scholarly journals Estimating epidemiologic dynamics from single cross-sectional viral load distributions

2020 ◽  
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.

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

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0258644
Author(s):  
Wendy Grant-McAuley ◽  
Ethan Klock ◽  
Oliver Laeyendecker ◽  
Estelle Piwowar-Manning ◽  
Ethan Wilson ◽  
...  
Keyword(s):  
Viral Suppression ◽  
Point Of Care ◽  
Population Level ◽  
Hiv Viral Load ◽  
Cross Sectional ◽  
Individual Level ◽  
Viral Loads ◽  
Incidence Estimation ◽  
Duration Of Infection ◽  
Recent Hiv Infection

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.

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

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.

scholarly journals 520. Longitudinal Analysis of SARS-CoV-2 Viruses in Hospitalized Adults

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S325-S326
Author(s):  
Lacy Simons ◽  
Ramon Lorenzo-Redondo ◽  
Hannah Nam ◽  
Scott C Roberts ◽  
Michael G Ison ◽  
...  
Keyword(s):  
Viral Load ◽  
Genome Sequencing ◽  
Viral Genome ◽  
Temporal Dynamics ◽  
Population Level ◽  
Hospital Staff ◽  
Therapeutic Interventions ◽  
Viral Loads ◽  
Qrt Pcr ◽  
Over Time

Abstract Background The rapid spread of SARS-CoV-2, the causative agent of Coronavirus disease 2019 (COVID-19), has been accompanied by the emergence of viral mutations, some of which may have distinct virological and clinical consequences. While whole genome sequencing efforts have worked to map this viral diversity at the population level, little is known about how SARS-CoV-2 may diversify within a host over time. This is particularly important for understanding the emergence of viral resistance to therapeutic interventions and immune pressure. The goal of this study was to assess the change in viral load and viral genome sequence within patients over time and determine if these changes correlate with clinical and/or demographic parameters. Methods Hospitalized patients admitted to Northwestern Memorial Hospital with a positive SARS-CoV-2 test were enrolled in a longitudinal study for the serial collection of nasopharyngeal specimens. Swabs were administered to patients by hospital staff every 4 ± 1 days for up to 32 days or until the patients were discharged. RNA was extracted from each specimen and viral loads were calculated by quantitative reverse transcriptase PCR (qRT-PCR). Specimens with qRT-PCR cycle threshold values less than or equal to 30 were subject to whole viral genome sequencing by reverse transcription, multiplex PCR, and deep sequencing. Variant populations sizes were estimated and subject to phylogenetic analysis relative to publicly available SARS-CoV-2 sequences. Sequence and viral load data were subsequently correlated to available demographic and clinical data. Results 60 patients were enrolled from March 26th to June 20th, 2020. We observed an overall decrease in nasopharyngeal viral load over time across all patients. However, the temporal dynamics of viral load differed on a patient-by-patient basis. Several mutations were also observed to have emerged within patients over time. Distribution of SARS-CoV-2 viral loads in serially collected nasopharyngeal swabs in hospitalized adults as determined by qRT-PCR. Samples were collected every 4 ± 1 days (T#1–8) and viral load is displayed by log(copy number). Conclusion These data indicate that SARS-CoV-2 viral loads in the nasopharynx decrease over time and that the virus can accumulate mutations during replication within individual patients. Future studies will examine if some of these mutations may provide fitness advantages in the presence of therapeutic and/or immune selective pressures. Disclosures Michael G. Ison, MD MS, AlloVir (Consultant)

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

2018 ◽  
Vol 148 (12) ◽  
pp. 1946-1953 ◽  
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.

scholarly journals Smart Sanitation—Biosensors as a Public Health Tool in Sanitation Infrastructure

2020 ◽  
Vol 17 (14) ◽  
pp. 5146 ◽  
Author(s):  
Emma Rary ◽  
Sarah M. Anderson ◽  
Brandon D. Philbrick ◽  
Tanvi Suresh ◽  
Jasmine Burton
Keyword(s):  
Public Health ◽  
Health Monitoring ◽  
Disease Surveillance ◽  
Population Level ◽  
Cost Effective ◽  
Small Scale ◽  
Individual Level ◽  
Emergent Technologies ◽  
The Individual ◽  
Sanitation Infrastructure

The health of individuals and communities is more interconnected than ever, and emergent technologies have the potential to improve public health monitoring at both the community and individual level. A systematic literature review of peer-reviewed and gray literature from 2000-present was conducted on the use of biosensors in sanitation infrastructure (such as toilets, sewage pipes and septic tanks) to assess individual and population health. 21 relevant papers were identified using PubMed, Embase, Global Health, CDC Stacks and NexisUni databases and a reflexive thematic analysis was conducted. Biosensors are being developed for a range of uses including monitoring illicit drug usage in communities, screening for viruses and diagnosing conditions such as diabetes. Most studies were nonrandomized, small-scale pilot or lab studies. Of the sanitation-related biosensors found in the literature, 11 gathered population-level data, seven provided real-time continuous data and 14 were noted to be more cost-effective than traditional surveillance methods. The most commonly discussed strength of these technologies was their ability to conduct rapid, on-site analysis. The findings demonstrate the potential of this emerging technology and the concept of Smart Sanitation to enhance health monitoring at the individual level (for diagnostics) as well as at the community level (for disease surveillance).

scholarly journals Modeling Dynamic Heterogeneity Using Gaussian Processes

2019 ◽  
Vol 57 (1) ◽  
pp. 55-77 ◽  
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.

scholarly journals Thrombocytopenia according to antiretroviral drug combinations, viremia and CD4 lymphocytes among HIV-infected patients in Cameroon: a snapshot from the City of Yaoundé

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Alex Durand Nka ◽  
Samuel Martin Sosso ◽  
Joseph Fokam ◽  
Yagai Bouba ◽  
Georges Teto ◽  
...  
Keyword(s):  
Viral Load ◽  
Blood Platelets ◽  
Undetectable Viral Load ◽  
Drug Combinations ◽  
People Living With Hiv ◽  
Cross Sectional ◽  
Viral Loads ◽  
Reference Centre ◽  
Antiretroviral Drug ◽  
Load Rate

Abstract Objective Thrombocytopenia is an abnormal decrease in blood platelets, which can affect the prognosis of people living with HIV (PLHIV). In order to assess the burden of this haematological disorder, we evaluated the frequency of thrombocytopenia according to antiretroviral drug combinations, viremia and the immune status of PLHIV. Results A cross-sectional and analytical study was conducted from June to November 2016 among 310 PLHIV at the “Chantal BIYA” International Reference Centre, Yaoundé, Cameroon. Overall rate of thrombocytopenia was 19.0% (59/310). The rate of thrombocytopenia was 64.6% (42/65) versus 6.9% (17/245) in ART-naïve versus ART-treated patients respectively, p < 0.0001. Following viral load, rate of thrombocytopenia was 15.8% (20/130) in those with undetectable viral load, and 34.1% (27/79) with viral loads > 3 log10 RNA/ml (p = 0.03). As concerns CD4-count, rate of thrombocytopenia was 16.2% (42/259) in those with ≥ 200 CD4/mm3 versus 33.3% (17/51) with < 200 CD4/mm3 (p = 0.0003). After adjusting for sex, ART, viral load and CD4, Viral load and ART exposure were significantly associated with decreased risk of thrombocytopenia (p < 0.05). Thrombocytopenia occurs especially among ART-naïve, high viremia and severe immune-compromised patients. Interestingly, ART coverage appears as an independent factor in preventing the occurrence of thrombocytopenia.

scholarly journals 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

2017 ◽  
Vol 21 (5) ◽  
pp. 948-956 ◽  
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.

scholarly journals Are normoglycaemic individuals at risk of depression? The depression-dysglycaemic phenotype from a European population-based cross-sectional study

2020 ◽  
Author(s):  
Sarah Cuschieri ◽  
Julian Mamo
Keyword(s):  
Public Health ◽  
Population Level ◽  
Cross Sectional Study ◽  
Health Concern ◽  
Sectional Study ◽  
Public Health Concern ◽  
Phenotypic Characteristics ◽  
Cross Sectional ◽  
Depression Prevalence ◽  
The Impact

Abstract Background Depression is a chronic non communicable disease. It is a growing public health concern with established links with a number of co-morbidities, including diabetes mellitus. The study aimed to estimate the prevalence of depression at a population level, establish the depression sub-population phenotypic characteristics while exploring for links between depression and a spectrum of glycemic abnormalities. Methods A nationally representative cross-sectional study was conducted in Malta between 2014 and 2016. Participants were categorized into different sub-populations according to their glycaemic status. Depression prevalence rates and phenotypic characteristics for each sub-population were established. Multiple regression analysis was performed to identify links with depression. Results Depression was prevalent in 17.15% (CI 95%: 16.01 – 18.36) with a female predominance. Those with known (as opposed to newly diagnosed) diabetes had the highest depression prevalence when compared to other glycemic sub-groups. These also exhibited a significant link with self-reported depression. However, at a population level, depression was mostly prevalent within the normoglycaemic sub-population. Conclusions The study confirms the strong link between diabetes and depression, especially, in a high risk dysglycaemic population. Of public health concern is the high depression occurrence within the normoglycaemic sub-population, which attributed for the majority of the Maltese population. In order to reduce the impact of mental health on the population, physicians may consider implementing depression screening clinical tools as part of their routine health check-ups at primary care level, irrespective of the glycaemic status of their patients.

scholarly journals Comparison of viral levels in individuals with or without symptoms at time of COVID-19 testing among 32,480 residents and staff of nursing homes and assisted living facilities in Massachusetts.

2020 ◽  
Author(s):  
Niall J Lennon ◽  
Roby P Bhattacharyya ◽  
Michael J Mina ◽  
Heidi L Rehm ◽  
Deborah T Hung ◽  
...  
Keyword(s):  
Public Health ◽  
Nursing Homes ◽  
Assisted Living ◽  
Assisted Living Facilities ◽  
Outbreak Response ◽  
Survey Period ◽  
Cross Sectional ◽  
Viral Loads ◽  
Qrt Pcr ◽  
Wide Range

Background Transmission of COVID-19 from people without symptoms poses considerable challenges to public health containment measures. The distribution of viral loads in individuals with and without symptoms remains uncertain. Comprehensive cross-sectional screening of all individuals in a given setting provides an unbiased way to assess viral loads independent of symptoms, which informs transmission risks. COVID-19 cases initially peaked in Massachusetts in mid-April 2020 before declining through June, and congregate living facilities were particularly affected during this early surge. We performed a retrospective analysis of data from a large public health-directed outbreak response initiative that involved comprehensive screening within nursing homes and assisted living facilities in Massachusetts to compare nasopharyngeal (NP) viral loads (as measured by RT-PCR cycle threshold (Ct) levels) in residents and staff to inform our ability to detect SARS-CoV-2 in individuals with or without symptoms in the population. Methods Between April 9 and June 9, 2020, we tested NP swabs from 32,480 unique individuals comprising staff and residents of the majority of nursing homes and assisted living facilities in Massachusetts. Under the direction of the MA Department of Public Health (MDPH), symptomatology at the time of sampling and demographic information was provided by each facility for each individual to facilitate reporting to health officials. NP swabs were collected, RNA extracted, and SARS-CoV-2 testing performed using quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). Results The nursing home and assisted living facilities resident cohort (N =16,966) was 65% female with a mean age of 82 years (SD 13 yrs). The staff cohort (N = 15,514) was 76% female with a median age of 45 (SD 15 yrs). A total 2654 residents (15.5%) and 624 staff (4.1%) tested positive for SARS-CoV-2. 12.7% of residents and 3.7% of staff without symptoms tested positive for SARS-CoV-2, compared to 53.1% of residents and 18.2% of staff with symptoms. Of the individuals who tested positive, 70.8% of residents and 92.4% of staff lacked symptoms at the time of testing. In aggregate, the distributions of Cts for viral probes used in the qRT-PCR assay were very similar, with a statistically but not meaningfully different mean (∆Ct 0.71 cycles, p = 0.006) and a similar range (12-38 cycles), between populations with and without symptoms over the entire time period, across all sub-categories examined (age, race, ethnicity, sex, resident/staff). Importantly, the Ct mean values and range were indistinguishable between the populations by symptom class during the peak of the outbreak in Massachusetts, with a Ct gap appearing only later in the survey period, reaching >3 cycles (p ≤ 0.001) for facilities sampled during the last two weeks of the study. Conclusions In a large cohort of individuals screened for SARS-CoV-2 by qRT-PCR, we found strikingly similar distributions of viral load in patients with or without symptoms at the time of testing during the local peak of the epidemic; as the epidemic waned, individuals without symptoms at the time of testing had lower viral loads. The size of the study population, including both staff and residents spanning a wide range of ages, provides a comprehensive cross-sectional point prevalence measurement of viral burden in a study spanning 2 months. Because the distributions of viral loads in infected individuals irrespective of symptomatology are very similar, existing testing modalities that have been validated for detection of SARS-CoV-2 RNA in symptomatic patients should perform similarly in individuals without symptoms at the time of testing.

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