Testing and Management of Iron Overload After Genetic Screening-Identified Hemochromatosis.

Importance: HFE gene-associated hereditary hemochromatosis type 1 (HH1) is underdiagnosed, resulting in missed opportunities for preventing morbidity and mortality. Objective: To assess whether screening for p.Cys282Tyr homozygosity is associated with recognition and management of asymptomatic iron overload. Design, Setting, and Participants: This cross-sectional study obtained data from the Geisinger MyCode Community Health Initiative, a biobank of biological samples and linked electronic health record data from a rural, integrated health care system. Participants included those who received a p.Cys282Tyr homozygous result via genomic screening (MyCode identified), had previously diagnosed HH1 (clinically identified), and those negative for p.Cys282Tyr homozygosity between 2017 and 2018. Data were analyzed from April 2020 to August 2023. Exposure: Disclosure of a p.Cys282Tyr homozygous result. Main Outcomes and Measures: Postdisclosure management and HFE-associated phenotypes in MyCode-identified participants were analyzed. Rates of HFE-associated phenotypes in MyCode-identified participants were compared with those of clinically identified participants. Relevant laboratory values and rates of laboratory iron overload among participants negative for p.Cys282Tyr homozygosity were compared with those of MyCode-identified participants. Results: A total of 86 601 participants had available exome sequences at the time of analysis, of whom 52 994 (61.4%) were assigned female at birth, and the median (IQR) age was 62.0 (47.0-73.0) years. HFE p.Cys282Tyr homozygosity was disclosed to 201 participants, of whom 57 (28.4%) had a prior clinical HH1 diagnosis, leaving 144 participants who learned of their status through screening. There were 86 300 individuals negative for p.Cys282Tyr homozygosity. After result disclosure, among MyCode-identified participants, 99 (68.8%) had a recommended laboratory test and 36 (69.2%) with laboratory or liver biopsy evidence of iron overload began phlebotomy or chelation. Fifty-three (36.8%) had iron overload; rates of laboratory iron overload were higher in MyCode-identified participants than participants negative for p.Cys282Tyr homozygosity (females: 34.1% vs 2.1%, P < .001; males: 39.0% vs 2.9%, P < .001). Iron overload (females: 34.1% vs 79.3%, P < .001; males: 40.7% vs 67.9%, P = .02) and some liver-associated phenotypes were observed at lower frequencies in MyCode-identified participants compared with clinically identified individuals. Conclusions and Relevance: Results of this cross-sectional study showed the ability of genomic screening to identify undiagnosed iron overload and encourage relevant management, suggesting the potential benefit of population screening for HFE p.Cys282Tyr homozygosity. Further studies are needed to examine the implications of genomic screening for health outcomes and cost-effectiveness.

Evaluation of Saccharomyces cerevisiae -like 1 (SEC14L1) in Gynecologic Malignancies Shows Overexpression in Endometrial Serous Carcinoma.

Saccharomyces cerevisiae -like 1 ( SEC14L1 ) is a member of the SEC14 family and is involved in liposoluble vitamin transfer, and in a large cohort of breast cancer cases, was one of the genes most significantly associated with lymphovascular invasion (LVI), and had a significant relationship with human epidermal growth factor receptor 2 status, survival, and histologic grade. In this study, 111 separate gynecologic tumors were studied for SEC14L1 protein expression, including: uterine adenosarcoma, ovarian clear cell carcinoma, endometrial stromal sarcoma, endometrioid carcinoma of the uterus, high-grade serous carcinoma, ovarian endometrioid carcinoma, uterine leiomyosarcoma, low-grade serous carcinoma, uterine carcinosarcoma, and uterine serous carcinoma (USC). Overall, LVI was noted in 31/111 (28%) cases, highest in uterine carcinosarcoma (5/11; 45%), high-grade serous carcinoma (9/21; 43%), and ovarian clear cell carcinoma (4/10; 40%). SEC14L1 was positive in 25/111 (23%) cases; the highest percentage and only statistically significant finding by tumor type was USC at 9/12 (75%) cases positive. No relation between LVI or survival and SEC14L1 expression was noted. The relation between USC, a tumor known to show human epidermal growth factor receptor 2 overexpression and SEC14L1 is a novel finding, the significance of which warrants further study.

Divergent preferences for enhanced HIV testing options among high-risk populations in northern Tanzania: a short report.

To achieve the UNAIDS target of diagnosing 95% of all persons living with HIV, enhanced HIV testing services with greater attractional value need to be developed and implemented. We conducted a discrete choice experiment (DCE) to quantify preferences for enhanced HIV testing features across two high-risk populations in the Kilimanjaro Region in northern Tanzania. We designed and fielded a survey with 12 choice tasks to systematically recruited female barworkers and male mountain porters. Key enhanced features included: testing availability on every day of the week, an oral test, integration of a general health check or an examination for sexually transmitted infections (STI) with HIV testing, and provider-assisted confidential partner notification in the event of a positive HIV test result. Across 300 barworkers and 440 porters surveyed, mixed logit analyses of 17,760 choices indicated strong preferences for everyday testing availability, health checks, and STI examinations. Most participants were averse to oral testing and confidential partner notification by providers. Substantial preference heterogeneity was observed within each risk group. Enhancing HIV testing services to include options for everyday testing, general health checks, and STI examinations may increase the appeal of HIV testing offers to high-risk populations.Trial registration: ClinicalTrials.gov identifier: NCT02714140.

Clinical validation of genomic functional screen data: Analysis of observed BRCA1 variants in an unselected population cohort.

Functional assessment of genomic variants provides a promising approach to systematically examine the potential pathogenicity of variants independent of associated clinical data. However, making such conclusions requires validation with appropriate clinical findings. To this end, here, we use variant calls from exome data and BRCA1-related cancer diagnoses from electronic health records to demonstrate an association between published laboratory-based functional designations of BRCA1 variants and BRCA1-related cancer diagnoses in an unselected cohort of patient-participants. These findings validate and support further exploration of functional assay data to better understand the pathogenicity of rare variants. This information may be valuable in the context of healthy population genomic screening, where many rare, potentially pathogenic variants may not have sufficient associated clinical data to inform their interpretation directly.

Clinician Conceptualization of the Benefits of Treatments for Individual Patients.

Importance: Knowing the expected effect of treatment on an individual patient is essential for patient care. Objective: To explore clinicians' conceptualizations of the chance that treatments will decrease the risk of disease outcomes. Design, Setting, and Participants: This survey study of attending and resident physicians, nurse practitioners, and physician assistants was conducted in outpatient clinical settings in 8 US states from June 2018 to November 2019. The survey was an in-person, paper, 26-item survey in which clinicians were asked to estimate the probability of adverse disease outcomes and expected effects of therapies for diseases common in primary care. Main Outcomes and Measures: Estimated chance that treatments would benefit an individual patient. Results: Of 723 clinicians, 585 (81%) responded, and 542 completed all the questions necessary for analysis, with a median (interquartile range [IQR]) age of 32 (29-44) years, 287 (53%) women, and 294 (54%) White participants. Clinicians consistently overestimated the chance that treatments would benefit an individual patient. The median (IQR) estimated chance that warfarin would prevent a stroke in the next year was 50% (5%-80%) compared with scientific evidence, which indicates an absolute risk reduction (ARR) of 0.2% to 1.0% based on a relative risk reduction (RRR) of 39% to 50%. The median (IQR) estimated chance that antihypertensive therapy would prevent a cardiovascular event within 5 years was 30% (10%-70%) vs evidence of an ARR of 0% to 3% based on an RRR of 0% to 28%. The median (IQR) estimated chance that bisphosphonate therapy would prevent a hip fracture in the next 5 years was 40% (10%-60%) vs evidence of ARR of 0.1% to 0.4% based on an RRR of 20% to 40%. The median (IQR) estimated chance that moderate-intensity statin therapy would prevent a cardiovascular event in the next 5 years was 20% (IQR 5%-50%) vs evidence of an ARR of 0.3% to 2% based on an RRR of 19% to 33%. Estimates of the chance that a treatment would prevent an adverse outcome exceeded estimates of the absolute chance of that outcome for 60% to 70% of clinicians. Clinicians whose overestimations were greater were more likely to report using that treatment for patients in their practice (eg, use of warfarin: correlation coefficient, 0.46; 95% CI, 0.40-0.53; P < .001). Conclusions and Relevance: In this survey study, clinicians significantly overestimated the benefits of treatment to individual patients. Clinicians with greater overestimates were more likely to report using treatments in actual patients.

Accuracy of Practitioner Estimates of Probability of Diagnosis Before and After Testing.

Importance: Accurate diagnosis is essential to proper patient care. Objective: To explore practitioner understanding of diagnostic reasoning. Design, Setting, and Participants: In this survey study, 723 practitioners at outpatient clinics in 8 US states were asked to estimate the probability of disease for 4 scenarios common in primary care (pneumonia, cardiac ischemia, breast cancer screening, and urinary tract infection) and the association of positive and negative test results with disease probability from June 1, 2018, to November 26, 2019. Of these practitioners, 585 responded to the survey, and 553 answered all of the questions. An expert panel developed the survey and determined correct responses based on literature review. Results: A total of 553 (290 resident physicians, 202 attending physicians, and 61 nurse practitioners and physician assistants) of 723 practitioners (76.5%) fully completed the survey (median age, 32 years; interquartile range, 29-44 years; 293 female [53.0%]; 296 [53.5%] White). Pretest probability was overestimated in all scenarios. Probabilities of disease after positive results were overestimated as follows: pneumonia after positive radiology results, 95% (evidence range, 46%-65%; comparison P < .001); breast cancer after positive mammography results, 50% (evidence range, 3%-9%; P < .001); cardiac ischemia after positive stress test result, 70% (evidence range, 2%-11%; P < .001); and urinary tract infection after positive urine culture result, 80% (evidence range, 0%-8.3%; P < .001). Overestimates of probability of disease with negative results were also observed as follows: pneumonia after negative radiography results, 50% (evidence range, 10%-19%; P < .001); breast cancer after negative mammography results, 5% (evidence range, <0.05%; P < .001); cardiac ischemia after negative stress test result, 5% (evidence range, 0.43%-2.5%; P < .001); and urinary tract infection after negative urine culture result, 5% (evidence range, 0%-0.11%; P < .001). Probability adjustments in response to test results varied from accurate to overestimates of risk by type of test (imputed median positive and negative likelihood ratios [LRs] for practitioners for chest radiography for pneumonia: positive LR, 4.8; evidence, 2.6; negative LR, 0.3; evidence, 0.3; mammography for breast cancer: positive LR, 44.3; evidence range, 13.0-33.0; negative LR, 1.0; evidence range, 0.05-0.24; exercise stress test for cardiac ischemia: positive LR, 21.0; evidence range, 2.0-2.7; negative LR, 0.6; evidence range, 0.5-0.6; urine culture for urinary tract infection: positive LR, 9.0; evidence, 9.0; negative LR, 0.1; evidence, 0.1). Conclusions and Relevance: This survey study suggests that for common diseases and tests, practitioners overestimate the probability of disease before and after testing. Pretest probability was overestimated in all scenarios, whereas adjustment in probability after a positive or negative result varied by test. Widespread overestimates of the probability of disease likely contribute to overdiagnosis and overuse.

Developing and Optimizing Innovative Tools to Address Familial Hypercholesterolemia Underdiagnosis: Identification Methods, Patient Activation, and Cascade Testing for Familial Hypercholesterolemia.

BACKGROUND: Familial hypercholesterolemia (FH) is the most common cardiovascular genetic disorder and, if left untreated, is associated with increased risk of premature atherosclerotic cardiovascular disease, the leading cause of preventable death in the United States. Although FH is common, fatal, and treatable, it is underdiagnosed and undertreated due to a lack of systematic methods to identify individuals with FH and limited uptake of cascade testing. METHODS AND RESULTS: This mixed-method, multi-stage study will optimize, test, and implement innovative approaches for both FH identification and cascade testing in 3 aims. To improve identification of individuals with FH, in Aim 1, we will compare and refine automated phenotype-based and genomic approaches to identify individuals likely to have FH. To improve cascade testing uptake for at-risk individuals, in Aim 2, we will use a patient-centered design thinking process to optimize and develop novel, active family communication methods. Using a prospective, observational pragmatic trial, we will assess uptake and effectiveness of each family communication method on cascade testing. Guided by an implementation science framework, in Aim 3, we will develop a comprehensive guide to identify individuals with FH. Using the Conceptual Model for Implementation Research, we will evaluate implementation outcomes including feasibility, acceptability, and perceived sustainability as well as health outcomes related to the optimized methods and tools developed in Aims 1 and 2. CONCLUSIONS: Data generated from this study will address barriers and gaps in care related to underdiagnosis of FH by developing and optimizing tools to improve FH identification and cascade testing.

What factors influence HIV testing? Modeling preference heterogeneity using latent classes and class-independent random effects.

Efforts to eliminate the HIV epidemic will require increased HIV testing rates among high-risk populations. To inform the design of HIV testing interventions, a discrete choice experiment (DCE) with six policy-relevant attributes of HIV testing options elicited the testing preferences of 300 female barworkers and 440 male Kilimanjaro mountain porters in northern Tanzania. Surveys were administered between September 2017 and July 2018. Participants were asked to complete 12 choice tasks, each involving first- and second-best choices from 3 testing options. DCE responses were analyzed using a random effects latent class logit (RELCL) model, in which the latent classes summarize common participant preference profiles, and the random effects capture additional individual-level preference heterogeneity with respect to three attribute domains: (a) privacy and confidentiality (testing venue, pre-test counseling, partner notification); (b) invasiveness and perceived accuracy (method for obtaining the sample for the HIV test); and (c) accessibility and value (testing availability, additional services provided). The Bayesian Information Criterion indicated the best model fit for a model with 8 preference classes, with class sizes ranging from 6% to 19% of participants. Substantial preference heterogeneity was observed, both between and within latent classes, with 12 of 16 attribute levels having positive and negative coefficients across classes, and all three random effects contributing significantly to participants' choices. The findings may help identify combinations of testing options that match the distribution of HIV testing preferences among high-risk populations; the methods may be used to systematically design heterogeneity-focused interventions using stated preference methods.

Using discrete choice experiments to design interventions for heterogeneous preferences: protocol for a pragmatic randomised controlled trial of a preference-informed, heterogeneity-focused, HIV testing offer for high-risk populations.

INTRODUCTION: Approximately one million undiagnosed persons living with HIV in Southern and Eastern Africa need to test for HIV. Novel approaches are necessary to identify HIV testing options that match the heterogeneous testing preferences of high-risk populations. This pragmatic randomised controlled trial (PRCT) will evaluate the efficacy of a preference-informed, heterogeneity-focused HIV counselling and testing (HCT) offer, for improving rates of HIV testing in two high-risk populations. METHODS AND ANALYSIS: The study will be conducted in Moshi, Tanzania. The PRCT will randomise 600 female barworkers and 600 male Kilimanjaro mountain porters across three study arms. All participants will receive an HIV testing offer comprised of four preference-informed testing options, including one 'common' option-comprising features that are commonly available in the area and, on average, most preferred among study participants-and three options that are specific to the study arm. Options will be identified using mixed logit and latent class analyses of data from a discrete choice experiment (DCE). Participants in Arm 1 will be offered the common option and three 'targeted' options that are predicted to be more preferred than the common option and combine features widely available in the study area. Participants in Arm 2 will be offered the common option and three 'enhanced' options, which also include HCT features that are not yet widely available in the study area. Participants in Arm 3, an active control arm, will be offered the common option and three predicted 'less preferred' options. The primary outcome will be uptake of HIV testing. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Duke University Health System IRB, the University of South Carolina IRB, the Ethics Review Committee at Kilimanjaro Christian Medical University College, Tanzania's National Institute for Medical Research, and the Tanzania Food & Drugs Authority (now Tanzania Medicines & Medical Devices Authority). Findings will be published in peer-reviewed journals. The use of rigorous DCE methods for the preference-based design and tailoring of interventions could lead to novel policy options and implementation science approaches. TRIAL REGISTRATION NUMBER: NCT02714140.

Can National Healthcare-Associated Infections (HAIs) Data Differentiate Hospitals in the United States?

OBJECTIVE To determine whether patients using the Centers for Medicare and Medicaid Services (CMS) Hospital Compare website (http://medicare.gov/hospitalcompare) can use nationally reported healthcare-associated infection (HAI) data to differentiate hospitals. DESIGN Secondary analysis of publicly available HAI data for calendar year 2013. METHODS We assessed the availability of HAI data for geographically proximate hospitals (ie, hospitals within the same referral region) and then analyzed these data to determine whether they are useful to differentiate hospitals. We assessed data for the 6 HAIs reported by hospitals to the Centers for Disease Control and Prevention (CDC). RESULTS Data were analyzed for 4,561 hospitals representing 88% of registered community and federal government hospitals in the United States. Healthcare-associated infection data are only useful for comparing hospitals if they are available for multiple hospitals within a geographic region. We found that data availability differed by HAI. Clostridium difficile infections (CDI) data were most available, with 82% of geographic regions (ie, hospital referral regions) having >50% of hospitals reporting them. In contrast, 4% of geographic regions had >50% of member hospitals reporting surgical site infections (SSI) for hysterectomies, which had the lowest availability. The ability of HAI data to differentiate hospitals differed by HAI: 72% of hospital referral regions had at least 1 pair of hospitals with statistically different risk-adjusted CDI rates (SIRs), compared to 9% for SSI (hysterectomy). CONCLUSIONS HAI data generally are reported by enough hospitals to meet minimal criteria for useful comparisons in many geographic locations, though this varies by type of HAI. CDI and catheter-associated urinary tract infection (CAUTI) are more likely to differentiate hospitals than the other publicly reported HAIs. Infect Control Hosp Epidemiol 2017;38:1167-1171.

Indirect Versus Direct Standardization Methods for Reporting Healthcare-Associated Infections: An Analysis of Central Line-Associated Bloodstream Infections in Maryland.

Whether healthcare-associated infection data should be presented using indirect (current CMS/CDC methodology) or direct standardization remains controversial. We applied both methods to central-line-associated bloodstream infection data from 45 acute-care hospitals in Maryland from 2012 to 2014. We found that the 2 methods generate different hospital rankings with payment implications. Infect Control Hosp Epidemiol 2017;38:989-992.

Improving the Understanding of Publicly Reported Healthcare-Associated Infection (HAI) Data.

OBJECTIVE Hospital-acquired infection (HAI) data are reported to the public on the Centers for Medicare and Medicaid Services (CMS) Hospital Compare website. We previously found that public understanding of these data is poor. Our objective was to develop an improved method for presenting HAI data that could be used on the CMS website. DESIGN Randomized controlled trial comparing understanding of data presented using the current CMS presentation strategy versus a new strategy. SETTING A 760-bed tertiary referral hospital. PARTICIPANTS A total of 61 patients were randomly selected within 24 hours of admission. INTERVENTION Participants were shown HAI data as presented on the CMS Hospital Compare website (control arm) or data formatted using a new method (experimental arm). RESULTS No statistically significant demographic differences were identified between study arms. Although 47% percent of participants said a website for comparing hospitals would have been helpful, only 10% had ever used such a website. Participants viewing data using the new presentation strategy compared hospitals correctly 56% of the time, compared with 32% in the control arm (P=.0002). CONCLUSIONS Understanding of HAI data increased significantly with the new data presentation method compared to the method currently used on the CMS Hospital Compare website. Many participants expressed interest in a website for comparing hospitals. Improved methods for presenting CMS HAI data, such as the one assessed here, should be adopted to increase public understanding. Infect Control Hosp Epidemiol 2016;1-6.

Lack of Patient Understanding of Hospital-Acquired Infection Data Published on the Centers for Medicare and Medicaid Services Hospital Compare Website.

BACKGROUND: Public reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex. OBJECTIVE: To assess interpretability of HAI data as presented on the Centers for Medicare and Medicaid Services Hospital Compare website among patients who might benefit from access to these data. METHODS: We randomly selected inpatients at a large tertiary referral hospital from June to September 2014. Participants performed 4 distinct tasks comparing hypothetical HAI data for 2 hospitals, and the accuracy of their comparisons was assessed. Data were presented using the same tabular formats used by Centers for Medicare and Medicaid Services. Demographic characteristics and healthcare experience data were also collected. RESULTS: Participants (N=110) correctly identified the better of 2 hospitals when given written descriptions of the HAI measure in 72% of the responses (95% CI, 66%-79%). Adding the underlying numerical data (number of infections, patient-time, and standardized infection ratio) to the written descriptions reduced correct responses to 60% (55%-66%). When the written HAI measure description was not informative (identical for both hospitals), 50% answered correctly (42%-58%). When no written HAI measure description was provided and hospitals differed by denominator for infection rate, 38% answered correctly (31%-45%). CONCLUSIONS: Current public HAI data presentation methods may be inadequate. When presented with numeric HAI data, study participants incorrectly compared hospitals on the basis of HAI data in more than 40% of the responses. Research is needed to identify better ways to convey these data to the public.

Frequency and predictors of seasonal influenza vaccination and reasons for refusal among patients at a large tertiary referral hospital.

We assessed frequency and predictors of seasonal influenza vaccination acceptance among inpatients at a large tertiary referral hospital, as well as reasons for vaccination refusal. Over 5 seasons, >60% of patients unvaccinated on admission refused influenza vaccination while hospitalized; "believes not at risk" was the reason most commonly given.

Risk factors for central-line-associated bloodstream infections: a focus on comorbid conditions.

Centers for Disease Control and Prevention (CDC) risk adjustment methods for central-line-associated bloodstream infections (CLABSI) only adjust for type of intensive care unit (ICU). This cohort study explored risk factors for CLABSI using 2 comorbidity classification schemes, the Charlson Comorbidity Index (CCI) and the Chronic Disease Score (CDS). Our study supports the need for additional research into risk factors for CLABSI, including electronically available comorbid conditions.

Survey of infection prevention informatics use and practitioner satisfaction in US hospitals.

We surveyed hospital epidemiologists and infection preventionists on their usage of and satisfaction with infection prevention-specific software supplementing their institution's electronic medical record. Respondents with supplemental software were more satisfied with their software's infection prevention and antimicrobial stewardship capabilities than those without. Infection preventionists were more satisfied than hospital epidemiologists.

Frequency of Klebsiella pneumoniae carbapenemase (KPC)-producing and non-KPC-producing Klebsiella species contamination of healthcare workers and the environment.

We examined contamination of healthcare worker (HCW) gown and gloves after caring for patients with Klebsiella pneumoniae carbapenemase (KPC)-producing and non-KPC-producing Klebsiella as a proxy for horizontal transmission. The rate of contamination with Klebsiella species is similar to that of contamination with methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococcus, with 31 (14%) of 220 of HCW-patient interactions resulting in contamination of gloves and gowns.

A brief assessment of learning for orphaned and abandoned children in low and middle income countries.

Assessment of children's learning and performance in low and middle income countries has been critiqued as lacking a gold standard, an appropriate norm reference group, and demonstrated applicability of assessment tasks to the context. This study was designed to examine the performance of three nonverbal and one adapted verbal measure of children's problem solving, memory, motivation, and attention across five culturally diverse sites. The goal was to evaluate the tests as indicators of individual differences affected by life events and care circumstances for vulnerable children. We conclude that the measures can be successfully employed with fidelity in non-standard settings in LMICs, and are associated with child age and educational experience across the settings. The tests can be useful in evaluating variability in vulnerable child outcomes.

A cost-effectiveness analysis of alternative HIV retesting strategies in sub-saharan Africa.

BACKGROUND: Guidelines in sub-Saharan Africa on when HIV-seronegative persons should retest range from never to annually for lower-risk populations and from annually to every 3 months for high-risk populations. METHODS: We designed a mathematical model to compare the cost-effectiveness of alternative HIV retesting frequencies. Cost of HIV counseling and testing, linkage to care, treatment costs, disease progression, and mortality, and HIV transmission are modeled for three hypothetical cohorts with posited annual HIV incidence of 0.8%, 1.3%, and 4.0%, respectively. The model compared costs, quality-adjusted life-years gained, and secondary infections averted from testing intervals ranging from 3 months to 30 years. Input parameters from sub-Saharan Africa were used and explored in sensitivity analyses. RESULTS: Accounting for secondary infections averted, the most cost-effective testing frequency was every 7.5 years for 0.8% incidence, every 5 years for 1.3% incidence, and every 2 years for 4.0% incidence. Optimal testing strategies and their relative cost-effectiveness were most sensitive to assumptions about HIV counseling and testing and treatment costs, rates of CD4 decline, rates of HIV transmission, and whether tertiary infections averted were taken into account. CONCLUSIONS: While higher risk populations merit more frequent HIV testing than low risk populations, regular retesting is beneficial even in low-risk populations. Our data demonstrate benefits of tailoring testing intervals to resource constraints and local HIV incidence rates.

Identification of genetic determinants of a tick-borne flavivirus associated with host-specific adaptation and pathogenicity.

Tick-borne flaviviruses are maintained in nature in an enzootic cycle involving a tick vector and a vertebrate host. Thus, the virus replicates in two disparate hosts, each providing selective pressures that can influence virus replication and pathogenicity. To identify viral determinants associated with replication in the individual hosts, plaque purified Langat virus (TP21pp) was adapted to growth in mouse or tick cell lines to generate two virus variants, MNBp20 and ISEp20, respectively. Virus adaptation to mouse cells resulted in four amino acid changes in MNBp20 relative to TP21pp, occurring in E, NS4A and NS4B. A comparison between TP21pp and ISEp20 revealed three amino acid modifications in M, NS3 and NS4A of ISEp20. ISEp20, but not MNBp20, was attenuated following intraperitoneal inoculation of mice. Following isolation from mice brains, additional mutations reproducibly emerged in E and NS3 of ISEp20 that were possibly compensatory for the initial adaptation to tick cells. Thus, our data implicate a role for E, M, NS3, NS4A and NS4B in host adaptation and pathogenicity of tick-borne flaviviruses.