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To address this challenge, we systematically collected parasite genetic data and travel history from thousands of malaria cases across northeastern Namibia and estimated human mobility from mobile phone data. We observed strong fine-scale spatial structure in local parasite populations, providing positive evidence that the majority of cases were due to local transmission. This result was largely consistent with estimates from mobile phone and travel history data. However, genetic data identified more detailed and extensive evidence of parasite connectivity over hundreds of kilometers than the other data, within Namibia and across the Angolan and Zambian borders. Our results provide a framework for incorporating genetic data into malaria surveillance and provide evidence that both strengthening of local interventions and regional coordination are likely necessary to eliminate malaria in this region of Southern Africa.<\/jats:p>","DOI":"10.7554\/elife.43510","type":"journal-article","created":{"date-parts":[[2019,4,1]],"date-time":"2019-04-01T20:00:13Z","timestamp":1554148813000},"source":"Crossref","is-referenced-by-count":124,"title":["Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa"],"prefix":"10.7554","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1057-5310","authenticated-orcid":true,"given":"Sofonias","family":"Tessema","sequence":"first","affiliation":[{"name":"EPPIcenter program, Division of HIV, Infectious Diseases and Global Medicine, Department of Medicine, University of California, San Francisco, San Francisco, United 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