Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020.

In this study, we evaluated and forecasted the cumulative opportunities for residents to access radiotherapy services in Cali, Colombia, while accounting for traffic congestion, using a new people-centred methodology with an equity focus. Furthermore, we identified 1-2 optimal locations where new services would maximise accessibility. We utilised open data and publicly available big data. Cali is one of South America's cities most impacted by traffic congestion. METHODOLOGY: Using a people-centred approach, we tested a web-based digital platform developed through an iterative participatory design. The platform integrates open data, including the location of radiotherapy services, the disaggregated sociodemographic microdata for the population and places of residence, and big data for travel times from Google Distance Matrix API. We used genetic algorithms to identify optimal locations for new services. We predicted accessibility cumulative opportunities (ACO) for traffic ranging from peak congestion to free-flow conditions with hourly assessments for 6-12 July 2020 and 23-29 November 2020. The interactive digital platform is openly available. PRIMARY AND SECONDARY OUTCOMES: We present descriptive statistics and population distribution heatmaps based on 20-min accessibility cumulative opportunities (ACO) isochrones for car journeys. There is no set national or international standard for these travel time thresholds. Most key informants found the 20-min threshold reasonable. These isochrones connect the population-weighted centroid of the traffic analysis zone at the place of residence to the corresponding zone of the radiotherapy service with the shortest travel time under varying traffic conditions ranging from free-flow to peak-traffic congestion levels. Additionally, we conducted a time-series bivariate analysis to assess geographical accessibility based on economic stratum. We identify 1-2 optimal locations where new services would maximize the 20-min ACO during peak-traffic congestion. RESULTS: Traffic congestion significantly diminished accessibility to radiotherapy services, particularly affecting vulnerable populations. For instance, urban 20-min ACO by car dropped from 91% of Cali's urban population within a 20-min journey to the service during free-flow traffic to 31% during peak traffic for the week of 6-12 July 2020. Percentages represent the population within a 20-min journey by car from their residence to a radiotherapy service. Specific ethnic groups, individuals with lower educational attainment, and residents on the outskirts of Cali experienced disproportionate effects, with accessibility decreasing to 11% during peak traffic compared to 81% during free-flow traffic for low-income households. We predict that strategically adding sufficient services in 1-2 locations in eastern Cali would notably enhance accessibility and reduce inequities. The recommended locations for new services remained consistent in both of our measurements.These findings underscore the significance of prioritising equity and comprehensive care in healthcare accessibility. They also offer a practical approach to optimising service locations to mitigate disparities. Expanding this approach to encompass other transportation modes, services, and cities, or updating measurements, is feasible and affordable. The new approach and data are particularly relevant for planning authorities and urban development actors.

The pathologies of migrants who travel by boat documented on imaging.

The migration phenomenon is increasingly common worldwide. It is essential for radiologists to be aware of the endemic diseases of the migrant's country as well as the characteristics of the journey to be able to understand and interpret radiological findings when admitted to our centre. This article aims to use imaging from our centre to describe the most common pathologies that migrant patients present with after long journeys by boat.

A travel time matrix data set for the Helsinki region 2023 that is sensitive to time, mode and interpersonal differences, and uses open data and novel open-source software.

Travel times between different locations form the basis for most contemporary measures of spatial accessibility. Travel times allow to estimate the potential for interaction between people and places, and is therefore a vital measure for understanding the functioning, sustainability, and equity of cities. Here, we provide an open travel time matrix dataset that describes travel times between the centroids of all cells in a grid (N = 13,132) covering the metropolitan area of Helsinki, Finland. The travel times recorded in the dataset follow a door-to-door approach that provides comparable travel times for walking, cycling, public transport and car journeys, including all legs of each trip by each mode, such as the walk to a bus stop, or the search for a parking spot. We used the r5py Python package, that we developed specifically for this computation. The data are sensitive to diurnal variations and to variations between people (e.g. slow and fast walking speed). We validated the data against the Google Directions API and present use cases from a planning practice. The five key principles that guided the data set design and production - comparability, simplicity, reproducibility, transferability, and sensitivity to temporal and interpersonal variations - ensure that urban and transport planners, business and researchers alike can use the data in a wide range of applications.

Perceived differences in coastal tourism image under tourist experience-IPA analysis based on UGC data of 12 coastal cities.

The destination image perceived by tourists is crucial to coastal tourism market positioning and marketing. This paper utilizes tourists' Internet-generated content from 2017-2021, adopts the jieba text analysis method to identify the cognitive, emotional, and overall image of coastal tourism, divides the constituent elements of the destination image into four main classes and 20 subclasses through the text clustering method, and explores the tourists' perception of the image of coastal tourism with the help of the IPA model. The study found that: 1) The commonality of the cognitive image of "ocean" in 12 coastal cities is outstanding, but the internal characteristics are obvious, tourists pay more attention to coastal tourism in Bohai Rim and southern coastal areas, and Shanghai, Ningbo and Hangzhou show strong correlation; 2) Tourists' emotional image of coastal tourism destinations is dominated by positive attitudes, with a high overlap of adjectives representing positive emotions, but with heat differences in different cities; 3) The overall image of coastal tourism can be divided into three circles, including "traditional core-characteristic structure-peripheral perception", and there are obvious differences in the characteristics of the social semantic network of each city; 4) Tourists are more satisfied with the components of coastal tourism image, but pay more attention to the construction of optimized coastal tourism environment. Based on this, in the process of coastal tourism development, it is necessary to focus on creating distinctive and diversified tourism values, focusing on tourists' experience needs, improving the construction of quality tourism facilities and services, and promoting the high-quality development of coastal tourism.

Governing the misconduct of OTA platforms: A tripartite evolutionary game analysis considering the collaborative supervision of airlines and consumers.

Online travel agency (OTA) platforms frequently engage in unfair behaviors that infringe on the legitimate rights and interests of consumers and airlines in the ticket sale market. Effective governance of the OTA platforms' misconduct has become an urgent topic. In order to address the governance dilemma of OTA platforms' misconduct, a tripartite evolutionary game model considering the collaborative supervision between airlines and consumers is constructed. This study analyzes the evolutionary path and stable strategy of the three participants, airlines, platforms and consumers by numerical simulation. The results show that some actions, such as airlines' strict control of ticket sales resources and high fines on the platform, reducing the cost of customers' rights protection, and effectively guiding online public opinion, can benefit airlines and consumers and enhance their willingness to cooperate in supervision. Legitimate consumer rights protection not only brings negative public opinion and image loss to airlines, but also to platforms, which can force airlines to impose stricter constraints on platforms and force platforms to strengthen self-restraint. Therefore, a market mechanism instead of government regulatory that can effectively suppress platforms misconduct should be established to promote platforms self-regulation through a collaborative effort between airlines and consumers. Some special measures that guide the interests of three participators are also provided.

Understanding the secondary outcomes of international travel measures during the covid-19 pandemic: a scoping review of social impact evidence.

BACKGROUND: Assessment of the effective use of international travel measures during the COVID-19 pandemic has focused on public health goals, namely limiting virus introduction and onward transmission. However, risk-based approaches includes the weighing of public health goals against potential social, economic and other secondary impacts. Advancing risk-based approaches thus requires fuller understanding of available evidence on such impacts. METHODS: We conducted a scoping review of existing studies of the social impacts of international travel measures during the COVID-19 pandemic. Applying a standardized typology of travel measures, and five categories of social impact, we searched 9 databases across multiple disciplines spanning public health and the social sciences. We identified 26 studies for inclusion and reviewed their scope, methods, type of travel measure, and social impacts analysed. RESULTS: The studies cover a diverse range of national settings with a strong focus on high-income countries. A broad range of populations are studied, hindered in their outbound or inbound travel. Most studies focus on 2020 when travel restrictions were widely introduced, but limited attention is given to the broader effects of their prolonged use. Studies primarily used qualitative or mixed methods, with adaptations to comply with public health measures. Most studies focused on travel restrictions, as one type of travel measure, often combined with domestic public health measures, making it difficult to determine their specific social impacts. All five categories of social impacts were observed although there was a strong emphasis on negative social impacts including family separation, decreased work opportunities, reduced quality of life, and inability to meet cultural needs. A small number of countries identified positive social impacts such as restored work-life balance and an increase in perceptions of safety and security. CONCLUSIONS: While international travel measures were among the most controversial interventions applied during the COVID-19 pandemic, given their prolonged use and widespread impacts on individuals and populations, there remains limited study of their secondary impacts. If risk-based approaches are to be advanced, involving informed choices between public health and other policy goals, there is a need to better understand such impacts, including their differential impacts across diverse populations and settings.

Where should we go - Estimating travel times for modelling accessibility to 24-hour emergency departments in Canada.

Estimating travel time to 24-hour emergency services is an important component to modelling accessibility of health services, particularly for rural areas. However, methods used to estimate travel time vary significantly, are not representative of the residential population, and are not openly validated. This makes the assessment of travel-based accessibility metrics between studies incomparable. To address this issue and develop a standardized measurement of emergency service access, this study utilized small geographic units (Dissemination Areas - DA) and geographical boundaries representative of municipal equivalents (Census Subdivision - CSD). Estimated travel times between the centroid of an inhabited DA to each 24-hr emergency department was computed with population-weighted travel times generated for each CSD. This dataset provides a nationally consistent measurement of proximity to emergency services accounting for travel pathing and population distribution. This methodology can be extended to generate estimated shortest travel routes for other healthcare resources or develop actual travel routes based on individuals' experiences with the healthcare system.

Identifying the determinants of tourism receipts of Thailand and relevant determinant-determinant interactions.

The study examined the determinants that affect tourism receipts in Thailand. To this end, quarterly data from eight main provinces of Thailand from the period 2015-2019 were used and constituted a repeated measures design. Accordingly, a generalized linear mixed model was applied for developing two different random intercept models by treating 1) province, and 2) a combination of province and calendar quarter as cluster-specific effects. It was found that determinants that increased tourism receipts were the number of visitors, the average cost per day, the length of stay of visitors, the presence of low-cost airlines, and a relatively low offence rate. Moreover, an increase in the number of visitors in the fourth quarter produced a higher amount of additional receipts as compared to a similar increase in the first quarter. Specifically, for Thailand attracting high-spending tourists and extending tourist visas for more than 30 days is recommended. Beyond Thailand, uncovering interaction effects as described above may help tourism agencies to focus their limited resources on the determinants that matter.

Perceptions of safety during everyday travel shaping older adults' mobility in Bengaluru, India.

BACKGROUND: In the context of socially sustainable urban development, comfortable, safe, and accessible public transport is crucial to motivating people to travel more sustainably. Using the framework given by Masoumi and Fastenmeier (2016) to examine the concepts of safety and security, we explore how perceptions of safety about different transport modes shaped the mobility of older adults in Bengaluru, India. METHODS: In-depth telephonic interviews were conducted with 60 adults, aged 50 years and over, residing in urban Bengaluru, using a semi-structured in-depth interview guide to explore the perceptions of safety in different transport modes. Observations were conducted prior to the COVID-19 pandemic. Applying thematic analysis, we present how the perceptions of safety during their everyday travel shaped their mobility. RESULTS: According to our research, older adults' perception of safety during their everyday travel is shaped by past negative experiences with accidents, pickpocketing, theft of mobile phones, and chain snatching. In addition, the Covid-19 pandemic exacerbated the already existing inequalities, further limiting older adults' mobility to carry out regular activities such as buying groceries, socialising, making a hospital visit, or going to work due to the fear of getting infected. CONCLUSION: Our findings indicate that the use of public transport needs to be encouraged among older adults by enhancing necessary safety features following the age-friendly cities framework. Furthermore, it can help policymakers develop transport polices, which suit the mobility needs of older adults.

Paris 2024 Olympic Games: A risk enhancer for autochthonous arboviral diseases epidemics?

OBJECTIVES: The anticipated increase in international tourist flows and the first locally acquired dengue cases in the Paris region in October 2023 have raised concerns about potential arbovirus outbreaks during the 2024 Olympics. Unlike previous mass sporting events at risk of arbovirus outbreaks, Paris is a nonendemic arbovirus area, requiring a unique investigation. METHODS: Therefore, we analyzed factors conducive to possible arbovirus epidemics in temperate regions: vector distribution in the Paris area, seasonal global arboviral disease patterns, projected visitor demographics, and international flight bookings. RESULTS AND CONCLUSION: Our results suggest that the expected visitors' profile for the summer of 2024 should not increase the risk of arbovirus importation into the Paris region compared to a typical year. Conversely, the primary risk of arbovirus outbreaks is likely to come from within France, particularly from the French West Indies, where a notable, albeit declining, dengue outbreak is underway. Vigilant surveillance by French health authorities will ensure that this trend continues.

Surveillance of global, travel-related illness using a novel app: a multivariable, cross-sectional study.

INTRODUCTION: Current traveller health surveillance is 'top-down'. Mobile-based surveillance could capture infection symptoms in real time. We aimed to evaluate the spectrum of illness in travellers using a mobile app-based system. METHODS: This study (ClinicalTrials.gov NCT04672577) used an application called Infection Tracking in Travellers (ITIT) that records travel-related illness symptoms with associated geolocation and weather data. The free ITIT app is available in 14 languages. Participants were recruited globally from April 2022 to July 2023. Participants >18 years of age travelled internationally and provided electronic consent. Incentives included the provision of travel health information imported from the WHO website. Symptoms were recorded with daily pop-up questionnaires and symptom severity was assessed using a Likert scale. Two post-travel questionnaires were administered. Logistic mixed models examined factors relating to symptom presence, and a random forest model examined symptom impact. RESULTS: 609 participants were recruited until July 2023. Participants had an average age of 37 years (18-79), and an average travel duration of 26 days (2-281). Most participants were travelling for leisure/tourism (401; 66%), followed by 'visiting friends and relatives' (99; 16%) and business travel (80; 13%). All continents were visited by at least one traveller. Of 470 registered trips, symptoms were reported on 163 trips (35%). Gastrointestinal symptoms were reported on 87 trips (19%) and respiratory symptoms on 81 trips (17%). The most important factors in predicting the presence of symptoms were duration of travel, travelling in winter and high humidity. Diarrhoea, headache and nausea were symptoms with most impact on daily activities. Post-travel questionnaires showed that 12% of surveyed participants experienced symptoms with several episodes of self-treatment. Two diagnoses were recorded: Lyme disease and amoebic dysentery. CONCLUSION: The digital tool ITIT successfully captures the spectrum of travel-related illness. This detailed epidemiology is crucial for outbreak detection and for the formulation of travel medicine guidelines. TRIAL REGISTRATION NUMBER: NCT04672577.