Estimating the infection-fatality risk of SARS-CoV-2 in New York City during the spring 2020 pandemic wave: a model-based analysis.

BACKGROUND: As the COVID-19 pandemic continues to unfold, the infection-fatality risk (ie, risk of death among all infected individuals including those with asymptomatic and mild infections) is crucial for gauging the burden of death due to COVID-19 in the coming months or years. Here, we estimate the infection-fatality risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New York City, NY, USA, the first epidemic centre in the USA, where the infection-fatality risk remains unclear. METHODS: In this model-based analysis, we developed a meta-population network model-inference system to estimate the underlying SARS-CoV-2 infection rate in New York City during the 2020 spring pandemic wave using available case, mortality, and mobility data. Based on these estimates, we further estimated the infection-fatality risk for all ages overall and for five age groups (<25, 25-44, 45-64, 65-74, and ≥75 years) separately, during the period March 1 to June 6, 2020 (ie, before the city began a phased reopening). FINDINGS: During the period March 1 to June 6, 2020, 205 639 people had a laboratory-confirmed infection with SARS-CoV-2 and 21 447 confirmed and probable COVID-19-related deaths occurred among residents of New York City. We estimated an overall infection-fatality risk of 1·39% (95% credible interval 1·04-1·77) in New York City. Our estimated infection-fatality risk for the two oldest age groups (65-74 and ≥75 years) was much higher than the younger age groups, with a cumulative estimated infection-fatality risk of 0·116% (0·0729-0·148) for those aged 25-44 years and 0·939% (0·729-1·19) for those aged 45-64 years versus 4·87% (3·37-6·89) for those aged 65-74 years and 14·2% (10·2-18·1) for those aged 75 years and older. In particular, weekly infection-fatality risk was estimated to be as high as 6·72% (5·52-8·01) for those aged 65-74 years and 19·1% (14·7-21·9) for those aged 75 years and older. INTERPRETATION: Our results are based on more complete ascertainment of COVID-19-related deaths in New York City than other places and thus probably reflect the true higher burden of death due to COVID-19 than that previously reported elsewhere. Given the high infection-fatality risk of SARS-CoV-2, governments must account for and closely monitor the infection rate and population health outcomes and enact prompt public health responses accordingly as the COVID-19 pandemic unfolds. FUNDING: National Institute of Allergy and Infectious Diseases, National Science Foundation Rapid Response Research Program, and New York City Department of Health and Mental Hygiene.

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020.

Importance: Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19. Objective: To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020. Design, Setting, and Population: This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020. Main Outcomes and Measures: Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data. Results: There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths. Conclusions and Relevance: Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

Estimating the early death toll of COVID-19 in the United States.

BACKGROUND: Efforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19. METHODS: We evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data. RESULTS: There were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I. CONCLUSIONS: Excess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.

A review of the 1918 herald pandemic wave: importance for contemporary pandemic response strategies.

Mounting epidemiological evidence supports the occurrence of a mild herald pandemic wave in the spring and summer of 1918 in North America and Europe, several months before the devastating autumn outbreak that killed an estimated 2% of the global population. These epidemiological findings corroborate the anecdotal observations of contemporary clinicians who reported widespread influenza outbreaks in spring and summer 1918, with sporadic occurrence of unusually severe clinical manifestations in young adults. Initially seen as controversial, these findings were eventually confirmed by retrospective identification of influenza specimens collected from U.S. soldiers who died from acute respiratory infections in May-August 1918. Other studies found that having an episode of influenza illness during the spring herald wave was highly protective in the severe autumn wave. Here, we conduct a systematic review of the clinical, epidemiological, and virological evidence supporting the global occurrence of mild herald waves of the 1918 pandemic and place these historic observations in the context of pandemic preparedness. Taken together, historic experience with the 1918 and subsequent pandemics shows that increased severity in second and later pandemic waves may be the rule rather than the exception. Thus, a sustained pandemic response in the first years following a future pandemic is critical; conversely, multiwave pandemic patterns allow for more time to rollout vaccines and antivirals.

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system.

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method's implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System's C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis.

Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems.

While big data have proven immensely useful in fields such as marketing and earth sciences, public health is still relying on more traditional surveillance systems and awaiting the fruits of a big data revolution. A new generation of big data surveillance systems is needed to achieve rapid, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying on clinical and laboratory reports. We then examine how large-volume medical claims data can, with great spatiotemporal resolution, help elucidate local disease patterns. Finally, we review efforts to develop surveillance systems based on digital and social data streams, including the recent rise and fall of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection which has traditionally been considered a model system for surveillance and modeling.

A multicomponent nutrient bar promotes weight loss and improves dyslipidemia and insulin resistance in the overweight/obese: chronic inflammation blunts these improvements.

This study determined if twice-daily consumption of a nutrient-dense bar intended to fill gaps in Western diets, without other dietary/lifestyle requirements, favorably shifted metabolic/anthropometric indicators of dysregulation in a healthy direction. Three 8-wk clinical trials in 43 healthy lean and overweight/obese (OW/OB) adults, who served as their own controls, were pooled for analysis. In less inflamed OW/OB [high-sensitivity C-reactive protein (hsCRP) <1.5], statistically significant decreases occurred in weight (-1.1 ± 0.5 kg), waist circumference (-3.1 ± 1.4 cm), diastolic blood pressure (-4.1 ± 1.6 mmHg), heart rate [HR; -4.0 ± 1.7 beats per minute (bpm)], triglycerides (-72 ± 38.2 mg/dl), insulin resistance (homeostatic model of insulin resistance) (-0.72 ± 0.3), and insulin (-2.8 ± 1.3 mU/L); an increase in HDL-2b (+303 ± 116 nM) and realignment of LDL lipid subfractions toward a less atherogenic profile [decreased small LDL IIIb (-44 ± 23.5 nM), LDL IIIa (-99 ± 43.7 nM), and increased large LDL I (+66 ± 28.0 nM)]. In the more inflamed OW/OB (hsCRP >1.5), inflammation was reduced at 2 wk (-0.66 mg/L), and HR at 8 wk (-3.4 ± 1.3 bpm). The large HDL subfraction (10.5-14.5 nm) increased at 8 wk (+346 ± 126 nM). Metabolic improvements were also observed in lean participants. Thus, favorable changes in measures of cardiovascular health, insulin resistance, inflammation, and obesity were initiated within 8 wk in the OW/OB by replacing deficiencies in Western diets without requiring other dietary or lifestyle modifications; chronic inflammation blunted most improvements.

Visualizing the quality of partially accruing data for use in decision making.

Secondary use of clinical health data for near real-time public health surveillance presents challenges surrounding its utility due to data quality issues. Data used for real-time surveillance must be timely, accurate and complete if it is to be useful; if incomplete data are used for surveillance, understanding the structure of the incompleteness is necessary. Such data are commonly aggregated due to privacy concerns. The Distribute project was a near real-time influenza-like-illness (ILI) surveillance system that relied on aggregated secondary clinical health data. The goal of this work is to disseminate the data quality tools developed to gain insight into the data quality problems associated with these data. These tools apply in general to any system where aggregate data are accrued over time and were created through the end-user-as-developer paradigm. Each tool was developed during the exploratory analysis to gain insight into structural aspects of data quality. Our key finding is that data quality of partially accruing data must be studied in the context of accrual lag-the difference between the time an event occurs and the time data for that event are received, i.e. the time at which data become available to the surveillance system. Our visualization methods therefore revolve around visualizing dimensions of data quality affected by accrual lag, in particular the tradeoff between timeliness and completion, and the effects of accrual lag on accuracy. Accounting for accrual lag in partially accruing data is necessary to avoid misleading or biased conclusions about trends in indicator values and data quality.

A nutrient-dense, high-fiber, fruit-based supplement bar increases HDL cholesterol, particularly large HDL, lowers homocysteine, and raises glutathione in a 2-wk trial.

Dietary intake modulates disease risk, but little is known how components within food mixtures affect pathophysiology. A low-calorie, high-fiber, fruit-based nutrient-dense bar of defined composition (e.g., vitamins and minerals, fruit polyphenolics, ß-glucan, docosahexaenoic acid) appropriate for deconstruction and mechanistic studies is described and evaluated in a pilot trial. The bar was developed in collaboration with the U.S. Department of Agriculture. Changes in cardiovascular disease and diabetes risk biomarkers were measured after 2 wk twice-daily consumption of the bar, and compared against baseline controls in 25 healthy adults. Plasma HDL-cholesterol (HDL-c) increased 6.2% (P=0.001), due primarily to a 28% increase in large HDL (HDL-L; P<0.0001). Total plasma homocysteine (Hcy) decreased 19% (P=0.017), and glutathione (GSH) increased 20% (P=0.011). The changes in HDL and Hcy are in the direction associated with decreased risk of cardiovascular disease and cognitive decline; increased GSH reflects improved antioxidant defense. Changes in biomarkers linked to insulin resistance and inflammation were not observed. A defined food-based supplement can, within 2 wk, positively impact metabolic biomarkers linked to disease risk. These results lay the groundwork for mechanistic/deconstruction experiments to identify critical bar components and putative synergistic combinations responsible for observed effects.

Chemiluminescence detection flow cells for flow injection analysis and high-performance liquid chromatography.

We have examined a range of new and previously described flow cells for chemiluminescence detection. The reactions of acidic potassium permanganate with morphine and amoxicillin were used as model systems representing the many fast chemiluminescence reactions between oxidising agents and organic analytes, and the preliminary partial reduction of the reagent was exploited to further increase the rates of reaction. The comparison was then extended to high-performance liquid chromatography separations of α- and ß-adrenergic agonists, with permanganate chemiluminescence detection. Flow cells constructed by machining novel channel designs into white polymer materials (sealed with transparent films or plates) have enabled improvements in mixing efficiency and overall transmission of light to the photodetector.

Chemiluminescence detectors for liquid chromatography.

In this tutorial we describe the construction of chemiluminescence detectors for high performance liquid chromatography (HPLC), comprising the components required to deliver the chemiluminescence reagent, a coiled-tubing flow cell, photomultiplier tube and detector housing, and various options for data acquisition. We also discuss two state-of-the-art commercially available chemiluminescence detectors for HPLC and other flow analysis methodology.

Solution mixing and the emission of light in flow-cells for chemiluminescence detection.

Constructing flow-through reactors for chemiluminescence detection by machining channels into polymer disks has enabled the exploration of new configurations and materials that can improve signal intensity beyond that attainable with the traditional coiled-tubing design. Several approaches to merge reactant solutions were examined: an intersection, chamber or deeper well in the centre of a serpentine configuration flow-cell (directly in front of a photomultiplier tube), or a confluence point outside the detection zone. For several analytically useful, rapid chemiluminescence reactions, the single-inlet flow-cell with external Y-piece was most suitable, but for others (such as KMnO(4)/Mn(II) with morphine, and [Ir(f-ppy)(2)BPS](-) with fluoroquinolones) the dual-inlet configuration provided greater signals. The introduction of central mixing zones with larger widths than the channel reduced the chemiluminescence response. The reversing turns of a serpentine channel promote efficient mixing and greater chemiluminescence intensities than a spiral channel, but increasing the sharpness of the turns created areas of poor solution flow and decreased the chemiluminescence response. Teflon disks impregnated with glass microspheres increased the chemiluminescence signals by 13%-17%, due to the greater reflection of stray light towards the photodetector.

Preliminary Estimates of Mortality and Years of Life Lost Associated with the 2009 A/H1N1 Pandemic in the US and Comparison with Past Influenza Seasons.

The on-going debate about the health burden of the 2009 influenza pandemic and discussions about the usefulness of vaccine recommendations has been hampered by an absence of directly comparable measures of mortality impact. Here we set out to generate an "apples-to-apples" metric to compare pandemic and epidemic mortality. We estimated the mortality burden of the pandemic in the US using a methodology similar to that used to generate excess mortality burden for inter-pandemic influenza seasons. We also took into account the particularly young age distribution of deaths in the 2009 H1N1 pandemic, using the metric "Years of Life Lost" instead of numbers of deaths. Estimates are based on the timely pneumonia and influenza mortality surveillance data from 122 US cities, and the age distribution of laboratory-confirmed pandemic deaths, which has a mean of 37 years. We estimated that between 7,500 and 44,100 deaths are attributable to the A/H1N1 pandemic virus in the US during May-December 2009, and that between 334,000 and 1,973,000 years of life were lost. The range of years of life lost estimates includes in its lower part the impact of a typical influenza epidemic dominated by the more virulent A/H3N2 subtype, and the impact of the 1968 pandemic in its upper bound. We conclude that the 2009 A/H1N1 pandemic virus had a substantial health burden in the US over the first few months of circulation in terms of years of life lost, justifying the efforts to protect the population with vaccination programs. Analysis of historic records from three other pandemics over the last century suggests that the emerging pandemic virus will continue to circulate and cause excess mortality in unusually young populations for the next few years. Continuing surveillance for indicators of increased mortality is of key importance, as pandemics do not always cause the majority of associated deaths in the first season of circulation.

Autocatalytic nature of permanganate oxidations exploited for highly sensitive chemiluminescence detection.

Manganese(II) salts catalyze the chemiluminescent oxidation of organic compounds with acidic potassium permanganate. The formation of insoluble manganese(IV) species from the reaction between manganese(II) and permanganate can be prevented with sodium polyphosphate, and therefore, relatively high concentrations of the catalyst can be added to the reagent before the light-producing reaction is initiated. The rapid and intense emissions from these manganese(II) catalyzed chemiluminescence reactions provide highly sensitive detection and greater compatibility with liquid chromatography.

Chemiluminescence detector with a serpentine flow cell.

We present a new chemiluminescence detector, with solution channels that have been machined into a Teflon disk and sealed with a sapphire window. The configuration of the flow cell can be conveniently modified by replacing the Teflon disk. A comparison of some existing and novel designs, using the chemiluminescence reaction of morphine with acidic potassium permanganate and the bioluminescence reaction of ATP with the commercially available "BacTiter-Glo" reagent, has revealed that a serpentine channel allows greater quantities of light to be captured than a spiral channel, due to more efficient mixing of the analyte and reagent solutions within the cell.

Optimization of an axial flow heart pump with active and passive magnetic bearings.

Optimization of a magnetically suspended left ventricular assist device (LVAD) is crucial. We desire a totally implantable, long-life LVAD that delivers the necessary flow rate, pressure rise, and blood compatibility. By using a novel combination of passive and active magnetic bearings (AMBs), we have developed an axial flow LVAD prototype, the LEV-VAD, which provides an unobstructed blood flow path, preventing stagnation regions for the blood. Our current effort is focused on the optimization of the magnetic suspension system to allow for control of the AMB, minimizing its size and power consumption. The properties of the passive magnetic bearings and AMBs serve as parameter space, over which a cost function is minimized, subject to constraints such as suspension stability and sufficient disturbance rejection capabilities. The design process is expected to lead to the construction of a small prototype pump along with the necessary robust controller for the AMB. Sensitivity of the LVAD performance with respect to various design parameters is examined in-depth and an optimized, more compact LVAD prototype is designed.

Measurement of unbound bilirubin by the peroxidase test using Zone Fluidics.

BACKGROUND: Measuring plasma unbound bilirubin concentration by the peroxidase test is useful in the management of jaundiced newborns. However, the commercially available peroxidase technology is manual, and the unbound bilirubin may be seriously underestimated at the 42-fold sample dilution and single peroxidase concentration used. We investigated improving the test by adapting it to Zone Fluidics, which is a system for automating reactant handling that requires small sample volumes and dilution. METHODS: A computer-directed Zone Fluidics system was constructed using small diameter tubing to connect in series a water-surfactant reservoir, a bi-directional pump, a multiport selection valve to which peroxidase test reactants (45 mul of sample) are attached with one port open to air, and a spectrophotometer flow cell. Test reactants and air are sequentially aspirated through the valve into the tubing connecting the pump and valve to form a reactant "zone" surrounded by air. The zone is advanced to the spectrophotometer flow cell where total and unbound bilirubin are determined (37 degrees C) from the absorbance at 460 nm at a 2-fold sample dilution and 4 peroxidase concentrations. Imprecision was assessed in artificial controls and newborn plasma. Plasma results were compared with those obtained using the commercial method. RESULTS: The CV for unbound bilirubin in the various controls ranged from 11% to 38% (within day) and 12% to 27% (between days). Triplicate CV measurements for newborn plasma measurements ranged from 0.6% to 31% (mean 11%, n=47). Mean unbound bilirubin by Zone Fluidics was 5-fold higher than that by the commercial method. CONCLUSION: Zone Fluidics can be used to automate the peroxidase test and overcome many of the limitations of the commercially available peroxidase technology.