Social isolation during the COVID-19 pandemic in Spain: a population study

Since March of 2020, billions of people worldwide have been asked to limit their social contacts in an effort to contain the spread of the SARS-CoV-2 virus. However, little research has been carried out to date on the impact of such social distancing measures on the social isolation levels of the population. In this paper, we study the impact of the pandemic on the social isolation of the Spanish population, by means of 32,359 answers to a citizen survey collected over a period of 7 months. We uncover (1) a significant increase in the prevalence of social isolation in the population, reaching almost 26%; (2) gender and age differences, with the largest prevalence of isolation among middle-aged individuals; (3) a strong relationship between economic impact and social isolation; and (4) differences in social isolation, depending on the number of COVID-19 protection measures and on the perception of coronavirus infection risk by our participants. Our research sheds quantitative light on the sociological impact of the pandemic, and enables us to identify key factors in the interplay between the deployment of non-pharmaceutical interventions to contain the spread of an infectious disease and a population’s levels of social isolation.


Scientific Reports
| (2022) 12:12543 | https://doi.org/10.1038/s41598-022-16628-y www.nature.com/scientificreports/ retirement, loss of a partner, relatives and friends) and ageism in society 11,[26][27][28] . Beyond the elder population, there are few studies that have assessed the prevalence of social isolation in the general population prior to the COVID-19 pandemic 29,30 . However, the pandemic has brought social isolation to the public eye, not only in the context of older adults, but for all age groups, because of the impact that confinement and social distancing measures have on everyone's social support structures 31 . During the pandemic, billions of people worldwide have been asked to limit their social contacts by physical distancing, home confinements and the temporary closure of many social activitiessuch as restaurants, bars, gyms, workplaces, soccer stadiums, museums, cinemas and theatres-in an effort to contain the spread of the SARS-CoV-2 virus.
Despite the importance of social isolation in this context, there are few population studies published to date that have analysed the impact of the COVID-19 pandemic on a population's levels of social isolation [32][33][34] . One of the most relevant pieces of previous work is by O'Sullivan et al. 35 where they studied the impact of the pandemic on the social isolation of the general population in 101 different countries, mainly from the United States (40%) and the UK (21%). The authors collected the answers to the LSNS-6 survey from 14,302 participants aged over 18 years old (M=53 years, SD=17.6) before and during the coronavirus pandemic. They found a 13% increase in the prevalence of social isolation during the pandemic. The most important factors associated with social isolation-both before and during the coronavirus pandemic-are a lack of financial resources to meet the participants' needs, their self-rated physical and mental health, living alone not by choice, poor sleep, low physical activity and alcohol consumption. The most cross-cutting aspects correlated with social isolation were economic and mental health factors. During the pandemic, rural residents were found to be significantly at larger risk of social isolation when compared to city dwellers.
In this paper we focus on studying the levels of social isolation in the Spanish population during the COVID-19 pandemic. Spain was one of the most affected countries in the early phases of the pandemic during the spring of 2020. In an effort to contain the spread of the virus, the government implemented an extremely restrictive lockdown that brought the country to a halt for several weeks, with tremendous economic and social implications. Spanish culture is highly social, with low levels of individualism, where families are a fundamental pillar in most people's lives [36][37][38][39] . People in Spain tend to handle their personal problems through their family, relying on relatives for support when facing difficult situations, such as a pandemic.
In order to measure social isolation, we use the LSNS-6 instrument, delivered as part of an online, anonymous survey called the COVID19ImpactSurvey 40 , with over 720,000 answers collected since March of 2020. The answers to the survey have been previously analysed for research purposes and extensively used by public authorities, the media and citizens in Spain to measure the impact of the COVID-19 pandemic on people's behaviours, perceptions and lives 41,42 . While the original survey did not include any questions to assess the levels of social isolation of the respondents, on June 6th 2021, the LSNS-6 questions were added to the survey. We analyse a sample of 32,359 answers collected in Spain for the time period between June 6th, 2021 and December 16th, 2021.
In our analysis, we aim to answer four research questions on the interplay between the levels of social isolation in the Spanish population, the economic and psychological impact of the COVID-19 pandemic and the self-reported behaviour: RQ1: What is the distribution and the temporal evolution of the levels of social isolation in the Spanish population during six months of the COVID-19 pandemic? RQ2: What is the relationship between social isolation and the economic impact of the pandemic on individuals? RQ3: What is the relationship between social isolation and the psychological impact of the pandemic on individuals? RQ4: Are there differences in the levels of social isolation between those with low perceptions of infection risk associated with common daily activities and those who do not adopt any COVID-19 protective measures when compared to the rest of the sample?
The paper is structured as follows: in the following section, we present the Results of analysing the survey answers to address the four previously stated research questions. Next, we Discuss the results and draw key conclusions from our research. Finally, we describe our "Materials and methods".

Results
We analyse 32,359 answers to the COVID19ImpactSurvey, which two of the authors designed and launched on March 28th, 2020. Our results are based on analysing a subset of 17 questions of this survey as per Table S3. We focus on the answers collected between June 6th, 2021 and the 16th of December, 2021 in Spain (N = 32,359). Respondents were required to be at least 18 years old. We refer the interested reader to 40 for a detailed description of the survey and its methodology.
The gender and age distributions of the collected sample are not proportional to those of the general population of Spain, as shown in Table S5. Thus, we follow the methodology described in Oliver et al. 40 and re-weigh the answers, such that the resulting gender and age distributions match the official statistics in Spain in 2020.
All answers are categorical or binary, thus we report the percentage of participants who selected each response and compute the 95% confidence intervals (CI) through the margin of error. All tests of significance have been done by means of t-test or ANOVA as appropriate and post-hoc comparisons have been performed using Tukey tests.

Figure 1.
Average LSNS-6 (a), LSNS-6 Friends (b) and LSNS-6 Family (c) scores per age group. The larger the LSNS-6 score, the lower the levels of social isolation; Proportion of non isolated individuals per age group, defining isolation as a LSNS-6 score < 12 (d), a LSNS-6 Friend score < 6 (e), and a LSNS-6-Family score < 6 (f). The greyed area shows the 95% CI. The grey continuous line corresponds to the overall average LSNS-6 score for all the age groups: µ LSNS−6 = 15.23 , SD = 0.043 ; prev iso = 25.98% , SD = 0.003 ; µ LSNS−6 fri = 7.43 , SD = 0.026 ; µ LSNS−6 fam = 7.80 , SD = 0.025 ; prev iso fri = 27.16% ; prev iso fam = 23.04%.   Table 1. Logistic regression analysis of social isolation with age, gender, number of people in the home, income, population, economic and psychological impact as independent variables. The asterisks denote statistical significance of the coefficient in the logistic model, p-values 0.001 < * * * , 0.01 < * * , 0.05 < * . Relationship between the contact number estimate and LSNS-6 scores. Question 9 in the survey (see Table S3) asks participants to estimate the number of different people from outside the home they have had a close contact with in the past week. This question is meant to assess the intensity of social relationships in the survey respondents. Figure 2d shows the relationship between the reported number of close contacts and the LSNS-6 scores of the participants in our sample. As seen in the Figure, the larger the number of close contacts, the higher the LSNS-6 scores, i.e. the lower the probability of social isolation.

Odds ratio Int low Int sup
RQ2: social isolation and economic impact of the pandemic. We address RQ2 by analysing the answers to questions Q20 and Q22 in the survey (see Tables S3 and S4), as described next. Figure 3 shows the results of the average LSNS-6 scores per age group, gender and severity of the economic impact of the pandemic. As seen in the Figure, those who report severe economic impact have significantly lower LSNS-6 scores when compared to the rest (ANOVA, p < 10 −16 , all with post-hoc Tukey p < 10 −6 ). Over 40% of participants with severe economic impact report being socially isolated. This difference in the LSNS-6 scores is particularly significant for female respondents when compared to male respondents of the same age with severe economic impact, as illustrated in Fig. 3, bottom. In terms of friends vs family, the LSNS-6 score related to friends is the largest contributor to this very clear gender difference. Regarding age, those aged 60+ with severe economic impact have the lowest LSNS-6 scores of the entire sample: 50.56% of participants in this group report being socially isolated. Table 1 shows the results of a logistic regression analysis of social isolation with age, gender, number of people in the home, income, population, economic and psychological impact as independent variables. All levels of To test the statistical significance of the differences, we applied a Tukey post-hoc test after obtaining a significant difference via an ANOVA test. Asterisks denote statistically significant differences with the rest of groups with α = 0.05 . Note how the more severe the economic impact, the lower the LSNS-6 scores and hence the larger the levels of social isolation. www.nature.com/scientificreports/ psychological and economic impact are positively associated with social isolation: the larger the psychological and/or economic impact, the larger the levels of social isolation. In addition to the type of economic impact, we analysed the relationship between social isolation and having received any kind of government economic assistance in the past month (Q22 in the survey). Figure 4 depicts the LSNS-6 scores for those who report receiving government support (red lines) vs those not receiving any type of support by the government (grey lines) per age group and gender. As shown in the Figure, the average LSNS-6 scores of those receiving government support are significantly lower than the scores of those who do not report receiving any kind of support ( µ LSNS−6 : 14.50 vs. 15.34 for those receiving government support vs not, t-test p < 10 −9 with a difference in means of 0.836).
The largest differences are found in the friend component of the LSNS-6 score, particularly in female respondents.
In terms of age, the lowest average LSNS-6 scores correspond to those who receive government support and are 50-59 years old, where 35.35% of individuals in this group report being socially isolated. RQ3: social isolation and the psychological impact of the pandemic. We address RQ3 by analysing the answers to question Q31 in the survey (see Tables S3 and S4). Figure 5 shows the average LSNS-6 scores per age group, gender and severity of the self-reported psychological impact of the pandemic ( µ LSNS−6 : None/Mild/Severe: [16.01, 15.85, 14.54]). Similarly to economic impact, those who report severe psychological impact have significantly lower LSNS-6 scores than the rest of the respondents. Interestingly, we do not identify significant differences by gender or by type of social support (friends or family) among those who report severe psychological impact. The lowest average LSNS-6 scores correspond to those aged 50 to 59 years old: 29.54% of respondents in this age group report being socially isolated, and 34.90% for those who report severe psychological impact.
A logistic regression analysis shown in Table 1 confirmed associations between psychological impact and social isolation in our sample, yet milder than the associations found with economic impact.  Tables S3 and S4. As noted in Fig. 6, there is a significant difference in the LSNS-6 scores between those who do not adopt any protection measures (red lines) and the rest of participants (blue and grey lines), with a t-test p < 10 −16 and a difference in means of 3.528. This difference is mainly due to the friends component of the LSNS-6 score: those who do not adopt any COVID-19 protection measures report significantly larger LSNS-6 scores than the rest of respondents, i.e. are significantly less likely to be socially isolated: µ LSNS−6 none − µ LSNS−6 any = 3.528 = 2.408 (friends) + 1.120 (family) , with t-test p < 10 −9 .
Next, we focus on the participants' perception of COVID-19 infection risk associated with activities that are part of our daily lives (Q21) and their levels of social isolation. As depicted in Fig. 7, the LSNS-6 scores of those who report that none or only essential activities can be carried out with low risk of contracting COVID-19 (grey lines) are significantly lower than the LSNS-6 scores of the rest of respondents (red lines). This difference mainly due to the friends component of the LSNS-6 score: µ LSNS−6 none−essential − µ LSNS−6 other = 2.436 = 1.586 (friends) + 0.850 (family) , with t-test p-values < 10 −16 .

Discussion
In this paper, we have quantitatively analysed the prevalence of social isolation in Spain during 7 months of the COVID-19 pandemic by means of the LSNS-6 instrument delivered via an online survey with 32,359 answers. We have also studied the relationship between social isolation and the economic and psychological impact of the pandemic on people's lives. Finally, we have reported the relationship between social isolation, the COVID-19 protection measures and the perception of infection risk associated with common daily activities by our participants. We draw several implications from these results. In our sample, we find a prevalence of social isolation of 25.98% ( SD = 0.003 ), which is almost 14 percentage points larger than that reported in 30 . The average LSNS-6 score in our sample is of 15.23. Respondents who are socially isolated have an average LSNS-6 score of 7.66 and those socially integrated of 17.89. These figures are significantly lower than those reported in the literature.
Our findings are aligned with those of O'Sullivan et al. 35 , who report a prevalence of social isolation of 21% in a study with 14,302 participants from different countries carried out between June and November of 2020. The authors find that 13% of the respondents in their survey experienced a substantial increase in social isolation during the COVID-19 pandemic.
Moreover, we find a statistically significant difference in the prevalence of social isolation among participants who report not adopting any COVID-19 protection measures-and hence do not reduce their social contacts and activities ( prev iso = 17.52%)-when compared to participants who report complying with five or more COVID-19 protection measures ( prev iso = 27.02%, χ 2 test p < 10 −8 ).
This result probably reflects the fact that many of the COVID-19 protection measures are of social naturesuch as reducing close contacts, keeping social distance, avoiding gatherings, hugging and kissing-and thus their impact on social isolation is evident. www.nature.com/scientificreports/ Hence, we hypothesise that the increase in the social isolation identified in our study is due to the pandemic and the social distancing and confinement measures that have been implemented in Spain to try to contain the spread of the SARS-CoV-2 virus.
Middle-aged participants are the most socially isolated. Surprisingly, the largest prevalence of social isolation in our sample is among those aged 50-59 years old, with 29.54% of the sample reporting LSNS-6 levels corresponding to social isolation. The LSNS-6 component related to the friends network is the main contributor to this result. This finding might be a consequence of the social distancing and confinement measures adopted by Spain during the period of study. According to our survey, the demographic group of those aged 50-59 years old is among the most compliant with the individual protection measures (washing hands, keeping social distancing, wearing masks, limiting social contacts) while also being a demographic group with a large number of contacts. Hence, the impact of adopting such measures on their friends social network might have been the largest in the sample.
Previous work has obtained similar results in smaller samples and geographies. In a small sample of 214 residents of Wandsworth, a South West London Borough in the United Kingdom 34 , the authors find that middleaged people reported a weaker social network and more loneliness, anxiety and depression than younger people. Sugaya et al. carry out a study with 11,333 participants from seven prefectures of Japan during the final phase of the state of emergency in May 2020 and report a greater prevalence of social isolation among male, middle-aged (40-64 years) participants 32 .
Interestingly, the U-shaped curve in the LSNS-6 scores that we obtain is similar to the previously reported U-shaped curve of happiness depending on age 44 where the lowest levels of happiness are reported by those aged 50 years old.
Given the strong correlation between social isolation and mental and physical health, it would be of paramount importance to deploy support programs for individuals particularly in such an age group. www.nature.com/scientificreports/ Economic impact and social isolation are strongly related. Previous work has also found a strong relationship between socioeconomic status and social isolation both before 5,8,37,[45][46][47][48] and during the COVID-19 pandemic 30,32,34,[49][50][51] . The general finding that we corroborate here is that the lower the socioeconomic status, the higher the risk for social isolation. The economic consequences of the COVID-19 pandemic are evident on a global scale, having been responsible for the second largest global recession in history, with more than a third of the global population at the time being placed on lockdown.
However, we are not aware of previous analyses on the relationship between the economic impact of the pandemic on an individual and their levels of social isolation. In our data, we find a strong correlation between the economic impact of the pandemic and the LSNS-6 scores of individuals: the lower the economic impact, the larger the LSNS-6 scores and hence the lower the social isolation (see Table 1). The prevalence of social isolation among those who report severe economic impact is significantly larger than the prevalence of the overall sample: prev iso = 41.39% and prev iso = 25.98% for those with severe economic impact vs the general population, respectively.
We also observe gender differences, mainly due to the friends component of the LSNS-6 scores: women who have been severely impacted economically because of the pandemic are more likely to be socially isolated ( prev iso = 43.04% ) than men who also report severe economic impact ( prev iso = 39.78% ), with average friend LSNS-6 scores that are almost one point smaller than the men's scores ( µ LSNS−6 fri−female : 6.04 µ LSNS−6 fri−male : 6.96).
This finding highlights the importance of deploying social programs to support women in vulnerable and economically precarious situations.
The social support by friends matters. We find that the friends component of the LSNS-6 score is a key determinant of social isolation in our sample across all age groups (see Fig. 1d), more so than the family component. This finding might be due to the fact that families are a fundamental pillar in Spanish culture across all demographic and socioeconomic groups, such that there might not be large differences in the social support provided by families. However, the friends networks vary widely with age, gender, education level and socioeconomic status 52 .
We identify gender differences in the levels of social isolation for those who report severe economic impact due to a much weaker friends social network among women.
There are also significant differences in the friends LSNS-6 scores among those who do not adopt any COVID-19 protection measures (particularly men) and the rest of participants; and those who consider that most activities can be performed with low risk of a SARS-CoV-2 infection and the rest of respondents. In this case, those who do not adopt any COVID-19 protection measures exhibit stronger social support by their friends. Similarly, those who consider that many non-essential activities can be carried out with a low risk of coronavirus infection also have higher LSNS-6 friend scores than the rest of participants.
This finding highlights not only the role that friends play in social isolation-particularly among the youth (see e.g. 53 ), but also the influence that having a strong network of friends plays on wanting to socialise even during pandemic times. Alternatively, this result might be explained by the fact that the COVID-19 protection measures are mostly of social nature and hence have an impact on the levels of social isolation of those who comply with them.
Gender also matters. There are several gender-based differences that can be drawn from our analyses. First, while the average LSNS-6 scores are lower among female ( µ LSNS−6 = 15.18 SD = 0.048 ) than male ( µ LSNS−6 = 15.29 SD = 0.074 ) respondents, the prevalence of social isolation is larger among male ( prev iso = 26.53% ) than female ( prev iso = 25.47% ) participants. This difference, however, is not statistically significant according to a χ 2 test.
To shed light on this finding, Fig. S2 depicts the distribution of LSNS-6 scores by gender. As can be observed in the Figure, the LSNS-6 scores by female respondents tend to be clustered around the mean of the distribution whereas the upper and lower extremes of the distribution have significantly more male than female respondents. Indeed, we observe a statistically significant difference between the variances of the distributions with a much larger support of answers by male participants in the tails of the distribution when compared to the answers by female respondents (see Tables S1 and S2).
Second, women with severe economic impact are significantly at higher risk of social isolation than men who have also suffered severe economic impact, mostly due to having a weaker support by their friends. Interestingly, this difference is not evident among those with psychological impact due to the pandemic.

The adoption of COVID-19 protection measures is related with social isolation.
When we divide our sample according to the COVID-19 protection measures adopted by the participants in our study, significant differences emerge in the respondents' levels of social isolation: those who report not adopting any measures have significantly larger LSNS-6 scores than those who adopt some or all of the possible COVID-19 protection measures (None/Some/Several: µ LSNS−6 : [18.65, 15.81, 14.88], ANOVA and Tukey tests p < 10 −16 .
This finding might be explained by the role that the friends network plays in influencing human behaviour. Many of the COVID-19 protection measures are meant to limit our social interactions. Those with strong friends networks are therefore more impacted by the adoption of such measures and hence could be less likely to adopt them. As previously reported, the difference in the LSNS-6 scores between those who do not adopt any measures and the rest of participants is of 3.524 points, mostly due to the friends component of the LSNS-6 score. www.nature.com/scientificreports/ Alternatively, this result might be explained by the fact that the COVID-19 protection measures are mostly of social nature and hence have an impact on the levels of social isolation of those who comply with such measures.

Higher perception of COVID-19 infection risk is related to social isolation.
Similarly, those who report that many daily activities can be performed with a low risk of a coronavirus infection are significantly less likely to be socially isolated than those who have a higher perception of infection risk: prev iso = 23.13% vs. prev iso = 41.73% ( χ 2 test with p < 10 −16 ). Again, the LSNS-6 component that contributes the most to this difference in LSNS-6 values (13.20 vs. 15.63) is the friends component: of the 2.44 points in the difference of the average LSNS-6 scores, 1.59 points are due to the friends component and 0.85 points due to the family component, with a t-test p < 10 −16 , and with a larger difference between female than male respondents.
Our results might be explained by several factors. First, previous work has found that the larger the social support, the lower the fear towards COVID-19 in a sample of healthcare workers in Jordan 54 . Second, in the context of the coronavirus pandemic, we tend to lower our perception of infection risk when carrying out activities that involve our friends and/or relatives 55 : "our evaluation of risk versus safety is inextricably tied to our group memberships".
Several of our findings highlight the crucial role that the friends support network plays in the levels of social isolation in Spain.

Materials and methods
Data collection and processing. In this paper, we analyse a subset of the answers to the COVID19Im-pactSurvey, an extensive, anonymous, online citizen survey about COVID-19 40 . Launched on March, 28th 2020, in Spain, the survey has since then collected over 700,000 anonymous answers from 11 countries (mostly Spain, Italy, Germany and Brazil), and it is available online at https:// covid 19imp actsu rvey. org. Participants must declare being 18 years or older to be able to fill the survey. All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all users and the data was collected in deidentified form.
We filter entries with inconsistent answers (5.19% of answers), which are entries where the respondents provided contradictory answers, such as reporting being a pregnant and aged 60+; being pregnant and male, etc. We also do not consider entries that appear to have been answered too fast (< 120 s) or too slow (> 36000 s), which correspond to 3.34% of answers. Note that the average completion time of the survey in our sample is 509 seconds. Finally, entries not providing age or male/female sex information (0.81%) are also excluded from the analysis. In total, we discard 9.34% of the answers.
The specific answers to the survey that we analyse in this paper collect information about the participants' demographic and household situation (Q1-Q5); their LSNS-6 scores (Q11-Q16); the economic impact of the pandemic in their lives (Q20, Q22); their perception of COVID-19 infection risk associated with different activities (Q21); the individual protection measures that they adopt to protect themselves against COVID-19 infections (Q26); the psychological impact of the pandemic in their households (Q31). All the questions to the survey are included in Table S3.
We analyse the data from Spain for the time period between June 6th, 2021 and the 16th of December, 2021. During this period, Spain had returned to the "new normality": the only COVID-19 protection measure implemented in the country was the requirement to wear face masks in indoor public spaces. Figure S3 depicts the daily number of new COVID-19 cases and deaths in Spain. The period of study includes a small wave of infections that took place in the summer of 2021. Survey answers were collected from volunteer respondents who learned about the survey via social media channels, word-of-mouth, universities and news organisations. We used Facebook and Instagram ads as an additional channel to recruit volunteers. This approach gave us a straightforward method to obtain a broad sample of users across different socioeconomic and demographic groups. We did not use any targeting feature except for gender, where we used separate budgets to balance the numbers of male and female respondents. The cost-per-successful-response was €0.24 and €0.11 for men and women respectively. Both men and women had similar completion rates (54%) once they began answering the survey.
The age and gender distribution of our sample is different from the population distribution in Spain. Thus, we follow the methodology described in Oliver et al. 40 and re-weight the answers such that the resulting gender and age distributions match the official statistics of each of the seven Nielsen geographical regions in Spain, depicted in Fig. S1, plus the metropolitan areas of Madrid and Barcelona. We compute the weights according to the official data reported by the Spanish National Institute of Statistics (INE) for 2020.
To further validate our methodology, in April 2020 we commissioned an IPSOS.digital FastFacts panel of a cohort of 1000 representative general population respondents aged 18-65 in Spain. This validation was done after we started using Facebook ads, but before the time period covered by this paper. The results of the IPSOS panel were within the margin of error of our survey results for the same time period and ages.
Ethical approval. All methods described in this manuscript were carried out in accordance with relevant guidelines and regulations. The survey instrument was approved by the Ethical Committee of the University Miguel Hernandez, which is called the Office for Responsible Research (OIR), in the context of previous research 40,41 . Informed consent was obtained from all subjects who had to confirm being at least 18 years old to be able to participate in the survey. The participation in the survey was voluntary and all the collected data was anonymous and confidential. Furthermore, the research complied with the ethical standards of the 1964 Declaration of Helsinki and its later amendments.  Tables S3 and S4.
Social isolation. We measure social isolation using the LSNS-6 instrument included in questions Q11-Q16 in the survey. The LSNS-6 is a quantitative measure of an individual's social network size that assesses both the number and frequency of contacts with friends and family and the social support received by them. It consists of six items: three questions ask about the frequency of meeting relatives, how many relatives the respondent feels close enough to ask for help and with how many relatives the respondent can talk about private matters; the remaining three questions are identical but concerning friends rather than relatives. Each of the LSNS-6 items is scored on a scale from 0 to 5 and they are all equally weighted. Thus, the total score ranges between 0 and 30. The higher the LSNS-6 scores, the lower the levels of social isolation. Social isolation is given by a score below 12. This corresponds to having less than 2 individuals to reach out to in each of the areas probed by the survey (i.e. family or friends). The LSNS-6 has good psychometric properties 13 .
Socio-demographic and household characteristics. Demographic variables selected for analysis were: (1) gender, where respondents were asked to self-report their gender as male, female or other. In this study, we only consider the answers of those who responded as male or female, which represent 99.33% of the answers (0.3% of answers selected "other" as their sex and 0.37% of answers did not provide sex information); (2)  Economic impact. The self-reported economic impact of the pandemic was assessed in Q20 and Q22 of the survey.
Question number 20 asks about the type of economic impact that the pandemic had on the respondents' lives. Based on the answers provided to Q20, we coded the severity of the economic impact in four levels: [None, Mild, Severe and Positive], as described in Table S3.
Question number 22 focuses on whether participants receive any kind of economic assistance from the government.
Based on the answers provided to Q22, we coded the reliance on government-based economic assistance in two levels: [None, Any], as described in Table S3.
Psychological impact. The self-reported psychological impact of the pandemic was assessed in Q31 of the survey.
Based on the answers provided to Q31, we code the severity of the psychological impact in three levels: [None, Mild and Severe], as described in Table S3.

COVID-19 protection measures.
The individual protection measures adopted by participants to limit their exposure to the SARS-CoV-2 virus were captured by Q26.
We code the possible answers into three groups: [All, Some, None], depending on whether respondents report adopting all, none or several of the measures, as described in Table S3.
Perception of COVID-19 infection risk. Question 21 asked participants about their perception of risk of a COVID-19 infection associated with different daily-life activities.
We code the possible answers into three groups: [None, Only essential activities and Other non-essential activities], as depicted in Table S3.
Statistical analysis. The prevalence of social isolation is computed in percent with 95% confidence intervals (CIs) from the overall sample. We stratify social isolation by gender and age. We perform χ 2 tests to determine the existence of statistically significant differences in the prevalence of social isolation among each of the stratified groups. We also use multi-variable logistic regression analysis to test the associations between social isolation and age, gender, number of members of the household, economic and psychological impact of the pandemic, individual COVID-19 protection measures adopted and risk perceptions of coronavirus infection associated with different daily activities. We use a significance level α = 0.05 (two-tailed) in all the analyses.
All statistical analyses, data preprocessing and figures were performed and plotted using the R software 56 package, version 4.1.2 (2021-11-01).
Limitations. Collecting a large sample of answers via an online survey does not come without limitations.
Even if the data size is large and the confidence intervals are small, errors might compound and under-or overestimate the results 57 . Moreover, even if we weighted 59 the data to mitigate gender and age survey's biases in each Nielsen region, and we deployed gender-balanced Facebook advertisement campaigns, the data is non-random and biases might still be present. For example, there are self-selection and sampling biases 59 as the survey is filled out by volunteers who have learned about the survey via social media, WhatsApp, newspapers' articles or Facebook ads, and who need to have access to a computing device (smartphone, tablet, PC) with an Internet connection. The survey might also be biased towards people who are more likely to fill-in surveys, such as young and highly educated people. Respondents must be adults-at least 18 years old. Hence, students are only partially covered. We acknowledge all these biases challenge the estimation of inferential statistics, and might lead to overconfidence in incorrect inferences due to the collected large data sample and small confidence intervals 57 . We also acknowledge that there might be a recall bias as respondents were asked about their perceptions and Scientific Reports | (2022) 12:12543 | https://doi.org/10.1038/s41598-022-16628-y www.nature.com/scientificreports/ behaviour in the last seven days (e.g. the number of close contacts in the last week). However, we have taken several measures (re-weighting, contrasting with two polls, comparing with relevant literature) to minimise such biases. Previous work has found that citizen (online) surveys are particularly valuable tools in situations of data scarcity where informed and timely decisions are needed 40 . Online surveys also allow monitoring people's perceptions and behaviours, enabling the design of more effective public policies and better education and communication with the public. Thus, we are confident about the value and validity of the results of our analyses.

Data availability
All data generated or analysed during this study are included in this published article [and its supplementary information files].

Code availability
The code used to analyse the data will be placed in a publicly available Github server.