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  1. Article ; Online: Did “long COVID” increase road deaths in the U.S.?

    Robertson, Leon S.

    medRxiv

    Abstract: Objective To examine data on COVID-19 disease associated with a 10 percent increase in U.S. road ... with road deaths monthly among U.S. states in 2021. Using the regression coefficients, changes ...

    Abstract Objective To examine data on COVID-19 disease associated with a 10 percent increase in U.S. road deaths from 2020 to 2021 that raises the question of the potential effect of pandemic stress and neurological damage from COVID-19 disease. Methods Poisson regression was used to estimate the association of recent COVID-19 cases, accumulated cases, maximum temperatures, truck registrations, and gasoline prices with road deaths monthly among U.S. states in 2021. Using the regression coefficients, changes in each risk factor from 2020 to 2021 were used to calculate expected deaths in 2021 if each factor had remained the same as in 2020. Results Corrected for the other risk factors, road deaths were associated with accumulated COVID-19 cases but not cases in the previous month More than 20,700 road deaths were associated with the changes in accumulated COVID-19 cases but were substantially offset by about 19,100 less-than-expected deaths associated with increased gasoline prices. Conclusions While more research is needed, the data are sufficient to warn people with long COVID to minimize driving.
    Keywords covid19
    Language English
    Publishing date 2023-10-16
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2023.10.11.23296868
    Database COVID19

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  2. Article ; Online: COVID-19 cases associated with testing policies in 34 highly democratic countries, 2020-2022

    Robertson, Leon S.

    medRxiv

    Abstract: COVID-19 testing policies varied in time from testing only the symptomatic, testing the symptomatic and persons at higher risk of severe disease, on-demand testing for people who wanted one, and two periods of government-imposed mass testing in Slovakia. ...

    Abstract COVID-19 testing policies varied in time from testing only the symptomatic, testing the symptomatic and persons at higher risk of severe disease, on-demand testing for people who wanted one, and two periods of government-imposed mass testing in Slovakia. Using Poisson regression, this study examines the associations of COVID-19 cases during the times that the noted policies were in effect in 34 countries rated highest on democracy scores. Statistically corrected for other risk factors, increases in negative tests were associated with subsequent surges in cases when on-demand testing was promoted, particularly when coupled with poor contact tracing. Mass testing in Slovakia was associated with reduced spread of the virus for short periods but was deemed unsustainable. The data support the hypothesis that on-demand testing resulted in the unanticipated consequence of increased travel and increased exposure of travelers to the virus.
    Keywords covid19
    Language English
    Publishing date 2023-10-19
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2023.10.19.23297270
    Database COVID19

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  3. Article ; Online: Association of COVID-19 mortality with politics and on-demand testing in 217 U.S. counties.

    Robertson, Leon S

    BMC public health

    2021  Volume 21, Issue 1, Page(s) 2203

    Abstract: ... of each corrected for the other and a variety of known risk factors.: Methods: Using data from 217 U.S. counties ...

    Abstract Background: Previous research found increased COVID-19 spread associated with politics and on-demand testing but not in the same study. The objective of this study is to estimate the contribution of each corrected for the other and a variety of known risk factors.
    Methods: Using data from 217 U.S. counties of more than 50,000 population where testing data were available in April, 2021, the associations of COVID-19 deaths with politics, testing and other risk factors were examined by Poisson and least squares regression.
    Results: Statistical controls for 15 risk factors failed to eliminate the association of COVID mortality risk with percent of vote for Donald Trump in 2016 or negative tests per population. Each is independently predictive of increased mortality.
    Conclusion: Apparently, many people who test negative for the SARS-CoV-2 virus engage in activities that increase their risk, a problem likely to increase with the availability of home tests. There is no association of negative tests with the Trump vote but, according to polling data, Trump voters' past resistance to public health recommendations has been extended to resistance to being vaccinated, threatening the goal of herd immunity.
    MeSH term(s) COVID-19 ; Humans ; Politics ; Public Health ; SARS-CoV-2
    Language English
    Publishing date 2021-12-02
    Publishing country England
    Document type Journal Article
    ISSN 1471-2458
    ISSN (online) 1471-2458
    DOI 10.1186/s12889-021-12063-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Predictors of COVID-19-Confirmed Cases and Fatalities in 883 US Counties with a Population of 50,000 or More: Estimated Effect of Initial Prevention Policies.

    Robertson, Leon S

    Journal of urban health : bulletin of the New York Academy of Medicine

    2021  Volume 98, Issue 2, Page(s) 205–210

    Abstract: Control of diseases transmitted from person to person may be more effectively and less economically damaging if preventive and ameliorative efforts are focused on the more vulnerable local areas rather than entire countries, provinces, or states. The ... ...

    Abstract Control of diseases transmitted from person to person may be more effectively and less economically damaging if preventive and ameliorative efforts are focused on the more vulnerable local areas rather than entire countries, provinces, or states. The spread of the COVID-19 virus is highly concentrated in urban US counties. Sixteen factors known or thought to be related to spread of the COVID-19 virus were studied by Poisson regression analysis of confirmed cases and deaths in 883 US counties with a population of 50,000 or more as of May 31, 2020. Evidence of crowding in homes, workplaces, religious gatherings, preexisting health conditions in the population, and local economic and demographic conditions, with one exception, was predictive of incidence and mortality. Based on the correlation of cases and deaths to length of stay-at-home orders, the orders were associated with about 52% reduced cases and about 55% reduced deaths from those expected without the orders.
    MeSH term(s) COVID-19 ; Humans ; Incidence ; Policy ; SARS-CoV-2 ; United States/epidemiology
    Language English
    Publishing date 2021-01-25
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1435288-6
    ISSN 1468-2869 ; 1099-3460
    ISSN (online) 1468-2869
    ISSN 1099-3460
    DOI 10.1007/s11524-021-00514-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Ua VI Zs.28: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: Did people's behavior after receiving negative COVID-19 tests contribute to the spread?

    Robertson, Leon S

    Journal of public health (Oxford, England)

    2021  Volume 43, Issue 2, Page(s) 270–273

    Abstract: Background: Testing on demand for coronavirus disease (COVID-19) is hypothesized to increase spread of the virus as some persons who test negative falsely assume that they can engage in activities that increase spread.: Methods: Daily new COVID-19 ... ...

    Abstract Background: Testing on demand for coronavirus disease (COVID-19) is hypothesized to increase spread of the virus as some persons who test negative falsely assume that they can engage in activities that increase spread.
    Methods: Daily new COVID-19 hospitalization counts through 2020 from 25 countries that reported testing and hospitalizations were studied by regression of logarithms of new hospitalizations 14 days out against log(new hospitalizations on a given day), log(negative tests), log(positivity rate) and days since the first hospitalizations were reported. The regression coefficients were examined separately for periods in countries that were following three different testing policies.
    Results: Corrected for the other factors, negative test numbers when tested on demand and tested if symptomatic only are associated with an increase in hospitalizations 14 days after the tests. When only the symptomatic and more vulnerable are tested, negative tests are associated with fewer hospitalizations 2 weeks out.
    Conclusions: A policy of testing only vulnerable populations, whether symptomatic or not, appears to avoid spreading the virus as a result of testing policy. False confidence of reduced risk among those who test negative may have contributed to the spread in countries that allowed testing on demand or testing only those who claimed to have symptoms.
    MeSH term(s) COVID-19 ; Hospitalization ; Humans ; SARS-CoV-2
    Language English
    Publishing date 2021-02-04
    Publishing country England
    Document type Journal Article
    ZDB-ID 2142082-8
    ISSN 1741-3850 ; 1741-3842
    ISSN (online) 1741-3850
    ISSN 1741-3842
    DOI 10.1093/pubmed/fdab010
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 2186: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  6. Book: Injury epidemiology

    Robertson, Leon S.

    research and control strategies

    2007  

    Author's details Leon Robertson
    Keywords Wounds and Injuries / epidemiology ; Epidemiologic Research Design ; Wounds and injuries/Epidemiology ; Wounds and injuries/Epidemiology/Research/Methodology ; United States / epidemiology
    Subject code 614.59
    Language English
    Size VIII, 248 S. : graph. Darst.
    Edition 3. ed.
    Publisher Oxford Univ. Press
    Publishing place Oxford u.a.
    Publishing country Great Britain
    Document type Book
    Note Includes bibliographical references and index. - Previous ed.: 1998
    HBZ-ID HT015278820
    ISBN 0-19-531384-4 ; 978-0-19-531384-0
    Database Catalogue ZB MED Medicine, Health

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    Shelf markLoan statusLocation
    2007 A 5505 order for loan Magazin

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  7. Article ; Online: Association of COVID-19 mortality with politics and on-demand testing in 217 U.S. counties

    Leon S. Robertson

    BMC Public Health, Vol 21, Iss 1, Pp 1-

    2021  Volume 6

    Abstract: ... of each corrected for the other and a variety of known risk factors. Methods Using data from 217 U.S. counties ...

    Abstract Abstract Background Previous research found increased COVID-19 spread associated with politics and on-demand testing but not in the same study. The objective of this study is to estimate the contribution of each corrected for the other and a variety of known risk factors. Methods Using data from 217 U.S. counties of more than 50,000 population where testing data were available in April, 2021, the associations of COVID-19 deaths with politics, testing and other risk factors were examined by Poisson and least squares regression. Results Statistical controls for 15 risk factors failed to eliminate the association of COVID mortality risk with percent of vote for Donald Trump in 2016 or negative tests per population. Each is independently predictive of increased mortality. Conclusion Apparently, many people who test negative for the SARS-CoV-2 virus engage in activities that increase their risk, a problem likely to increase with the availability of home tests. There is no association of negative tests with the Trump vote but, according to polling data, Trump voters’ past resistance to public health recommendations has been extended to resistance to being vaccinated, threatening the goal of herd immunity.
    Keywords COVID testing ; COVID politics ; COVID mortality ; COVID risk factors ; Public aspects of medicine ; RA1-1270
    Subject code 310
    Language English
    Publishing date 2021-12-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Association of COVID-19 spread with on-demand testing

    Robertson, Leon S / Robertson, Leon S.

    medRxiv

    Abstract: Comparisons of COVID-19 testing policies in 99 countries indicate that testing on demand is associated with an increase in cases 14 days after the tests. Adjusted for number of new cases and the positivity rate, for each 10,000 negative tests on a given ... ...

    Abstract Comparisons of COVID-19 testing policies in 99 countries indicate that testing on demand is associated with an increase in cases 14 days after the tests. Adjusted for number of new cases and the positivity rate, for each 10,000 negative tests on a given day there were 90-110 new cases in 14 days that would not have otherwise occurred. Approximately 3.1 million or 21 percent of new cases in periods of on-demand testing are likely due to that policy through early November 2020. During periods in a given country when only persons with symptoms were tested, or persons with symptoms and key vulnerable populations were tested, negative tests were associated with fewer new cases 14 days out. Apparently when tests are available on demand, those who test negative are engaging in activities that increase the risk of exposure.
    Keywords covid19
    Language English
    Publishing date 2020-12-07
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.12.04.20244079
    Database COVID19

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  9. Article ; Online: Predicting Growth of COVID-19 Confirmed Cases in Each U.S. County with a Population of 50,000 or More

    Robertson, Leon S

    medRxiv

    Abstract: ... to predict increases in reported cases two weeks in advance for each of 914 counties in the U.S ...

    Abstract Models of local spread of COVID-19 are needed to assist local governments and health care providers to prepare for surges of clinical cases in their communities. National and state based models are inadequate because the virus is introduced and spreads at different rates in local areas. Models based on motor vehicle traffic measured by tracking cell phones movement in relation to daily numbers of confirmed cases are being developed but this study finds that indicator less effective in predicting future cases than time since the first case in a county. Each county has its own function of time since the first case that can be used to predict increases in reported cases two weeks in advance for each of 914 counties in the U.S. with populations of 50,000 or more inhabitants.
    Keywords covid19
    Language English
    Publishing date 2020-05-29
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.05.29.20117044
    Database COVID19

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  10. Article ; Online: Predicting Growth of COVID-19 Confirmed Cases in Each U.S. County with a Population of 50,000 or More

    Robertson, Leon S

    Abstract: ... inadequate because the virus is introduced and spreads at different rates in local areas. In the U.S ... increases in reported cases two weeks in advance for each of 988 counties in the U.S. with populations of 50 ... for the 988 U.S. counties will be published online daily. ...

    Abstract A simple model of local spread of COVID-19 is needed to assist local governments and health care providers prepare for surges of clinical cases in their communities. National and state based models are inadequate because the virus is introduced and spreads at different rates in local areas. In the U.S. as of July 3, 2020, 73 percent of cases and 84 percent of deaths occurred in the 200 counties with the most cases and deaths. Each county has its own function of cases in time that can be used to predict increases in reported cases two weeks in advance for each of 988 counties in the U.S. with populations of 50,000 or more inhabitants. A logarithmic model based on growth in cases during the past 30 days is substantially predictive of increase in cases during the subsequent 14 days. Predicted increase in cases for the 988 U.S. counties will be published online daily.
    Keywords covid19
    Publisher MedRxiv; WHO
    Document type Article ; Online
    Note WHO #Covidence: #20117044
    DOI 10.1101/2020.05.29.20117044
    Database COVID19

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