Characterizing COVID-19 case detection utilizing influenza surveillance data in the United States, January-March, 2020

COVID-19 reached the US in January, 2020, but state and local case detection efforts varied in timing and scale. We conducted a state-level ecological analysis of COVID-19 epidemiology alongside CDC influenza surveillance data and policy timelines. Our findings show wide variation in COVID-19 case detection and influenza-like-illness activity between states.

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Estimating the Early Outbreak Cumulative Incidence of COVID-19 in the United States: Three Complementary Approaches

10.1101/2020.04.18.20070821 ◽

2020 ◽

Cited By ~ 12

Author(s):

Fred S. Lu ◽

Andre T. Nguyen ◽

Nicholas B. Link ◽

Marc Lipsitch ◽

Mauricio Santillana

Keyword(s):

United States ◽

Cumulative Incidence ◽

State Level ◽

The United States ◽

Positive Test ◽

Influenza Surveillance ◽

Accurate Estimation ◽

Surveillance Systems ◽

Influenza Like Illness ◽

The Us

AbstractEffectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the weekly incidence of COVID-19. Unfortunately, a lack of systematic testing across the United States (US) due to equipment shortages and varying testing strategies has hindered the usefulness of the reported positive COVID-19 case counts. We introduce three complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 during the early outbreak in each state in the US as well as in New York City, using a combination of excess influenza-like illness reports, COVID-19 test statistics, and COVID-19 mortality reports. Instead of relying on an estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our three approaches, there is a consistent conclusion that estimated state-level COVID-19 symptomatic case counts from March 1 to April 4, 2020 varied from 5 to 50 times greater than the official positive test counts. Nationally, our estimates of COVID-19 symptomatic cases in the US as of April 4 have a likely range of 2.2 to 5.1 million cases, with possibly as high as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 12.2 million, which compares with 1.5 million positive test counts. Our approaches demonstrate the value of leveraging existing influenza-like-illness surveillance systems during the flu season for measuring the burden of new diseases that share symptoms with influenza-like-illnesses. Our methods may prove useful in assessing the burden of COVID-19 during upcoming flu seasons in the US and other countries with comparable influenza surveillance systems.

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International Religious Freedom Promotion and US Foreign Policy

Religions ◽

10.3390/rel11050260 ◽

2020 ◽

Vol 11 (5) ◽

pp. 260 ◽

Cited By ~ 1

Author(s):

Lee Marsden

Keyword(s):

United States ◽

Religious Freedom ◽

State Level ◽

The United States ◽

Human Right ◽

National Interests ◽

Politics And Religion ◽

The Us ◽

The World ◽

Political Background

The freedom to practice one’s religious belief is a fundamental human right and yet, for millions of people around the world, this right is denied. Yearly reports produced by the US State Department, United States Commission on International Religious Freedom, Open Doors International, Aid to the Church in Need and Release International reveal a disturbing picture of increased religious persecution across much of the world conducted at individual, community and state level conducted by secular, religious, terrorist and state actors. While religious actors both contribute to persecution of those of other faiths and beliefs and are involved in peace and reconciliation initiatives, the acceptance of the freedom to practice one’s faith, to disseminate that faith and to change one’s faith and belief is fundamental to considerations of the intersection of peace, politics and religion. In this article, I examine the political background of the United States’ promotion of international religious freedom, and current progress on advancing this under the Trump administration. International Religious Freedom (IRF) is contentious, and seen by many as the advancement of US national interests by other means. This article argues that through an examination of the accomplishments and various critiques of the IRF programme it is possible, and desirable, to discover what works, and where further progress needs to be made, in order to enable people around the world to enjoy freedom of thought, conscience and religion.

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Crisis Standards of Care Implementation at the State Level in the United States

Prehospital and Disaster Medicine ◽

10.1017/s1049023x20001089 ◽

2020 ◽

Vol 35 (6) ◽

pp. 599-603 ◽

Cited By ~ 1

Author(s):

Colton Margus ◽

Ritu R. Sarin ◽

Michael Molloy ◽

Gregory R. Ciottone

Keyword(s):

United States ◽

Large Scale ◽

State Level ◽

The United States ◽

The State ◽

Pediatric Care ◽

Standards Of Care ◽

Institute Of Medicine ◽

Full Spectrum ◽

The Us

AbstractIntroduction:In 2009, the Institute of Medicine published guidelines for implementation of Crisis Standards of Care (CSC) at the state level in the United States (US). Based in part on the then concern for H1N1 pandemic, there was a recognized need for additional planning at the state level to maintain health system preparedness and conventional care standards when available resources become scarce. Despite the availability of this framework, in the years since and despite repeated large-scale domestic events, implementation remains mixed.Problem:Coronavirus disease 2019 (COVID-19) rejuvenates concern for how health systems can maintain quality care when faced with unrelenting burden. This study seeks to outline which states in the US have developed CSC and which areas of care have thus far been addressed.Methods:An online search was conducted for all 50 states in 2015 and again in 2020. For states without CSC plans online, state officials were contacted by email and phone. Public protocols were reviewed to assess for operational implementation capabilities, specifically highlighting guidance on ventilator use, burn management, sequential organ failure assessment (SOFA) score, pediatric standards, and reliance on influenza planning.Results:Thirty-six states in the US were actively developing (17) or had already developed (19) official CSC guidance. Fourteen states had no publicly acknowledged effort. Eleven of the 17 public plans had updated within five years, with a majority addressing ventilator usage (16/17), influenza planning (14/17), and pediatric care (15/17), but substantially fewer addressing care for burn patients (9/17).Conclusion:Many states lacked publicly available guidance on maintaining standards of care during disasters, and many states with specific care guidelines had not sufficiently addressed the full spectrum of hazard to which their health care systems remain vulnerable.

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Development and application of a United States-wide correction for PM<sub>2.5</sub> data collected with the PurpleAir sensor

Atmospheric Measurement Techniques ◽

10.5194/amt-14-4617-2021 ◽

2021 ◽

Vol 14 (6) ◽

pp. 4617-4637

Author(s):

Karoline K. Barkjohn ◽

Brett Gantt ◽

Andrea L. Clements

Keyword(s):

United States ◽

Air Quality ◽

Reference Method ◽

Ambient Air ◽

The United States ◽

Global Network ◽

Raw Data ◽

The Us ◽

State And Local ◽

Multiplicative Models

Abstract. PurpleAir sensors, which measure particulate matter (PM), are widely used by individuals, community groups, and other organizations including state and local air monitoring agencies. PurpleAir sensors comprise a massive global network of more than 10 000 sensors. Previous performance evaluations have typically studied a limited number of PurpleAir sensors in small geographic areas or laboratory environments. While useful for determining sensor behavior and data normalization for these geographic areas, little work has been done to understand the broad applicability of these results outside these regions and conditions. Here, PurpleAir sensors operated by air quality monitoring agencies are evaluated in comparison to collocated ambient air quality regulatory instruments. In total, almost 12 000 24 h averaged PM2.5 measurements from collocated PurpleAir sensors and Federal Reference Method (FRM) or Federal Equivalent Method (FEM) PM2.5 measurements were collected across diverse regions of the United States (US), including 16 states. Consistent with previous evaluations, under typical ambient and smoke-impacted conditions, the raw data from PurpleAir sensors overestimate PM2.5 concentrations by about 40 % in most parts of the US. A simple linear regression reduces much of this bias across most US regions, but adding a relative humidity term further reduces the bias and improves consistency in the biases between different regions. More complex multiplicative models did not substantially improve results when tested on an independent dataset. The final PurpleAir correction reduces the root mean square error (RMSE) of the raw data from 8 to 3 µg m−3, with an average FRM or FEM concentration of 9 µg m−3. This correction equation, along with proposed data cleaning criteria, has been applied to PurpleAir PM2.5 measurements across the US on the AirNow Fire and Smoke Map (https://fire.airnow.gov/, last access: 14 May 2021) and has the potential to be successfully used in other air quality and public health applications.

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Evaluating Surveillance for and Estimating Administration of Rabies Postexposure Prophylaxis in the United States, 2012–2018

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0009878 ◽

2021 ◽

Vol 15 (10) ◽

pp. e0009878

Author(s):

Erin R. Whitehouse ◽

Marissa K. Person ◽

Catherine M. Brown ◽

Sally Slavinski ◽

Agam K. Rao ◽

...

Keyword(s):

Public Health ◽

United States ◽

National Level ◽

State Level ◽

The United States ◽

Surveillance Data ◽

Human Rabies ◽

Accurate Assessment ◽

Postexposure Prophylaxis ◽

Ed Visits

Background An evaluation of postexposure prophylaxis (PEP) surveillance has not been conducted in over 10 years in the United States. An accurate assessment would be important to understand current rabies trends and inform public health preparedness and response to human rabies. Methodology/Principle findings To understand PEP surveillance, we sent a survey to public health leads for rabies in 50 U.S. states, Puerto Rico, Washington DC, Philadelphia, and New York City. Of leads from 54 jurisdictions, 39 (72%) responded to the survey; 12 reported having PEP-specific surveillance, five had animal bite surveillance that included data about PEP, four had animal bite surveillance without data about PEP, and 18 (46%) had neither. Although 12 jurisdictions provided data about PEP use, poor data quality and lack of national representativeness prevented use of this data to derive a national-level PEP estimate. We used national-level and state specific data from the Healthcare Cost & Utilization Project (HCUP) to estimate the number of people who received PEP based on emergency department (ED) visits. The estimated annual average of initial ED visits for PEP administration during 2012–2017 in the United States was 46,814 (SE: 1,697), costing upwards of 165 million USD. State-level ED data for initial visits for administration of PEP for rabies exposure using HCUP data was compared to state-level surveillance data from Maryland, Vermont, and Georgia between 2012–2017. In all states, state-level surveillance data was consistently lower than estimates of initial ED visits, suggesting even states with robust PEP surveillance may not adequately capture individuals who receive PEP. Conclusions Our findings suggest that making PEP a nationally reportable condition may not be feasible. Other methods of tracking administration of PEP such as syndromic surveillance or identification of sentinel states should be considered to obtain an accurate assessment.

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Forecasting type-specific seasonal influenza after 26 weeks in the United States using influenza activities in other countries

10.1101/705855 ◽

2019 ◽

Author(s):

S. B. Choi ◽

J. Kim ◽

I. Ahn

Keyword(s):

United States ◽

Time Series ◽

Deep Learning ◽

Seasonal Influenza ◽

Prediction Models ◽

Time Lag ◽

The United States ◽

Surveillance Data ◽

Influenza Surveillance ◽

The U.S

AbstractTo identify countries that have seasonal patterns similar to the time series of influenza surveillance data in the United States and other countries, and to forecast the 2018–2019 seasonal influenza outbreak in the U.S. using linear regression, auto regressive integrated moving average, and deep learning. We collected the surveillance data of 164 countries from 2010 to 2018 using the FluNet database. Data for influenza-like illness (ILI) in the U.S. were collected from the Fluview database. This cross-correlation study identified the time lag between the two time-series. Deep learning was performed to forecast ILI, total influenza, A, and B viruses after 26 weeks in the U.S. The seasonal influenza patterns in Australia and Chile showed a high correlation with those of the U.S. 22 weeks and 28 weeks earlier, respectively. The R2 score of DNN models for ILI for validation set in 2015–2019 was 0.722 despite how hard it is to forecast 26 weeks ahead. Our prediction models forecast that the ILI for the U.S. in 2018–2019 may be later and less severe than those in 2017–2018, judging from the influenza activity for Australia and Chile in 2018. It allows to estimate peak timing, peak intensity, and type-specific influenza activities for next season at 40th week. The correlation for seasonal influenza among Australia, Chile, and the U.S. could be used to decide on influenza vaccine strategy six months ahead in the U.S.

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A spatial database of wildfires in the United States, 1992-2011

Earth System Science Data ◽

10.5194/essd-6-1-2014 ◽

2014 ◽

Vol 6 (1) ◽

pp. 1-27 ◽

Cited By ~ 77

Author(s):

K. C. Short

Keyword(s):

United States ◽

Program Analysis ◽

The United States ◽

Federal State ◽

Record Keeping ◽

The Us ◽

Survey System ◽

State And Local ◽

Wildfire Planning ◽

Data Elements

Abstract. The statistical analysis of wildfire activity is a critical component of national wildfire planning, operations, and research in the United States (US). However, there are multiple federal, state, and local entities with wildfire protection and reporting responsibilities in the US, and no single, unified system of wildfire record keeping exists. To conduct even the most rudimentary interagency analyses of wildfire numbers and area burned from the authoritative systems of record, one must harvest records from dozens of disparate databases with inconsistent information content. The onus is then on the user to check for and purge redundant records of the same fire (i.e., multijurisdictional incidents with responses reported by several agencies or departments) after pooling data from different sources. Here we describe our efforts to acquire, standardize, error-check, compile, scrub, and evaluate the completeness of US federal, state, and local wildfire records from 1992–2011 for the national, interagency Fire Program Analysis (FPA) application. The resulting FPA Fire-Occurrence Database (FPA FOD) includes nearly 1.6 million records from the 20 yr period, with values for at least the following core data elements: location, at least as precise as a Public Land Survey System section (2.6 km2 grid), discovery date, and final fire size. The FPA FOD is publicly available from the Research Data Archive of the US Department of Agriculture, Forest Service (doi:10.2737/RDS-2013-0009). While necessarily incomplete in some aspects, the database is intended to facilitate fairly high-resolution geospatial analysis of US wildfire activity over the past two decades, based on available information from the authoritative systems of record.

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Air passenger travel and international surveillance data predict spatiotemporal variation in measles importations to the United States

10.1101/2021.01.21.21250251 ◽

2021 ◽

Author(s):

Marya L. Poterek ◽

Moritz U.G. Kraemer ◽

Alexander Watts ◽

Kamran Khan ◽

T. Alex Perkins

Keyword(s):

United States ◽

Measles Virus ◽

Pearson Correlation ◽

Area Under The Curve ◽

The United States ◽

Air Travel ◽

Surveillance Data ◽

Data Type ◽

The Us ◽

Imported Cases

AbstractMeasles incidence in the United States has grown dramatically, as vaccination rates are declining and transmission internationally is on the rise. Measles virus is highly infectious and can cause severe symptoms and even death. Because imported cases are necessary drivers of outbreaks in non-endemic settings, predicting measles outbreaks in the US depends on predicting imported cases. To assess the predictability of imported measles cases, we performed a regression of imported measles cases in the US against an inflow variable that combines air travel data with international measles surveillance data. To understand the contribution of each data type to these predictions, we repeated the regression analysis with alternative versions of the inflow variable that replaced each data type with averaged values and with versions of the inflow variable that used modeled inputs. We assessed the performance of these regression models using correlation, coverage probability, and area under the curve statistics, including with resampling and cross-validation. Our regression model had good predictive ability with respect to the presence or absence of imported cases in a given state in a given year (AUC = 0.78) and the magnitude of imported cases (Pearson correlation = 0.84). By comparing alternative versions of the inflow variable averaging over different inputs, we found that both air travel data and international surveillance data contribute to the model’s ability to predict numbers of imported cases, and individually contribute to its ability to predict the presence or absence of imported cases. Predicted sources of imported measles cases varied considerably across years and US states, depending on which countries had high measles activity in a given year. Our results emphasize the importance of the relationship between global connectedness and the spread of measles.

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The United States: The First Formalization of Banking Supervision

Formalization of Banking Supervision ◽

10.1007/978-981-16-6783-1_2 ◽

2021 ◽

pp. 23-41

Author(s):

Eiji Hotori ◽

Mikael Wendschlag ◽

Thibaud Giddey

Keyword(s):

United States ◽

Banking System ◽

State Level ◽

The United States ◽

State Governments ◽

Banking Supervision ◽

The Great Depression ◽

The Us ◽

Social And Economic Development ◽

National Banking System

AbstractThis chapter examines the formalization of banking supervision in the United States (US), focusing on the federal level. During the “free banking era” from the late 1830s to 1864, several state governments created banking supervisory systems at the state level. Triggered by the fiscal needs of the Civil War, as well as the demand for a national currency, the US became the first country to introduce uniform nationwide banking supervision with the creation of the Office of the Comptroller of the Currency (OCC) and the national banking system. The main purpose of the OCC was to ensure that the national banks did not violate the regulations related to the new currency, the US dollar. From a historical perspective, the rapid social and economic development of the US from the 1850s provided the background for this institutional change. Although the US case demonstrates that financial crises have not always driven the formalization of banking supervision, the crises of 1907 and the Great Depression served to further strengthen the formalization of banking supervision by prompting the introduction of multi-agency banking supervision in the US.

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Economic uncertainty and suicide in the United States

European Journal of Epidemiology ◽

10.1007/s10654-021-00770-4 ◽

2021 ◽

Author(s):

Sotiris Vandoros ◽

Ichiro Kawachi

Keyword(s):

United States ◽

Panel Data ◽

State Level ◽

The United States ◽

Demographic Characteristics ◽

Economic Uncertainty ◽

Uncertainty Index ◽

The Us ◽

Prevention Interventions ◽

Econometric Approach

AbstractPrevious studies have found an association between recessions and increased rates of suicide. In the present study we widened the focus to examine the association between economic uncertainty and suicides. We used monthly suicide data from the US at the State level from 2000 to 2017 and combined them with the monthly economic uncertainty index. We followed a panel data econometric approach to study the association between economic uncertainty and suicide, controlling for unemployment and other indicators. Economic uncertainty is positively associated with suicide when controlling for unemployment [coeff: 8.026; 95% CI: 3.692–12.360] or for a wider range of economic and demographic characteristics [coeff: 7.478; 95% CI: 3.333–11.623]. An increase in the uncertainty index by one percent is associated with an additional 11–24.4 additional monthly suicides in the US. Economic uncertainty is likely to act as a trigger, which underlines the impulsive nature of some suicides. This highlights the importance of providing access to suicide prevention interventions (e.g. hotlines) during periods of economic uncertainty.

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