Performance of rapid subtyping tools used for the classification of HIV type 1 recombinants isolated from selected countries in west and central Africa

HIV-1 genetic diversity in sub-Saharan Africa is broad and the AIDS epidemic is driven predominantly by recombinants in Central and West Africa. The classification of HIV-1 strains is therefore necessary to understand diagnostic efficiency, individual treatment responses as well as options for designing vaccines and antiretroviral (ARV) treatment guidelines. More so, accurate subtyping of a partial or full genome would represent the population dynamics of HIV and provide evidence for designing surveillance strategies within a geographic region. Evaluating the performance of rapid subtyping tools with options that incorporate phylogeny could be fast, more user-friendly and of high performance. A total of 570 HIV-1 partial sequences from Cameroon, Angola, Democratic Republic of Congo, Gabon and Senegal were obtained from the Los Alamos National Library (LANL) HIV Sequence Database. Phylogeny was performed using MEGA v6 and the results were used to evaluate the performance of eleven different rapid HIV-1 subtyping tools: REGA v2, REGA v3, NCBI, Stanford HIVDB, SUDI, Geno2Pheno, Euresist, STAR, jpHMM, COMET and SCUEAL. The performance of these subtyping tools differed among HIV-1 clades and across different viral genes. NCBI and SUDI showed the highest performance in subtyping. The discordance observed between the rapid subtyping tools and phylogeny implies that phylogenetic analysis is still the more suitable method for HIV-1 classification. However, the need to update the reference datasets of the subtyping tools, and validate algorithms for rapid subtyping and quality control is imperative as this information is relevant for clinical use and policymaking to the AIDS response.Keywords: HIV, phylogeny, performance, subtyping tools, algorith

Characterization of human immunodeficiency virus type 1 and host genetic determinants of infection in Cameroon rural inhabitants

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Regional vulnerability for COVID-19 in Cameroon

Introductionfew studies have assessed risk for coronavirus disease 2019 (COVID-19) within African countries. Here we examine differences in vulnerability to COVID-19 among the ten administrative regions and two major cities of Cameroon based on epidemiological risk factors and access to healthcare resources.Methodsregional epidemiological and healthcare access vulnerability indices were created and compared with cumulative COVID-19 cases, case fatality rates, co-morbidities, and healthcare resources in Cameroon.Resultsbased on epidemiological risk factors, populations in the East Region, Douala (in the Littoral Region), West Region, and Yaoundé (in the Center Region) are at highest risk for COVID-19. Meanwhile, the North, Far North, East, and Adamawa Regions had the most healthcare access vulnerability. COVID-19 cases per population were highest in the Center, Littoral, and East Regions. Case fatality rates were greatest in the North Region. Potential co-morbidities with greater prevalence among COVID-19 patients included male sex, hypertension, and diabetes.Conclusionepidemiological risk factors for COVID-19 and access to healthcare varies between the regions of Cameroon. These discrepancies are potentially reflected in regional differences of COVID-19 cases and case fatality rates. In particular, the East Region has high epidemiological risk factors and low healthcare accessibility compared to other regions. Understanding the relationships between epidemiological risk factors, access to healthcare resources, and COVID-19 cases in Cameroon could aid decision-making among national policymakers and inform further research

Reference Values of Lymphocyte Subsets in Healthy, HIV-Negative Children in Cameroon▿

Lymphocyte subset reference values used to monitor infectious diseases, including HIV/AIDS, tuberculosis, malaria, or other immunological disorders in healthy children in Cameroon, are lacking. Values for Caucasian cohorts are already being utilized for clinical decisions but could be inappropriate for African populations. We report here the immunological profile for children aged from birth through 6 years in Cameroon and also compare our values to data from other African and Caucasian populations. In a cohort of 352 healthy children, aged 0 to 6 years, the relative and absolute numbers of T-cell subsets, B cells, and NK lymphocytes were determined from peripheral blood collected in EDTA tubes. Samples were stained with BD Multitest reagents in Trucount tubes and analyzed by using CellQuest-Pro and FlowJo software. We evaluated about 23 different lymphocyte subsets in which the absolute number and percentage values differed significantly (P < 0.05) with age and peaked between 6 and 12 months. B-cell values were higher compared to reported values from developed countries. Differences in activated and differentiated T cells were observed in subjects between 1 and 6 years of age. The absolute CD8+ T-cell count and the CD4+/CD8+ ratio seem to depend on gender. Normal lymphocyte subsets values among children from Cameroon differ from reported values in Caucasian and some African populations. The differences observed could be due to genetic and environmental factors coupled with the methodology used. These values could be used as initial national reference guidelines as more data are assembled