Increase Service Availability Research Articles

Understanding experiences, unmet needs and priorities related to post-stroke aphasia care: stage one of an experience-based co-design project

ObjectivePeople with post-stroke aphasia (language/communication impairment) and their supporters report mixed satisfaction with stroke and aphasia care. To date, however, their journey of care and the key service interactions that...

Enhancing service availability and resource deployment in IoT using a shared service replication method

In many real-world contexts, the Internet of Things (IoT) is valued for its capacity to facilitate the smooth operation of interoperable applications and services. It is critical to ensure the accessibility and replication of IoT resources to improve the agility of these applications. As a solution, the Network Function Virtualization (NFV) paradigm is embedded into the IoT design to leverage information from various endpoint applications better and maximize resource utilization. In this study, the Shared Replication Augmenting Method (SRAM) is proposed to increase resource usage in underutilized NFVs and maintain service availability simultaneously. The regressive decision-making learning used by SRAM enables the detection of NFV needs for data and application portability across various real-time use cases. This regression method can uncover data needs and their causes, allowing for prompt answers and more efficient use of available resources. The suggested SRAM technique dynamically modifies the procedure while considering computation-less function allocations, making it suitable for various interoperable applications. It distributes root-to-service virtualization and availability based on historical use and data replication. Therefore, SRAM improves resource usage by 7.09 % with no increase in latency or delays. It also increases service availability by 10.4 %, reduces latency by 11.89 %, eliminates backlogs by 11.1 %, and reduces data repetition by 8.97 %. This study enhances resource consumption and productivity in IoT settings by offering SRAM as a viable solution. The study's results prove its potential to reduce the occurrence of replication, delay, and queues while raising the availability of services.

FPGA Live Migration of Content‐Based Anonymization Mechanism with Network Consistency

In smart communities, data are aggregated, and various services are provided based on it. When considering the optimization of service delivery through cooperative processing between the edge and the cloud in smart communities, it is essential to realize network transparent edge services due to the constraints of not touching end devices in order to improve user convenience and additional cost reduction. Moreover, considering the minimization of service provision and service delivery latency at the edge, it is desirable to use field‐programmable gate arrays (FPGAs), which have lower power consumption, lower latency, and higher throughput than conventional processors. Additionally, to advance towards even lower latency, the distribution of processing load is important, and service migration is necessary for this purpose. Service migration is generally used to increase service availability, and even for edge services, service migration is important because the distribution of processing and the location where the service should be provided changes over time due to user mobility. When considering network transparency, service migration should be performed on the communication path between the end device and the cloud. Furthermore, to enhance service transparency, it is essential to maintain communication consistency for continuous service provision and minimize service downtime. Therefore, this study proposes a migration mechanism with FPGAs to satisfy these requirements. As an example of a real application, we target a network‐transparent data anonymization application to protect the privacy of data providers and evaluate the proposed architecture based on the reality of latency and other factors. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

MetaVSID: A Robust Meta-Reinforced Learning Approach for VSI-DDoS Detection on the Edge

The explosive growth of end devices that generate massive amounts of data requires close-proximity computing resources for processing at the network’s edge. Having geographic distributions and limited resources of edge nodes or servers opens several doors for attackers to exploit them primarily to the detriment of deployed services; one of the recent attacks is Very Short Intermittent Distributed Denial of Services (VSI-DDoS). Deep learning-based models have been developed to detect and mitigate such attacks but cause the degrading quality of models due to covariate shifts when deployed in real-world environments. Therefore, we propose a new approach, called MetaVSID, to detect VSI-DDoS attacks in edge clouds using meta-reinforcement learning followed by ensemble learning to increase the robustness of the model in detecting VSI-DDoS attacks early. The proposed model can capture dynamic patterns of VSI-DDoS attacks, from which it identifies manipulated services and increase service availability when covariate shifts at deployment time. We carry out extensive experiments to validate the MetaVSID using both testbed and benchmark datasets. Via the meta-reinforced downsampling process, the proposed method improves sample efficiency, leading to cost-effective policies. Moreover, the optimized policies are generalized to adapt to dynamic changes in the training distribution. Our experimental results demonstrate that MetaVSID stably achieves better performance in multiple evaluation settings with the difference from baseline models from 1.5% to 7.5% in terms of AUC for both VSI-DDoS and DDoS detection, especially under covariate shift settings.

Consumer housing choices among residents living in wooden multi-storey buildings

Wooden multi-storey construction (WMC) offers an alternative building solution for urban consumers seeking a low-carbon, sustainable lifestyle yet, the literature on consumer experiences in newly constructed WMC-apartments is sparse. This exploratory study develops an understanding about consumer choices with newly built WMC-apartments through thematic interviews of residents and property managers in five cities across Finland and Sweden. Contents analysis reveals that neither building material nor sustainability triggered the residents’ initial interest in the new apartment. Residents found WMC appealing but traditional housing choice criteria (e.g. location, floor plan and affordability) guided the ultimate purchasing decision. Notwithstanding, residents expressed that the newly developed neighbourhoods suffered from limited services but trusted that future long-term development would increase service availability. Wood material was experienced as mainly positive and was assessed together with overall aesthetics, sustainability and durability aspects of the building. Residents trusted that the builders considered the apartment’s sustainability criteria during construction (e.g. material durability and resistance to changing climate conditions).

Treating opioid use disorder in veterans with co-occurring substance use: a qualitative study with buprenorphine providers in primary care, mental health, and pain settings

BackgroundMost people with opioid use disorder (OUD) have co-occurring substance use, which is associated with lower receipt of OUD medications (MOUD). Expanding MOUD provision and care linkage outside of substance use disorder (SUD) specialty settings is a key strategy to increase access. Therefore, it is important to understand how MOUD providers in these settings approach care for patients with co-occurring substance use. This qualitative study of Veterans Health Administration (VA) clinicians providing buprenorphine care in primary care, mental health, and pain settings aimed to understand (1) their approach to addressing OUD in patients with co-occurring substance use, (2) perspectives on barriers/facilitators to MOUD receipt for this population, and (3) support needed to increase MOUD receipt for this population.MethodsWe interviewed a purposive sample of 27 clinicians (12 primary care, 7 mental health, 4 pain, 4 pharmacists) in the VA northwest network. The interview guide assessed domains of the Tailored Implementation for Chronic Diseases Checklist. Interviews were transcribed and qualitatively analyzed using inductive content analysis.ResultsParticipants reported varied approaches to identifying co-occurring substance use and addressing OUD in this patient population. Although they reported that this topic was not clearly addressed in clinical guidelines or training, participants generally felt that patients with co-occurring substance use should receive MOUD. Some viewed their primary role as providing this care, others as facilitating linkage to OUD care in SUD specialty settings. Participants reported multiple barriers and facilitators to providing buprenorphine care to patients with co-occurring substance use and linking them to SUD specialty care, including provider, patient, organizational, and external factors.ConclusionsEfforts are needed to support clinicians outside of SUD specialty settings in providing buprenorphine care to patients with co-occurring substance use. These could include clearer guidelines and policies, more specific training, and increased care integration or cross-disciplinary collaboration. Simultaneously, efforts are needed to improve linkage to specialty SUD care for patients who would benefit from and are willing to receive this care, which could include increased service availability and improved referral/hand-off processes. These efforts may increase MOUD receipt and improve OUD care quality for patients with co-occurring substance use.

Online-to-offline on the railway: Optimization of on-demand meal ordering on high-speed railway

On-demand meal ordering on high-speed railway is an emerging on-demand service that is becoming increasingly popular. One key challenge about this service is how to design the ordering system to maximize profits while guaranteeing timely delivery. However, few related studies have been done for this new business. In this paper, we first develop a mathematical model to optimize the existing ordering procedure, which sets a deadline for order placement. Furthermore, we propose a pre-ordering policy which cancels the order deadline but ensures timely delivery via stocking up. Considering the ambiguity in demand distributions and uncertainty in delivery time, we develop distributionally robust stochastic optimization models for both the existing and the pre-ordering procedures. Cutting-plane algorithms are developed to solve the proposed models. Computational studies on a real-world high-speed railway line in China show that our proposed new policy could simultaneously increase service availability, improve the profit, and reduce delay rate.

Assisted tree migration can reduce but not avert the decline of forest ecosystem services in Europe

European forests are facing multiple natural and anthropogenic pressures that are expected to become more severe in the next decades. Tree diversity is projected to decline in many areas across the continent. How this will affect the provision of forest services remains an open question, whose answer depends, among others, on the practical and theoretical challenges of incorporating assisted migration into climate adaptation strategies. Here, we tackle the issue by combining a large dataset of tree species occurrences, future climatic projections, and data on tree functional traits and tree-specific forest services into a novel modelling framework. We estimate that, by the end of the century and under a natural dispersal scenario, the provision of forest services would decrease on average by 15% in Europe (for RCP 4.5; 23% for RCP 8.5), and up to 52% (70% for RCP 8.5) in the Mediterranean. To explore if and how management could reduce the projected losses, we simulated a suite of alternative assisted migration strategies aimed at identifying, for each locality, the tree species communities offering the best compromise in terms of resilience to climate change and delivery of specific combinations of ecosystem services. Such strategies could reduce losses of services by 10% (15%) on average in Europe, and even increase service availability in the Alpine and Boreal regions but not in the Mediterranean, where losses will remain as high as 33% (54% for RCP 8.5). Our findings highlight how science-driven management strategies could be vital to reduce an otherwise dramatic, European-wide decline of forest services. Our results are qualitatively robust to different assumptions on future carbon emissions and related climate trajectories. That is, our simulated assisted migration strategies identify similar tree species communities under different pathways (RCP 4.5 vs RCP 8.5). This makes our approach a powerful tool for forest management, as it generates advice that is valid regardless of whether, and to what extent, human society will steer away from business-as-usual emission trajectories.

Trends in the availability of community-based home visiting services for oldest-old in China, 2005–2018

ObjectivesThis study aims to examine trends in neighbourhood availability of community-based home visiting services (CHVS) (ie, coverage by local primary healthcare providers) over time and disparities in service availability according...

Trends in the availability of community-based psychological counselling services for oldest-old in China, 2005 to 2018

BackgroundCommunity-based psychological counselling services (CPCS) is crucial for the oldest-old who often faces challenges or are reluctant to seek care at the healthcare settings. This study aims to examine trends in availability of CPCS over time and rural-urban disparities in service availability among nationwide oldest-old in China. MethodsMultiple cross-sectional data were derived from the 2005–2018 Chinese Longitudinal Health Longevity Survey. Service availability was reported by each oldest-old participant or their next-of-kins as having CPCS in one's neighborhood. We used Cochran-Armitage tests to estimate service availability trends and applied sample-weighted logistic regression models to examine its rural-urban disparities. ResultsOf 38,032 oldest-old, CPCS availability decreased from 6.7 % in 2005 to 4.8 % in 2008/2009, followed by continual increases to 13.6 % in 2017/2018. In 2017/2018, rural oldest-old's neighborhoods had no greater service availability. Oldest-old residing in the Central (6.7 %), Western (13.4 %) and Northeast China (8.1 %) were less likely to report having services locally than their Eastern counterparts (17.8 %). Oldest-old having any disability or living in the nursing homes reported having greater service availability than those without disability or living at home. LimitationService availability might have been disrupted during the COVID-19 pandemic. ConclusionsDespite the increasing service availability, as of 2017/2018, only 13.6 % oldest-old in China had reported CPCS availability. It raises concerns on the disproportionate access to and continuity of mental health care, especially for those living the Central, Western China and those living at home. Policy efforts are needed to incentivize service expansion and eliminate disparities in the service availability.

The capacity of primary healthcare facilities in Bangladesh to prevent and control non-communicable diseases

BackgroundThe rapid rise of non-communicable diseases (NCDs) has become a significant public health concern in Bangladesh. This study assesses the readiness of primary healthcare facilities to manage the following NCDs: diabetes mellitus (DM), cervical cancer, chronic respiratory diseases (CRIs), and cardiovascular diseases (CVDs).MethodsA cross-sectional survey was conducted between May 2021 and October 2021 among 126 public and private primary healthcare facilities (nine Upazila health complexes (UHCs), 36 union-level facilities (ULFs), 53 community clinics (CCs), and 28 private hospitals/clinics). The NCD-specific service readiness was assessed using the World Health Organization’s (WHO) Service Availability and Readiness Assessment (SARA) reference manual. The facilities’ readiness was assessed using the following four domains: guidelines and staff, basic equipment, diagnostic facility, and essential medicine. The mean readiness index (RI) score for each domain was calculated. Facilities with RI scores of above 70% were considered ‘ready’ to manage NCDs.ResultsThe general services availability ranged between 47% for CCs and 83% for UHCs and the guidelines and staff accessibility were the highest for DM in the UHCs (72%); however, cervical cancer services were unavailable in the ULFs and CCs. The availability of basic equipment was the highest for cervical cancer (100%) in the UHCs and the lowest for DM (24%) in the ULFs. The essential medicine for CRI was 100% in both UHCs and ULFs compared to 25% in private facilities. The diagnostic capacity for CVD and essential medicine for cervical cancer was unavailable at all levels of public and private healthcare facilities. The overall mean RI for each of the four NCDs was below the cut-off value of 70%, with the highest (65%) for CRI in UHCs but unavailable for cervical cancer in CCs.ConclusionAll levels of primary healthcare facilities are currently not ready to manage NCDs. The notable deficits were the shortage of trained staff and guidelines, diagnostic facilities, and essential medicine. This study recommends increasing service availability to address the rising burden of NCDs at primary healthcare levels in Bangladesh.

Using Geopandas for locating virtual stations in a free-floating bike sharing system

Free-floating bike-sharing systems can have a positive influence on the mobility of urban centers and developing efficient localization strategies is crucial to avoid crowding at peak times and increase service availability. Our study aims to efficiently resolve the location of virtual bike stations in a Latin American city through a geospatial data wrangling methodology that allows us to respond opportunely to the potential demand forecasted for the city. This approach is implemented in Python, and it uses the Geopandas and LocalSolver libraries to determine locations for the virtual bike stations that maximize the system coverage. The decision-making process is supported by a binary integer mathematical programming model, and the instances are built from intercity travel surveys that provide realistic data based on travel demand. The developed decision support system prototype provides a recommendation about where virtual bike stations should be located during peak hours and improve general availability by more than 37%. Moreover, when the system's users participate in the relocation of bicycles, the model can eliminate up to 80% of the CO2 emissions and nearly 50% of the operational costs associated with the relocation process.

Building power-ful health systems: the impacts of electrification on health outcomes in LMICs

ABSTRACT Critical disparities threaten health care in developing countries and hinder progress towards global development commitments. Almost a billion people and thousands of public services are not yet connected to electricity – a majority in sub-Saharan Africa. In economically fragile settings, clinics and health services struggle to gain and maintain their access to the most basic energy infrastructure. Less than 30% of health facilities in LMICs report access to reliable energy sources, truncating health outcomes and endangering patients in critical conditions. While ‘universal health coverage’ and ‘sustainable energy for all’ are two distinct SDGs with their respective targets, this review challenges their disconnect and inspects their interdependence in LMICs. To evaluate the impact of electrification on healthcare facilities in LMICs, this systematic review analysed relevant publications up to March 2021, using MEDLINE, Embase, Scopus, CENTRAL, clinicaltrials.gov and CINAHL. Outcomes captured were in accordance with the WHO HHFA modules. A total of 5083 studies were identified, 12 fulfilled the inclusion criteria of this review – most were from Africa, with the exception of two studies from India and one from Fiji. Electrification was associated with improvements in the quality of antenatal care services, vaccination rates, emergency capabilities and primary health services; with many facilities reporting high-quality, reliable and continuous oxygen supplies, refrigeration and enhanced medical supply chains. Renewable energy sources were considered in six of the included studies, most highlighting their suitability for rural health facilities. Notably, solar-powered oxygen delivery systems reduced childhood mortality and length of hospital stay. Unavailable and unreliable electricity is a bottleneck to health service delivery in LMICs. Electrification was associated with increased service availability, readiness and quality of care – especially for women, children and those under critical care. This study indicates that stable and clean electrification allows new heights in achieving SDG 3 and SDG7 in LMICs.

An evidence-based synthesis of instructional reading and spelling procedures using telepractice: A rapid review in the context of COVID-19.

BackgroundDue to COVID‐19, many educators and allied health practitioners are facing the challenge of rapidly transitioning to telepractice delivery of instructional reading and spelling procedures without being fully informed of the evidence.AimsA rapid review was conducted to provide educators, allied health practitioners and policymakers with a synthesis of valid, relevant and actionable evidence relating to telepractice delivery of instructional reading and spelling procedures. The aim was to investigate the nature and outcomes of studies examining instructional reading and spelling procedures delivered via telepractice to school‐aged students.Methods & ProceduresA rapid review was undertaken in accordance with the eight‐step process published by the Cochrane Rapid Reviews Methods Group. Medline (all databases), Embase, Cochrane and ProQuest Central were systematically searched with predefined search terms organized across four key concepts relating to the research questions.Outcomes & ResultsNine studies were included in this rapid review. Reading and spelling instruction and intervention using telepractice can be feasible and engaging. Telepractice assessment for reading and spelling can be equally effective as onsite assessment.Conclusions & ImplicationsThe evidence base for telepractice delivery of reading and spelling procedures is in its infancy in terms of both the quantity and the quality of the evidence. Insufficient evidence exists to draw clear conclusions about its efficacy, and therefore practitioners should proceed cautiously. What this paper addsWhat is already known on the subject For onsite delivery, evidence‐based reading and spelling assessment, instruction and interventions delivered by educators and allied health practitioners have been shown to accelerate students’ skills; less is known about the efficacy of instructional reading and spelling procedures in a telepractice model, which have rapidly become the new norm in many countries due to the COVID‐19 pandemic. The benefits of telepractice include improved access to services, increased service availability, convenience, time efficiency, caseload management efficiency and removal of logistical barriers relating to cost and geographical location. During the COVID‐19 pandemic, telepractice has facilitated continued access to services. What this study adds to existing knowledge Reading and spelling instruction and intervention delivered via telepractice can be feasible and engaging. Telepractice is a viable mode to deliver reading and spelling assessments with strong agreement between telepractice and onsite scores. Given their low methodological quality, the studies in this review provide valuable information around the how of telepractice reading and spelling procedures and highlight the factors that may contribute to positive outcomes with this service delivery model. What are the potential or actual clinical implications of this work? Educators and allied health practitioners need a thorough understanding of the student's telepractice environment and require adequate training and support to engage in telepractice service delivery. Educators and allied health practitioners should consider students for telepractice on a case‐by‐case basis. Practitioners should proceed cautiously with telepractice reading and spelling assessment, intervention and instruction, with the knowledge that the current available evidence is of limited quality.

Void-hole aware and reliable data forwarding strategy for underwater wireless sensor networks

Abstract Reliable data transfer and energy efficiency are the essential considerations for network performance in resource-constrained underwater environments. One of the efficient approaches for data routing in underwater wireless sensor networks (UWSNs) is clustering, in which the data packets are transferred from sensor nodes to the cluster head (CH). Data packets are then forwarded to a sink node in a single or multiple hops manners, which can possibly increase energy depletion of the CH as compared to other nodes. While several mechanisms have been proposed for cluster formation and CH selection to ensure efficient delivery of data packets, less attention has been given to massive data communication processes with sink node. As such, failure in communicating nodes would lead to a significant network void-holes problem. Considering the limited energy resources of nodes in UWSNs along with the heavy load of CHs in the routing process, this paper proposes a void-holes aware and reliable data forwarding strategy (VHARD-FS) in a proactive mode to control data packets delivery from CH nodes to the sink in UWSNs. In the proposed strategy, each CH node is aware of its neighbor’s performance ranking index to conduct a reliable packet transmission to the sink via the most energy-efficient route. Extensive simulation results indicate that the VHARD-FS outperforms existing routing approaches while comparing energy efficiency and network throughput. This study helps to effectively alleviate the resource limitations associated with UWSNs by extending network life and increasing service availability even in a harsh underwater environment.

DLSense: Distributed Learning-Based Smart Virtual Sensing for Precision Agriculture

This work presents the design of an efficient edge-empowered sensor-cloud architecture equipped with a smart virtual sensing scheme for precision agriculture. Traditionally, in agricultural sensor-cloud, sensor nodes send raw sensed data periodically to the cloud, resulting in higher latency and higher energy and bandwidth consumption. The environment-dependent nature of agricultural parameters also limits the serviceability of sensor-cloud in regions with damaged or unemployed sensors. Moreover, agricultural sensor-cloud suffers from privacy issues due to the sharing of sensitive farming data across third-party service providers. To address these drawbacks, we first propose a modified sensor-cloud architecture using edge devices as the middleware layer for sensor virtualization, thereby reducing service provisioning latency and resource consumption. Next, we propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DLSense</i> , a novel intelligent virtualization scheme to aid in the design of virtual sensors in the absence of working sensor nodes in a region. DLSense utilizes correlation theory and distributed learning in the edge devices to predict sensor data and enables the sharing of information of the trained models instead of raw sensed data, thus imparting privacy. Finally, we evaluate the performance of the DLSense scheme through extensive simulations and an experimental case study of an agricultural application. Results demonstrate that our proposed scheme reduces latency and service cost by 81% and 66%, respectively, and increases service availability by 39% compared to the state-of-the-art methods.

Acceptability of telehealth in post-stroke memory rehabilitation: A qualitative analysis

ABSTRACT Despite evidence of the efficacy of telerehabilitation post-stroke, uptake has lagged behind the development of available technology, slowed by low confidence in user experience. We aimed to explore the issue of acceptability by characterizing the experience of telerehabilitation for service providers and consumers of a memory rehabilitation program. Semi-structured interviews were conducted with nine clinicians (M age = 33.29; SD = 7.37; range 25–44) and 25 stroke survivors with memory difficulties (M age = 54.12; SD = 10.99; range 36–82) following a 6-week compensatory memory skills program delivered via in-home videoconferencing. Thematic analysis identified a range of perspectives under three overarching themes: (1) Content and Delivery; (2) Relationship and Connection; and (3) The Role and Benefits of Telerehabilitation. Reports from both respondent groups were overwhelmingly positive about the telerehabilitation experience and identified the benefits of increasing service availability. Videoconferencing technology was usable and occasional reliability issues were not a barrier. Users identified a range of benefits and challenges regarding communication, rapport building, and integration of rehabilitation in the home environment. Furthermore, most stroke survivors reported benefit from the intervention, via the acquisition of memory strategies and improved self-confidence through better understanding of their deficits. Overall, telerehabilitation of memory was acceptable to users.

COVID-19: Reducing the risk of infection might increase the risk of intimate partner violence

COVID-19: Reducing the risk of infection might increase the risk of intimate partner violence

Nowhere to go? Examining facility acceptance levels for serving individuals using medications for opioid used disorder

Medications for opioid use disorder (OUD) are associated with better overall outcomes for individuals managing their OUD. While much attention has focused on expanding access to these medications, this study aimed to gain further clarity on how facility-level characteristics may be contributing to availability of complementary recovery-oriented and/or recovery support services for individuals diagnosed with OUD. We created a census of 410 facilities located within a Midwestern metropolitan area that provided services aligning with the substance use disorder (SUD) continuum of care between September 2017 and March 2018. Among facilities serving individuals with opioid-related needs (N = 360), we triangulated five sources of data to measure facility-reported acceptance for individuals who are using medications for OUD. We also obtained facility rationale for their acceptance level (N = 89). We used multinomial logistic regression to identify facility-level factors associated with acceptance for medication use, and we used content analysis to identify categories of common rationales. Compared to moderate acceptance facilities, zero and low acceptance facilities were more likely to provide recovery support services or less likely to provide more than one type of SUD service. In contrast, high acceptance facilities were more likely than moderate acceptance facilities to focus primarily on mental health needs or provide multiple types of SUD services. Qualitative feedback suggests that the factors contributing to these relationships are complex and varied, providing multiple points for intervention at a facility level to increase service availability for individuals using medications for OUD. We address implications for policy and practice, highlighting the need to build an infrastructure that promotes availability of complementary recovery-oriented and recovery support service for individuals once they are prescribed medications for OUD.

Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia

The demand for public transport and commuter behaviour are evidently affected by a series of D-factors relating to the built environment, including density, diversity, design, destination and/or demography. The effect of fare policies, however, in conjunction with built and non-built environment features has not been assessed. Given the 2017 fare policy change introduced in South East Queensland, Australia, this study examines how the policy reform (changes in fares, its structure and incentives) affects public transport ridership. Drawing on two like-for-like periods of transport smart card data before and after the policy reform, we compare the number of card users, journeys, and travel costs under the two fare systems. Through a set of statistical analysis and spatial lag regression, we examine the impact of the fare policy change on ridership, controlled by variations of built and non-built environment features, including population density, land use diversity, demographic features of commuters, distance to the central business district (CBD) and destination accessibility. Our findings show that public transit ridership can be boosted by reducing the fare cost per journey which can then result in overall revenue gain. However, such attraction by fare reduction varies substantially by user groups. Furthermore, the influences of population density, destination accessibility, distance to CBD and demographic features of commuters on ridership are significant (p < 0.01); while the influences of land use diversity and fare change tend to be insignificant compared to the other D-factors. We argue that in order to increase public transport usage policy makers need to consider fare policy reform in conjunction with built environment and demographic factors in order to increase service availability and ensure that services are accessible and affordable to the general public. This study also offers a generic framework that employs big data analytics to assess public policy intervention in the Australian context.