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Cuervo LG, Villamizar CJ, Osorio L, Ospina MB, Cuervo DE, Cuervo D, Bula MO, Zapata P, Owens NJ, Hatcher-Roberts J, Martín EA, Piquero F, Pinilla LF, Martínez-Herrera E, Jaramillo C. Dynamic measurements of geographical accessibility considering traffic congestion using open data: a cross-sectional assessment for haemodialysis services in Cali, Colombia. LANCET REGIONAL HEALTH. AMERICAS 2024; 34:100752. [PMID: 38737772 PMCID: PMC11087994 DOI: 10.1016/j.lana.2024.100752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 03/19/2024] [Accepted: 04/16/2024] [Indexed: 05/14/2024]
Abstract
Background Many cities with traffic congestion lack accessibility assessments accounting for traffic congestion and equity considerations but have disaggregated georeferenced municipal-level open data on health services, populations, and travel times big data. We convened a multistakeholder intersectoral collaborative group that developed a digital, web-based platform integrating open and big data to derive dynamic spatial-temporal accessibility measurements (DSTAM) for haemodialysis services. We worked with stakeholders and data scientists and considered people's places of residence, service locations, and travel time to the service with the shortest travel time. Additionally, we predicted the impacts of strategically introducing haemodialysis services where they optimise accessibility. Methods Cross-sectional analyses of DSTAM, accounting for traffic congestion, were conducted using a web-based platform. This platform integrated traffic analysis zones, public census and health services datasets, and Google Distance Matrix API travel-time data. Predictive and prescriptive analytics identified optimal locations for new haemodialysis services and estimated improvements. Primary outcomes included the percentage of residents within a 20-min car drive of a haemodialysis service during peak and free-flow traffic congestion. Secondary outcomes focused on optimal locations to maximise accessibility with new services and potential improvements. Findings were disaggregated by sociodemographic characteristics, providing an equity perspective. The study in Cali, Colombia, used geographic and disaggregated sociodemographic data from the adjusted 2018 Colombian census. Predicted travel times were obtained for two weeks in 2020. Findings There were substantial traffic variations. Congestion reduced accessibility, especially among marginalised groups. For 6-12 July, free-flow and peak-traffic accessibility rates were 95.2% and 45.0%, respectively. For 23-29 November, free-flow and peak traffic accessibility rates were 89.1% and 69.7%. The locations where new services would optimise accessibility had slight variation and would notably enhance accessibility and health equity. Interpretation Establishing haemodialysis services in targeted areas has significant potential benefits. By increasing accessibility, it would enhance urban health and equity. Funding No external or institutional funding was received.
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Affiliation(s)
| | | | - Lyda Osorio
- School of Public Health, Universidad del Valle, Cali, Colombia
| | | | | | | | | | | | - Nancy J. Owens
- Independent Content and Communications Consultant, Fairfax, VA, USA
| | - Janet Hatcher-Roberts
- School of Epidemiology and Public Health in the Faculty of Medicine, and Bruyère Research Institute, University of Ottawa, Ottawa, ON, Canada
| | | | - Felipe Piquero
- Patient Advocate and Author of an Autopathography, Bogotá, Colombia
| | | | | | - Ciro Jaramillo
- School of Civil and Geomatic Engineering of the Universidad del Valle, Cali, Colombia
| | - The AMORE Project Collaborationp
- Universitat Autònoma de Barcelona, Barcelona, Spain
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- School of Public Health, Universidad del Valle, Cali, Colombia
- Faculty of Health Sciences, Queen's University, Kingston, ON, Canada
- National Disability Board of Colombia, Bogotá, Colombia
- IQuartil SAS, Bogotá, Colombia
- Independent Researcher, Bogotá, Colombia
- Independent Content and Communications Consultant, Fairfax, VA, USA
- School of Epidemiology and Public Health in the Faculty of Medicine, and Bruyère Research Institute, University of Ottawa, Ottawa, ON, Canada
- Colombian Association of Transplanted Athletes, Bogota, Colombia
- Patient Advocate and Author of an Autopathography, Bogotá, Colombia
- Universidad de la Sabana, Campus del Puente del Común, Chía, Cundinamarca, Colombia
- National Faculty of Public Health, Universidad de Antioquia, Medellín, Colombia
- School of Civil and Geomatic Engineering of the Universidad del Valle, Cali, Colombia
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Macharia PM, Wong KLM, Beňová L, Wang J, Makanga PT, Ray N, Banke-Thomas A. Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations. GEOSPATIAL HEALTH 2024; 19. [PMID: 38801322 DOI: 10.4081/gh.2024.1266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024]
Abstract
Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API's in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors.
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Affiliation(s)
- Peter M Macharia
- Population and Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; Department of Public Health, Institute of Tropical Medicine, Antwerp.
| | - Kerry L M Wong
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
| | - Lenka Beňová
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London.
| | - Jia Wang
- School of Computing and Mathematical Sciences, University of Greenwich, London.
| | - Prestige Tatenda Makanga
- Surveying and Geomatics Department, Midlands State University Faculty of the Built Environment, Gweru, Midlands, Zimbabwe; Climate, Environment and Health Department, Centre for Sexual Health and HIV/AIDS Research, Harare, Zimbabwe; Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool.
| | - Nicolas Ray
- GeoHealth Group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute for Environmental Sciences, University of Geneva, Geneva.
| | - Aduragbemi Banke-Thomas
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom; School of Human Sciences, University of Greenwich, London, United Kingdom; Maternal and Reproductive Health Research Collective, Surulere, Lagos.
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Song J, Ramírez MC, Okano JT, Service SK, de la Hoz J, Díaz-Zuluaga AM, Upegui CV, Gallago C, Arias A, Sánchez AV, Teshiba T, Sabatti C, Gur RC, Bearden CE, Escobar JI, Reus VI, Jaramillo CL, Freimer NB, Olde Loohuis LM, Blower S. Geospatial investigations in Colombia reveal variations in the distribution of mood and psychotic disorders. COMMUNICATIONS MEDICINE 2024; 4:26. [PMID: 38383761 PMCID: PMC10881503 DOI: 10.1038/s43856-024-00441-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 01/19/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Geographical variations in mood and psychotic disorders have been found in upper-income countries. We looked for geographic variation in these disorders in Colombia, a middle-income country. We analyzed electronic health records from the Clínica San Juan de Dios Manizales (CSJDM), which provides comprehensive mental healthcare for the one million inhabitants of Caldas. METHODS We constructed a friction surface map of Caldas and used it to calculate the travel-time to the CSJDM for 16,295 patients who had received an initial diagnosis of mood or psychotic disorder. Using a zero-inflated negative binomial regression model, we determined the relationship between travel-time and incidence, stratified by disease severity. We employed spatial scan statistics to look for patient clusters. RESULTS We show that travel-times (for driving) to the CSJDM are less than 1 h for ~50% of the population and more than 4 h for ~10%. We find a distance-decay relationship for outpatients, but not for inpatients: for every hour increase in travel-time, the number of expected outpatient cases decreases by 20% (RR = 0.80, 95% confidence interval [0.71, 0.89], p = 5.67E-05). We find nine clusters/hotspots of inpatients. CONCLUSIONS Our results reveal inequities in access to healthcare: many individuals requiring only outpatient treatment may live too far from the CSJDM to access healthcare. Targeting of resources to comprehensively identify severely ill individuals living in the observed hotspots could further address treatment inequities and enable investigations to determine factors generating these hotspots.
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Affiliation(s)
- Janet Song
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Justin T Okano
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Susan K Service
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Juan de la Hoz
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ana M Díaz-Zuluaga
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Cristian Gallago
- Department of Mental Health and Human Behavior, University of Caldas, Manizales, Colombia
| | - Alejandro Arias
- Department of Psychiatry, University of Antioquía, Medellín, Colombia
| | | | - Terri Teshiba
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Chiara Sabatti
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania School of Medicine and the Penn-CHOP Lifespan Brain Institute, Philadelphia, PA, USA
| | - Carrie E Bearden
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Javier I Escobar
- Department of Psychiatry, Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Victor I Reus
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | | | - Nelson B Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Loes M Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| | - Sally Blower
- Center for Biomedical Modeling, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
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Macharia PM, Wong KLM, Olubodun T, Beňová L, Stanton C, Sundararajan N, Shah Y, Prasad G, Kansal M, Vispute S, Shekel T, Gwacham-Anisiobi U, Ogunyemi O, Wang J, Abejirinde IOO, Makanga PT, Afolabi BB, Banke-Thomas A. A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations. Sci Data 2023; 10:736. [PMID: 37872185 PMCID: PMC10593805 DOI: 10.1038/s41597-023-02651-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/16/2023] [Indexed: 10/25/2023] Open
Abstract
Travel time estimation accounting for on-the-ground realities between the location where a need for emergency obstetric care (EmOC) arises and the health facility capable of providing EmOC is essential for improving pregnancy outcomes. Current understanding of travel time to care is inadequate in many urban areas of Africa, where short distances obscure long travel times and travel times can vary by time of day and road conditions. Here, we describe a database of travel times to comprehensive EmOC facilities in the 15 most populated extended urban areas of Nigeria. The travel times from cells of approximately 0.6 × 0.6 km to facilities were derived from Google Maps Platform's internal Directions Application Programming Interface, which incorporates traffic considerations to provide closer-to-reality travel time estimates. Computations were done to the first, second and third nearest public or private facilities. Travel time for eight traffic scenarios (including peak and non-peak periods) and number of facilities within specific time thresholds were estimated. The database offers a plethora of opportunities for research and planning towards improving EmOC accessibility.
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Affiliation(s)
- Peter M Macharia
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
- Population & Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
- Centre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UK
| | - Kerry L M Wong
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Tope Olubodun
- Department of Community Medicine and Primary Care, Federal Medical Centre Abeokuta, Abeokuta, Ogun, Nigeria
| | - Lenka Beňová
- Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium
| | | | | | | | | | | | | | | | | | | | - Jia Wang
- School of Computing & Mathematical Sciences, University of Greenwich, London, UK
| | - Ibukun-Oluwa Omolade Abejirinde
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Women's College Hospital Institute for Health System Solutions and Virtual Care, Toronto, Canada
| | - Prestige Tatenda Makanga
- Surveying and Geomatics Department, Midlands State University Faculty of Science and Technology, Gweru, Midlands, Zimbabwe
- Climate and Health Division, Centre for Sexual Health and HIV/AIDS Research, Harare, Zimbabwe
| | - Bosede B Afolabi
- Maternal and Reproductive Health Research Collective, Lagos, Nigeria
- Department of Obstetrics and Gynaecology, College of Medicine of the University of Lagos, Lagos, Nigeria
| | - Aduragbemi Banke-Thomas
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
- Maternal and Reproductive Health Research Collective, Lagos, Nigeria.
- School of Human Sciences, University of Greenwich, London, UK.
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Cuervo LG, Jaramillo C, Cuervo D, Martínez-Herrera E, Hatcher-Roberts J, Pinilla LF, Bula MO, Osorio L, Zapata P, Piquero Villegas F, Ospina MB, Villamizar CJ. Dynamic geographical accessibility assessments to improve health equity: protocol for a test case in Cali, Colombia. F1000Res 2022; 11:1394. [PMID: 37469626 PMCID: PMC10352632 DOI: 10.12688/f1000research.127294.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/18/2022] [Indexed: 07/21/2023] Open
Abstract
This protocol proposes an approach to assessing the place of residence as a spatial determinant of health in cities where traffic congestion might impact health services accessibility. The study provides dynamic travel times presenting data in ways that help shape decisions and spur action by diverse stakeholders and sectors. Equity assessments in geographical accessibility to health services typically rely on static metrics, such as distance or average travel times. This new approach uses dynamic spatial accessibility measures providing travel times from the place of residence to the health service with the shortest journey time. It will show the interplay between traffic congestion, accessibility, and health equity and should be used to inform urban and health services monitoring and planning. Available digitised data enable efficient and accurate accessibility measurements for urban areas using publicly available sources and provide disaggregated sociodemographic information and an equity perspective. Test cases are done for urgent and frequent care (i.e., repeated ambulatory care). Situational analyses will be done with cross-sectional urban assessments; estimated potential improvements will be made for one or two new services, and findings will inform recommendations and future studies. This study will use visualisations and descriptive statistics to allow non-specialized stakeholders to understand the effects of accessibility on populations and health equity. This includes "time-to-destination" metrics or the proportion of the people that can reach a service by car within a given travel time threshold from the place of residence. The study is part of the AMORE Collaborative Project, in which a diverse group of stakeholders seeks to address equity for accessibility to essential health services, including health service users and providers, authorities, and community members, including academia.
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Affiliation(s)
- Luis Gabriel Cuervo
- Department of Paediatrics, Obstetrics & Gynaecology and Preventative Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Ciro Jaramillo
- School of Civil and Geomatic Engineering, Universidad del Valle, Cali, Valle del Cauca, Colombia
| | | | | | - Janet Hatcher-Roberts
- WHO Collaborating Centre for Knowledge Translation and Health Technology Assessment for Health Equity, Bruyère Research Institute, University of Ottawa, Ottawa, Ontario, K1R6M1, Canada
| | | | | | - Lyda Osorio
- School of Public Health, Universidad del Valle, Cali, Valle del Cauca, Colombia
| | | | | | - Maria Beatriz Ospina
- Department of Public Health Sciences, Faculty of Health Sciences, Queen's University, Kingston, ON, K7L 3N6, Canada
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