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.

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 338. Analysis of Etiologies of Aseptic Meningitis within a Nation-Wide Hospital Network

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S239-S239
Author(s):  
Arunmozhi S Aravagiri ◽  
Scott Kubomoto ◽  
Ayutyanont Napatkamon ◽  
Sarah Wilson ◽  
Sudhakar Mallela
Keyword(s):  
United States ◽  
West Nile Virus ◽  
Aseptic Meningitis ◽  
Epidemiologic Study ◽  
The United States ◽  
Positive Test ◽  
Diagnostic Tools ◽  
West Nile ◽  
Varicella Zoster ◽  
The Us

Abstract Background Aseptic meningitis can be caused by an array of microorganisms, both bacterial and non-bacterial, as well as non-infectious conditions. Some etiologies of aseptic meningitis require treatment with antibiotics, antiviral, antifungals, anti-parasitic agents, immunosuppressants, and or chemotherapy. There are limited diagnostic tools for diagnosing certain types of aseptic meningitis, therefore knowing the differential causes of aseptic meningitis, and their relative percentages may assist in diagnosis. Review of the literature reveals that there are no recent studies of etiologies of aseptic meningitis in the United States (US). This is an epidemiologic study to delineate etiologies of aseptic meningitis in a large database of 185 HCA hospitals across the US. Methods Data was collected from January 2016 to December 2019 on all patients diagnosed with meningitis. CSF PCR studies, and CSF antibody tests were then selected for inclusion. Results Total number of encounters were 3,149 hospitalizations. Total number of individual labs analyzed was 10,613, and of these 262 etiologies were identified. 23.6% (62) of cases were due to enterovirus, 18.7% (49) due to HSV-2, 14.5% (38) due to West Nile virus, 13.7% (36) due to Varicella zoster (VZV), 10.5% (27) due to Cryptococcus. Additionally, we analyzed the rate of positive test results by region. Nationally, 9.7% of tests ordered for enterovirus were positive. In contrast, 0.5% of tests ordered for HSV 1 were positive. The southeastern United States had the highest rate of positive tests for HSV 2 (7% of tests ordered for HSV 2 were positive). The central United States had the highest rate of positive test for West Nile virus (11% of tests ordered for West Nile were positive). The northeastern region and the highest rate of positive tests for varicella zoster (18%). Table 1: Percentage of positive CSF tests (positive tests/tests ordered) Table 2: Lists the number of HIV patients and transplant patients that had positive CSF PCR/serologies Figure 1: Percentage of positive CSF tests in each region Conclusion Approximately 40% of aseptic meningitis population had treatable etiologies. A third of the Cryptococcus meningitis population had HIV. Furthermore, enteroviruses had the majority of cases within the US, which are similar to studies done in other parts of the world. Disclosures All Authors: No reported disclosures

scholarly journals Cryptic transmission of SARS-CoV-2 and the first COVID-19 wave in Europe and the United States

2021 ◽  
Author(s):  
Jessica T Davis ◽  
Matteo Chinazzi ◽  
Nicola Perra ◽  
Kunpeng Mu ◽  
Ana Pastore y Piontti ◽  
...  
Keyword(s):  
United States ◽  
Early Stage ◽  
The United States ◽  
International Travel ◽  
Surveillance Systems ◽  
Model Driven ◽  
Global Dynamic ◽  
The Us ◽  
Community Transmission ◽  
Spatio Temporal

Given the narrowness of the initial testing criteria, the SARS-CoV-2 virus spread through cryptic transmission in January and February, setting the stage for the epidemic wave experienced in March and April, 2020. We use a global metapopulation epidemic model to provide a mechanistic understanding of the global dynamic underlying the establishment of the COVID-19 pandemic in Europe and the United States (US). The model is calibrated on international case introductions at the early stage of the pandemic. We find that widespread community transmission of SARS-CoV-2 was likely in several areas of Europe and the US by January 2020, and estimate that by early March, only 1-3 in 100 SARS-CoV-2 infections were detected by surveillance systems. Modeling results indicate international travel as the key driver of the introduction of SARS-CoV-2 with possible importation and transmission events as early as December, 2019. We characterize the resulting heterogeneous spatio-temporal spread of SARS-CoV-2 and the burden of the first COVID-19 wave (February-July 2020). We estimate infection attack rates ranging from 0.78%-15.2% in the US and 0.19%-13.2% in Europe. The spatial modeling of SARS-CoV-2 introductions and spreading provides insights into the design of innovative, model-driven surveillance systems and preparedness plans that have a broader initial capacity and indication for testing.

scholarly journals Evaluation of Point of Need Diagnostic Tests for Use in California Influenza Outbreaks

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Ashlynn Daughton ◽  
Alina Deshpande
Keyword(s):  
Data Streams ◽  
Surveillance System ◽  
Laboratory Data ◽  
Developed Countries ◽  
The United States ◽  
Diagnostic Tools ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Surveillance Systems ◽  
Influenza Outbreaks

Because of the potential threats flu viruses pose, the United States, like many developed countries, has a very well established flu surveillance system consisting of 10 components collecting laboratory data, mortality data, hospitalization data and sentinel outpatient care data. Currently, this surveillance system is estimated to lag behind the actual seasonal outbreak by one to two weeks. As new data streams come online, it is important to understand what added benefit they bring to the flu surveillance system complex. For data streams to be effective, they should provide data in a more timely fashion or provide additional data that current surveillance systems cannot provide. Two multiplexed diagnostic tools designed to test syndromically relevant pathogens and wirelessly upload data for rapid integration and interpretation were evaluated to see how they fit into the influenza surveillance scheme in California.

scholarly journals The US Public Health Service House-to-House Canvass Survey of the Morbidity and Mortality of the 1918 Influenza Pandemic

2020 ◽  
pp. e1-e8
Author(s):  
Alfredo Morabia
Keyword(s):  
Public Health ◽  
United States ◽  
Health Service ◽  
Cumulative Incidence ◽  
Public Health Service ◽  
San Antonio ◽  
Influenza Pandemic ◽  
The United States ◽  
Population Based ◽  
The Us

Between November 20, 1918, and March 12, 1919, the US Public Health Service carried out a vast population-based survey to assess the incidence rate and mortality of the influenza pandemic among 146 203 persons in 18 localities across the United States. The survey attempted to retrospectively assess all self-reported or diagnosed cases of influenza since August 1, 1918. It indicated that the cumulative incidence of symptomatic influenza over 6 months had been 29.4% (range = 15% in Louisville, KY, to 53.3% in San Antonio, TX). The overall case fatality rate (CFR) was 1.70%, and it ranged from 0.78% in San Antonio to 3.14% in New London, Connecticut. Localities with high cumulative incidence were not necessarily those with high CFR. Overall, assuming the survey missed asymptomatic cases, between August 1, 1918, and February 21, 1919, maybe more than 50% of the population was infected, and about 1% of the infected died. Eight months into the COVID-19 pandemic, the United States has not yet launched a survey that would provide population-based estimates of incidence and CFRs analogous to those generated by the 1918 US Public Health Service house-to-house canvass survey of influenza. Published online ahead of print December 8, 2020: 1–8. https://doi.org/10.2105/AJPH.2020.306025 )

scholarly journals Benchmarking COVID-19 Mortality in the United States

2020 ◽  
Author(s):  
Ruth Etzioni ◽  
Elan Markowitz ◽  
Ivor S. Douglas
Keyword(s):  
United States ◽  
Cumulative Incidence ◽  
Ethnic Disparities ◽  
The United States ◽  
Age Group ◽  
Effective Response ◽  
Death Rates ◽  
The Us ◽  
Hispanic Populations ◽  
Racial Ethnic

AbstractOn September 22nd the US officially recorded 200,000 COVID-19 deaths. It is unclear how many deaths might have been expected in the case of an early and effective response to the pandemic. We aim to provide a best-case estimate of COVID-19 deaths in the US by September 22nd using the experience of Germany as a benchmark. Our methods accommodate the differences in demographics between Germany and the US. We match cumulative incidence of COVID-19 deaths by age group in Germany to non-Hispanic whites in the US and project the implied number of deaths in this population and among the black and Hispanic populations under observed racial/ethnic disparities in cumulative COVID-19 mortality in the US. We estimate that if the US had been as successful as Germany in managing the pandemic we would have expected 22% of the deaths actually recorded. The number of deaths would have been lower by a further one-third if we could have eliminated racial/ethnic disparites in COVID-19 outcomes. We conclude that almost 80 percent of the COVID-19 deaths in the US by September 22nd could have been avoided with an early and effective response producing similar age-specific death rates among non-Hispanic whites as in Germany.

scholarly journals Excess Mortality in the United States During the First Peak of the COVID-19 Pandemic

2020 ◽  
Author(s):  
R. Rivera ◽  
J. E. Rosenbaum ◽  
W. Quispe
Keyword(s):  
United States ◽  
New York ◽  
New Jersey ◽  
Excess Mortality ◽  
Case Fatality ◽  
The United States ◽  
Mortality Data ◽  
Surveillance Systems ◽  
Pandemic Response ◽  
Mortality Surveillance

1AbstractDeaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for pandemic response and public adherence to non-pharmaceutical interventions. This study estimates excess all-cause, pneumonia, and influenza mortality during the COVID-19 health emergency using the June 12, 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance Survey (MSS) from September 27, 2015 to May 9, 2020, using semiparametric and conventional time-series models in 9 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Florida, Illinois, Massachusetts, Michigan, New Jersey, New York, and Washington. The May 9 endpoint was chosen due to apparently increased reporting lags in provisional mortality counts. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) (80862, 107284) vs. 78834 COVID-19 deaths) and 6 states: California (excess mortality 95% CI (2891, 5873) vs. 2849 COVID-19 deaths); Illinois (95% CI (4412, 5871) vs. 3525 COVID-19 deaths); Massachusetts (95% CI (5061, 6317) vs. 5050 COVID-19 deaths); New Jersey (95% CI (12497, 15307) vs. 10465 COVID-19 deaths); and New York (95% CI (30469, 37722) vs. 26584 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise.Official COVID-19 mortality substantially understates actual mortality, suggesting greater case-fatality rates. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

scholarly journals Excess mortality in the United States during the first three months of the COVID-19 pandemic

2020 ◽  
Vol 148 ◽  
Author(s):  
R. Rivera ◽  
J. E. Rosenbaum ◽  
W. Quispe
Keyword(s):  
United States ◽  
New York ◽  
New Jersey ◽  
Excess Mortality ◽  
The United States ◽  
Mortality Data ◽  
Surveillance Systems ◽  
Pandemic Response ◽  
Mortality Surveillance ◽  
Mortality Estimates

Abstract Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for emergency response. This study estimates excess all-cause, pneumonia and influenza mortality during the coronavirus disease 2019 (COVID-19) pandemic using the 11 September 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance System (MSS) from 27 September 2015 to 9 May 2020, using semiparametric and conventional time-series models in 13 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Connecticut, Florida, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, Pennsylvania and Washington. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) 100 013–127 501 vs. 78 834 COVID-19 deaths) and 9 states: California (excess mortality 95% CI 3338–6344) vs. 2849 COVID-19 deaths); Connecticut (excess mortality 95% CI 3095–3952) vs. 2932 COVID-19 deaths); Illinois (95% CI 4646–6111) vs. 3525 COVID-19 deaths); Louisiana (excess mortality 95% CI 2341–3183 vs. 2267 COVID-19 deaths); Massachusetts (95% CI 5562–7201 vs. 5050 COVID-19 deaths); New Jersey (95% CI 13 170–16 058 vs. 10 465 COVID-19 deaths); New York (95% CI 32 538–39 960 vs. 26 584 COVID-19 deaths); and Pennsylvania (95% CI 5125–6560 vs. 3793 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise. Significant excess pneumonia deaths were also found for all locations and we estimated hundreds of excess influenza deaths in New York. We find that official COVID-19 mortality substantially understates actual mortality, excess deaths cannot be explained entirely by official COVID-19 death counts. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

scholarly journals Detection of the United States Neisseria meningitidis urethritis clade in the United Kingdom, August and December 2019 – emergence of multiple antibiotic resistance calls for vigilance

2020 ◽  
Vol 25 (15) ◽  
Author(s):  
Avril Brooks ◽  
Jay Lucidarme ◽  
Helen Campbell ◽  
Laura Campbell ◽  
Helen Fifer ◽  
...  
Keyword(s):  
United States ◽  
Antibiotic Resistance ◽  
United Kingdom ◽  
Neisseria Meningitidis ◽  
The United States ◽  
Surveillance Systems ◽  
Multiple Antibiotic Resistance ◽  
The United Kingdom ◽  
The Us ◽  
Sex With Men

Since 2015 in the United States (US), the US Neisseria meningitidis urethritis clade (US_NmUC) has caused a large multistate outbreak of urethritis among heterosexual males. Its ‘parent’ strain caused numerous outbreaks of invasive meningococcal disease among men who have sex with men in Europe and North America. We highlight the arrival and dissemination of US_NmUC in the United Kingdom and the emergence of multiple antibiotic resistance. Surveillance systems should be developed that include anogenital meningococci.

scholarly journals Baseline phenotype and 30-day outcomes of people tested for COVID-19: an international network cohort including >3.32 million people tested with real-time PCR and >219,000 tested positive for SARS-CoV-2 in South Korea, Spain and the United States

2020 ◽  
Author(s):  
Asieh Golozar ◽  
Lana YH Lai ◽  
Anthony G. Sena ◽  
David Vizcaya ◽  
Lisa M. Schilling ◽  
...  
Keyword(s):  
United States ◽  
South Korea ◽  
Large Scale ◽  
The United States ◽  
Routine Care ◽  
Positive Test ◽  
The Us ◽  
Scale Characterization ◽  
Study Participants

ABSTRACTEarly identification of symptoms and comorbidities most predictive of COVID-19 is critical to identify infection, guide policies to effectively contain the pandemic, and improve health systems’ response. Here, we characterised socio-demographics and comorbidity in 3,316,107persons tested and 219,072 persons tested positive for SARS-CoV-2 since January 2020, and their key health outcomes in the month following the first positive test. Routine care data from primary care electronic health records (EHR) from Spain, hospital EHR from the United States (US), and claims data from South Korea and the US were used. The majority of study participants were women aged 18-65 years old. Positive/tested ratio varied greatly geographically (2.2:100 to 31.2:100) and over time (from 50:100 in February-April to 6.8:100 in May-June). Fever, cough and dyspnoea were the most common symptoms at presentation. Between 4%-38% required admission and 1-10.5% died within a month from their first positive test. Observed disparity in testing practices led to variable baseline characteristics and outcomes, both nationally (US) and internationally. Our findings highlight the importance of large scale characterization of COVID-19 international cohorts to inform planning and resource allocation including testing as countries face a second wave.

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