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Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021—an analysis based on the German COVIMOD study
by
Treskova, Marina
, Berger, Tom
, Jarvis, Christopher I.
, Bartz, Antonia
, Killewald, Robin
, Rübsamen, Nicole
, Bucksch, Karolin
, Jaeger, Veronika K.
, Karch, André
, Chaturvedi, Madhav
, Tomori, Damilola Victoria
, Scholz, Stefan
, Mikolajczyk, Rafael
, Walde, Jasmin
, Lange, Berit
in
Age
/ Age groups
/ Analysis
/ Asthma
/ Bone marrow
/ Cardiovascular disease
/ Clustering
/ Comparative analysis
/ Contact behaviour
/ Control
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Decision analysis
/ Decision making
/ Diabetes
/ Epidemics
/ Germany
/ Health aspects
/ Health risk assessment
/ Health risks
/ Heart
/ Humans
/ Infection control
/ Infectious Diseases
/ Internal Medicine
/ Liver diseases
/ Lung diseases
/ Mathematical models
/ Medical Microbiology
/ Medicine
/ Medicine & Public Health
/ Methods
/ Missing data
/ Pandemics
/ Parasitology
/ Population
/ Public Health
/ Questionnaires
/ Reduction
/ Research Article
/ Risk
/ Risk factors
/ Risk groups
/ SARS-CoV-2
/ Severe acute respiratory syndrome coronavirus 2
/ Steroids
/ Surveys
/ Surveys and Questionnaires
/ Tropical Medicine
/ Viral diseases
2023
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Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021—an analysis based on the German COVIMOD study
by
Treskova, Marina
, Berger, Tom
, Jarvis, Christopher I.
, Bartz, Antonia
, Killewald, Robin
, Rübsamen, Nicole
, Bucksch, Karolin
, Jaeger, Veronika K.
, Karch, André
, Chaturvedi, Madhav
, Tomori, Damilola Victoria
, Scholz, Stefan
, Mikolajczyk, Rafael
, Walde, Jasmin
, Lange, Berit
in
Age
/ Age groups
/ Analysis
/ Asthma
/ Bone marrow
/ Cardiovascular disease
/ Clustering
/ Comparative analysis
/ Contact behaviour
/ Control
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Decision analysis
/ Decision making
/ Diabetes
/ Epidemics
/ Germany
/ Health aspects
/ Health risk assessment
/ Health risks
/ Heart
/ Humans
/ Infection control
/ Infectious Diseases
/ Internal Medicine
/ Liver diseases
/ Lung diseases
/ Mathematical models
/ Medical Microbiology
/ Medicine
/ Medicine & Public Health
/ Methods
/ Missing data
/ Pandemics
/ Parasitology
/ Population
/ Public Health
/ Questionnaires
/ Reduction
/ Research Article
/ Risk
/ Risk factors
/ Risk groups
/ SARS-CoV-2
/ Severe acute respiratory syndrome coronavirus 2
/ Steroids
/ Surveys
/ Surveys and Questionnaires
/ Tropical Medicine
/ Viral diseases
2023
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Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021—an analysis based on the German COVIMOD study
by
Treskova, Marina
, Berger, Tom
, Jarvis, Christopher I.
, Bartz, Antonia
, Killewald, Robin
, Rübsamen, Nicole
, Bucksch, Karolin
, Jaeger, Veronika K.
, Karch, André
, Chaturvedi, Madhav
, Tomori, Damilola Victoria
, Scholz, Stefan
, Mikolajczyk, Rafael
, Walde, Jasmin
, Lange, Berit
in
Age
/ Age groups
/ Analysis
/ Asthma
/ Bone marrow
/ Cardiovascular disease
/ Clustering
/ Comparative analysis
/ Contact behaviour
/ Control
/ Coronaviruses
/ COVID-19
/ COVID-19 - epidemiology
/ COVID-19 vaccines
/ Decision analysis
/ Decision making
/ Diabetes
/ Epidemics
/ Germany
/ Health aspects
/ Health risk assessment
/ Health risks
/ Heart
/ Humans
/ Infection control
/ Infectious Diseases
/ Internal Medicine
/ Liver diseases
/ Lung diseases
/ Mathematical models
/ Medical Microbiology
/ Medicine
/ Medicine & Public Health
/ Methods
/ Missing data
/ Pandemics
/ Parasitology
/ Population
/ Public Health
/ Questionnaires
/ Reduction
/ Research Article
/ Risk
/ Risk factors
/ Risk groups
/ SARS-CoV-2
/ Severe acute respiratory syndrome coronavirus 2
/ Steroids
/ Surveys
/ Surveys and Questionnaires
/ Tropical Medicine
/ Viral diseases
2023
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Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021—an analysis based on the German COVIMOD study
Journal Article
Effect of risk status for severe COVID-19 on individual contact behaviour during the SARS-CoV-2 pandemic in 2020/2021—an analysis based on the German COVIMOD study
2023
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Overview
Background
One of the primary aims of contact restriction measures during the SARS-CoV-2 pandemic has been to protect people at increased risk of severe disease from the virus. Knowledge about the uptake of contact restriction measures in this group is critical for public health decision-making. We analysed data from the German contact survey COVIMOD to assess differences in contact patterns based on risk status, and compared this to pre-pandemic data to establish whether there was a differential response to contact reduction measures.
Methods
We quantified differences in contact patterns according to risk status by fitting a generalised linear model accounting for within-participant clustering to contact data from 31 COVIMOD survey waves (April 2020-December 2021), and estimated the population-averaged ratio of mean contacts of persons with high risk for a severe COVID-19 outcome due to age or underlying health conditions, to those without. We then compared the results to pre-pandemic data from the contact surveys HaBIDS and POLYMOD.
Results
Averaged across all analysed waves, COVIMOD participants reported a mean of 3.21 (95% confidence interval (95%CI) 3.14,3.28) daily contacts (truncated at 100), compared to 18.10 (95%CI 17.12,19.06) in POLYMOD and 28.27 (95%CI 26.49,30.15) in HaBIDS.
After adjusting for confounders, COVIMOD participants aged 65 or above had 0.83 times (95%CI 0.79,0.87) the number of contacts as younger age groups. In POLYMOD, this ratio was 0.36 (95%CI 0.30,0.43). There was no clear difference in contact patterns due to increased risk from underlying health conditions in either HaBIDS or COVIMOD. We also found that persons in COVIMOD at high risk due to old age increased their non-household contacts less than those not at such risk after strict restriction measures were lifted.
Conclusions
Over the course of the SARS-CoV-2 pandemic, there was a general reduction in contact numbers in the German population and also a differential response to contact restriction measures based on risk status for severe COVID-19. This differential response needs to be taken into account for parametrisations of mathematical models in a pandemic setting.
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