Skip to main content

Results of the Cologne Corona Surveillance (CoCoS) study – a cross-sectional study: survey data on risk factors of SARS-CoV-2 infection in adults

Abstract

Background

The personal, environmental, and behavioral risk factors that play an important role in the spread of SARS-CoV-2 are still largely unclear. At the same time, there is limited evidence on the effectiveness of specific countermeasures for SARS-CoV-2. As a first approach to these questions, we use data from the Cologne Corona Surveillance (CoCoS) study, a large cross-sectional study conducted in Cologne, Germany, in June 2021.

Methods

This study was conducted in Cologne, Germany. Six thousand randomly selected Cologne residents who were 18 years of age or older were invited to participate in this study. Participant information was obtained via an online survey. Previous SARS-CoV-2 infections were recorded using self-reports. Sociodemographic and environmental information such as age, sex, living situation were collected. Potential SARS-CoV-2 risk behaviors were captured (workplace situation, adherence to hygiene regulations, and regular use of public transportation). Adherence to hygiene regulations was surveyed by determining the compliance with the ‘AHA’-rules (German acronym that stands for keeping a distance of 1.5 m from fellow citizens, hand disinfection, and wearing a face mask). Binary logistic regression analysis was used to identify risk factors for SARS-CoV-2 infection.

Results

A sample of 2,433 study participants provided information. Comparison of the sample with the general population showed representativeness for most sociodemographic characteristics with a preference for higher level of education in the study sample. Younger age, as well as living with minor children (under 18 years) in the same household were associated with a higher number of self-reported SARS-CoV-2 infections. Adherence to hygiene regulations was associated with fewer self-reported SARS-CoV-2 infections in adults. Gender, size of living space per person, workplace situation (work from home versus working with contact to colleagues/customers), and regular use of public transportation showed no significant association with self-reported SARS-CoV-2 infections in multivariable analysis.

Conclusion

The presented results provide initial indications of which sociodemographic and behavioral factors may be associated with SARS-CoV-2 infection. However, the fact that these factors were recorded without exact dates and could have changed accordingly during the pandemic or after infection limits the strength of the results.

Trial registration

DRKS.de, German Clinical Trials Register (DRKS), Identifier: DRKS00024046, Registered on 25 February 2021.

Peer Review reports

Introduction

The SARS-CoV-2 pandemic has resulted in a global health crisis. More than 570 million people worldwide tested positive for SARS-CoV-2 at the time of writing in August 2022 [1]. Meanwhile, German health authorities have reported over 30 million cases and over 144,000 SARS-CoV-2-related deaths [2].

In order to prevent an overload of the health care system, the federal government of Germany initiated countermeasures against the spread of SARS-CoV-2. Citizens had to severely limit their social contacts [3]. This also included the occupational sector. Employees were encouraged to work from home or to minimize contact with customers and colleagues [4]. A closure of public schools and kindergartens was implemented over long periods [5]. At times, further closures, for example restaurants and retail were initiated [3] and curfews imposed. It was strongly recommended to follow the applicable hygiene regulations, which, in addition to social distancing, included washing hands regularly and wearing a face mask [5]. Local public transport was maintained to a reduced extent [6].

Groups with a higher risk for severe courses of illness were mainly defined by older age and pre-existing health conditions [7]. Those individuals were entitled to protective measures like an early supply of face masks, transportation services to avoid public traffic, and prioritized access to early vaccinations [6].

Implementing countermeasures came with the price of serious psychological, social and economic burden [8]. At the same time, the effectiveness of specific countermeasures and their interrelation remains largely unclear and little evidence is publicly available to this day. As a first approach to these questions, we use data from the Cologne Corona Surveillance (CoCoS) study, a large cross-sectional study conducted in Cologne, Germany, in March and June 2021 [9]. The aim was to identify associations between specific sociodemographic and behavioral factors and the cumulative prevalence of SARS-CoV-2 infection.

Methods

A detailed description of the CoCoS study design can be found elsewhere [1]. First results of the CoCoS study including saliva probes have been published [10]. Participants had to be citizens of Cologne 18 years of age or older and were identified using municipal registration. In the official registration management program (MESO, HSH Soft- und Hardware Vertriebs GmbH, Ahrensfelde OT Lindenberg, Germany) a random sample of citizens meeting the inclusion criteria for inclusion in the database was drawn using a generator. The original study consisted of two surveillance rounds, the first in March 2021 and the second in June 2021. We present the data from the second surveillance round. The study design thus corresponds to a cross-sectional study design. A flowchart of the enrollment of study participants is shown in Fig. 1.

Fig. 1
figure 1

Flow chart of enrollment and written consent in each surveillance round

Setting

Cologne is located in the federal state of North Rhine-Westphalia and is the fourth largest city in Germany. The city has 1.1 million inhabitants of 183 different nationalities. Administratively, Cologne is organized into nine districts and 86 sub-districts. Of note, 17.5% of the population belong to the vulnerable age group (over 65 years) for SARS-CoV-2-infections [11]. Meanwhile, over 413,000 SARS-CoV-2-cases have been officially reported in Cologne [12]. Locally reported cases of SARS-CoV-2 infections were primarily congruent with the numbers throughout Germany [12]. The citizens of Cologne were subjected to SARS-CoV-2-countermeasures according to instructions of the federal state authorities of North Rhine-Westphalia and their local implementation by a municipal crisis unit [5].

Questionnaire

The participants received the invitation to our study by mail. Besides a request for written consent, the invitation letter contained a QR code with authorization to participate in the online survey. The questionnaire was designed similarly to the ELISA and MuSPAD questionnaires developed by the ‘Helmholtz Zentrum für Infektionsforschung, Braunschweig, Germany’ [13]. Firstly, the online survey requested basic information such as age and gender. Participants were asked if they received a positive SARS-CoV-2 test result in the past. This question did not include COVID-19 self-tests but asked explicitly for PCR-test confirmed infection. Subjects could answer ‘yes’, ‘no’ or ‘do not specify’ as response options here. If subjects selected ‘Yes’, the follow-up question presented the following options: ‘I had a positive test result at least once’, ‘I had negative test results only’, ‘test result not known' or ‘no indication’. This strategy of questioning was intended to indicate all PCR test confirmed infections known to the subjects themselves. The questionnaire also included questions about participants’ living conditions. Participants were asked about the size of the living space per person and the number of minor children in the household. For data analysis the variable ‘age’ was stratified into the categories 18 to 44, 45 to 64, and 65 years of age or older with the latter as reference category. Living space per person was divided into categories ‘less than 25m2 per person’, ‘25 to 50m2 per person’, and ‘more than 50m2 per person’ (reference category). The variable ‘number of minor children in household’ was subdivided into the categories ‘no children under 18 years in household’, ‘one child under 18 years in household’, and ‘two or more children under 18 years in household’ because only 45 participants stated that they had three children or more.

In the following section, data considering potential risk behaviors of the participants was collected. These included the workplace situation, adherence to hygiene regulations, and regular use of public transportation. With regard to workplace situation, participants were asked about the use of ‘working from home’ and contact with employees or customers at work. The variable ‘workplace situation’ included the categories ‘working from home or at working without contact to customers or colleagues’, ‘at work with contact to customers and/or colleagues’, and ‘not working’ (reference category). Adherence to hygiene regulations was defined as adherence to the so-called ‘AHA-rules’. The acronym 'AHA' stands for the German initials of the words for keeping your distance, washing/disinfecting your hands and wearing a face mask. The acronym 'AHA' was also used in official language in Germany to communicate hygiene regulations [4] and should have been widely known accordingly. Participants could indicate whether or not they followed the AHA-rules. The regular use of public transportation was queried by asking subjects to indicate whether they regularly used public transportation in the period from February 1, 2020 (the start of the pandemic) to the day of the survey. Participants were given the choice of answering: 'Yes, I regularly used public transport during this period' or 'No, I did not regularly use public transport during this period'. Regular use was counted if the participant reported to frequently use one of the vehicles 'bus', 'train', or 'cab' in the given time period.

It was assumed that uncertainties about online questionnaires occur disproportionately often in the group of older participants, and to prevent distortions here, the option of conducting the questionnaire in the form of a telephone interview was set up.

Statistical analysis

Absolute and relative frequencies of key sociodemographic characteristics of the sample of 6,000 potential participants were determined using data from the municipal registration office. Absolute and relative frequencies of the more in-depth sociodemographic information from the questionnaire were determined from the participant sample. The sociodemographic information of potential participants and the participant sample were compared with the official statistics of the city of Cologne on its adult general population [11].

Binary logistic regression analysis was used to identify associations between the surveyed sociodemographic and behavioral factors and self-reported SARS-CoV-2 infection. The following sociodemographic and behavioral factors were considered: age, gender, living space per person, number of minor children in household, workplace situation, adherence to hygiene regulations (AHA-regulations) and use of public transportation. Univariable logistic regression was fitted for each variable. Before multivariable logistic regression was carried out, multicollinearity was assessed by examining variance inflation factors (VIFs) of all included variables. Any variable with VIF larger than five was supposed to be excluded.

All variables were initially included in the multivariable analysis. In the case of the variables 'Age' and 'Living space per person', which were evaluated univariably both continuously and discretely, the continuous variable was included in the multivariable analysis, since it provides more information than the variables divided into categories. Stepwise backward selection based on p > 0.05 (Wald statistic) was used for exclusion to identify relevant associations.

All reported p-values are 2-sided and were considered statistically significant if below 0.05. We did not adjust for multiple testing due to the explorative and descriptive character of this study. Calculations and figures were carried out using SPSS Statistics (IBM Corp., Armonk, NY, USA) and Excel (Microsoft Corp., Redmond, WA, USA), as well as R (R Foundation for Statistical Computing, Vienna, Austria).

Results

Study recruitment and population

The flow chart of study recruitment is depicted in Fig. 1. In the first round of CoCoS study in March 2021, 6,000 participants were invited. Participants who had completed the first round were invited again for the second round in June 2021. The number of participants who had completed the first surveillance round and were therefore invited to the second round was 2,321 corresponding to 38.7%. Therefore, 3,679 new participants were additionally invited. From this resulting sample of 6,000 for the second round, 2,500 provided written consent and 2,433 who completed the online survey will be used to examine SARS-CoV-2 risk factors using their information given at the time of June 2021.

Description of study participants

A detailed description of the study population’s sociodemographic characteristics is provided in Table 1. The study population was reasonably representative of the general adult population regarding gender, age, and size of household. However, the participants in the CoCoS study showed a higher level of education than the general population of Cologne regarding high school graduation (55.00%/75.14%). Moreover, the participants with citizenship other than German were underrepresented with 5.87% in the study whereas 20.32% of the general adult population of Cologne have a citizenship other than German. Not least, the study participants reported fewer SARS-CoV-2 infections with 3.45% (95% CI 2.73%-4.18%) compared to 5.06% (95% CI 3.60%-5.61%) officially recorded by Cologne health authorities in June 2021. In addition, the vaccination rate of the study sample was significantly higher with 79.95% receiving at least one vaccination in comparison to 66.23% of the general adult population receiving at least one vaccination by June 18th, 2021. At the same time, the rate of unvaccinated individuals in the study sample was lower compared to the general adult population (33.76%/20.05%).

Table 1 Sociodemographic characteristics and SARS-CoV-2 specific information of the CoCoS study collective (survey completed, n = 2,433) compared to the potential participants and the general adult Cologne population

Analysis of associations between the surveyed sociodemographic and behavioral factors and SARS-CoV-2 infection

Data of 2,433 participants were included in the statistical analysis. Eighty-four participants reported a previous infection with SARS-CoV-2 (3.45%; CI 2.73–4.18). The results of both univariable and multivariable logistic regression analyses are presented in Table 2 and depicted in Fig. 2. Estimated marginal means of probabilities for SARS-CoV-2 infection from multivariable logistic regression are shown in Fig. 3. In the multivariable analysis, 1,794 participants could be included. The multicollinearity test did not reveal any indication to take further steps, all predictors had a VIF smaller than 1.4. The results of the multicollinearity assessment are included in the Supplementary Material to this article. Sensitivity analysis using the subset of participants for multivariable analysis on univariable analyses is also provided in the Supplementary Material to this article.

Table 2 Results of univariable and multivariable logistic regression
Fig. 2
figure 2

Forest plots of the results of univariable and multivariable logistic regression. A Univariable risk factor analysis, B Multivariable risk factor analysis, CI: confidence interval

Fig. 3
figure 3

Estimated marginal means of probabilities for SARS-CoV-2 infection from multivariable logistic regression with stepwise backward selection (Wald statistic as criterion). *Calculated as estimated marginal means from multivariable analysis. A Probability for SARS-CoV-2 infection [%] depending on predictor variable ‘age’ (continuous). B Probability for SARS-CoV-2 infection [%] depending on predictor variable ‘number of minor children in household’. C Probability for SARS-CoV-2 infection [%] depending on predictor variable ‘adherence to hygiene regulations’

Associations between sociodemographic factors and SARS-CoV-2 infection

The univariable analysis revealed that younger age was significantly associated with a higher number of SARS-CoV-2 infections (OR 0.972, 95% CI: 0.959–0.985, p < 0.001). Accordingly, the percentage of participants reporting an infection was the lowest within the age group of over65 years with 1.1% (6/546) compared to 3.4% (31/906) within the age group 45–64 years and 4.8% (47/981) within the age group 18–44 years. Compared to reference age group of over 65 years, participants in the age group 45–64 years (OR 3.189, 95% CI: 1.322–7.693, p = 0.010) and in the age group 18–44 years (OR 4.529, 95% CI: 1.924–10.663, p = 0.001) were significantly less likely to report past SARS-CoV-2 infections. The association between younger age and more SARS-CoV-2 infections also persisted in the multivariable model. Multivariable logistic regression showed a significant decrease in the odds of infection by 2.6% per year of age (OR 0.974, 95% CI: 0.959–0.990, p = 0.002). Gender did not show to be significantly associated with SARS-CoV-2 infection, neither in univariable nor in multivariable logistic regression (p = 0.705).

In univariable analysis, a significantly higher probability of self-reported infection with SARS-CoV-2 was found for smaller living space per person (OR 0.983, 95% CI: 0.970–0.996, p = 0.010). A percentage of 2.6% (17/652) of participants reported a SARS-CoV-2 infection in the category living in > 50m2 per person, 4.2% (42/993) in the category living in 25-50m2 per person and 9.0% (17/188) in the category living in less than25m2 per person. Participants in the category with less than 25m2 were significantly more likely to report past SARS-CoV-2 infections than the reference category of participants with more than 50 m2 of living space (OR 3.713, 95% CI: 1.857–7.427, p < 0.001). Interestingly, the association between square meters per person of living space and SRAS-CoV-2 infection was no longer statistically significant in the multivariable logistic regression. The variable was excluded from the model during stepwise backward selection.

The number of minor children in household was found to be significantly associated with the number of reported SARS-CoV-2 infections in univariable analysis (p = 0.005). Among participants living without minor children in the household, 2.9% (59/2014) reported that they had undergone a SARS-CoV-2 infection. Among those living with one minor child in the household, 4.9% (11/223) reported past SARS-CoV-2 infections, and those living with two or more minor children in the same household, 7.1% (14/196) reported past SARS-CoV-2 infections. Participants living with two children or more were statistically significant more likely to report past SARS-CoV-2 infections than the reference category of participants without minor children in household in univariable analysis (OR 2.549, 95% CI: 1.396–4.654, p = 0.002). This pattern also persisted in the multivariable model (p = 0.016, comparison between ‘two or more children’ and ‘no children’: OR 2.326, 95% CI: 1.243–4.354, p = 0.008).

Associations between behavioral factors and SARS-CoV-2 infection

Univariable analysis identified a significant association between workplace situation and reported SARS-CoV-2 infections (p = 0.013). The workplace situation with work from home or at work without contact to customers or colleagues showed a percentage of 3.0% (25/823) reported infections compared to 6.2% (34/547) reported infections in the workplace situation with regular contact to customers and colleagues. At the same time, the not-working reference group reported 3.5% (20/564) of infections. The greater odds of participants with regular contact to customers and colleagues to report past SARS-CoV-2 infections compared to reference group of not-working individuals reached statistical significance in univariable analysis (OR 1.803, 95% 1.024–3.173, p = 0.041). However, in the multivariable analysis, the significant association between the situation at work and reported past SARS-CoV-2 infections did not hold. The variable was excluded from the model during stepwise backward selection.

Adherence to hygiene regulations (adherence to the widely implemented AHA-rules) was associated with a lower probability of SARS-CoV-2 infection. In the adherent group, a percentage of 2.5% (15/604) of participants reported an infection compared to 3.8% (69/1829) in the non-adherent group. This result failed to reach statistical significance in univariable analysis using the entire sample (n = 2,433, p = 0.135). However, sensitivity analysis using the subset of participants for multivariable analysis on univariable analysis (see supplementary material to this article) showed significant influence of adherence to hygiene regulations (p = 0.018). In the multivariable analysis, non-adherence to hygiene regulation was found to be significantly associated with a higher number of SARS-CoV-2 infections (OR 1.957, 95% CI 1.043, 3.669, p = 0.036) compared to adherence to hygiene regulations. Whether or not participants regularly used public transportation was not significantly associated with reported past SARS-CoV-2 infections, neither in univariable (p = 0.751) nor in multivariable logistic regression. A joint description based on the actual data of the high-risk group with younger age, minor children living in the same household, and no adherence to hygiene recommendations is provided in the supplementary material to this article.

Discussion

This study provides data on cumulative self-reported SARS-CoV-2 infections in the adult Cologne population from the beginning of the pandemic until June 2021. Combined with a questionnaire on sociodemographic characteristics and behaviors, the study provides first indications of which sociodemographic characteristics and which behaviors might be associated with a higher number of SARS-CoV-2 infections. Our results show that younger people are more likely to acquire SARS-CoV-2 infection than older people. In addition, the results show an association between self-reported SARS-CoV-2 infection and living with minor children (under 18 years) in the household, as well as non-adherence to common hygiene regulations (AHA-regulations). At the same time, multivariable analysis showed no statistically significant association between self-reported SARS-CoV-2 infection and gender, living space per person, workplace situation, and regular use of public transportation (regular use of bus, train, or cab).

The model derived from the survey results shows that cumulative cases decrease sharply with age. Similar studies have confirmed that older age is associated with a lower prevalence of SARS-CoV-2 [14]. A possible explanation for this finding is that older people are more risk averse, having a higher likelihood of severe course of illness and higher mortality [15]. Studies show that older people indeed reported to be more careful and adherent to protective measures [16]. Furthermore, the decrease of infections by year of age could also be influenced by early vaccinations in the older population [14]. Although much less common, younger adults can also become seriously ill with COVID-19. In addition, numerous infections in the younger population can lead to a faster spread of SARS-CoV-2 [17]. One way to reduce the number of infections among younger people could be to increase awareness campaigns explicitly targeting this age group. This is already being addressed in the campaign presented by the German Federal Ministry of Health in October 2022, in which younger testimonials also emphasize the importance of protecting against the pandemic. The data of the present study do not provide any indications as to which aspects such campaigns should particularly address in order to reach younger people especially well. Future studies should explore these questions in order to make campaigns as effective as possible.

The finding that living with minor children in the same household is significantly associated with more self-reported SARS-CoV-2 infections of adults should be further investigated in future studies. It should be noted that similar studies have also reached other conclusions that argue against an increased risk for adults living with minor children in the household [17]. A comparison between the risk of living with other adults and the risk of living with minors would allow a more nuanced risk evaluation, since living with minor children entails different daily chores and external exposures. If it is confirmed that living with children favors infections, measures such as additional sick leave for parents, as the German government has done for 2021, would certainly be a useful relief for families.

Adherence versus non-adherence to hygiene recommendations did not prove to be significant in the univariable model, but it did prove to be significantly associated with SARS-CoV-2 infection in the multivariable model. Wearing face masks, hand disinfection and keeping a 1.5 m distance from fellow citizens have been enforced by the German government (commonly known in Germany by the acronym ‘AHA-rules’, which stands for the first letters of the German words for keep your distance, wash your hands and wear a face mask) since early in the pandemic in 2020 [6]. In line with similar previous findings [17], adherence to the hygiene measures known as ‘AHA-rules’ in Germany were associated with fewer self-reported SARS-CoV-2 infections in the examined study population. However, it should not be ignored that people who follow the AHA rules may also be more likely to adopt broader preventive measures, such as general avoidance of social contact. Future studies should capture these further prevention strategies and analyze the effectiveness of adherence to the AHA rules in the context of these broader prevention strategies.

In the presented study population, gender was not associated with the cumulative prevalence of self-reported SARS-CoV-2 infection among the participants (p = 0.705). This was different in other studies that found a slightly increased risk of infection among male participants [17]. Those differences could be explained by varying sociodemographic characteristics in different study samples. Therefore, the effect of gender should be further investigated in upcoming studies.

Moreover, previous studies have shown that lesser living space per person increases the risk of SARS-CoV-2 infection [18]. In a recent study of our group, a lower socio-economic status was shown to be associated with an increased risk for SARS-CoV-2 infection [18]. However, in the current study, statistically significant association between less living space per person and more SARS-CoV-2 infections was only detected in the univariable logistic analysis indicating interactions with other living conditions such as children in the household.

Compared to the unemployed reference group, participants in the regular workplace situation with customer and coworker contact reported a much higher percentage of SARS-CoV-2 infections. This result was significant in univariable logistic regression. According to the ‘SARS-CoV-2 Occupational Health and Safety’ ordinance from January 21, 2021 [4], general measures such as wearing a face mask, regular ventilation in closed rooms, and frequent SARS-CoV-2 testing were required in the regular workplace situation [5]. Therefore, protection against SARS-CoV-2 should have been provided to a certain degree in the regular work situation with customer and employee contact, although it remains unclear to what degree these specified measures were actually implemented. Work from home and work without interpersonal contact showed a lower percentage and lower association with SARS-CoV-2 infection. In addition, the effect of working from home in reducing infection risk has been observed in similar studies [17]. Results regarding the risk of infection at the regular workplace were published, especially about occupations with much SARS-CoV-2 contact showing a higher risk of infection [19]. It must be mentioned that not every occupational group has the opportunity of working from home, such as health care workers. Additionally, the association was no longer apparent in the multivariable logistic regression. This could be due to interactions with other included variables.

The here presented analyses come with strengths and limitations. A strength of the study is its large, representative sample. The participation rate of this study is comparable to most cohort studies with multiple conduction rounds in Germany [20]. The questionnaire covered a wide range of areas and created a detailed picture of the participant’s sociodemographic profile and behaviors potentially associated with SARS-CoV-2 infection. A detailed analysis of the estimated SARS-CoV-2 incidence in this study sample has been published elsewhere [10]. However, the cumulative SARS-CoV-2 cases in the study population are 3.45% (95% CI 2.73–4.18). This is less than the official figures in this period, which were 5.06% (95% CI 3.60%-5.61). The difference could be explained by sociodemographic differences in the study sample with a higher acceptance of measures to contain COVID-19 compared to the general population resulting in fewer infections. Future conduction periods could aim at a higher participation rate, especially in underrepresented sociodemographic groups more likely to report a SARS-CoV-2 infection [18].

The sociodemographic characteristics of the sample indicate differences to the general adult population of Cologne in some respects. The sample shows a clear preference for a higher level of education, which can be associated with a higher socio-economic status. This assumption can be supported by a significantly lower percentage of unemployment in the study sample (4.6% in the general Cologne population versus 2.45% in the sample). These selection effects might have favored a lower estimated incidence in the sample. A recent study of our group shows that districts of Cologne with a lower socio-economic status reported more cumulative SARS-CoV-2 cases from February 2020 to October 2021[18].

Since the presented cumulative SARS-CoV-2 cases are based on questionnaire data, the unreported number of asymptomatic infections discovered by blood sampling cannot be determined. Another relevant limitation of our study is the survey of infections in the population aged 18 and older. Results based on household information showed a significant association between children in the household and SARS-CoV-2 infection. This association could be further investigated by surveying the estimated seroprevalence of children and adolescents under 18 years of age. Furthermore, our study did not include institutionalized individuals who were shown to have a more SARS-CoV-2 infections at the given period [21].

The study design entails the risk of selection effects, which is particularly evident in the study group regarding school leaving certificate and higher education. Since we did not offer monetary compensation, the participation in several implementation rounds could be motivated by an increased sense of social responsibility, also leading to a higher adherence to countermeasures and regulations. Especially adherence to the hygiene regulations was significantly associated with fewer self-reported SARS-CoV-2 infections, both in univariable and multivariable logistic regression. Therefore, selection of risk-aware individuals and those with higher education could have led to observing a decreased number of SARS-CoV-2 infections in the study population.

The study primarily observed associations between the presence or absence of self-reported SARS-CoV-2 infection in relation to sociodemographic and behavioral factors. Severity of the course of infection should be included in the examination of infection risk in future studies.

The categories of variables, such as the situation at work, are very broad due to the exploratory nature of the study. There is a risk that participants with very different characteristics and behaviors are subsumed into the same category despite the inherent differences between professions in terms of interpersonal contact. This fact may have biased the results of the present study. Given the fairly high level of education of our sample, it is more likely that office work or similar occupations predominated among the participants. Future studies should go into further detail here in order to assess more accurately the associations with SARS-CoV-2 infection posed by the situation in the workplace.

The fact that the participants could only answer yes or no regarding adherence to hygiene regulations represents a simplification of the realities. Gradations, such as a 5-point Likert scale with the options 'never', 'rarely', 'sometimes', 'often' or 'always' can significantly increase the information content in future studies. The same applies to the joint consideration of the various hygiene measures. Individual observations of the three different measures would have provided more detailed insights.

The definition of regular use of public transport is imprecise. The term regular is not clearly defined and could have been interpreted differently between participants. Future studies can increase the information value by asking about the use of public transport with the answer options of, for example, a 5-point Likert scale from 'never' to 'daily'.

Associations between behavioral factors and cumulative prevalence must be interpreted with caution, as it is unclear whether behavior may have changed as a result of a positive test result or infection. Future surveys should ask more clearly about behavior before a possible infection. Last but not least, it should also be noted that we did not correct for multiple testing due to the exploratory and descriptive nature of our analysis.

Conclusion

Despite selection bias the study provides important insights into regional associations between SARS-Cov-2 infection and sociodemographic and behavioral factors. In the presented study, adherence to hygiene regulations (AHA) was significantly associated with fewer self-reported SARS-CoV-2 infections. Whether this result is an indication of the effectiveness of corresponding measures remains open due to the cross-sectional nature of the study. In addition, younger age and living with minor children in the household was significantly associated with self-reported SARS-CoV-2 infection. The presented results can help identify constellations with higher risk of acquiring SARS-CoV-2 infection and therefore target and communicate protective measures.

Availability of data and materials

The datasets used and/or analysed within the current study are available from the corresponding author upon reasonable request.

Abbreviations

DRKS:

German Clinical Trials Register

SARS-CoV-2:

Severe Acute Respiratory Syndrome-Coronavirus-2

CoCoS-study:

Cologne Corona Surveillance Study

COVID-19:

Corona Virus Disease 19

References

  1. WHO. WHO Coronavirus COVID-19 Dashboard. Geneva: World Health Organization (WHO); 2022. https://covid19.who.int/.

    Google Scholar 

  2. WHO. COVID-19 weekly epidemiological update. 107th ed. Geneva: World Health Organization; 2022. https://www.who.int/publications/m/item/weekly-epidemiological-update-on-covid-19-31-august-2022.

    Google Scholar 

  3. Bundesregierung D. Erweiterung der beschlossenen Leitlinien zur Beschränkung sozialer Kontakte. Berlin: Die Bundesregierung; 2020.

    Google Scholar 

  4. BfAu S. SARS-CoV-2-Arbeitsschutzverordnungen. Berlin: Bundesministerium für Arbeit und Soziales; 2021.

    Google Scholar 

  5. Bundesminesterium für Gesundheit, Arbeit und Soziales. Verordnungen und Allgemeinverfügungen zur Bekämpfung der Corona-Pandemie. Bundesminesterium für Gesundheit, Arbeit und Soziales; 2021.

  6. Bundesministerium für Gesundheit. Coronavirus-Pandemie: Was geschah wann? Chronik aller Entwicklungen im Kampf gegen COVID-19 (Coronavirus SARS-CoV-2) und der dazugehörigen Maßnahmen des Bundesgesundheitsministeriums. Bundesministerium für Gesundheit; 2022. https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html.

  7. Robert Koch-Institut. Informationen und Hilfestellungen für Personen mit einem höheren Risiko für einen schweren COVID-19-Krankheitsverlauf. Robert Koch-Institut; 2020.

  8. Peters A, Rospleszcz S, Greiser KH, Dallavalle M, Berger K. The Impact of the COVID-19 Pandemic on Self-Reported Health. Dtsch Arztebl Int. 2020;117(50):861–7.

    Google Scholar 

  9. Oberste M, Pusch LM, Roth R, Shah-Hosseini K, Dewald F, Muller C, et al. Protocol of the Cologne Corona surveillance (CoCoS) study- a prospective population-based cohort study. BMC Public Health. 2021;21(1):1295.

    Article  CAS  Google Scholar 

  10. Oberste M, Pusch L-M, Roth R, Shah-Hosseini K, Schmitz J, Heger E, et al. Results of the Cologne Corona surveillance (CoCoS) study – a prospective population-based cohort study: incidence data and potential underestimation of new SARS-CoV-2 adult infections by health authorities. BMC Public Health. 2022;22(1):1379.

    Article  CAS  Google Scholar 

  11. Stadt Köln: Amt für Stadtenwicklung und Statistik. Kölner Zahlenspiegel. Stadt Köln: Amt für Stadtenwicklung und Statistik; 2020. https://www.stadt-koeln.de/mediaasset/content/pdf15/statistikstandardinformationen/k%C3%B6lner_zahlenspiegel_2020_deutsch.pdf.

  12. Robert-Koch-Institut COVID-19 Dashboard. Robert Koch-Institut; 2022. https://experience.arcgis.com/experience/478220a4c454480e823b17327b2bf1d4

  13. Helmholtz-Zentrum für Infektionsforschung. Webpage of the Multi-local and serial cross-sectional prevalence study on antibodies against SARS-CoV-2 in Germany. Helmholtz-Zentrum für Infektionsforschung; 2021.

  14. Soiza RL, Scicluna C, Thomson EC. Efficacy and safety of COVID-19 vaccines in older people. Age Ageing. 2021;50(2):279–83.

    Article  Google Scholar 

  15. Kang S-J, Jung SI. Age-Related Morbidity and Mortality among Patients with COVID-19. Infect Chemother. 2020;52(2):154–64.

    Article  CAS  Google Scholar 

  16. Vernooij-Dassen M, Verhey F, Lapid M. The risks of social distancing for older adults: a call to balance. Int Psychogeriatr. 2020;32(10):1235–7.

    Article  Google Scholar 

  17. Universitätsmedizin Mainz. Dashboard zur Gutenberg COVID -19 Studie. Universitätsmedizin Mainz; 2021. https://www.unimedizin-mainz.de/GCS/dashboard/#/.

  18. Neuhann, F., Ginzel, S., Buess, M. et al. Die zeitlich-räumliche Verteilung von COVID-19 in Köln und beeinflussende soziale Faktoren im Zeitraum Februar 2020 bis Oktober 2021. Bundesgesundheitsbl. 2022;65:853–62. https://doi.org/10.1007/s00103-022-03573-4.

  19. Pritsch M, Radon K, Bakuli A, Le Gleut R, Olbrich L, GuggenbüehlNoller JM, et al. Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich. Int J Environ Res Public Health. 2021;18(7):3572.

    Article  CAS  Google Scholar 

  20. Rach S, Günther K, Hadeler B. Participants who were difficult to recruit at baseline are less likely to complete a follow-up questionnaire - results from the German National Cohort. BMC Med Res Methodol. 2020;20(1):187.

    Article  Google Scholar 

  21. Robert-Koch-Institut. Aktueller Lage−/Situationsbericht des RKI zu COVID-19. Berlin: Robert-Koch-Institut; 2022.

Download references

Acknowledgements

The authors would like to thank all participants in the study for filling out our questionnaire. We thank the City of Cologne (Stadt Köln) for support with drawing the random sample of Cologne residents, Daniela Rehburg and Claudia Müller for practical support.

Funding

Open Access funding enabled and organized by Projekt DEAL. German Federal Ministry of Education and Research (“Nationales Netzwerk Universitätsmedizin” grant number 01KX2021). The funding body did not play a role in the design of the study and collection, analysis, nor in interpretation of data or in writing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

MO and NS have written the manuscript. MH, FN, AK, GF, CL, FK, TA, FD, MB and KS contributed to the manuscript development and provided scientific expertise. MH, KS, NS, FN, KR and MO designed the statistical procedures. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Martin Hellmich.

Ethics declarations

Ethics approval and consent to participate

This study was approved both by the Ethics Committee of the Medical Faculty of the University of Cologne (reference number 20-1685_2) and by the Ethics Committee of the North Rhine Medical Association (reference number 2020447). All methods were carried out in accordance with relevant guidelines and regulations. The trial was registered at www.drks.de (ID: DRKS00024046) prior to enrolment. Participants were informed about the risks and potential benefits of the study. Participation was voluntary. Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

None of the authors have any competing interests to declare.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Oberste, M., Schnörch, N., Shah-Hosseini, K. et al. Results of the Cologne Corona Surveillance (CoCoS) study – a cross-sectional study: survey data on risk factors of SARS-CoV-2 infection in adults. BMC Public Health 23, 260 (2023). https://doi.org/10.1186/s12889-023-15047-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12889-023-15047-6

Keywords