Prevalence of drug-resistant mutations in newly diagnosed drug-naïve HIV-1-infected individuals in a treatment site in the Waterberg district, Limpopo province

Aim. We studied the prevalence of resistance mutations in drugnaïve HIV-infected individuals at the Bela-Bela treatment site to gather information on the presence of antiretroviral (ARV) drug-resistant viruses in drug-naïve populations, so as to improve treatment guidance. Subjects and methods. Drug-naïve HIV-1-infected individuals were sequentially recruited between February 2008 and December 2008 from individuals visiting the voluntary counselling and testing (VCT) services of the Bela-Bela HIV/AIDS Wellness Clinic. Viral subtyping was done by phylogenetic analysis; drug-resistant mutations were determined according to the Stanford HIV Drug Resistance Interpretation and the International AIDS Society-USA Guidelines. Results. A drug-resistant mutation prevalence of 3.5% (95% confidence interval 0.019796 - 0.119077) comprising Y181C and L33F was observed; 98% of the viruses were HIV-1 subtype C on the protease (PR) and reverse transcriptase (RT) gene regions. Conclusion. The prevalence of drug-resistant mutations in drug-naïve persons may be low in Bela-Bela after 8 years of access to antiretroviral treatment (ART), and resistance testing before initiating treatment may not be needed

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Tools for genotyping human immunodeficiency virus, and implications of genetic diversity on diagnostics, treatment and prevention

Human immunodeficiency virus (HIV) presents an unprecedented genetic variability within infected individuals and across geographical locales. Sub-Saharan Africa accounts for almost 70% of all HIV infections worldwide and represents the region with the highest diversity of genetic variants of the virus. This review looks at the current approaches and techniques for the determination of HIV genetic diversity. In addition, the rationale for a continuous periodic monitoring of the genetic landscape due to the implications of shifting genetics on the efficacy of diagnostics, treatment and prevention strategies is highlighted

Data from: DNA of diverse adenoviruses detected in Cameroonian rodent and shrew species

Rodent adenoviruses are important models for human disease. In contrast to the over 70 adenovirus types isolated from humans, few rodent adenoviruses are known, despite the vast diversity of rodent species. PCR and Sanger sequencing were used to investigate adenovirus diversity in wild rodents and shrews in Cameroon. Adenovirus DNA was detected in 13.8% of animals (n=218). All detected sequences differ from known adenovirus types by more than 10% on the amino acid level, thus indicating up to 14 novel adenovirus species. These results highlight the diversity of rodent adenoviruses, their phylogeny, and opportunities for studying alternative adenovirus rodent models