scholarly journals Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States

2020 ◽  
Author(s):  
Melanie H. Chitwood ◽  
Marcus Russi ◽  
Kenneth Gunasekera ◽  
Joshua Havumaki ◽  
Virginia E. Pitzer ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
District Of Columbia ◽  
The United States ◽  
Considerable Variability ◽  
Us States ◽  
Secular Changes ◽  
Policy Responses ◽  
Time Estimates ◽  
Reporting Delays

AbstractReal-time estimates of the true size and trajectory of local COVID-19 epidemics are key metrics to guide policy responses. We developed a Bayesian nowcasting approach that explicitly accounts for reporting delays and secular changes in case ascertainment to generate real-time estimates of COVID-19 epidemiology on the basis of reported cases and deaths. Using this approach, we estimate time trends in infections, symptomatic cases, and deaths for all 50 US states and the District of Columbia from early-March through June 11, 2020. At the beginning of June, our best estimates of the effective reproduction number (Rt) are close to 1 in most states, indicating a stabilization of incidence, but there is considerable variability in the level of incidence and the estimated proportion of the population that has already been infected.One Sentence SummaryA new method to track epidemiologic measures of COVID-19, available in the covidestim package for R.

Estimation of Truck Traffic Volume from Single Loop Detectors with Lane-to-Lane Speed Correlation

2003 ◽  
Vol 1856 (1) ◽  
pp. 106-117 ◽  
Author(s):  
Jaimyoung Kwon ◽  
Pravin Varaiya ◽  
Alexander Skabardonis
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
The United States ◽  
Truck Traffic ◽  
Single Loop ◽  
Loop Detectors ◽  
Time Estimates ◽  
Surveillance Technology ◽  
Traffic Volumes ◽  
Urban Freeway

An algorithm for real-time estimation of truck traffic in multilane freeways was proposed. The algorithm used data from single loop detectors—the most widely installed surveillance technology for urban freeways in the United States. The algorithm worked for those freeway locations that have a truck-free lane and exhibit high lane-to-lane speed correlation. These conditions are met by most urban freeway locations. The algorithm produced real-time estimates of the truck traffic volumes at the location. It also can be used to produce alternative estimates of the mean effective vehicle length, which can improve speed estimates from single loop detector data. The algorithm was tested with real freeway data and produced estimates of truck traffic volumes with only 5.7% error. It also captured the daily patterns of truck traffic and mean effective vehicle length. Applied to loop data on Interstate 710 near Long Beach, California, during the dockworkers’ lockout October 1 to 9, 2002, the algorithm found a 32% reduction in five-axle truck volume.

scholarly journals Coronavirus Disease 2019 (COVID-19) Transmission in the United States Before Versus After Relaxation of Statewide Social Distancing Measures

2020 ◽  
Author(s):  
Alexander C Tsai ◽  
Guy Harling ◽  
Zahra Reynolds ◽  
Rebecca F Gilbert ◽  
Mark J Siedner
Keyword(s):  
United States ◽  
State Government ◽  
Disease Burden ◽  
Reproduction Number ◽  
District Of Columbia ◽  
The United States ◽  
Third Party ◽  
Social Distancing ◽  
Significant Reversal ◽  
The Mean

Abstract Background Weeks after issuing social distancing orders to suppress severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and reduce growth in cases of severe coronavirus disease 2019 (COVID-19), all US states and the District of Columbia partially or fully relaxed these measures. Methods We identified all statewide social distancing measures that were implemented and/or relaxed in the United States between 10 March and 15 July 2020, triangulating data from state government and third-party sources. Using segmented linear regression, we estimated the extent to which relaxation of social distancing affected epidemic control, as indicated by the time-varying, state-specific effective reproduction number (Rt). Results In the 8 weeks prior to relaxation, mean Rt declined by 0.012 units per day (95% confidence interval [CI], −.013 to −.012), and 46/51 jurisdictions achieved Rt < 1.0 by the date of relaxation. After relaxation of social distancing, Rt reversed course and began increasing by 0.007 units per day (95% CI, .006–.007), reaching a mean Rt of 1.16. Eight weeks later, the mean Rt was 1.16 and only 9/51 jurisdictions were maintaining an Rt < 1.0. Parallel models showed similar reversals in the growth of COVID-19 cases and deaths. Indicators often used to motivate relaxation at the time of relaxation (eg, test positivity rate <5%) predicted greater postrelaxation epidemic growth. Conclusions We detected an immediate and significant reversal in SARS-CoV-2 epidemic suppression after relaxation of social distancing measures across the United States. Premature relaxation of social distancing measures undermined the country’s ability to control the disease burden associated with COVID-19.

scholarly journals Consumers and COVID-19: A Real-Time Survey

2020 ◽  
pp. 1-6 ◽  
Author(s):  
Edward S. Knotek ◽  
Raphael S. Schoenle ◽  
Alexander M. Dietrich ◽  
Keith Kuester ◽  
Gernot J. Müller ◽  
...  
Keyword(s):  
United States ◽  
Real Time ◽  
The United States ◽  
Policy Responses ◽  
High Uncertainty

We summarize the results from an ongoing survey that asks consumers questions related to the recent coronavirus outbreak, including their expectations for how the economy is likely to be affected by the outbreak and how their own behavior has changed in response to it. The survey began in early March, providing a window into how consumers’ responses have evolved in real time since the early days of the acknowledged spread of COVID-19 in the United States. In updating and charting the survey’s findings on the Cleveland Fed’s website going forward, we seek to inform policymakers and researchers about consumers’ beliefs during a time of high uncertainty and unprecedented policy responses.

scholarly journals Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking

2019 ◽  
Author(s):  
Sarah F. McGough ◽  
Michael A. Johansson ◽  
Marc Lipsitch ◽  
Nicolas A. Menzies
Keyword(s):  
Real Time ◽  
Temporal Relationship ◽  
The United States ◽  
Time Varying ◽  
Widespread Application ◽  
Delay Distribution ◽  
Wide Range ◽  
Reporting Delays ◽  
Reporting Delay ◽  
Bayesian Smoothing

AbstractDelays in case reporting are common to disease surveillance systems, making it difficult to track diseases in real-time. “Nowcast” approaches attempt to estimate the complete case counts for a given reporting date, using a time series of case reports that is known to be incomplete due to reporting delays. Modeling the reporting delay distribution is a common feature of nowcast approaches. However, many nowcast approaches ignore a crucial feature of infectious disease transmission—that future cases are intrinsically linked to past reported cases—and are optimized to a single application, which may limit generalizability. Here, we present a Bayesian approach, NobBS (Nowcasting by Bayesian Smoothing) capable of producing smooth and accurate nowcasts in multiple disease settings. We test NobBS on dengue in Puerto Rico and influenza-like illness (ILI) in the United States to examine performance and robustness across settings exhibiting a range of common reporting delay characteristics (from stable to time-varying), and compare this approach with a published nowcasting package. We show that introducing a temporal relationship between cases considerably improves performance when the reporting delay distribution is time-varying, and we identify trade-offs in the role of moving windows to accurately capture changes in the delay. We present software implementing this new approach (R package “NobBS”) for widespread application.SignificanceAchieving accurate, real-time estimates of disease activity is challenged by delays in case reporting. However, approaches that seek to estimate cases in spite of reporting delays often do not consider the temporal relationship between cases during an outbreak, nor do they identify characteristics of robust approaches that generalize to a wide range of surveillance contexts with very different reporting delays. Here, we present a smooth Bayesian nowcasting approach that produces accurate estimates that capture the time evolution of the epidemic curve and outperform a previous approach in the literature. We assess the performance for two diseases to identify important features of the reporting delay distribution that contribute to the model’s performance and robustness across surveillance settings.

scholarly journals The Pandemic Policy U-Turn: Partisanship, Public Health, and Race in Decisions to Ease COVID-19 Social Distancing Policies in the United States

2021 ◽  
pp. 1-23
Author(s):  
Christopher Adolph ◽  
Kenya Amano ◽  
Bree Bang-Jensen ◽  
Nancy Fullman ◽  
Beatrice Magistro ◽  
...  
Keyword(s):  
Original Data ◽  
The United States ◽  
Economic Conditions ◽  
Party Affiliation ◽  
Us States ◽  
Social Distancing ◽  
Policy Responses ◽  
The Us ◽  
Per Capita ◽  
Black Populations

We explore the US states’ evolving policy responses to the COVID-19 pandemic by examining governors’ decisions to begin easing five types of social distancing policies after the initial case surge in March–April 2020. Applying event history models to original data on state COVID-19 policies, we test the relative influence of health, economic, and political considerations on their decisions. We find no evidence that differences in state economic conditions influenced when governors began easing. Governors of states with larger recent declines in COVID-19 deaths per capita and improving trends in new confirmed cases and test positivity were quicker to ease. However, politics played as powerful a role as epidemiological conditions, driven primarily by governors’ party affiliation. Republican governors made the policy U-turn from imposing social distancing measures toward easing those measures a week earlier than Democratic governors, all else equal. Most troubling of all, we find that states with larger Black populations eased their social distancing policies more quickly, despite Black Americans’ higher exposure to infection from SARS-CoV-2 and subsequent death from COVID-19.

scholarly journals Real-time monitoring the transmission potential of COVID-19 in Singapore, February 2020

2020 ◽  
Author(s):  
Amna Tariq ◽  
Yiseul Lee ◽  
Kimberlyn Roosa ◽  
Seth Blumberg ◽  
Ping Yan ◽  
...  
Keyword(s):  
Real Time ◽  
Branching Process ◽  
Reproduction Number ◽  
Process Analysis ◽  
Case Series ◽  
Mean Value ◽  
Transmission Potential ◽  
Recent Estimate ◽  
Reporting Delays ◽  
Local Transmission

AbstractBackgroundThe ongoing COVID-19 epidemic that spread widely in China since December 2019 is now generating local transmission in multiple countries including Singapore as of February 27, 2020. This highlights the need to monitor in real time the transmission potential of COVID-19. In Singapore, four major COVID-19 case clusters have emerged thus far.MethodsHere we estimate the effective reproduction number, Rt, of COVID-19 in Singapore from the publicly available daily case series of imported and autochthonous cases by date of symptoms onset, after adjusting the local cases for reporting delays. We also derive the reproduction number from the distribution of cluster sizes using a branching process analysis.ResultsThe effective reproduction number peaked with a mean value ∼1.1 around February 2nd, 2020 and declined thereafter. As of February 27th, 2020, our most recent estimate of Rt is at 0.5 (95% CI: 0.2,0.7) while an estimate of the overall R based on cluster size distribution is at 0.7 (95% CI: 0.5, 0.9).ConclusionThe trajectory of the reproduction number in Singapore underscore the significant effects of containment efforts in Singapore while at the same time suggest the need to sustain social distancing and active case finding efforts to stomp out all active chains of transmission.

scholarly journals A survey of interprofessional education in chiropractic continuing education in the United States

2014 ◽  
Vol 28 (2) ◽  
pp. 152-156 ◽  
Author(s):  
Edward M. Bednarz ◽  
Anthony J. Lisi
Keyword(s):  
Medical Education ◽  
Continuing Education ◽  
Interprofessional Education ◽  
District Of Columbia ◽  
The United States ◽  
Sufficient Information ◽  
Medical Doctors ◽  
Us States ◽  
Electronic Survey ◽  
Integrated Practice

Objective The purpose of this study is to describe the state of chiropractic continuing education vis-à-vis interprofessional education (IPE) with medical doctors (MD) in a survey of a sample of US doctors of chiropractic (DC) and through a review of policies. Methods Forty-five chiropractors with experience in interprofessional settings completed an electronic survey of their experiences and perceptions regarding DC-MD IPE in chiropractic continuing education (CE). The licensing bodies of the 50 US states and the District of Columbia were queried to assess the applicability of continuing medical education (CME) to chiropractic relicensure. Results The majority (89.1%) of survey respondents who attend CE-only events reported that they rarely to never experienced MD-IPE at these activities. Survey respondents commonly attended CME-only events, and 84.5% stated that they commonly to very commonly experienced MD-IPE at these activities. More than half (26 of 51) of the licensing bodies did not provide sufficient information to determine if CME was applicable to DC relicensure. Thirteen jurisdictions (25.5%) do not, and 12 jurisdictions (23.5%) do accept CME credits for chiropractic relicensure. Conclusion The majority of integrated practice DCs we surveyed reported little to no IPE occurring at CE-only events, yet significant IPE occurring at CME events. However, we found only 23.5% of chiropractic licensing bodies allow CME credit to apply to chiropractic relicensure. These factors may hinder DC-MD IPE in continuing education.

Potential Urban Rainfall Prediction Measurement System

1984 ◽  
Vol 16 (8-9) ◽  
pp. 349-362 ◽  
Author(s):  
John L Vogel
Keyword(s):  
Real Time ◽  
The United States ◽  
Monitoring Systems ◽  
Climatic Region ◽  
Convective Storm ◽  
Rainfall Prediction ◽  
Water Quality Regulations ◽  
General Data ◽  
Real Time Information ◽  
Time Information

Continued growth of urban regions and more stringent water quality regulations have resulted in an increased need for more real-time information about past, present, and future patterns and intensities of precipitation. Detailed, real-time information about precipitation can be obtained using radar and raingages for monitoring and prediction of precipitation amounts. The philosophy and the requirements for the development of real-time radar prediction-monitoring systems are described for climatic region similar to the Midwest of the united States. General data analysis and interpretation techniques associated with rainfall from convective storm systems are presented.

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