{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T05:54:42Z","timestamp":1780379682200,"version":"3.54.1"},"reference-count":19,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Public Health"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>This paper evaluates the increase in coverage and use of Covid-19 testing services for vulnerable and hard-to-reach populations through the introduction of community-based walk-up sites in New Orleans, LA. While most GIS work on Covid-19 testing coverage and access has used census tract or ZIP code aggregated data, this manuscript is unique in that it uses individual level demographics and exact addresses to calculate distances actually traveled by patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used testing data recorded for 9721 patients at 20 sites operating in May\u2013June 2020. The dataset includes detailed age, race and ethnicity, and testing results as well as the exact address of each individual. Using GIS, we estimated changes in testing coverage for minority neighborhoods and calculated the actual distance covered by individuals. Logistic regression and multivariate linear regression were used to identify socio-demographic variables associated with distance travelled to and used of nearest testing site. We used a secondary dataset from drive-through sites to evaluate change in coverage at the census tract level for the metropolitan area.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Walk-up sites significantly increased testing availability in New Orleans, and specifically in minority neighborhoods. Both African Americans and Asians were more likely (14.7 and 53.0%) to be tested at the nearest walk-up site. They also covered shorter distances to get tested. Being elderly was also significantly and positively associated with testing at the nearest site. Hispanics, however, were not associated with increased proximity to and use of nearest sites, and they traveled an additional 0.745\u2009km to get tested. Individuals who tested positive also travelled significantly longer distances to obtain a test.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Walk-up sites increased testing availability for some vulnerable populations who took advantage of the sites\u2019 proximity, although inequalities appear at the metropolitan scale. As cities are planning community vaccination campaigns, mobile, walk-up sites appear to improve both coverage and accessibility for hard-to-reach populations. With adequate technical (vaccine dose refrigeration) and messaging (addressing reticence to immunization) adaptations, they could constitute a key complementary approach to health facility points of delivery.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12889-021-10717-9","type":"journal-article","created":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T19:08:03Z","timestamp":1617217683000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Is Covid-19 community level testing effective in reaching at-risk populations? Evidence from spatial analysis of New Orleans patient data at walk-up sites"],"prefix":"10.1186","volume":"21","author":[{"given":"Julie H.","family":"Hernandez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dimitris","family":"Karletsos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Avegno","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chantell H.","family":"Reed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,1]]},"reference":[{"issue":"38","key":"10717_CR1","doi-asserted-by":"publisher","first-page":"1369","DOI":"10.15585\/mmwr.mm6938a4","volume":"69","author":"NM Lewis","year":"2020","unstructured":"Lewis NM, Friedrichs M, Wagstaff S, Sage K, LaCross N, Bui D, et al. Disparities in COVID-19 incidence, hospitalizations, and testing, by area-level deprivation\u2014Utah, march 3\u2013July 9, 2020. Morb Mortal Wkly Rep. 2020;69(38):1369\u201373. https:\/\/doi.org\/10.15585\/mmwr.mm6938a4.","journal-title":"Morb Mortal Wkly Rep"},{"key":"10717_CR2","doi-asserted-by":"crossref","unstructured":"Abedi, V., Olulana, O., Avula, V., Chaudhary, D., Khan, A., Shahjouei, S., ... & Zand, R. (2020). Racial, economic, and health inequality and COVID-19 infection in the United States. J Racial Ethnic Health Disparities, 1\u201311.","DOI":"10.1007\/s40615-020-00833-4"},{"issue":"10","key":"10717_CR3","doi-asserted-by":"publisher","first-page":"e2025197","DOI":"10.1001\/jamanetworkopen.2020.25197","volume":"3","author":"T Gu","year":"2020","unstructured":"Gu T, Mack JA, Salvatore M, Sankar SP, Valley TS, Singh K, et al. Characteristics associated with racial\/ethnic disparities in COVID-19 outcomes in an academic health care system. JAMA Netw Open. 2020;3(10):e2025197. https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.25197.","journal-title":"JAMA Netw Open"},{"issue":"9","key":"10717_CR4","doi-asserted-by":"publisher","first-page":"e2021213","DOI":"10.1001\/jamanetworkopen.2020.21213","volume":"3","author":"HN Kim","year":"2020","unstructured":"Kim HN, Lan KF, Nkyekyer E, Neme S, Pierre-Louis M, Chew L, et al. Assessment of disparities in COVID-19 testing and infection across language groups in Seattle, Washington. JAMA Netw Open. 2020;3(9):e2021213. https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.21213.","journal-title":"JAMA Netw Open"},{"key":"10717_CR5","doi-asserted-by":"crossref","unstructured":"Tai DBG, Shah A, Doubeni CA, Sia IG, Wieland ML. The disproportionate impact of COVID-19 on racial and ethnic minorities in the United States. Clin Infect Dis. 2020.","DOI":"10.1093\/cid\/ciaa815"},{"key":"10717_CR6","doi-asserted-by":"crossref","unstructured":"Owen, W. F., Carmona, R., & Pomeroy, C. (2020). Failing another national stress test on health disparities. Jama, Failing Another National Stress Test on Health Disparities.","DOI":"10.1001\/jama.2020.6547"},{"key":"10717_CR7","doi-asserted-by":"crossref","unstructured":"Dodds, C., & Fakoya, I. (2020). Covid-19: ensuring equality of access to testing for ethnic minorities.","DOI":"10.1136\/bmj.m2122"},{"issue":"3","key":"10717_CR8","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.amepre.2020.06.005","volume":"59","author":"W Lieberman-Cribbin","year":"2020","unstructured":"Lieberman-Cribbin W, Tuminello S, Flores RM, Taioli E. Disparities in COVID-19 testing and positivity in New York City. Am J Prev Med. 2020;59(3):326\u201332. https:\/\/doi.org\/10.1016\/j.amepre.2020.06.005.","journal-title":"Am J Prev Med"},{"key":"10717_CR9","doi-asserted-by":"crossref","unstructured":"Tao R, Downs J, Beckie TM, Chen Y, McNelley W. Examining spatial accessibility to COVID-19 testing sites in Florida. Ann GIS. 2020:1\u20139.","DOI":"10.1080\/19475683.2020.1833365"},{"key":"10717_CR10","doi-asserted-by":"crossref","unstructured":"Rader, B., Astley, C. M., Sy, K. T. L., Sewalk, K., Hswen, Y., Brownstein, J. S., & Kraemer, M. U. (2020). Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates. Journal of travel medicine, Geographic access to United States SARS-CoV-2 testing sites highlights healthcare disparities and may bias transmission estimates.","DOI":"10.1093\/jtm\/taaa076"},{"issue":"3","key":"10717_CR11","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1111\/jrh.12476","volume":"36","author":"CH Zhang","year":"2020","unstructured":"Zhang CH, Schwartz GG. Spatial disparities in coronavirus incidence and mortality in the United States: an ecological analysis as of may 2020. 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(2020). \u2018Huge hole\u2019 in testing data blurs racial, ethnic disparities.","DOI":"10.1126\/science.369.6501.237"}],"container-title":["BMC Public Health"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12889-021-10717-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s12889-021-10717-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s12889-021-10717-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,30]],"date-time":"2021-04-30T18:21:18Z","timestamp":1619806878000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcpublichealth.biomedcentral.com\/articles\/10.1186\/s12889-021-10717-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,1]]},"references-count":19,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["10717"],"URL":"https:\/\/doi.org\/10.1186\/s12889-021-10717-9","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-198724\/v1","asserted-by":"object"}]},"ISSN":["1471-2458"],"issn-type":[{"value":"1471-2458","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,1]]},"assertion":[{"value":"1 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 March 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Data collection for this research was approved by Tulane University Institutional Review Board (REF#: 2020\u2013988). All methods were performed in accordance with the principles of the Declaration of Helsinki. All anonymized datasets were shared by health authorities following HIPAA protocols. Informed consent was obtained from all individuals tested at drive-through and walk-up site to use their data for future research when registering at the site.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interest.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"632"}}