Programs that monitor local, national, and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programs. To accurately compare transmitted drug resistance rates across geographic regions and times, the World Health Organization has recommended the adoption of a consensus genotypic definition of transmitted HIV-1 drug resistance. In January 2007, we outlined criteria for developing a list of mutations for drug-resistance surveillance and compiled a list of 80 RT and protease mutations meeting these criteria (surveillance drug resistance mutations; SDRMs). Since January 2007, several new drugs have been approved and several new drug-resistance mutations have been identified. In this paper, we follow the same procedures described previously to develop an updated list of SDRMs that are likely to be useful for ongoing and future studies of transmitted drug resistance. The updated SDRM list has 93 mutations including 34 NRTI-resistance mutations at 15 RT positions, 19 NNRTI-resistance mutations at 10 RT positions, and 40 PI-resistance mutations at 18 protease positions.

Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases. Public-health need Digital tool or technology Example of use Refs. Digital epidemiological surveillance Machine learning Web-based epidemic intelligence tools and online syndromic surveillance Web-based epidemic intelligence tools: 20-23,25 Based on social media or online search data: 30-33 Survey apps and websites Symptom reporting 37,38,48,49 Data extraction and visualization Data dashboard 39-45 Rapid case identification Connected diagnostic device Point-of-care diagnosis 58 Sensors including wearables Febrile symptoms checking 51-53 Machine learning Medical image analysis 65,66

Resistance to antiretroviral drugs remains an important limitation to successful human immunodeficiency virus type 1 (HIV-1) therapy. Resistance testing can improve treatment outcomes for infected individuals. The availability of new drugs from various classes, standardization of resistance assays, and the development of viral tropism tests necessitate new guidelines for resistance testing. The International AIDS Society-USA convened a panel of physicians and scientists with expertise in drug-resistant HIV-1, drug management, and patient care to review recently published data and presentations at scientific conferences and to provide updated recommendations. Whenever possible, resistance testing is recommended at the time of HIV infection diagnosis as part of the initial comprehensive patient assessment, as well as in all cases of virologic failure. Tropism testing is recommended whenever the use of chemokine receptor 5 antagonists is contemplated. As the roll out of antiretroviral therapy continues in developing countries, drug resistance monitoring for both subtype B and non-subtype B strains of HIV will become increasingly important.

Background The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. Methods In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1•5, 2•0, and 3•0 at differing infection rate scenarios, including full suppression (0•001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. Findings We included 3 862 012 individuals (1 957 935 [50•7%] women and 1 904 077 [49•3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13•7% were older than 70 years and 6•3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4•46% (95% CI 4•41-4•51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1•5, four with an RR of 2•0, and seven with an RR of 3•0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1•5, 36 749 with an RR of 2•0, and 73 498 with an RR of 3•0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1•5, 293 991 with an RR of 2•0, and 587 982 with an RR of 3•0. Interpretation We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indir...

The recently identified restriction factor tetherin/BST-2/CD317 is an interferon-inducible trans-membrane protein that restricts HIV-1 particle release in the absence of the HIV-1 countermeasure viral protein U (Vpu). It is known that Tantalus monkey CV1 cells can be rendered non-permissive to HIV-1 release upon stimulation with type 1 interferon, despite the presence of Vpu, suggesting species-specific sensitivity of tetherin proteins to viral countermeasures such as Vpu. Here we demonstrate that Tantalus monkey tetherin restricts HIV-1 by nearly two orders of magnitude, but in contrast to human tetherin the Tantalus protein is insensitive to HIV-1 Vpu. We have investigated tetherin's sensitivity to Vpu using positive selection analyses, seeking evidence for evolutionary conflict between tetherin and viral countermeasures. We provide evidence that tetherin has undergone positive selection during primate evolution. Mutation of a single amino acid (showing evidence of positive selection) in the trans-membrane cap of human tetherin to that in Tantalus monkey (T45I) substantially impacts on sensitivity to HIV-1 Vpu, but not on antiviral activity. Finally, we provide evidence that cellular steady state levels of tetherin are substantially reduced by Vpu, and that the T45I mutation abrogates this effect. This study provides evidence that tetherin is important in protecting mammals against viral infection, and that the HIV-1 Vpu–mediated countermeasure is specifically adapted to act against human tetherin. It also emphasizes the power of selection analyses to illuminate the molecular details of host–virus interactions. This work suggests that tetherin binding agents might protect it from viral encoded countermeasures and thus make powerful antivirals.

Risk if ART is deferred is taken from [328]. The predicted 6-month risk if ART is initiated is based on the assumption that the rate with immediate therapy initiation is one-third the rate without therapy initiation. This (probably conservative) value is based on considering evidence from multiple sources, including references [32,[329][330][331][332][333].BHIVA treatment guidelines 569 r 2008 British HIV Association HIV Medicine (2008) 9, 563-608 but high CD4 percentages, but also may support a decision to start therapy earlier in patients with absolute CD4 counts 4350 cells/mL but with low CD4 percentages {e.g. o14%, where Pneumocystis carinii pneumonia (PCP) prophylaxis is indicated [35]; some studies have indicated increased risk of disease progression in patients with CD4 percentages o15-17% [36]}. Patients with a CD4 count 4350 cells/mLAs detailed above, at CD4 counts 4350 cells/mL, multiple cohort studies have suggested that there might be benefits to ART. This is supported by data from the substudy of patients not on therapy at entry to the SMART study [32]. Some of the previous concerns about earlier initiation of therapy have been reduced because of the availability of simpler, less toxic and better tolerated antiretroviral regimens, improved pharmacokinetic profiles and increasing options after virological failure. For the majority of patients, the absolute risk of deferring therapy until the CD4 count is o350 cells/mL is likely to be low, but in a subgroup at particularly high risk of clinical events that may be preventable by ART, this is not the case. For all these reasons, in a small number of patients, treatment may be started or considered before the CD4 count is below 350 cells/mL, including the following: AIDS diagnosis (e.g. Kaposi's sarcoma); any HIV-related comorbidity; hepatitis B infection, where treatment of hepatitis B is indicated (see hepatitis guidelines); hepatitis C infection in some cases, where treatment for hepatitis is deferred; low CD4 percentage (e.g. o14%, where PCP prophylaxis would be indicated); established CVD or a very high risk of cardiovascular events (e.g. Framingham risk of CVD 420% over 10 years).Additionally, it is likely that successful antiretroviral treatment, by reducing viral load, reduces infectivity irrespective of the current CD4 cell count, and this may be taken into account in deciding on the timing of starting treatment, particularly in discordant couples where the infected partner has a high viral load. This is likely to be an issue in a very small number of patients, and it must be stressed that antiretroviral treatment in this context would be an adjunct rather than an alternative to safer sex.In patients who do not have an AIDS diagnosis or coinfection with hepatitis B or C virus, and whose CD4 counts are above 500 cells/mL, the benefits of starting therapy remain unclear, the risk of deferring therapy is low, and we recommend that they consider enrolment in the START study, where this is an option. ComorbiditiesWhilst it has been clearly shown that...

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