Literature DB >> 33056949

Transmission Dynamics by Age Group in COVID-19 Hotspot Counties - United States, April-September 2020.

Alexandra M Oster1, Elise Caruso1, Jourdan DeVies1, Kathleen P Hartnett1, Tegan K Boehmer1.   

Abstract

CDC works with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to state, tribal, local, and territorial health departments to limit the spread of SARS-CoV-2, the virus that causes COVID-19 (1). Understanding whether increasing incidence in hotspot counties is predominantly occurring in specific age groups is important for identifying opportunities to prevent or reduce transmission. The percentage of positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results (percent positivity) is an important indicator of community transmission.* CDC analyzed temporal trends in percent positivity by age group in COVID-19 hotspot counties before and after their identification as hotspots. Among 767 hotspot counties identified during June and July 2020, early increases in the percent positivity among persons aged ≤24 years were followed by several weeks of increasing percent positivity in persons aged ≥25 years. Addressing transmission among young adults is an urgent public health priority.

Entities:  

Mesh:

Year:  2020        PMID: 33056949      PMCID: PMC7561089          DOI: 10.15585/mmwr.mm6941e1

Source DB:  PubMed          Journal:  MMWR Morb Mortal Wkly Rep        ISSN: 0149-2195            Impact factor:   17.586


CDC works with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to state, tribal, local, and territorial health departments to limit the spread of SARS-CoV-2, the virus that causes COVID-19 (). Understanding whether increasing incidence in hotspot counties is predominantly occurring in specific age groups is important for identifying opportunities to prevent or reduce transmission. The percentage of positive SARS-CoV-2 reverse transcription–polymerase chain reaction (RT-PCR) test results (percent positivity) is an important indicator of community transmission.* CDC analyzed temporal trends in percent positivity by age group in COVID-19 hotspot counties before and after their identification as hotspots. Among 767 hotspot counties identified during June and July 2020, early increases in the percent positivity among persons aged ≤24 years were followed by several weeks of increasing percent positivity in persons aged ≥25 years. Addressing transmission among young adults is an urgent public health priority. Hotspot counties were identified by applying previously described standardized criteria to detect counties that had >100 cases during the past 7 days and experienced increases in cases in the preceding 3–7 days (). Counties identified as hotspots during June 1–July 31, 2020, that had not met hotspot criteria in the previous 21 days were included. SARS-CoV-2 RT-PCR test results were obtained from data submitted by state health departments and laboratories. Percent positivity was calculated by dividing the number of positive test results by the sum of positive and negative test results for each age group (0–17, 18–24, 25–44, 45–64, and ≥65 years) for the 45 days before and 45 days after hotspot detection (spanning April–September 2020) based on specimen collection or test order date. Data were presented using a 7-day moving average. Results were aggregated across all hotspot counties and stratified by age group. Analyses were conducted using R software (version 3.6.0; The R Foundation). The 767 hotspot counties detected during June 1–July 31 represented 24% of all U.S. counties and 63% of the U.S. population. Percent positivity among persons aged 0–17 and 18–24 years began increasing 31 days before hotspot identification. Increases in percent positivity among older age groups began after the increases in younger age groups: among adults aged 25–44 years, 45–64 years, and ≥65 years, increases began 28 days, 23 days, and 20 days, respectively, before hotspot identification (Figure 1). At the time of hotspot detection, the highest percent positivity was among persons aged 18–24 years (14%), followed by those aged 0–17 years (11%), 25–44 years (10%), 45–64 years (8%), and ≥65 years (6%). Percent positivity among persons aged 18–24 years was near its peak of 15% by the date of hotspot detection; however, among other age groups, percent positivity continued to increase for 21–33 days after hotspot detection, peaking at 10%–14%, and the decline for other age groups was slower than that for persons aged 18–24 years.
FIGURE 1

Percentage of positive SARS-CoV-2 reverse transcription–polymerase chain reaction test results (7-day moving average)* in COVID-19 hotspot counties before and after date of hotspot detection, by age group — United States, June 1–July 31, 2020

Abbreviation: COVID-19 = coronavirus disease 2019.

* From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, using specimen collection or test order date.

Percentage of positive SARS-CoV-2 reverse transcription–polymerase chain reaction test results (7-day moving average)* in COVID-19 hotspot counties before and after date of hotspot detection, by age group — United States, June 1–July 31, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, using specimen collection or test order date. Important differences were identified when analyzing percent positivity by U.S. Census region (Figure 2). Trends by age for hotspot counties in the South (488 counties) and West (98 counties) aligned with national trends, although percent positivity was higher in the South than in the West for all age groups. In hotspot counties in the Midwest (134 counties), percent positivity among persons aged 18–24 years peaked before hotspot detection, and percent positivity increased minimally in other age groups. In hotspot counties in the Northeast (47 counties), there was a small increase in percent positivity among persons aged 18–24 years but minimal or no increases in other age groups.
FIGURE 2

Percentage of positive SARS-CoV-2 reverse transcription–polymerase chain reaction test results (7-day moving average)* in COVID-19 hotspot counties before and after date of hotspot detection, by age group and U.S. Census region — United States, June 1–July 31, 2020

Abbreviation: COVID-19 = coronavirus disease 2019.

* From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, using specimen collection or test order date.

† South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia. West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont.

Percentage of positive SARS-CoV-2 reverse transcription–polymerase chain reaction test results (7-day moving average)* in COVID-19 hotspot counties before and after date of hotspot detection, by age group and U.S. Census region — United States, June 1–July 31, 2020 Abbreviation: COVID-19 = coronavirus disease 2019. * From COVID-19 electronic laboratory reporting data submitted by state health departments for 37 states and from data submitted directly by public health, commercial, and reference laboratories for 13 states and the District of Columbia, using specimen collection or test order date. † South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia. West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In hotspot counties, particularly those in the South and West, percent positivity increased earliest in younger persons, followed by several weeks of increasing percent positivity among older age groups. An increase in the percentage of positive test results in older age groups is likely to result in more hospitalizations, severe illnesses, and deaths. These findings corroborate regional patterns in the southern United States, where increased percent positivity among adults aged 20–39 years preceded increases among those aged ≥60 years (); provide evidence that among young adults, those aged 18–24 years demonstrate the earliest increases in percent positivity; and underscore the importance of reducing transmission from younger populations to those at highest risk for severe illness or death. There is an urgent need to address transmission among young adult populations, especially given recent increases in COVID-19 incidence among young adults (). These data also demonstrate the urgency of health care preparedness in hotspot counties,** which are likely to experience increases in COVID-19 cases and hospitalizations among older populations in the weeks after meeting hotspot criteria.
  3 in total

1.  Changing Age Distribution of the COVID-19 Pandemic - United States, May-August 2020.

Authors:  Tegan K Boehmer; Jourdan DeVies; Elise Caruso; Katharina L van Santen; Shichao Tang; Carla L Black; Kathleen P Hartnett; Aaron Kite-Powell; Stephanie Dietz; Matthew Lozier; Adi V Gundlapalli
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-10-02       Impact factor: 17.586

2.  Trends in Number and Distribution of COVID-19 Hotspot Counties - United States, March 8-July 15, 2020.

Authors:  Alexandra M Oster; Gloria J Kang; Amy E Cha; Vladislav Beresovsky; Charles E Rose; Gabriel Rainisch; Laura Porter; Eduardo E Valverde; Elisha B Peterson; Anne K Driscoll; Tina Norris; Nana Wilson; Matthew Ritchey; Henry T Walke; Dale A Rose; Nadia L Oussayef; Monica E Parise; Zack S Moore; Aaron T Fleischauer; Margaret A Honein; Emilio Dirlikov; Julie Villanueva
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-08-21       Impact factor: 17.586

3.  Recent Increase in COVID-19 Cases Reported Among Adults Aged 18-22 Years - United States, May 31-September 5, 2020.

Authors:  Phillip P Salvatore; Erisa Sula; Jayme P Coyle; Elise Caruso; Amanda R Smith; Rebecca S Levine; Brittney N Baack; Roger Mir; Edward R Lockhart; Tejpratap S P Tiwari; Deborah L Dee; Tegan K Boehmer; Brendan R Jackson; Achuyt Bhattarai
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-10-02       Impact factor: 17.586

  3 in total
  24 in total

1.  A mixed-methods study to assess COVID-19 vaccination acceptability among university students in the United Arab Emirates.

Authors:  Hamzah Alzubaidi; Catarina Samorinha; Basema Saddik; Ward Saidawi; Abduelmula R Abduelkarem; Eman Abu-Gharbieh; Susan M Sherman
Journal:  Hum Vaccin Immunother       Date:  2021-09-17       Impact factor: 4.526

2.  Predicting COVID-19 county-level case number trend by combining demographic characteristics and social distancing policies.

Authors:  Megan Mun Li; Anh Pham; Tsung-Ting Kuo
Journal:  JAMIA Open       Date:  2022-06-25

3.  Characterization of test positivity among patients with coronavirus disease 2019 (COVID-19) in three electronic health records databases, February-November 2020.

Authors:  Patrick Saunders-Hastings; Cindy Ke Zhou; Shayan Hobbi; Hui-Lee Wong; Patricia Lloyd; Eva Boyd; Nader Alawar; Tainya C Clarke; Jeff Beers; Timothy Burrell; Azadeh Shoaibi
Journal:  BMC Public Health       Date:  2022-06-18       Impact factor: 4.135

4.  Clinical Characteristics and Potential Risk Factors Associated with the SARS-CoV-2 Infection: Survey on a Health Care Workers (HCWs) Population in Northern Italy.

Authors:  Viola Novelli; Federico Fassio; Guido Resani; Martino Bussa; Alessandro Durbano; Alessandro Meloni; Giovanni Oliva; Sara Cutti; Daniela Girardi; Anna Odone; Simona Villani; Carlo Marena; Alba Muzzi; Maria Cristina Monti
Journal:  Int J Environ Res Public Health       Date:  2022-07-04       Impact factor: 4.614

5.  Epidemiology of Coronavirus Disease 2019 in Japan: Descriptive Findings and Lessons Learned through Surveillance during the First Three Waves.

Authors:  Yuzo Arima; Kazuhiko Kanou; Takeshi Arashiro; Yura K Ko; Kanako Otani; Yuuki Tsuchihashi; Takuri Takahashi; Reiko Miyahara; Tomimasa Sunagawa; Motoi Suzuki
Journal:  JMA J       Date:  2021-07-09

6.  Outcomes of a Student-Led Telemedicine Clinic in Response to COVID-19.

Authors:  Elliot H Akama-Garren; Shivani A Shah; Aniket N Zinzuwadia; Andrew Bartuska; Mie Hashimoto; Jacqueline T Chu; Gina R Kruse; Marya J Cohen
Journal:  J Ambul Care Manage       Date:  2021 Jul-Sep 01

7.  The influence of selection bias on identifying an association between allergy medication use and SARS-CoV-2 infection.

Authors:  Lindsay A Thompson; Matthew J Gurka; Stephanie L Filipp; Desmond A Schatz; Rebeccah E Mercado; David A Ostrov; Mark A Atkinson; Sonja A Rasmussen
Journal:  EClinicalMedicine       Date:  2021-06-04

8.  Conduct Problems and Adherence to COVID-19 Guidelines: A Developmental Psychopathology-Informed Approach.

Authors:  Alexa Martin-Storey; Caroline Temcheff; Michèle Déry; Mélanie Lapalme; Melina Tomasiello; Audrey Mariamo; Jean-Pascal Lemelin
Journal:  Res Child Adolesc Psychopathol       Date:  2021-03-19

9.  Analyzing changes to U.S. municipal heat response plans during the COVID-19 pandemic.

Authors:  Andrew Shida Jin; Kelly T Sanders
Journal:  Environ Sci Policy       Date:  2021-11-30       Impact factor: 5.581

10.  Recent Increase in COVID-19 Cases Reported Among Adults Aged 18-22 Years - United States, May 31-September 5, 2020.

Authors:  Phillip P Salvatore; Erisa Sula; Jayme P Coyle; Elise Caruso; Amanda R Smith; Rebecca S Levine; Brittney N Baack; Roger Mir; Edward R Lockhart; Tejpratap S P Tiwari; Deborah L Dee; Tegan K Boehmer; Brendan R Jackson; Achuyt Bhattarai
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2020-10-02       Impact factor: 17.586

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.