Departamento de Pediatría, de Obstetricia y Ginecología y de Medicina Preventiva y Salud Pública. Facultad de Medicina - Edificio M, Universitat Autònoma de Barcelona, Campus Universitario UAB, 08193, Bellaterra, (Cerdanyola del Vallès) Cataluña, Spain.
Academia Nacional de Medicina de Colombia, Cra. 7ª # 69-11, 110231, Bogotá, Colombia.
Int J Equity Health. 2024 Aug 15;23(1):161. doi: 10.1186/s12939-024-02211-6.
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.
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.
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.
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.
本研究旨在评估和预测哥伦比亚卡利市居民接受放射治疗服务的累积机会,同时考虑交通拥堵因素,采用一种新的以人群为中心、注重公平的方法。此外,我们还确定了 1-2 个最佳位置,在这些位置新增服务可以最大限度地提高可达性。我们利用了开放数据和公共可用的大数据。卡利是南美洲交通拥堵最严重的城市之一。
采用以人群为中心的方法,我们测试了一个通过迭代参与式设计开发的基于网络的数字平台。该平台整合了开放数据,包括放射治疗服务的位置、人口的细分社会人口微观数据和居住地点,以及来自 Google Distance Matrix API 的旅行时间大数据。我们使用遗传算法来确定新增服务的最佳位置。我们预测了 2020 年 7 月 6 日至 12 日和 11 月 23 日至 29 日每小时交通拥堵从高峰到自由流动条件下的可达性累积机会 (ACO)。交互式数字平台是公开的。
我们根据 20 分钟可达性累积机会 (ACO)等时线呈现了描述性统计数据和人口分布热图,这些等时线适用于汽车旅行。对于这些旅行时间阈值,没有设定国家或国际标准。大多数关键知情者认为 20 分钟的阈值是合理的。这些等时线将交通分析区居住地点的人口加权质心与相应的放射治疗服务区连接起来,在不同交通条件下(从自由流动到高峰交通拥堵水平),旅行时间最短。此外,我们进行了时间序列双变量分析,根据经济阶层评估地理可达性。我们确定了 1-2 个最佳位置,在高峰交通拥堵期间,新增服务可以最大限度地提高 20 分钟 ACO。
交通拥堵显著降低了放射治疗服务的可达性,特别是对弱势群体造成了影响。例如,在自由流动的交通条件下,城市 20 分钟可达性从 91%的卡利城市人口下降到高峰交通条件下的 31%,时间为 2020 年 7 月 6 日至 12 日这一周。百分比代表从居住地点乘坐汽车到放射治疗服务的 20 分钟旅程内的人口。特定族裔群体、教育程度较低的个人以及卡利郊区的居民受到的影响不成比例,高峰交通时可达性下降到 11%,而自由流动交通时可达性为 81%,低收入家庭的可达性下降尤其明显。我们预测,在卡利东部的 1-2 个地点战略性地增加足够的服务,将显著提高可达性,并减少不平等。在我们的两项测量中,建议的新服务地点保持一致。这些发现强调了在医疗保健可达性中优先考虑公平和综合护理的重要性。它们还提供了一种优化服务地点以减轻差异的实用方法。扩展这种方法以涵盖其他交通模式、服务和城市,或更新测量方法是可行且负担得起的。这种新方法和数据对于规划当局和城市发展参与者特别相关。