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Population structure and genetic connectivity of Plasmodium falciparum in pre-elimination settings of Southern Africa.
Gwarinda, Hazel B; Tessema, Sofonias K; Raman, Jaishree; Greenhouse, Bryan; Birkholtz, Lyn-Marié.
Afiliação
  • Gwarinda HB; Malaria Parasite Molecular Laboratory, Department of Biochemistry, Genetics and Microbiology, Institute for Sustainable Malaria Control, University of Pretoria, Pretoria, South Africa.
  • Tessema SK; EppiCenter, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
  • Raman J; Laboratory for Antimalarial Resistance Monitoring and Malaria Operational Research (ARMMOR), Centre for Emerging Zoonotic and Parasitic Diseases, A Division of the National Health Laboratory Service, National Institute for Communicable Diseases, Johannesburg, South Africa.
  • Greenhouse B; Faculty of Health Sciences, Wits Research Institute for Malaria, University of Witwatersrand, Johannesburg, South Africa.
  • Birkholtz LM; EppiCenter, Division of HIV, Infectious Diseases, and Global Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
Front Epidemiol ; 3: 1227071, 2023.
Article em En | MEDLINE | ID: mdl-38455947
ABSTRACT
To accelerate malaria elimination in the Southern African region by 2030, it is essential to prevent cross-border malaria transmission. However, countries within the region are highly interconnected due to human migration that aids in the movement of the parasite across geographical borders. It is therefore important to better understand Plasmodium falciparum transmission dynamics in the region, and identify major parasite source and sink populations, as well as cross-border blocks of high parasite connectivity. We performed a meta-analysis using collated parasite allelic data generated by microsatellite genotyping of malaria parasites from Namibia, Eswatini, South Africa, and Mozambique (N = 5,314). The overall number of unique alleles was significantly higher (P ≤ 0.01) in Namibia (mean A = 17.3 ± 1.46) compared to South Africa (mean A = 12.2 ± 1.22) and Eswatini (mean A = 13.3 ± 1.27, P ≤ 0.05), whilst the level of heterozygosity was not significantly different between countries. The proportion of polyclonal infections was highest for Namibia (77%), and lowest for Mozambique (64%). A was significant population structure was detected between parasites from the four countries, and patterns of gene flow showed that Mozambique was the major source area and Eswatini the major sink area of parasites between the countries. This study showed strong signals of parasite population structure and genetic connectivity between malaria parasite populations across national borders. This calls for strengthening the harmonization of malaria control and elimination efforts between countries in the southern African region. This data also proves its potential utility as an additional surveillance tool for malaria surveillance on both a national and regional level for the identification of imported cases and/or outbreaks, as well as monitoring for the potential spread of anti-malarial drug resistance as countries work towards malaria elimination.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article