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      Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia

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      ISPRS International Journal of Geo-Information
      MDPI AG

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          Abstract

          This paper examines OpenStreetMap data quality at different stages of a participatory mapping process in seven slums in Africa and Asia. Data were drawn from an OpenStreetMap-based participatory mapping process developed as part of a research project focusing on understanding inequalities in healthcare access of slum residents in the Global South. Descriptive statistics and qualitative analysis were employed to examine the following research question: What is the spatial data quality of collaborative remote mapping achieved by volunteer mappers in morphologically complex urban areas? Findings show that the completeness achieved by remote mapping largely depends on the morphology and characteristics of slums such as building density and rooftop architecture, varying from 84% in the best case, to zero in the most difficult site. The major scientific contribution of this study is to provide evidence on the spatial data quality of remotely mapped data through volunteer mapping efforts in morphologically complex urban areas such as slums; the results could provide insights into how much fieldwork would be needed in what level of complexity and to what extent the involvement of local volunteers in these efforts is required.

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          Impact of the societal response to COVID-19 on access to healthcare for non-COVID-19 health issues in slum communities of Bangladesh, Kenya, Nigeria and Pakistan: results of pre-COVID and COVID-19 lockdown stakeholder engagements

          Introduction With COVID-19, there is urgency for policymakers to understand and respond to the health needs of slum communities. Lockdowns for pandemic control have health, social and economic consequences. We consider access to healthcare before and during COVID-19 with those working and living in slum communities. Methods In seven slums in Bangladesh, Kenya, Nigeria and Pakistan, we explored stakeholder perspectives and experiences of healthcare access for non-COVID-19 conditions in two periods: pre-COVID-19 and during COVID-19 lockdowns. Results Between March 2018 and May 2020, we engaged with 860 community leaders, residents, health workers and local authority representatives. Perceived common illnesses in all sites included respiratory, gastric, waterborne and mosquitoborne illnesses and hypertension. Pre-COVID, stakeholders described various preventive, diagnostic and treatment services, including well-used antenatal and immunisation programmes and some screening for hypertension, tuberculosis, HIV and vectorborne disease. In all sites, pharmacists and patent medicine vendors were key providers of treatment and advice for minor illnesses. Mental health services and those addressing gender-based violence were perceived to be limited or unavailable. With COVID-19, a reduction in access to healthcare services was reported in all sites, including preventive services. Cost of healthcare increased while household income reduced. Residents had difficulty reaching healthcare facilities. Fear of being diagnosed with COVID-19 discouraged healthcare seeking. Alleviators included provision of healthcare by phone, pharmacists/drug vendors extending credit and residents receiving philanthropic or government support; these were inconsistent and inadequate. Conclusion Slum residents’ ability to seek healthcare for non-COVID-19 conditions has been reduced during lockdowns. To encourage healthcare seeking, clear communication is needed about what is available and whether infection control is in place. Policymakers need to ensure that costs do not escalate and unfairly disadvantage slum communities. Remote consulting to reduce face-to-face contact and provision of mental health and gender-based violence services should be considered.
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            Quality Assessment of the French OpenStreetMap Dataset

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              The world’s user-generated road map is more than 80% complete

              OpenStreetMap, a crowdsourced geographic database, provides the only global-level, openly licensed source of geospatial road data, and the only national-level source in many countries. However, researchers, policy makers, and citizens who want to make use of OpenStreetMap (OSM) have little information about whether it can be relied upon in a particular geographic setting. In this paper, we use two complementary, independent methods to assess the completeness of OSM road data in each country in the world. First, we undertake a visual assessment of OSM data against satellite imagery, which provides the input for estimates based on a multilevel regression and poststratification model. Second, we fit sigmoid curves to the cumulative length of contributions, and use them to estimate the saturation level for each country. Both techniques may have more general use for assessing the development and saturation of crowd-sourced data. Our results show that in many places, researchers and policymakers can rely on the completeness of OSM, or will soon be able to do so. We find (i) that globally, OSM is ∼83% complete, and more than 40% of countries—including several in the developing world—have a fully mapped street network; (ii) that well-governed countries with good Internet access tend to be more complete, and that completeness has a U-shaped relationship with population density—both sparsely populated areas and dense cities are the best mapped; and (iii) that existing global datasets used by the World Bank undercount roads by more than 30%.
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                Journal
                ISPRS International Journal of Geo-Information
                IJGI
                MDPI AG
                2220-9964
                April 2021
                April 14 2021
                : 10
                : 4
                : 265
                Article
                10.3390/ijgi10040265
                0b41a6ac-b9c9-4d32-9cea-796469135698
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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