow faster than those with a deficit in these indicators by as much as 2.5 percentage points annually. Good governance is associated with both a higher level of per capita GDP as well as higher rates of GDP growth over time. This suggests that good governance, while important in and of itself, can also help in improving a country's economic prospects