Spatial phylodynamics of HIV-1 epidemic emergence in east Africa
Gray, R.R., Tatem, A.J., Lamers, S., Hou, W., Laeyendecker, O., Serwadda, D., Sewankambo, N., Gray, R.H., Wawer, M., Quinn, T.C., Goodenow, M.M. and Salemi, M. (2009) Spatial phylodynamics of HIV-1 epidemic emergence in east Africa. AIDS, 23, (14), F9-F17. (doi:10.1097/QAD.0b013e32832faf61). (PMID:19644346).
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DESIGN: We sought to investigate the evolutionary and historical reasons for the different epidemiological patterns of HIV-1 in the early epidemic. In order to characterize the demographic history of HIV-1 subtypes A and D in east Africa, we examined molecular epidemiology, geographical and historical data.
METHODOLOGY: We employed high-resolution phylodynamics to investigate the introduction of HIV-1A and D into east Africa, the geographic trends of viral spread, and the demographic growth of each subtype. We also used geographic information system data to investigate human migration trends, population growth, and human mobility. RESULTS: HIV-1A and D were introduced into east Africa after 1950 and spread exponentially during the 1970s, concurrent with eastward expansion. Spatiotemporal data failed to explain the establishment and spread of HIV based on urban population growth and migration. The low prevalence of the virus in the Democratic Republic of Congo before and after the emergence of the pandemic was, however, consistent with regional accessibility data, highlighting the difficulty in travel between major population centers in central Africa. In contrast, the strong interconnectivity between population centers across the east African region since colonial times has likely fostered the rapid growth of the epidemic in this locale.
CONCLUSION: This study illustrates how phylodynamic analysis of pathogens informed by geospatial data can provide a more holistic and evidence-based interpretation of past epidemics. We advocate that this 'landscape phylodynamics' approach has the potential to provide a framework both to understand epidemics' spread and to design optimal intervention strategies.
|Digital Object Identifier (DOI):||doi:10.1097/QAD.0b013e32832faf61|
|Keywords:||africa, eastern, epidemiology, bayes theorem disease outbreaks, emigration and immigration, statistics & numerical data trends, evolution, molecular geographic information systems, HIV infections, virology HIV-1,classification, genetics, humans phylogeny, population growth|
|Subjects:||H Social Sciences > HA Statistics
Q Science > QR Microbiology > QR180 Immunology
|Divisions :||Faculty of Social and Human Sciences > Geography and Environment
|Accepted Date and Publication Date:||
|Date Deposited:||05 Nov 2012 16:15|
|Last Modified:||31 Mar 2016 14:36|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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