Evaluation of multi-assay algorithms for identifying individuals with recent HIV infection: HPTN 071 (PopART)

Background Assays and multi-assay algorithms (MAAs) have been developed for population-level cross-sectional HIV incidence estimation. These algorithms use a combination of serologic and/or non-serologic biomarkers to assess the duration of infection. We evaluated the performance of four MAAs for individual-level recency assessments. Methods Samples were obtained from 220 seroconverters (infected <1 year) and 4,396 non-seroconverters (infected >1 year) enrolled in an HIV prevention trial (HPTN 071 [PopART]); 28.6% of the seroconverters and 73.4% of the non-seroconverters had HIV viral loads ≤400 copies/mL. Samples were tested with two laboratory-based assays (LAg-Avidity, JHU BioRad-Avidity) and a point-of-care assay (rapid LAg). The four MAAs included different combinations of these assays and HIV viral load. Seroconverters on antiretroviral treatment (ART) were identified using a qualitative multi-drug assay. Results The MAAs identified between 54 and 100 (25% to 46%) of the seroconverters as recently-infected. The false recent rate of the MAAs for infections >2 years duration ranged from 0.2%-1.3%. The MAAs classified different overlapping groups of individuals as recent vs. non-recent. Only 32 (15%) of the 220 seroconverters were classified as recent by all four MAAs. Viral suppression impacted the performance of the two LAg-based assays. LAg-Avidity assay values were also lower for seroconverters who were virally suppressed on ART compared to those with natural viral suppression. Conclusions The four MAAs evaluated varied in sensitivity and specificity for identifying persons infected <1 year as recently infected and classified different groups of seroconverters as recently infected. Sensitivity was low for all four MAAs. These performance issues should be considered if these methods are used for individual-level recency assessments.

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Estimating epidemiologic dynamics from single cross-sectional viral load distributions

10.1101/2020.10.08.20204222 ◽

2020 ◽

Cited By ~ 4

Author(s):

James A. Hay ◽

Lee Kennedy-Shaffer ◽

Sanjat Kanjilal ◽

Marc Lipsitch ◽

Michael J. Mina

Keyword(s):

Public Health ◽

Growth Rate ◽

Viral Load ◽

Population Level ◽

Accurate Estimation ◽

Cross Sectional ◽

Individual Level ◽

Viral Loads ◽

Single Cross ◽

Testing Practices

AbstractVirologic testing for SARS-CoV-2 has been central to the COVID-19 pandemic response, but interpreting changes in incidence and fraction of positive tests towards understanding the epidemic trajectory is confounded by changes in testing practices. Here, we show that the distribution of viral loads, in the form of Cycle thresholds (Ct), from positive surveillance samples at a single point in time can provide accurate estimation of an epidemic’s trajectory, subverting the need for repeated case count measurements which are frequently obscured by changes in testing capacity. We identify a relationship between the population-level cross-sectional distribution of Ct values and the growth rate of the epidemic, demonstrating how the skewness and median of detectable Ct values change purely as a mathematical epidemiologic rule without any change in individual level viral load kinetics or testing. Although at the individual level measurement variation can complicate interpretation of Ct values for clinical use, we show that population-level properties reflect underlying epidemic dynamics. In support of these theoretical findings, we observe a strong relationship between the time-varying effective reproductive number, R(t), and the distribution of Cts among positive surveillance specimens, including median and skewness, measured in Massachusetts over time. We use the observed relationships to derive a novel method that allows accurate inference of epidemic growth rate using the distribution of Ct values observed at a single cross-section in time, which, unlike estimates based on case counts, is less susceptible to biases from delays in test results and from changing testing practices. Our findings suggest that instead of discarding individual Ct values from positive specimens, incorporation of viral loads into public health data streams offers a new approach for real-time resource allocation and assessment of outbreak mitigation strategies, even where repeat incidence data is not available. Ct values or similar viral load data should be regularly reported to public health officials by testing centers and incorporated into monitoring programs.

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Examining the Effects of the Sacramento Dockless E-Bike Share on Bicycling and Driving

Sustainability ◽

10.3390/su13010368 ◽

2021 ◽

Vol 13 (1) ◽

pp. 368

Author(s):

Dillon T. Fitch ◽

Hossain Mohiuddin ◽

Susan L. Handy

Keyword(s):

Travel Behavior ◽

Regression Models ◽

Population Level ◽

Panel Survey ◽

Multilevel Regression ◽

Combine Data ◽

Cross Sectional ◽

Individual Level ◽

Before And After ◽

Bike Share

One way cities are looking to promote bicycling is by providing publicly or privately operated bike-share services, which enable individuals to rent bicycles for one-way trips. Although many studies have examined the use of bike-share services, little is known about how these services influence individual-level travel behavior more generally. In this study, we examine the behavior of users and non-users of a dockless, electric-assisted bike-share service in the Sacramento region of California. This service, operated by Jump until suspended due to the coronavirus pandemic, was one of the largest of its kind in the U.S., and spanned three California cities: Sacramento, West Sacramento, and Davis. We combine data from a repeat cross-sectional before-and-after survey of residents and a longitudinal panel survey of bike-share users with the goal of examining how the service influenced individual-level bicycling and driving. Results from multilevel regression models suggest that the effect of bike-share on average bicycling and driving at the population level is likely small. However, our results indicate that people who have used-bike share are likely to have increased their bicycling because of bike-share.

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Urine Spot Samples Can Be Used to Estimate 24-Hour Urinary Sodium Excretion in Children

Journal of Nutrition ◽

10.1093/jn/nxy211 ◽

2018 ◽

Vol 148 (12) ◽

pp. 1946-1953 ◽

Cited By ~ 6

Author(s):

Magali Rios-Leyvraz ◽

Pascal Bovet ◽

René Tabin ◽

Bernard Genin ◽

Michel Russo ◽

...

Keyword(s):

Sodium Excretion ◽

Salt Intake ◽

Sodium Intake ◽

Population Level ◽

Urinary Sodium Excretion ◽

Cross Sectional Study ◽

Urinary Sodium ◽

Cross Sectional ◽

High Sodium ◽

Individual Level

ABSTRACT Background The gold standard to assess salt intake is 24-h urine collections. Use of a urine spot sample can be a simpler alternative, especially when the goal is to assess sodium intake at the population level. Several equations to estimate 24-h urinary sodium excretion from urine spot samples have been tested in adults, but not in children. Objective The objective of this study was to assess the ability of several equations and urine spot samples to estimate 24-h urinary sodium excretion in children. Methods A cross-sectional study of children between 6 and 16 y of age was conducted. Each child collected one 24-h urine sample and 3 timed urine spot samples, i.e., evening (last void before going to bed), overnight (first void in the morning), and morning (second void in the morning). Eight equations (i.e., Kawasaki, Tanaka, Remer, Mage, Brown with and without potassium, Toft, and Meng) were used to estimate 24-h urinary sodium excretion. The estimates from the different spot samples and equations were compared with the measured excretion through the use of several statistics. Results Among the 101 children recruited, 86 had a complete 24-h urine collection and were included in the analysis (mean age: 10.5 y). The mean measured 24-h urinary sodium excretion was 2.5 g (range: 0.8–6.4 g). The different spot samples and equations provided highly heterogeneous estimates of the 24-h urinary sodium excretion. The overnight spot samples with the Tanaka and Brown equations provided the most accurate estimates (mean bias: −0.20 to −0.12 g; correlation: 0.48–0.53; precision: 69.7–76.5%; sensitivity: 76.9–81.6%; specificity: 66.7%; and misclassification: 23.0–27.7%). The other equations, irrespective of the timing of the spot, provided less accurate estimates. Conclusions Urine spot samples, with selected equations, might provide accurate estimates of the 24-h sodium excretion in children at a population level. At an individual level, they could be used to identify children with high sodium excretion. This study was registered at clinicaltrials.gov as NCT02900261.

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Annual and durable HIV retention in care and viral suppression among patients of Peter Ho Clinic, 2013-2017

PLoS ONE ◽

10.1371/journal.pone.0244376 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0244376

Author(s):

Debbie Y. Mohammed ◽

Lisa Marie Koumoulos ◽

Eugene Martin ◽

Jihad Slim

Keyword(s):

Medical Care ◽

Viral Suppression ◽

Virologic Failure ◽

Private Insurance ◽

Retention In Care ◽

P Value ◽

Hiv Viral Load ◽

Cross Sectional ◽

Persons Living With Hiv ◽

Urban Clinic

Objectives To determine rates of annual and durable retention in medical care and viral suppression among patients enrolled in the Peter Ho Clinic, from 2013–2017. Methods This is a retrospective review of medical record data in an urban clinic, located in Newark, New Jersey, a high prevalence area of persons living with HIV. Viral load data were electronically downloaded, in rolling 1-year intervals, in two-month increments, from January 1, 2013 to December 31, 2019. Three teams were established, and every two months, they were provided with an updated list of patients with virologic failure. Retention and viral suppression rates were first calculated for each calendar-year. After patients were determined to be retained/suppressed annually, the proportion of patients with durable retention and viral suppression were calculated in two, three, four, five and six-year periods. Descriptive statistics were used to summarize sample characteristics by retention in care, virologic failure and viral suppression with Pearson Chi-square; p-value <0.05 was statistically significant. Multiple logistic regression models identified patient characteristics associated with retention in medical care, virologic failure and suppression. Results As of December 31, 2017, 1000 (57%) patients were retained in medical care of whom 870 (87%) were suppressed. Between 2013 and 2016, decreases in annual (85% to 77%) and durable retention in care were noted: two-year (72% to 70%) and three-year (63% to 59%) periods. However, increases were noted for 2017, in annual (89%) and durable retention in the two-year period (79%). In the adjusted model, when compared to current patients, retention in care was less likely among patients reengaging in medical care (adjusted Odds Ratio (aOR): 0.77, 95% CI: 0.61–0.98) but more likely among those newly diagnosed from 2014–2017 (aOR: 1.57, 95% CI: 1.08–2.29), compared to those in care since 2013. A higher proportion of patients re-engaging in medical care had virologic failure than current patients (56% vs. 47%, p < 0.0001). As age decreased, virologic failure was more likely (p<0.0001). Between 2013 and 2017, increases in annual (74% to 87%) and durable viral suppression were noted: two-year (59% to 73%) and three-year (49% to 58%) periods. Viral suppression was more likely among patients retained in medical care up to 2017 versus those who were not (aOR: 5.52, 95% CI: 4.08–7.46). Those less likely to be suppressed were 20–29 vs. 60 years or older (aOR: 0.52, 95% CI: 0.28–0.97), had public vs. private insurance (aOR: 0.29, 95% CI: 0.15–0.55) and public vs. private housing (aOR: 0.59, 95% CI: 0.40–0.87). Conclusions Restructuring clinical services at this urban clinic was associated with improved viral suppression. However, concurrent interventions to ensure retention in medical care were not implemented. Both retention in care and viral suppression interventions should be implemented in tandem to achieve an end to the epidemic. Retention in care and viral suppression should be measured longitudinally, instead of cross-sectional yearly evaluations, to capture dynamic changes in these indicators.

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Modeling Dynamic Heterogeneity Using Gaussian Processes

Journal of Marketing Research ◽

10.1177/0022243719874047 ◽

2019 ◽

Vol 57 (1) ◽

pp. 55-77 ◽

Cited By ~ 3

Author(s):

Ryan Dew ◽

Asim Ansari ◽

Yang Li

Keyword(s):

Gaussian Processes ◽

Marketing Research ◽

Population Level ◽

Online Reviews ◽

Parameter Estimates ◽

Model Parameters ◽

Dynamic Heterogeneity ◽

Cross Sectional ◽

Individual Level ◽

The Rich

Marketing research relies on individual-level estimates to understand the rich heterogeneity of consumers, firms, and products. While much of the literature focuses on capturing static cross-sectional heterogeneity, little research has been done on modeling dynamic heterogeneity, or the heterogeneous evolution of individual-level model parameters. In this work, the authors propose a novel framework for capturing the dynamics of heterogeneity, using individual-level, latent, Bayesian nonparametric Gaussian processes. Similar to standard heterogeneity specifications, this Gaussian process dynamic heterogeneity (GPDH) specification models individual-level parameters as flexible variations around population-level trends, allowing for sharing of statistical information both across individuals and within individuals over time. This hierarchical structure provides precise individual-level insights regarding parameter dynamics. The authors show that GPDH nests existing heterogeneity specifications and that not flexibly capturing individual-level dynamics may result in biased parameter estimates. Substantively, they apply GPDH to understand preference dynamics and to model the evolution of online reviews. Across both applications, they find robust evidence of dynamic heterogeneity and illustrate GPDH’s rich managerial insights, with implications for targeting, pricing, and market structure analysis.

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Meeting UK dietary recommendations is associated with higher estimated consumer food costs: an analysis using the National Diet and Nutrition Survey and consumer expenditure data, 2008–2012

Public Health Nutrition ◽

10.1017/s1368980017003275 ◽

2017 ◽

Vol 21 (5) ◽

pp. 948-956 ◽

Cited By ~ 12

Author(s):

Nicholas RV Jones ◽

Tammy YN Tong ◽

Pablo Monsivais

Keyword(s):

Saturated Fat ◽

Population Level ◽

Cross Sectional Study ◽

Primary Outcome Measure ◽

Future Research ◽

Consumer Expenditure ◽

Dietary Recommendations ◽

Nutrition Survey ◽

Cross Sectional ◽

Individual Level

AbstractObjectiveTo test whether diets achieving recommendations from the UK’s Scientific Advisory Committee on Nutrition (SACN) were associated with higher monetary costs in a nationally representative sample of UK adults.DesignA cross-sectional study linking 4 d diet diaries in the National Diet and Nutrition Survey (NDNS) to contemporaneous food price data from a market research firm. The monetary cost of diets was assessed in relation to whether or not they met eight food- and nutrient-based recommendations from SACN. Regression models adjusted for potential confounding factors. The primary outcome measure was individual dietary cost per day and per 2000 kcal (8368 kJ).SettingUK.SubjectsAdults (n 2045) sampled between 2008 and 2012 in the NDNS.ResultsOn an isoenergetic basis, diets that met the recommendations for fruit and vegetables, oily fish, non-milk extrinsic sugars, fat, saturated fat and salt were estimated to be between 3 and 17 % more expensive. Diets meeting the recommendation for red and processed meats were 4 % less expensive, while meeting the recommendation for fibre was cost-neutral. Meeting multiple targets was also associated with higher costs; on average, diets meeting six or more SACN recommendations were estimated to be 29 % more costly than isoenergetic diets that met no recommendations.ConclusionsFood costs may be a population-level barrier limiting the adoption of dietary recommendations in the UK. Future research should focus on identifying systems- and individual-level strategies to enable consumers achieve dietary recommendations without increasing food costs. Such strategies may improve the uptake of healthy eating in the population.

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Association between RT-PCR Ct Values and COVID-19 New Daily Cases: A Multicenter Cross-Sectional Study

10.1101/2020.12.07.20245233 ◽

2020 ◽

Author(s):

Abdulkarim Abdulrahman ◽

Saad Mallah ◽

Abdulla Ismael AlAwadhi ◽

Simone Perna ◽

Essam Janahi ◽

...

Keyword(s):

Population Studies ◽

Population Level ◽

Female Gender ◽

Cross Sectional Study ◽

Newly Diagnosed ◽

Sectional Study ◽

Rt Pcr ◽

Cross Sectional ◽

Viral Loads ◽

Epidemiological Changes

Introduction: Proactive prediction of the epidemiologic dynamics of viral diseases and outbreaks of the likes of COVID-19 has remained a difficult pursuit for scientists, public health researchers, and policymakers. It is unclear whether RT-PCR Cycle Threshold (Ct) values of COVID-19 (or any other virus) as indicator of viral load, could represent a possible predictor for underlying epidemiological changes on a population level. Objectives: To investigate whether population-wide changes in SARS-CoV-2 RT-PCR Ct values over time are associated with the daily fraction of positive COVID-19 tests. In addition, this study analyses the factors that could influence the RT-PCR Ct values. Method: A retrospective cross-sectional study was conducted on 63,879 patients from May 4, 2020 to September 30, 2020, in all COVID-19 facilities in the Kingdom of Bahrain. Data collected included number of tests and newly diagnosed cases, as well as Ct values, age, gender nationality, and symptomatic status. Results: Ct values were found to be negatively and very weakly correlated with the fraction of daily positive cases in the population r = -0.06 (CI95%: -0.06; -0.05; p=0.001). The R-squared for the regression model (adjusting for age and number of daily tests) showed an accuracy of 45.3%. Ct Values showed an association with nationality (p=0.012). After the stratification, the association between Ct values and the fraction of daily positive cases was only maintained for the female gender and Bahraini-nationality. Symptomatic presentation was significantly associated with lower Ct values (higher viral loads). Ct values do not show any correlation with age (p=0.333) or gender (p=0.522). Conclusion: We report one of the first and largest studies to investigate the epidemiological associations of Ct values with COVID-19. Ct values offer a potentially simple and widely accessible tool to predict and model epidemiological dynamics on a population level. More population studies and predictive models from global cohorts are necessary.

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Bimodal distribution and set point HBV DNA viral loads in chronic infection: retrospective analysis of cohorts from the UK and South Africa

Wellcome Open Research ◽

10.12688/wellcomeopenres.15941.2 ◽

2020 ◽

Vol 5 ◽

pp. 113

Author(s):

Louise O. Downs ◽

Sabeehah Vawda ◽

Phillip Armand Bester ◽

Katrina A. Lythgoe ◽

Tingyan Wang ◽

...

Keyword(s):

South Africa ◽

Large Population ◽

Population Level ◽

Bimodal Distribution ◽

Skewed Distribution ◽

Stable Set ◽

Cross Sectional ◽

Set Point ◽

Viral Loads ◽

The Uk

Hepatitis B virus (HBV) viral load (VL) is used as a biomarker to assess risk of disease progression, and to determine eligibility for treatment. While there is a well recognised association between VL and the expression of the viral e-antigen protein, the distributions of VL at a population level are not well described. We here present cross-sectional, observational HBV VL data from two large population cohorts in the UK and in South Africa, demonstrating a consistent bimodal distribution. The right skewed distribution and low median viral loads are different from the left-skew and higher viraemia in seen in HIV and hepatitis C virus (HCV) cohorts in the same settings. Using longitudinal data, we present evidence for a stable ‘set-point’ VL in peripheral blood during chronic HBV infection. These results are important to underpin improved understanding of HBV biology, to inform approaches to viral sequencing, and to plan public health interventions.

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Public health surveillance of habitual physical activity in adolescents and adults in Namibia: a cross-sectional validation of activity questionnaires against accelerometry

Journal of Public Health ◽

10.1093/pubmed/fdaa067 ◽

2020 ◽

Author(s):

Hilde L Nashandi ◽

John J Reilly ◽

Xanne Janssen

Keyword(s):

Physical Activity ◽

Adolescent Girls ◽

Rank Order ◽

Vigorous Physical Activity ◽

Population Level ◽

Self Report ◽

Adult Women ◽

Cross Sectional ◽

Individual Level ◽

Activity Questionnaires

Abstract Background Monitoring population-level physical activity is crucial for examining adherence to global guidelines and addressing obesity. This study validated self-reported moderate-to-vigorous physical activity (MVPA) against an accurate device-based method in Namibia. Methods Adolescent girls (n = 52, mean age 16.2 years [SD 1.6]) and adult women (n = 51, mean age 31.3 years [SD 4.7]) completed the PACE+/GPAQ self-report questionnaires and were asked to wear an Actigraph accelerometer for 7 days. Validity of self-reported MVPA was assessed using rank-order correlations between self-report and accelerometry, and classification ability of the questionnaires with Mann–Whitney tests, kappa’s, sensitivity and specificity. Results In the adolescents, Spearman’s rank coefficients between self-reported MVPA (days/week) and accelerometry measured MVPA were positive but not significant (r = 0.240; P = 0.104). In the adults, self-reported MVPA (minutes/day) was moderately and significantly correlated with accelerometer-measured MVPA (r = 0.396; P = 0.008). In both groups, there was fair agreement between accelerometry and questionnaire-defined tertiles of MVPA (adolescents κ = 0.267; P = 0.010; adults κ = 0.284; P = 0.008), and measured MVPA was significantly higher in the individuals self-reporting higher MVPA than those reporting lower MVPA. Conclusions The PACE+ and GPAQ questionnaires have a degree of validity in adolescent girls and adult females in Namibia, though more suitable for population than individual level measurement.

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Reconstructing heterogeneous pathogen interactions from co-occurrence data via statistical network inference

10.1101/2021.11.15.468692 ◽

2021 ◽

Author(s):

Irene Man ◽

Elisa Benincà ◽

Mirjam E Kretzschmar ◽

Johannes A Bogaards

Keyword(s):

Sample Size ◽

Network Inference ◽

Network Models ◽

Population Level ◽

Unbiased Estimation ◽

Large Sample Size ◽

Cross Sectional ◽

Individual Level ◽

Heterogeneous Interaction ◽

Pathogen Strains

Infectious diseases often involve multiple pathogen species or multiple strains of the same pathogen. As such, knowledge of how different pathogen species or pathogen strains interact is key to understand and predict the outcome of interventions that target only a single pathogen or subset of strains involved in disease. While population-level data have been used to infer pathogen strain interactions, most previously used inference methods only consider uniform interactions between all strains, or focus on marginal interactions between pairs of strains (without correction for indirect interactions through other strains). Here, we evaluate whether statistical network inference could be useful for reconstructing heterogeneous interaction networks from cross-sectional surveys tracking co-occurrence of multi-strain pathogens. To this end, we applied a suite of network models to data simulating endemic infection states of pathogen strains. Satisfactory performance was demonstrated by unbiased estimation of interaction parameters for large sample size. Accurate reconstruction of networks may require regularization or penalizing for sample size. Of note, performance deteriorated in the presence of host heterogeneity, but this could be overcome by correcting for individual-level risk factors. Our work demonstrates how statistical network inference could prove useful for detecting pathogen interactions and may have implications beyond epidemiology.

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