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Recent epidemiologic, virologic, and modeling reports support the possibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission from persons who are presymptomatic (SARS-CoV-2 detected before symptom onset) or asymptomatic (SARS-CoV-2 detected but symptoms never develop). SARS-CoV-2 transmission in the absence of symptoms reinforces the value of measures that prevent the spread of SARS-CoV-2 by infected persons who may not exhibit illness despite being infectious. Critical knowledge gaps include the relative incidence of asymptomatic and symptomatic SARS-CoV-2 infection, the public health interventions that prevent asymptomatic transmission, and the question of whether asymptomatic SARS-CoV-2 infection confers protective immunity.

Tecovirimat and the Treatment of MonkeypoxTecovirimat might speed resolution of monkeypox illness and improve outcomes, but how can we manage compassionate access to a drug whose safety and efficacy in humans have not been established?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiology of coronavirus disease 2019 (COVID-19), is readily transmitted person to person. Optimal control of COVID-19 depends on directing resources and health messaging to mitigation efforts that are most likely to prevent transmission, but the relative importance of such measures has been disputed. To assess the proportion of SARS-CoV-2 transmissions in the community that likely occur from persons without symptoms. This decision analytical model assessed the relative amount of transmission from presymptomatic, never symptomatic, and symptomatic individuals across a range of scenarios in which the proportion of transmission from people who never develop symptoms (ie, remain asymptomatic) and the infectious period were varied according to published best estimates. For all estimates, data from a meta-analysis was used to set the incubation period at a median of 5 days. The infectious period duration was maintained at 10 days, and peak infectiousness was varied between 3 and 7 days (-2 and +2 days relative to the median incubation period). The overall proportion of SARS-CoV-2 was varied between 0% and 70% to assess a wide range of possible proportions. Level of transmission of SARS-CoV-2 from presymptomatic, never symptomatic, and symptomatic individuals. The baseline assumptions for the model were that peak infectiousness occurred at the median of symptom onset and that 30% of individuals with infection never develop symptoms and are 75% as infectious as those who do develop symptoms. Combined, these baseline assumptions imply that persons with infection who never develop symptoms may account for approximately 24% of all transmission. In this base case, 59% of all transmission came from asymptomatic transmission, comprising 35% from presymptomatic individuals and 24% from individuals who never develop symptoms. Under a broad range of values for each of these assumptions, at least 50% of new SARS-CoV-2 infections was estimated to have originated from exposure to individuals with infection but without symptoms. In this decision analytical model of multiple scenarios of proportions of asymptomatic individuals with COVID-19 and infectious periods, transmission from asymptomatic individuals was estimated to account for more than half of all transmissions. In addition to identification and isolation of persons with symptomatic COVID-19, effective control of spread will require reducing the risk of transmission from people with infection who do not have symptoms. These findings suggest that measures such as wearing masks, hand hygiene, social distancing, and strategic testing of people who are not ill will be foundational to slowing the spread of COVID-19 until safe and effective vaccines are available and widely used.

ABSTRACT BACKGROUND Among aging HIV-infected adults, polypharmacy and its consequences have not been well-described. OBJECTIVE To characterize the extent of polypharmacy and the risk of antiretroviral (ARV) drug interactions among persons of different ages. DESIGN AND PARTICIPANTS Cross-sectional analysis among patients within the HIV Outpatient Study (HOPS) cohort who were prescribed ARVs during 2006–2010. MAIN MEASURES We used the University of Liverpool HIV drug interactions database to identify ARV/non-ARV interactions with potential for clinical significance. KEY RESULTS Of 3,810 patients analyzed (median age 46 years, 34 % ≥ 50 years old) at midpoint of observation, 1,494 (39 %) patients were prescribed ≥ 5 non-ARV medications: 706 (54 %) of 1,312 patients ≥ 50 years old compared with 788 (32 %) of 2,498 patients < 50 years. During the five-year period, the number of patients who were prescribed at least one ARV/non-ARV combination that was contraindicated or had moderate or high evidence of interaction was 267 (7 %) and 1,267 (33 %), respectively. Variables independently associated with having been prescribed a contraindicated ARV/non-ARV combination included older age (adjusted odds ratio [aOR] per 10 years of age 1.17, 95 % CI 1.01–1.35), anxiety (aOR 1.78, 95 % CI 1.32–2.40), dyslipidemia (aOR 1.96, 95 % CI 1.28–2.99), higher daily non-ARV medication burden (aOR 1.13, 95 % CI 1.10–1.17), and having been prescribed a protease inhibitor (aOR 2.10, 95 % CI 1.59–2.76). Compared with patients < 50 years, older patients were more likely to have been prescribed an ARV/non-ARV combination that was contraindicated (unadjusted OR 1.44, 95 % CI 1.14–1.82), or had moderate or high evidence of interaction (unadjusted OR 1.29, 95 % CI 1.15–1.44). CONCLUSIONS A substantial percentage of patients were prescribed at least one ARV/non-ARV combination that was contraindicated or had potential for a clinically significant interaction. As HIV-infected patients age and experience multiple comorbidities, systematic reviews of current medications by providers may reduce risk of such exposures.

On December 14, 2020, the United Kingdom reported a SARS-CoV-2 variant of concern (VOC), lineage B.1.1.7, also referred to as VOC 202012/01 or 20I/501Y.V1.* The B.1.1.7 variant is estimated to have emerged in September 2020 and has quickly become the dominant circulating SARS-CoV-2 variant in England (1). B.1.1.7 has been detected in over 30 countries, including the United States. As of January 13, 2021, approximately 76 cases of B.1.1.7 have been detected in 12 U.S. states. Multiple lines of evidence indicate that B.1.1.7 is more efficiently transmitted than are other SARS-CoV-2 variants (1-3). The modeled trajectory of this variant in the U.S. exhibits rapid growth in early 2021, becoming the predominant variant in March. Increased SARS-CoV-2 transmission might threaten strained health care resources, require extended and more rigorous implementation of public health strategies (4), and increase the percentage of population immunity required for pandemic control. Taking measures to reduce transmission now can lessen the potential impact of B.1.1.7 and allow critical time to increase vaccination coverage. Collectively, enhanced genomic surveillance combined with continued compliance with effective public health measures, including vaccination, physical distancing, use of masks, hand hygiene, and isolation and quarantine, will be essential to limiting the spread of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). Strategic testing of persons without symptoms but at higher risk of infection, such as those exposed to SARS-CoV-2 or who have frequent unavoidable contact with the public, provides another opportunity to limit ongoing spread.

In January 2015, an outbreak of undiagnosed human immunodeficiency virus (HIV) infections among persons who inject drugs (PWID) was recognized in rural Indiana. By September 2016, 205 persons in this community of approximately 4400 had received a diagnosis of HIV infection. We report results of new approaches to analyzing epidemiologic and laboratory data to understand transmission during this outbreak. HIV genetic distances were calculated using the polymerase region. Networks were generated using data about reported high-risk contacts, viral genetic similarity, and their most parsimonious combinations. Sample collection dates and recency assay results were used to infer dates of infection. Epidemiologic and laboratory data each generated large and dense networks. Integration of these data revealed subgroups with epidemiologic and genetic commonalities, one of which appeared to contain the earliest infections. Predicted infection dates suggest that transmission began in 2011, underwent explosive growth in mid-2014, and slowed after the declaration of a public health emergency. Results from this phylodynamic analysis suggest that the majority of infections had likely already occurred when the investigation began and that early transmission may have been associated with sexual activity and injection drug use. Early and sustained efforts are needed to detect infections and prevent or interrupt rapid transmission within networks of uninfected PWID.

Background. Traditional cardiovascular disease (CVD) risk factors, human immunodeficiency virus (HIV) infection, and antiretroviral (ARV) agents have been associated with CVD events in HIV-infected patients. We investigated the association of low CD4+ T lymphocyte cell count with incident CVD in a cohort of outpatients treated in 10 HIV specialty clinics in the United States. Methods. We studied patients who were under observation from 1 January 2002 (baseline), categorized them according to National Cholesterol Education Program guidelines into 10-year cardiovascular risk score (10-y CVR) groups, and observed them until CVD event, death, last HIV Outpatient Study contact, or 30 September 2009. We calculated rates of incident CVD events and identified associated baseline risk factors using Cox proportional hazard models. We also performed a nested case-control study to examine the association of latest CD4+ cell count with CVD events. Results. Among 2005 patients, 148 experienced incident CVD events. CVD incidence increased steadily from 0.4 to 3.0 events per 100 person-years from lowest to highest 10-y CVR group ( P < .001). In multivariable Cox analyses adjusted for 10-y CVR, CD4+ cell count <350 cells/mm3 was associated with incident CVD events (hazard ratio, 1.58 [95% confidence interval, 1.09–2.30], compared with 1500 cells/mm3), suggesting an attributable risk of ∼20%. In the multivariable case-control analyses, traditional CVD risk factors and latest CD4+ cell count <500 cells/mm3, but not cumulative use of ARV class or individual drugs, were associated with higher odds of experiencing CVD events. Conclusion. CD4+ count <500 cells/mm3 is an independent risk factor for incident CVD, comparable in attributable risk to several traditional CVD risk factors in the HIV Outpatient Study cohort.

Immune activation plays a key role in HIV pathogenesis. Markers of inflammation have been associated with vitamin D deficiency in the general population. Studies have also demonstrated associations of vitamin D deficiency with increased risk of HIV progression and death. The relationship between persistent inflammation and immune activation during chronic HIV infection and vitamin D deficiency remains unclear. Cryopreserved specimens were analyzed from 663 participants at the time of enrollment from the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (SUN Study) from 2004 to 2006. Biomarkers of inflammation, atherosclerosis, and coagulation were measured using enzyme-linked immunosorbent assays (ELISAs) and electrochemiluminescence. 25(OH)D, the stable precursor form of vitamin D, was measured using a radioimmunoassay with levels defined as: normal (≥30ng/mL), insufficient (20-29 ng/mL) and deficient (<20 ng/mL). Monocyte phenotypes were assessed by flow cytometry. Linear and logistic regression models were used to determine statistical associations between biomarkers and vitamin D deficiency. 25(OH)D levels were deficient in 251 (38%) participants, insufficient in 222 (34%), and normal in 190 (29%). Patients with vitamin D deficiency, when compared to those with insufficient or normal vitamin D levels, had increased levels of IL-6 (23%; p<0.01), TNF-α (21%, p = 0.03), D-dimer (24%, p = 0.01), higher proportions of CD14dimCD16+ (22%, p<0.01) and CX3CR1+ monocytes (48%; p<0.001) and decreased frequency of CCR2+ monocytes (-3.4%, p<0.001). In fully adjusted models, vitamin D associations with abnormal biomarker levels persisted for IL-6 levels and CX3CR1+ and CCR2+ phenotypes. Vitamin D deficiency is associated with greater inflammation and activated monocyte phenotypes. The role of vitamin D deficiency in persistent immune activation and associated complications during chronic HIV disease should be further evaluated as a possible target for intervention.

BackgroundShiga toxin–producing Escherichia coli (STEC) O157:H7 is a well-recognized cause of bloody diarrhea and hemolytic-uremic syndrome (HUS). Non-O157 STEC contribute to this burden of illness but have been underrecognized as a result of diagnostic limitations and inadequate surveillance MethodsBetween 1983 and 2002, 43 state public health laboratories submitted 940 human non-O157 STEC isolates from persons with sporadic illnesses to the Centers for Diseases Control and Prevention reference laboratory for confirmation and serotyping ResultsThe most common serogroups were O26 (22%), O111 (16%), O103 (12%), O121 (8%), O45 (7%), and O145 (5%). Non-O157 STEC infections were most frequent during the summer and among young persons (median age, 12 years; interquartile range, 3–37 years). Virulence gene profiles were as follows: 61% stx1 but not stx2; 22% stx2 but not stx1; 17% both stx1 and stx2; 84% intimin (eae); and 86% enterohemolysin (E-hly). stx2 was strongly associated with an increased risk of HUS, and eae was strongly associated with an increased risk of bloody diarrhea. STEC O111 accounted for most cases of HUS and was also the cause of 3 of 7 non-O157 STEC outbreaks reported in the United States ConclusionsNon-O157 STEC can cause severe illness that is comparable to the illness caused by STEC O157. Strains that produce Shiga toxin 2 are much more likely to cause HUS than are those that produce Shiga toxin 1 alone. Improving surveillance will more fully elucidate the incidence and pathological spectrum of these emerging agents. These efforts require increased clinical suspicion, improved clinical laboratory isolation, and continued serotyping of isolates in public health laboratories