Small area analysis methods in an area of limited mapping: exploratory geospatial analysis of firearm injuries in Port-au-Prince, Haiti

Springer Science and Business Media LLC
Athanasios Burlotos1,2, Tayana Jean Pierre3,4,5, Walter D. Johnson6, Seth Wiafe6, Christian A. Péan, Monet McCalla, Carl Stephane Lominy, James G. Lefevre, Yvelie Saint Lot1,2, Jean Wilguens Lartigue, Alence Therone, Carolina Torres, Gabrielle Cahill, Mathai Joseph3,4,7
1Harvard T.H. Chan School of Public Health, Boston, USA
2Department of Emergency Medicine, Boston Medical Center, Boston, USA
3Program in Global Surgery and Social Change, Harvard Medical School, Boston, USA
4Department of Global Health and Social Medicine, Harvard Medical School, Boston, USA
5Universite Notre Dame D’Haiti, Faculte de Medecine, Port-au-Prince, Haïti
6Loma Linda University School of Public Health, Loma Linda, USA
7Clinical Trials Unit, University of Warwick, Coventry, United Kingdom

Tóm tắt

Abstract Background The city of Port-au-Prince, Haiti, is experiencing an epidemic of firearm injuries which has resulted in high burdens of morbidity and mortality. Despite this, little scientific literature exists on the topic. Geospatial research could inform stakeholders and aid in the response to the current firearm injury epidemic. However, traditional small-area geospatial methods are difficult to implement in Port-au-Prince, as the area has limited mapping penetration. Objectives of this study were to evaluate the feasibility of geospatial analysis in Port-au-Prince, to seek to understand specific limitations to geospatial research in this context, and to explore the geospatial epidemiology of firearm injuries in patients presenting to the largest public hospital in Port-au-Prince. Results To overcome limited mapping penetration, multiple data sources were combined. Boundaries of informally developed neighborhoods were estimated from the crowd-sourced platform OpenStreetMap using Thiessen polygons. Population counts were obtained from previously published satellite-derived estimates and aggregated to the neighborhood level. Cases of firearm injuries presenting to the largest public hospital in Port-au-Prince from November 22nd, 2019, through December 31st, 2020, were geocoded and aggregated to the neighborhood level. Cluster analysis was performed using Global Moran’s I testing, local Moran’s I testing, and the SaTScan software. Results demonstrated significant geospatial autocorrelation in the risk of firearm injury within the city. Cluster analysis identified areas of the city with the highest burden of firearm injuries. Conclusions By utilizing novel methodology in neighborhood estimation and combining multiple data sources, geospatial research was able to be conducted in Port-au-Prince. Geospatial clusters of firearm injuries were identified, and neighborhood level relative-risk estimates were obtained. While access to neighborhoods experiencing the largest burden of firearm injuries remains restricted, these geospatial methods could continue to inform stakeholder response to the growing burden of firearm injuries in Port-au-Prince.

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Tài liệu tham khảo

GBD 2019 Diseases and Injuries Collaborators. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1204–22.

Fene F, Ríos-Blancas MJ, Lachaud J, Razo C, Lamadrid-Figueroa H, Liu M, et al. Life expectancy, death, and disability in Haiti, 1990–2017: a systematic analysis from the Global Burden of Disease Study 2017. Rev Panam Salud Publica. 2020;44: e136.

Guerin O. Haiti: Inside the capital city taken hostage by brutal gangs. BBC News. 2022. https://www.bbc.com/news/world-latin-america-63707429. Accessed 22 Jan 2023.

Pean C. Pattern of Firearm Injuries in a Tertiary Care Center in Port-au-Prince, Haiti. 2022.

Rowhani-Rahbar A, Fan MD, Simonetti JA, Lyons VH, Wang J, Zatzick D, et al. Violence perpetration among patients hospitalized for unintentional and assault-related firearm injury: a case-control study and a cohort study. Ann Intern Med. 2016;165:841–7.

Larsen DA, Lane S, Jennings-Bey T, Haygood-El A, Brundage K, Rubinstein RA. Spatio-temporal patterns of gun violence in Syracuse, New York 2009–2015. PLoS ONE. 2017;12: e0173001.

OpenStreetMap Contributors. OpenStreetMap. 2022. http://www.openstreetmap.org. Accessed 18 Apr 2022.

Institut Haïtien de Statistique et d’Informatique (IHSI). Mars 2015 Population Totale, Population de 18 Ans et Plus Menages et Densites Estimes En 2015. Republique D’Haiti; 2015.

The World Bank. Haiti | Data. 2022. https://data.worldbank.org/country/HT. Accessed 12 Aug 2022.

World Bank. Haiti Overview. 2021. https://www.worldbank.org/en/country/haiti/overview. Accessed 13 May 2022.

R Core Team. R: A Language and Environment for Statistical Computing. Computer software. Vienna, Austria: R Foundation for Statistical Computing; 2022.

Myers SR, Branas CC, Kallan MJ, Wiebe DJ, Nance ML, Carr BG. The use of home location to proxy injury location and implications for regionalized trauma system planning. J Trauma. 2011;71:1428–34.

Google Developers. Geocoding API. https://developers.google.com/maps/documentation/geocoding/start. Accessed 4 Apr 2022.

Kahle D, Wickham H. ggmap: Spatial Visualization with ggplot2. R J. 2013;5:144.

OpenStreetMap Contributors. OpenStreetMap Wiki: Tag:place=suburb. 2022. https://wiki.openstreetmap.org/wiki/Tag%3Aplace%3Dsuburb. Accessed 13 May 2022.

Martin Raifer. Overpass Turbo. 2022. https://overpass-turbo.eu. Accessed 13 May 2022.

Padgham M, Lovelace R, Salmon M, Rudis B. osmdata. JOSS. 2017;2:305.

Pebesma E. Simple features for R: standardized support for spatial vector data. R J. 2018;10:439.

Bondarenko M, Kerr D, Sorichetta A, Tatem A. Census/projection-disaggregated gridded population datasets for 189 countries in 2020 using Built-Settlement Growth Model (BSGM) outputs. University of Southampton. 2020.

Hijmans RJ. raster: Geographic Data Analysis and Modeling. 2023.

Humanitarian Data Exchange, Centre National de l’Information Géo-Spatiale (CNIGS). Haiti—Subnational Administrative Boundaries. 2021. https://data.humdata.org/dataset/cod-ab-hti. Accessed 21 Mar 2022.

Kaufman EJ, Wiebe DJ, Xiong RA, Morrison CN, Seamon MJ, Delgado MK. Epidemiologic trends in fatal and nonfatal firearm injuries in the US, 2009–2017. JAMA Intern Med. 2021;181:237–44.

Wickham H. ggplot2: Elegant Graphics for Data Analysis (Use R!). 2nd ed. Cham: Springer; 2016.

Bivand RS, Wong DWS. Comparing implementations of global and local indicators of spatial association. TEST. 2018;27:716–48.

Bivand RS, Pebesma E, Gomez-Rubio V. Applied spatial data analysis with R, Second edition. Springer, NY; 2013.

Bivand R. R packages for analyzing spatial data: a comparative case study with areal data. Geogr Anal. 2022;54:488.

Caldas de Castro M, Singer BH. Controlling the false discovery rate: a new application to account for multiple and dependent tests in local statistics of spatial association. Geogr Anal. 2006;38:180–208.

Li X, Anselin L. rgeoda: R Library for Spatial Data Analysis. 2021.

Kulldorff M. Information management services, Inc. SaTScanTM v8 0: Software for the spatial and space-time scan statistics. 2009.

Kulldorff M. Bernoulli, discrete Poisson and continuous Poisson models. Commun Stat Theor Methods. 1997;:1481–96.

Dunnington D. ggspatial: Spatial Data Framework for ggplot2. 2021.

Auguie B. egg: Extensions for “ggplot2”: Custom Geom, Custom Themes, Plot Alignment, Labelled Panels, Symmetric Scales, and Fixed Panel Size. 2019.

Tennekes M. tmap: Thematic Maps in R. J Stat Softw. 2018;84.

Tennekes M. tmaptools: Thematic Map Tools. 2021.

Ram K, Wickham H. wesanderson: A Wes Anderson Palette Generator. 2018.

Schwalb-Willmann J. basemaps: Accessing Spatial Basemaps in R. 2021.

Dare AJ, Irving H, Guerrero-López CM, Watson LK, Kolpak P, Reynales Shigematsu LM, et al. Geospatial, racial, and educational variation in firearm mortality in the USA, Mexico, Brazil, and Colombia, 1990–2015: a comparative analysis of vital statistics data. Lancet Public Health. 2019;4:e281–90.

Green B, Horel T, Papachristos AV. Modeling contagion through social networks to explain and predict gunshot violence in Chicago, 2006 to 2014. JAMA Intern Med. 2017;177:326–33.

Newgard CD, Sanchez BJ, Bulger EM, Brasel KJ, Byers A, Buick JE, et al. A geospatial analysis of severe firearm injuries compared to other injury mechanisms: event characteristics, location, timing, and outcomes. Acad Emerg Med. 2016;23:554–65.

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