Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa

Sofonias Tessema, Amy Wesolowski, Anna Chen, Maxwell Murphy, Jordan Wilheim, Anna Rosa Mupiri, Nick W. Ruktanonchai, Victor A. Alegana, Andrew J. Tatem, Munyaradzi Tambo, Bradley Didier, Justin M. Cohen, Adam Bennett, Hugh Jw Sturrock, Roland Gosling, Michelle S. Hsiang, David L. Smith, Davis R. Mumbengegwi, Jennifer L. Smith, Bryan Greenhouse

Research output: Contribution to journalArticle

Abstract

Local and cross-border importation remain major challenges to malaria elimination and are difficult to measure using traditional surveillance data. 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.

Original languageEnglish (US)
JournaleLife
Volume8
DOIs
StatePublished - Apr 2 2019

Fingerprint

Southern Africa
Medical Genetics
Malaria
Parasites
Namibia
Mobile phones
Cell Phones
History
Population

Keywords

  • epidemiology
  • genetic epidemiology
  • global health
  • malaria
  • mobility
  • P. falciparum
  • parasite genomics

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

Cite this

Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa. / Tessema, Sofonias; Wesolowski, Amy; Chen, Anna; Murphy, Maxwell; Wilheim, Jordan; Mupiri, Anna Rosa; Ruktanonchai, Nick W.; Alegana, Victor A.; Tatem, Andrew J.; Tambo, Munyaradzi; Didier, Bradley; Cohen, Justin M.; Bennett, Adam; Sturrock, Hugh Jw; Gosling, Roland; Hsiang, Michelle S.; Smith, David L.; Mumbengegwi, Davis R.; Smith, Jennifer L.; Greenhouse, Bryan.

In: eLife, Vol. 8, 02.04.2019.

Research output: Contribution to journalArticle

Tessema, S, Wesolowski, A, Chen, A, Murphy, M, Wilheim, J, Mupiri, AR, Ruktanonchai, NW, Alegana, VA, Tatem, AJ, Tambo, M, Didier, B, Cohen, JM, Bennett, A, Sturrock, HJ, Gosling, R, Hsiang, MS, Smith, DL, Mumbengegwi, DR, Smith, JL & Greenhouse, B 2019, 'Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa', eLife, vol. 8. https://doi.org/10.7554/eLife.43510
Tessema, Sofonias ; Wesolowski, Amy ; Chen, Anna ; Murphy, Maxwell ; Wilheim, Jordan ; Mupiri, Anna Rosa ; Ruktanonchai, Nick W. ; Alegana, Victor A. ; Tatem, Andrew J. ; Tambo, Munyaradzi ; Didier, Bradley ; Cohen, Justin M. ; Bennett, Adam ; Sturrock, Hugh Jw ; Gosling, Roland ; Hsiang, Michelle S. ; Smith, David L. ; Mumbengegwi, Davis R. ; Smith, Jennifer L. ; Greenhouse, Bryan. / Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa. In: eLife. 2019 ; Vol. 8.
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