scholarly journals Influenza Surveillance, United States, 1960

1961 ◽  
Vol 76 (12) ◽  
pp. 1099 ◽  
Author(s):  
Theodore C. Eickhoff ◽  
Roslyn Q. Robinson
Keyword(s):  
United States ◽  
Influenza Surveillance

scholarly journals Large-Scale Avian Influenza Surveillance in Wild Birds throughout the United States

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104360 ◽  
Author(s):  
Sarah N. Bevins ◽  
Kerri Pedersen ◽  
Mark W. Lutman ◽  
John A. Baroch ◽  
Brandon S. Schmit ◽  
...  
Keyword(s):  
United States ◽  
Avian Influenza ◽  
Large Scale ◽  
The United States ◽  
Wild Birds ◽  
Influenza Surveillance

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

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.

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

2020 ◽  
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.

scholarly journals Preliminary results of 2009 pandemic influenza surveillance in the United States using the Aggregate Hospitalization and Death Reporting Activity

2011 ◽  
Vol 5 (5) ◽  
pp. 321-327 ◽  
Author(s):  
Michael A. Jhung ◽  
Heidi Davidson ◽  
Anne McIntyre ◽  
William J. Gregg ◽  
Sharoda Dasgupta ◽  
...  
Keyword(s):  
United States ◽  
Pandemic Influenza ◽  
The United States ◽  
Influenza Surveillance ◽  
Preliminary Results

scholarly journals Meeting the Challenge of Emerging Pathogens: The Role of the United States Air Force in Global Influenza Surveillance

1997 ◽  
Vol 162 (2) ◽  
pp. 82-86 ◽  
Author(s):  
R. Joel Williams ◽  
Nancy J. Cox ◽  
Helen L. Regnery ◽  
Donald L. Noah ◽  
Ali S. Khan ◽  
...  
Keyword(s):  
United States ◽  
Air Force ◽  
United States Air Force ◽  
The United States ◽  
Influenza Surveillance ◽  
Emerging Pathogens

scholarly journals Using influenza surveillance networks to estimate state-specific prevalence of SARS-CoV-2 in the United States

2020 ◽  
Vol 12 (554) ◽  
pp. eabc1126 ◽  
Author(s):  
Justin D. Silverman ◽  
Nathaniel Hupert ◽  
Alex D. Washburne
Keyword(s):  
United States ◽  
False Negative ◽  
Emerging Infectious Diseases ◽  
The United States ◽  
Influenza Surveillance ◽  
Chain Reaction ◽  
Seroprevalence Data ◽  
Rapid Spread ◽  
Community Transmission ◽  
Polymerase Chain

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections to date has relied heavily on reverse transcription polymerase chain reaction testing. However, limited test availability, high false-negative rates, and the existence of asymptomatic or subclinical infections have resulted in an undercounting of the true prevalence of SARS-CoV-2. Here, we show how influenza-like illness (ILI) outpatient surveillance data can be used to estimate the prevalence of SARS-CoV-2. We found a surge of non-influenza ILI above the seasonal average in March 2020 and showed that this surge correlated with coronavirus disease 2019 (COVID-19) case counts across states. If one-third of patients infected with SARS-CoV-2 in the United States sought care, this ILI surge would have corresponded to more than 8.7 million new SARS-CoV-2 infections across the United States during the 3-week period from 8 to 28 March 2020. Combining excess ILI counts with the date of onset of community transmission in the United States, we also show that the early epidemic in the United States was unlikely to have been doubling slower than every 4 days. Together, these results suggest a conceptual model for the COVID-19 epidemic in the United States characterized by rapid spread across the United States with more than 80% infected individuals remaining undetected. We emphasize the importance of testing these findings with seroprevalence data and discuss the broader potential to use syndromic surveillance for early detection and understanding of emerging infectious diseases.

scholarly journals The reduction in influenza rates in the United States during the COVID-19 pandemic

2021 ◽  
Vol 9 (39) ◽  
pp. 22-24
Author(s):  
Anna Sabu-Kurian ◽  
Kripa Shrestha ◽  
Sharmila Dissanaike
Keyword(s):  
United States ◽  
Great Britain ◽  
Hand Hygiene ◽  
Influenza Season ◽  
Face Mask ◽  
The United States ◽  
Influenza Surveillance ◽  
Infection Rates ◽  
Sharp Decline ◽  
Safety Measures

Influenza affects many lives worldwide each year during the months of October through February. The 2020-2021 influenza season saw a sharp decline in the cases reported in the United States and in other countries like Great Britain in comparison to previous influenza seasons. The most likely explanations for this decline are the safety measures taken during the COVID-19 pandemic, such as physical distancing, face mask use, and better hand hygiene in the mass population, which likely reduced the transmission and infection rates of influenza this season. Key words: influenza, surveillance, pandemic, transmission

scholarly journals Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: Four complementary approaches

2021 ◽  
Vol 17 (6) ◽  
pp. e1008994
Author(s):  
Fred S. Lu ◽  
Andre T. Nguyen ◽  
Nicholas B. Link ◽  
Mathieu Molina ◽  
Jessica T. Davis ◽  
...  
Keyword(s):  
United States ◽  
Cumulative Incidence ◽  
The United States ◽  
Positive Test ◽  
Influenza Surveillance ◽  
Accurate Estimation ◽  
Mortality Data ◽  
Surveillance Systems ◽  
The Us ◽  
Single Data

Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the prevalence of COVID-19 across the United States (US). Equipment shortages and varying testing capabilities have however hindered the usefulness of the official reported positive COVID-19 case counts. We introduce four complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 in each state in the US as well as Puerto Rico and the District of Columbia, using a combination of excess influenza-like illness reports, COVID-19 test statistics, COVID-19 mortality reports, and a spatially structured epidemic model. Instead of relying on the 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 four approaches emerges the consistent conclusion that on April 4, 2020, the estimated case count was 5 to 50 times higher than the official positive test counts across the different states. Nationally, our estimates of COVID-19 symptomatic cases as of April 4 have a likely range of 2.3 to 4.8 million, with possibly as many as 7.6 million cases, up to 25 times greater than the cumulative confirmed cases of about 311,000. Extending our methods to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 4.9 to 10.1 million, as opposed to 1.5 million positive test counts. The proposed combination of approaches may prove useful in assessing the burden of COVID-19 during resurgences in the US and other countries with comparable surveillance systems.

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