Evaluating completion rates of COVID-19 contact tracing surveys in New York City.

IMPORTANCE: Contact tracing is the process of identifying people who have recently been in contact with someone diagnosed with an infectious disease. During an outbreak, data collected from contact tracing can inform interventions to reduce the spread of infectious diseases. Understanding factors associated with completion rates of contact tracing surveys can help design improved interview protocols for ongoing and future programs. OBJECTIVE: To identify factors associated with completion rates of COVID-19 contact tracing surveys in New York City (NYC) and evaluate the utility of a predictive model to improve completion rates, we analyze laboratory-confirmed and probable COVID-19 cases and their self-reported contacts in NYC from October 1st 2020 to May 10th 2021. METHODS: We analyzed 742,807 case investigation calls made during the study period. Using a log-binomial regression model, we examined the impact of age, time of day of phone call, and zip code-level demographic and socioeconomic factors on interview completion rates. We further developed a random forest model to predict the best phone call time and performed a counterfactual analysis to evaluate the change of completion rates if the predicative model were used. RESULTS: The percentage of contact tracing surveys that were completed was 79.4%, with substantial variations across ZIP code areas. Using a log-binomial regression model, we found that the age of index case (an individual who has tested positive through PCR or antigen testing and is thus subjected to a case investigation) had a significant effect on the completion of case investigation - compared with young adults (the reference group,24 years old < age < = 65 years old), the completion rate for seniors (age > 65 years old) were lower by 12.1% (95%CI: 11.1% - 13.3%), and the completion rate for youth group (age < = 24 years old) were lower by 1.6% (95%CI: 0.6% -2.6%). In addition, phone calls made from 6 to 9 pm had a 4.1% (95% CI: 1.8% - 6.3%) higher completion rate compared with the reference group of phone calls attempted from 12 and 3 pm. We further used a random forest algorithm to assess its potential utility for selecting the time of day of phone call. In counterfactual simulations, the overall completion rate in NYC was marginally improved by 1.2%; however, certain ZIP code areas had improvements up to 7.8%. CONCLUSION: These findings suggest that age and time of day of phone call were associated with completion rates of case investigations. It is possible to develop predictive models to estimate better phone call time for improving completion rates in certain communities.

Community transmission of SARS-CoV-2 during the Delta wave in New York City.

BACKGROUND: Understanding community transmission of SARS-CoV-2 variants of concern (VOCs) is critical for disease control in the post pandemic era. The Delta variant (B.1.617.2) emerged in late 2020 and became the dominant VOC globally in the summer of 2021. While the epidemiological features of the Delta variant have been extensively studied, how those characteristics shaped community transmission in urban settings remains poorly understood. METHODS: Using high-resolution contact tracing data and testing records, we analyze the transmission of SARS-CoV-2 during the Delta wave within New York City (NYC) from May 2021 to October 2021. We reconstruct transmission networks at the individual level and across 177 ZIP code areas, examine network structure and spatial spread patterns, and use statistical analysis to estimate the effects of factors associated with COVID-19 spread. RESULTS: We find considerable individual variations in reported contacts and secondary infections, consistent with the pre-Delta period. Compared with earlier waves, Delta-period has more frequent long-range transmission events across ZIP codes. Using socioeconomic, mobility and COVID-19 surveillance data at the ZIP code level, we find that a larger number of cumulative cases in a ZIP code area is associated with reduced within- and cross-ZIP code transmission and the number of visitors to each ZIP code is positively associated with the number of non-household infections identified through contact tracing and testing. CONCLUSIONS: The Delta variant produced greater long-range spatial transmission across NYC ZIP code areas, likely caused by its increased transmissibility and elevated human mobility during the study period. Our findings highlight the potential role of population immunity in reducing transmission of VOCs. Quantifying variability of immunity is critical for identifying subpopulations susceptible to future VOCs. In addition, non-pharmaceutical interventions limiting human mobility likely reduced SARS-CoV-2 spread over successive pandemic waves and should be encouraged for reducing transmission of future VOCs.

A Phone Call Away: New York's Hotline And Public Health In The Rapidly Changing COVID-19 Pandemic.

In early March 2020 an outbreak of coronavirus disease 2019 (COVID-19) in New York City exerted sudden and extreme pressures on emergency medical services and quickly changed public health policy and clinical guidance. Recognizing this, New York City Health + Hospitals established a clinician-staffed COVID-19 hotline for all New Yorkers. The hotline underwent three phases as the health crisis evolved. As of May 1, 2020, the hotline had received more than ninety thousand calls and was staffed by more than a thousand unique clinicians. Hotline clinicians provided callers with clinical assessment and guidance, registered them for home symptom monitoring, connected them to social services, and provided a source of up-to-date answers to COVID-19 questions. By connecting New Yorkers with hotline clinicians, regardless of their regular avenues of accessing care, the hotline aimed to ease the pressures on the city's overtaxed emergency medical services. Future consideration should be given to promoting easy access to clinician hotlines by disadvantaged communities early in a public health crisis and to evaluating the impact of clinician hotlines on clinical outcomes.

Both lipopolysaccharide and lipoteichoic acids potently induce anomalous fibrin amyloid formation: assessment with novel Amytracker™ stains.

In recent work, we discovered that the presence of highly substoichiometric amounts (10-8 molar ratio) of lipopolysaccharide (LPS) from Gram-negative bacteria caused fibrinogen clotting to lead to the formation of an amyloid form of fibrin. We here show that the broadly equivalent lipoteichoic acids (LTAs) from two species of Gram-positive bacteria have similarly (if not more) potent effects. Using thioflavin T fluorescence to detect amyloid as before, the addition of low concentrations of free ferric ion is found to have similar effects. Luminescent conjugated oligothiophene dyes (LCOs), marketed under the trade name Amytracker™, also stain classical amyloid structures. We here show that they too give very large fluorescence enhancements when clotting is initiated in the presence of the four amyloidogens (LPS, ferric ions and two LTA types). The staining patterns differ significantly as a function of both the amyloidogens and the dyes used to assess them, indicating clearly that the nature of the clots formed is different. This is also the case when clotting is measured viscometrically using thromboelastography. Overall, the data provide further evidence for an important role of bacterial cell wall products in the various coagulopathies that are observable in chronic, inflammatory diseases. The assays may have potential in both diagnostics and therapeutics.

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description.

Models based on deep convolutional networks have dominated recent image interpretation tasks; we investigate whether models which are also recurrent are effective for tasks involving sequences, visual and otherwise. We describe a class of recurrent convolutional architectures which is end-to-end trainable and suitable for large-scale visual understanding tasks, and demonstrate the value of these models for activity recognition, image captioning, and video description. In contrast to previous models which assume a fixed visual representation or perform simple temporal averaging for sequential processing, recurrent convolutional models are "doubly deep" in that they learn compositional representations in space and time. Learning long-term dependencies is possible when nonlinearities are incorporated into the network state updates. Differentiable recurrent models are appealing in that they can directly map variable-length inputs (e.g., videos) to variable-length outputs (e.g., natural language text) and can model complex temporal dynamics; yet they can be optimized with backpropagation. Our recurrent sequence models are directly connected to modern visual convolutional network models and can be jointly trained to learn temporal dynamics and convolutional perceptual representations. Our results show that such models have distinct advantages over state-of-the-art models for recognition or generation which are separately defined or optimized.

Efficacy of darbepoetin alfa in alleviating fatigue and the effect of fatigue on quality of life in anemic patients with lymphoproliferative malignancies.

Anemia-related fatigue in cancer patients reduces health-related quality of life (HRQOL). These analyses evaluate the effect of hemoglobin level on fatigue and examine the relationship between improved fatigue and HRQOL. Data were collected during a multicenter, randomized trial involving 344 anemic patients with lymphoproliferative malignancies receiving chemotherapy and darbepoetin alfa or placebo. At baseline, interim study visits, and end of treatment, patients completed an HRQOL questionnaire. Improved hemoglobin levels were significantly associated (P < 0.001) with improved fatigue. Mean change in the Functional Assessment of Cancer Therapy (FACT) Fatigue score was 5.9 points greater when hemoglobin improved > 2 g/dl than when it declined. Patients experiencing a clinically meaningful improvement in fatigue reported significantly (P < 0.001) greater improvements in all other scales, except the FACT Social subscale. Managing anemia-related fatigue appears to have a positive impact on HRQOL, enhancing cancer patients' activity levels, mood, and perceived overall health.

Phase I/II randomised study of a novel erythropoiesis-stimulating agent (AMG 114) for the treatment of anaemia with concomitant chemotherapy in patients with non-myeloid malignancies.

AMG 114 is a novel, hyperglycosylated erythropoiesis-stimulating agent. In preclinical studies, AMG 114 demonstrated increased potency and longer half-life than darbepoetin alfa and epoetin alfa. This phase I/II, randomised, double-blind, placebo-controlled, dose-escalation study evaluated safety, pharmacokinetics, and efficacy of AMG 114 in patients with non-myeloid malignancies and chemotherapy-induced anaemia. Patients were randomised (1:5) to receive subcutaneous placebo or AMG 114 Q3W for 6 weeks in 3 dose cohorts of 15 µg (cohort A1), 50 µg (cohort A2), or 200 µg (cohort A3). Safety endpoints included incidence of adverse events and dose-limiting toxicities (DLTs). The PK profile of AMG 114 was evaluated. Efficacy was assessed by change in haemoglobin from baseline to end of treatment. Forty-eight patients enrolled: 8 received placebo, 40 received AMG 114. No DLTs were observed; adverse events were consistent with underlying malignancies. The PK profile was dose-proportional over the dose range tested; terminal half-life of AMG 114 was approximately 130 h. Mean change (range) in haemoglobin from baseline in AMG 114-treated patients was -0.16 (-1.8 to 1.3), 0.21 (-1.5 to 3.4), and 0.76 (-1.0 to 2.9) g/dl in cohorts A1, A2, and A3, respectively. AMG 114 appeared to be well tolerated, but the study was halted, in part because of modest efficacy.

Sample stability and variability of B-cell subsets in blood from healthy subjects and patients with systemic lupus erythematosus.

OBJECTIVE: Characterization of peripheral leukocytes is an important aspect of monitoring the effect of immunotherapeutic interventions in systemic lupus erythematosus (SLE). We analyzed cell surface markers commonly used to assess patients with SLE, focusing on the effect of holding blood prior to processing/analysis and the relative reliability of the measurements that were conducted. METHODS: Healthy volunteers (HV; n = 20) and patients with SLE (n = 42) were studied. Whole blood was collected for flow cytometric analysis on days 1, 8, 15, 105, 195, 285, and 375 and held overnight for analysis. A subset of samples was additionally analyzed on the day of collection. RESULTS: Variability arising from overnight storage of whole blood was found to be within 20% for most lymphocyte subsets. There was greater between rather than within subject variability over a 1-year period. As anticipated, the data showed higher CD38 and lower CD19 densities on B cells from patients with SLE compared to HV. Although a higher percentage of cells with markers of plasmablasts/cells were observed in the blood of patients with SLE relative to HV, these measurements were found to be among the least reliable (i.e., most variable). CONCLUSIONS: This study provides technical perspectives for those conducting immunophenotypic analyses of B-cells in patients with SLE. We envision that our data, which addresses sample stability issues and presents a method to describe the relative reliability of one measure over another, holds value for clinical assessments of B-cells in SLE and the evaluation of investigational agents designed to modify the B-cell compartment.