Understanding the Transmission Dynamics of the Chikungunya Virus in Africa.

Africa Chikungunya virus epidemiology genomic distribution genomic surveillance transmission dynamics

Journal

Pathogens (Basel, Switzerland)
ISSN: 2076-0817
Titre abrégé: Pathogens
Pays: Switzerland
ID NLM: 101596317

Informations de publication

Date de publication:
22 Jul 2024
Historique:
received: 15 06 2024
revised: 09 07 2024
accepted: 16 07 2024
medline: 26 7 2024
pubmed: 26 7 2024
entrez: 26 7 2024
Statut: epublish

Résumé

The Chikungunya virus (CHIKV) poses a significant global public health concern, especially in Africa. Since its first isolation in Tanzania in 1953, CHIKV has caused recurrent outbreaks, challenging healthcare systems in low-resource settings. Recent outbreaks in Africa highlight the dynamic nature of CHIKV transmission and the challenges of underreporting and underdiagnosis. Here, we review the literature and analyse publicly available cases, outbreaks, and genomic data, providing insights into the epidemiology, genetic diversity, and transmission dynamics of CHIKV in Africa. Our analyses reveal the circulation of geographically distinct CHIKV genotypes, with certain regions experiencing a disproportionate burden of disease. Phylogenetic analysis of sporadic outbreaks in West Africa suggests repeated emergence of the virus through enzootic spillover, which is markedly different from inferred transmission dynamics in East Africa, where the virus is often introduced from Asian outbreaks, including the recent reintroduction of the Indian Ocean lineage from the Indian subcontinent to East Africa. Furthermore, there is limited evidence of viral movement between these two regions. Understanding the history and transmission dynamics of outbreaks is crucial for effective public health planning. Despite advances in surveillance and research, diagnostic and surveillance challenges persist. This review and secondary analysis highlight the importance of ongoing surveillance, research, and collaboration to mitigate the burden of CHIKV in Africa and improve public health outcomes.

Identifiants

pubmed: 39057831
pii: pathogens13070605
doi: 10.3390/pathogens13070605
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Subventions

Organisme : Rockefeller Foundation
ID : HTH 017
Organisme : Abbott Pandemic Defense Coalition (APDC)
Organisme : NIAID NIH HHS
ID : U01 AI151698
Pays : United States
Organisme : World Bank Group
ID : TF0B8412
Organisme : MRF
ID : MRF-RG-ICCH-2022-100069
Pays : United Kingdom
Organisme : Wellcome Trust for the Global.health project
ID : 228186/Z/23/Z

Auteurs

Yajna Ramphal (Y)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

Houriiyah Tegally (H)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

James Emmanuel San (JE)

Duke Human Vaccine Institute, Duke University, Durham, NC 27710, USA.

Martina Larissa Reichmuth (ML)

Institute of Social and Preventive Medicine (ISPM), University in Bern, 3012 Bern, Switzerland.

Marije Hofstra (M)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

Eduan Wilkinson (E)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

Cheryl Baxter (C)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

Tulio de Oliveira (T)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.
KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), University of KwaZulu-Natal, Durban 4001, South Africa.

Monika Moir (M)

Centre for Epidemic Response Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.

Classifications MeSH