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[Paper] Effects of local and national regulations in response to COVID-19 on social contact in the United Kingdom: a longitudinal natural experiment.

[Paper] Effects of local and national regulations in response to COVID-19 on social contact in the United Kingdom: a longitudinal natural experiment.

Summary

Background

The UK COVID-19 response moved from national lockdowns to localized interventions. In response to a growing number of cases, these were supplemented by national restrictions on contacts (six rules), 10 pm closures for bars and restaurants, and encouragement to work at home. These were followed rapidly by a three-tier system applying different restrictions in different areas. As incidents continued to increase, a second national shutdown was declared. A national survey was used to quantify the impact of these restrictions on epidemiologically relevant contacts.

Method

The authors compared paired measures of setting-specific contacts before and after the start of each restriction and tested for differences using paired replacement tests for mean change and percentage of contacts.

Result

After each measure was implemented, individuals tended to have fewer contacts than before. However, the magnitude of change varied relatively little. For example, the early closure of bars and restaurants did not appear to have a measurable effect on contacts, but work at home orders reduced average daily work contacts by 0.99 (95% CI) 0.03-1.94, and the 6 rules reduced average daily non-work and school contacts by 0.25 (0.01-0 .5) per day. Three of the phases appear to have also reduced non-work and school contact, and the evidence for the impact of the lesser restrictions (phases 1 and 2) was much weaker. There may also be evidence that patients in Period 1 (least restrictive) had significantly fewer contacts when they entered lockdown, saturating the effect. This is not reflected in similar changes in patients who were already severely restricted (Periods 2 and 3).

Conclusion.

During the summer and fall of 2020, the number of contacts has been gradually decreasing due to various local and national measures taken in the United Kingdom. However, these changes are smaller than the initial lockdown in March. This may be because many individuals had already started with fewer contacts.

Keywords:

COVID-19 "Contact Survey", lockdown, pandemic, disease outbreak, non-pharmaceutical intervention, United Kingdom

Background

On March 23, 2020, the U.K. joined the rest of the U.K. in domestic regulation in response to COVID-19. This required people to leave their homes for essential shopping, medical care, or just one type of exercise per day. Educational facilities and nonessential retail outlets were closed, as was the leisure and hospitality sector. National lockdowns were also implemented in many European countries, and a combination of extensive regulation significantly reduced the number of contacts, mobility, and transmission, ultimately reducing the number of daily cases and deaths.

As the incidence of cases declined, national restrictions were relaxed. The United Kingdom moved to a localized response and only applied more stringent regulations to specific areas where cases were increasing. The first of these regional measures was announced in Raistel on June 29, followed by other regions, mostly in the northern part of the United Kingdom. Regional restrictions vary in scale, but may include early closure of businesses, take-out service in bars and restaurants only, bans on meeting with other households, travel restrictions, etc.

In parallel with regional restrictions, several national measures were also introduced in response to the increase in cases. On September 14, the "rule of six" was announced in the United Kingdom, preventing meetings in groups of six or more people. On September 24 it was announced that pubs and restaurants would be required to close at 10 PM and individuals would be encouraged to work from home. Incidents continued to increase, and the government combined several restrictions to create a three-tier system, from tier 1 (moderate risk) to tier 3 (very high risk). A second UK lockdown then took place between November 5 and December 2.

The impact of less stringent measures remains unclear, with cases continuing to rise in most areas even after the measures were implemented. It is expected to be difficult to extract any (perhaps moderate) changes in cases, hospitalizations, or deaths sometime after the restrictions were introduced. In this paper, we circumvent these problems by using repeated measures of an individual's epidemiologically relevant setting-specific contacts before and after restriction to estimate whether these measures had any effect and the magnitude of the effect, if any.

Method

Code of ethics

Participation in this opt-in study was voluntary and all anonymous data were analyzed. The study was approved by the Ethics Committee of the London School of Hygiene and Tropical Medicine.

Data

Data from UK participants in the UK CoMix study were combined with information on UK government local and national regulations. Details of the CoMix study, including the study protocol and survey instrument, have been published previously. In essence, CoMix is an online survey, where individuals record details of all direct (i.e., potentially at-risk) contacts on the day before the survey. A direct contact was defined as a person who was met and at least one word was exchanged, or with whom the participant had some form of skin contact. Individual contacts under the age of 18 were collected by asking parents to respond on behalf of their children. Information was collected weekly from two alternately broadly representative panels (each approximately 2500 persons in size), with each individual being surveyed once every two weeks. The start and end dates of the restrictions and their locations were extracted from the UK government between August 31 and December 7, 2020. CoMix participants were considered to be affected by local restrictions if they reported living in a sub-local authority (UK administrative region) under a different restriction than the one applied in the country. To allow for a full 2-week response, data were restricted to 16 days before and after each restriction went into effect. Survey responses closest to the time before and after each restriction date were then extracted. Participants with missing survey responses in any aspect at the start of the restriction were excluded, and two records were submitted per participant.

Restrictions

Regional restrictions included a set of regulations that were applied inconsistently across regions. Most regional restrictions fell into four categories: travel restrictions, nonessential closures, prevention of indoor mixing, and curtailment of overnight stays. Travel restrictions included only essential travel; travel was curtailed and residents were prohibited from leaving the area. Non-essential closures included places of worship, non-essential retail stores, gyms, public buildings, nursing services, art venues, and tourist attractions.

The six-person rule prevented individuals from meeting in groups of six or more indoors and outdoors. The 10 p.m. closing required the hospitality venue to be closed and customers to leave by 10 p.m. Telecommuting involved individuals being encouraged to work from home when possible.

The T3 tier system was created on October 14, with each tier building on the previous one, with the first tier being the most stringent. Tier 1 (middle risk) generally corresponds to the "rule of 6," "work from home," and "10 p.m. rule," with the addition of music and dances held at night to close businesses. In Tier 2, there was no gathering of indoor space between households, movement was restricted, and more venues were closed. Tier 3 prevented private outdoor space meetings with non-household members, restricted restaurants and bars to table service only, and served alcoholic beverages only when consumed with a substantial meal.

The second country regulation was less stringent than the first, as schools remained open, but included the closure of pubs, restaurants, gyms, non-essential stores, and housing.

Test Design

This study is a longitudinal natural experiment. For each participant, there will be one observation before implementation and one observation after restriction. The observation period will be a maximum of 16 days from the start date of the restriction. This allows the individuals in our study to be their own controls, thus reducing the effects of interindividual variability as well as the effects of long-term temporal trends. The types of contacts reported were categorized as home, workplace, school, and other situations.

To assess the impact of (i) regional restrictions, (ii) three national restrictions (1) the rule of 6, (2) the 10 o'clock closure, (3) work from home, (iii) entry into each of the first, second, and third periods, and (iv) entry into the national lockdown from the first, second, and third periods, the authors compared the number of contacts before restriction implementation compared to the number of contacts. To evaluate the effects of the various restrictions, the authors concentrated on changes in setting-specific contacts. For example, the regional restrictions and the tier system primarily target leisure contacts, while the six rules do not apply to businesses or schools. Therefore, for these two restrictions, the authors analyzed changes in contacts excluding work and school. The 10 p.m. closure rule, which requires restaurants, pubs, and bars to close early, is not expected to have a direct impact on contacts at home, work, or school. Therefore, in these situations, contacts were excluded as a result of this restriction and the remaining contacts were referred to as "other contacts." To assess the effect of work from home advice, we focused on work contacts of employed respondents. Because schools remained open during the second national lockdown period, we only excluded contacts when assessing the impact of contacts in schools.

Statistical Analysis

All analyses were conducted using R version 4.0.0, with code and data available on Github (see "Availability of Data and Materials" section). Descriptive and illustrative summaries of participant characteristics with respect to age, gender, employment, and socioeconomic status were generated for each restriction, changes in the average number of contacts, and spatial and temporal changes in restrictions. Mean contact uncertainty was calculated using cluster bootstrapping [15], sampling on a per capita basis rather than at the observation level to preserve the correlational structure of the data.

The authors compared contacts before and during restriction by calculating mean, median, and interquartile range (IQR). Changes in the number of contacts were categorized as increases, same (no change), and decreases. The authors assessed uncertainty by calculating the mean of the pairwise difference in contacts before and after restriction and constructing 95% confidence intervals (95% CI) from a bootstrap sample of 10,000 [15] of the pairwise difference.

For each restriction, the authors performed a paired permutation test [16] with 50,000 permutations per test. A replacement test was chosen because it is robust to the assumptions of the underlying data distribution [14]. To preserve study structure, we computed pair differences by subtracting the number of reported contacts during restriction from the number of reported contacts before restriction and then randomly changing the sign of each pair. In practice, this means taking -1 and 1 of the same length as the number of participants and multiplying this vector by the change in contacts to produce a vector of random values.

Two test statistics were to be computed for each substitution and each restriction: (1) the percentage of individuals whose contacts decreased after the restriction was implemented, and (2) the mean change in contacts before and after the restriction. The proportion of reductions is robust to large values, with a skewed distribution that treats the difference between -1 and -1000 in the same way. It measures the relative effect of restriction, but does not estimate the magnitude of the effect. The mean difference estimates the absolute effect, but is affected by the skewed data. To reduce the effects of skewness, we limited the total number of contacts to 200 per person per day, just for the purposes of comparing means.

We further evaluated the restrictions by age group for the 6-year-old rule and the 10 p.m. rule. These restrictions may have a greater impact in younger individuals who are more mobile, asymptomatic when infected, and unshielded, because they are more likely to have a greater impact in younger individuals who are more mobile, asymptomatic when infected, and unshielded. These analyses were stratified by age groups 5-17, 18-39, 40-59, and 60+.

Result

Participant Characteristics

The analysis of the Law of 6 included 3884 participants, 3887 for the 10 p.m. closure, 1408 for work at home, and 572 for local restrictions (Table 1). Tier 1 added 2415, Tier 2 added 1654, and Tier 3 added 368. In addition, 2095 participants left Tier 1 to the national lockdown, 1445 participants left Tier 2 to the national lockdown, and 323 participants left Tier 3 to the national lockdown. The age distribution of the Rule of Six, 10 p.m. closure, local regulation, entry into tiers, and national lockdown samples was similar, with more than 30% of the sample aged 50~69 in all nine analyses. Work from the household by definition category included only participants 18 years and older, and nearly 70% of participants were 30~59 years old. The split between men and women was close to 50% for all restrictions. Excluding work from the home analysis, about 40% of participants were employed in each limit (which reflects the broad age range of the sample, including children and the elderly). Socioeconomic status was consistent across each analysis sample, with the mode group being C1-lower middle class for all restrictions, with A-upper middle class and E-the lowest number of lower living categories (Table 1).

All adult contacts and restrictions

From March to June, restrictions were applied throughout the United Kingdom (Figure 1). During the summer months, restrictions were relaxed and regional restrictions on travel, nonessential closures, indoor mixing, and curtailment of nighttime stays were applied (Figure 1c). These restrictions were applied primarily in northern England (Figure 1a). The August deregulation coincided with an increase in the average number of adult contacts, and from September to November the number of contacts gradually declined as the restrictions became stricter and wider (Figure 1b). After the second national lockdown, the average number of daily reported contacts returned to about the same level as in July. Figure 1 shows the average number of contacts over time for adults only, since data on children were not collected during the study period and the second national lockdown did not include school closures.

Distribution of setting intrinsic contacts

Setting-specific contacts were positively skewed for all restrictions (Figure 2a, Table 2). The 6 rules and area restrictions showed a similar distribution, with modal response being the one contact prior to restriction, while work at home and the 10 o'clock rule accounted for the majority of individuals who reported no contacts. The distribution of entry into and exit from phases to lockdown was similar with a median of 2 and IQR of 1~3, except for exit phase 1 with an IQR of 1~4. Overall, the magnitude of change in the number of contacts was small, and the number of reported contacts remained unchanged after the introduction of each measure (Table 2). To show patterns in the data, the axes were restricted and the zero values in Figures 2b, 3a, and b were removed. These graphs are reproduced in Additional file 1: Figures S1A and S1B and Additional file 2: Figures S2A and S2B, with no axes restricted for zero value removal or comparison.

Domestic Regulations

The six internal rules

The authors compared non-work and non-school contacts for 3884 individuals before and after the 6 rules went into effect. There was strong evidence to suggest that the number of contacts (excluding work and school) who followed the rule of six restrictions was higher than would be expected by chance, with 1314 (33.8%) having fewer contacts compared to 997 (25.7%) (p<0.001). However, for most participants, 1573 (40.5%) recorded the same number of contacts, with a median number of contacts of 2 (IQR 1-3) before and after the introduction of the measure. There was a slight suggestion (p = 0.05) of a slight decrease (-0.25; -0.5 to -0.01) in the average number of non-working and non-school contacts per day (Table 2). The age-stratified analysis (Table 3) suggests that Rule 6 had the greatest impact on contact patterns among young adults (18-39), reducing non-work and non-education contacts by an average of -0.59 (-1.09 to -0.04).

Closure at 10 p.m.

We compared "other" contacts (excluding home, work, and school) for 3887 participants before and after the 10 p.m. closure. There was strong evidence to suggest that, following the 10:00 rule, more people had fewer contacts than expected due to chance, with 990 (25.5%) having fewer contacts than 843 (21.7%), while 843 (21.7%) had more contacts (p<0.001). However, more than half (52.8%) of the 2054 participants recorded the same number of contacts and the median number of contacts was very low (0; IQR 0 to 1) before and after the 10:00 rule. The data were consistent with no absolute effect (p = 0.915), with an estimated change in the mean number of "other" contacts of 0.01 (- 0.23~0.23) (Table 2). Subgroup analysis suggested an inconsistent pattern by age group (Table 3), which is to be expected in the absence of evidence of changes in contacts according to this indicator overall.

Working at home

More than two-thirds of the participants, 933 (66.3%), had the same number of work contacts before and after being encouraged to work from home. Nonetheless, the data strongly suggest that a larger number had fewer of their work contacts after the restriction went into effect than would be expected by chance (p =0.001). Differences in the number of contacts were highly skewed, with 40 participants reporting a difference of 50 or more contacts, but the 25th and 50th quartiles of the difference were zero (Figure 2, Table 2). The data were compatible with a decrease in mean work contacts (p = 0.05). There was significant uncertainty around the point estimate, but it was far from zero (-0.99 contacts per day, 95% CI -1.94~-0.03, Table 2).

Table 1: Characteristics of CoMix Survey Participants for Each Limit

Restrictions   Entry into Exit from tier to lockdown
  Rule of Six 10 pm closure Work from home Local lockdown Tier 1 Tier 2 Tier 3 Tier 1 Tier 2 Tier 3
  N (col %) N (col %) N (col %) N (col %) N (col %) N (col %) N (col %) N (col %) N (col %) N (col %)
Total 3884 3887 1408 572 2415 1654 368 2095 1455 323
Age groups
0–4 129 (3.3%) 142 (3.7%) 0 22 (3.9%) 96 (4.0%) 65 (4.0%) 12 (3.3%) 53 (2.5%) 49 (3.4%) 13 (4.0%)
5–11 214 (5.5%) 275 (7.1%) 0 54 (9.5%) 151 (6.3%) 117 (7.1%) 36 (9.9%) 120 (5.8%) 85 (5.9%) 31 (9.7%)
12–17 261 (6.8%) 291 (7.5%) 0 59 (10.4%) 202 (8.4%) 121 (7.4%) 48 (13.2%) 149 (7.1%) 101 (7.0%) 41 (12.8%)
18–29 364 (9.4%) 384 (9.9%) 222 (15.8%) 61 (10.7%) 197 (8.2%) 161 (9.8%) 23 (6.3%) 158 (7.6%) 124 (8.6%) 20 (6.2%)
30–39 462 (12.0%) 432 (11.2%) 308 (21.9%) 65 (11.4%) 240 (10.0%) 191 (11.6%) 42 (11.6%) 194 (9.3%) 153 (10.6%) 34 (10.6%)
40–49 495 (12.8%) 531 (13.7%) 363 (25.8%) 89 (15.6%) 326 (13.6%) 219 (13.3%) 47 (12.9%) 288 (13.8%) 200 (13.8%) 42 (13.1%)
50–59 708 (18.3%) 613 (15.8%) 322 (22.9%) 90 (15.8%) 402 (16.7%) 277 (16.9%) 63 (17.4%) 355 (17.0%) 262 (18.1%) 49 (15.3%)
60–69 723 (18.7%) 751 (19.4%) 174 (12.4%) 88 (15.5%) 449 (18.7%) 309 (18.8%) 50 (13.8%) 428 (20.5%) 291 (20.1%) 48 (15.0%)
70+ 506 (13.1%) 449 (11.6%) 19 (1.3%) 41 (7.2%) 341 (14.2%) 181 (11.0%) 42 (11.6%) 341 (16.3%) 182 (12.6%) 43 (13.4%)
Missing 22 19 3 11 13 5 9 8 2
Gender
Female 2013 (52.0%) 2004 (51.6%) 718 (51.1%) 277 (48.7%) 1252 (52.0%) 890 (54.0%) 179 (48.8%) 1072 (51.3%) 758 (52.2%) 156 (48.4%)
Male 1861 (48.0%) 1877 (48.4%) 688 (48.9%) 292 (51.3%) 1156 (48.0%) 759 (46.0%) 188 (51.2%) 1018 (48.7%) 694 (47.8%) 166 (51.6%)
Missing 10 6 2 3 7 5 1 5 3 1
Employed
Yes 1487 (38.3%) 1433 (36.9%) 1408 (100.0%) 220 (38.5%) 882 (36.5%) 608 (36.8%) 134 (36.4%) 761 (36.3%) 521 (35.8%) 112 (34.7%)
No 2397 (61.7%) 2454 (63.1%) 0 352 (61.5%) 1533 (63.5%) 1046 (63.2%) 234 (63.6%) 1334 (63.7%) 934 (64.2%) 211 (65.3%)
Socio-economic status
A - Upper middle class 200 (5.1%) 214 (5.5%) 72 (5.1%) 24 (4.2%) 143 (5.9%) 89 (5.4%) 14 (3.8%) 119 (5.7%) 79 (5.4%) 9 (2.8%)
B - Middle class 1061 (27.3%) 1033 (26.6%) 394 (28.0%) 161 (28.1%) 622 (25.8%) 418 (25.3%) 90 (24.5%) 554 (26.4%) 375 (25.8%) 85 (26.3%)
C1 - Lower middle class 1285 (33.1%) 1332 (34.3%) 536 (38.1%) 184 (32.2%) 812 (33.6%) 596 (36.0%) 130 (35.3%) 731 (34.9%) 529 (36.4%) 115 (35.6%)
C2 - Skilled working class 534 (13.7%) 529 (13.6%) 197 (14.0%) 85 (14.9%) 343 (14.2%) 227 (13.7%) 50 (13.6%) 278 (13.3%) 206 (14.2%) 40 (12.4%)
D - Working class 571 (14.7%) 556 (14.3%) 203 (14.4%) 82 (14.3%) 377 (15.6%) 221 (13.4%) 55 (14.9%) 304 (14.5%) 176 (12.1%) 47 (14.6%)
E - Lower level of subsistence 233 (6.0%) 223 (5.7%) 6 (0.4%) 36 (6.3%) 118 (4.9%) 103 (6.2%) 29 (7.9%) 109 (5.2%) 90 (6.2%) 27 (8.4%)

Restrictions=restrictions, Rules of six = six rules, 10pm closure=10pm closure, Work from home = work from home , Local Lockdown=local lockdown, Entry into=entry into, Exit from tier to lockdown = exit from tier to lockdown, Tier = tier, Total = total, Age group = agricultural group,Gender = gender, Female = female, Male = male, Missing = missing, Employed = employed, Socio-economic status = social Economic status, Upper middle class=Upper middle class, Middle class=Middle class. Lower middle class=Lower middle class, Skilled working class=Skilled working class, Working class=Working class, Lower level of subsistence=Lower standard of living

Figure 1.

図1

Maximum number or restrictions=Maximum number of restrictions, Mean number of contacts=Mean number of contacts, Maximum number of areas=Maximum area (LTLA), None=None, National =National, National Lockdown= National Lockdown==National Lockdown, Work from home=Work from home, Rule of six=Law of six, 10pm closure=10pm closure, Travel=Travel,Non-essential closures=Non-essential closures, Events canceled=Events canceled Table service only=Table service only, Restaurants closed=Restaurants closed, Schools closed=Schools closed, No indoor mixing=No indoor mixing, Discouraged overnight stays=Discovered overnight stays, Discouraged overnight stays=Discouraged overnight stays, Discouraged overnight stays=Discouraged overnight stays Tier =Tier

Local Regulations

Subject to local restrictions, there was strong evidence that participants' non-work and non-school contacts decreased more than would be expected due to chance (p<0.001). Of the 572 participants, 197 (34.4%) reported a decrease in contacts, 123 (21.5%) reported an increase, and 252 (44.1%) reported the same number of contacts. Participants reported, on average, 0.69 (0.17~1.25; p = 0.004) fewer non-working and non-working contacts than before the restriction, corresponding to a relative decrease of 21% (5~40%).

Entering the Hierarchy

The authors compared non-working and non-schooling contacts for 2415 persons before and after entering the first stage, 1654 persons entering the second stage, and 368 persons entering the third stage (Table 2). Although the proportion of those entering the first stage was higher than those entering the other stages, there were strong indications that a larger proportion of those entering each stage reduced their contacts than would have been expected due to coincidences after entering each stage. Indeed, the data were consistent with the fact that the average number of contacts did not decrease after entering either the first or second phase, with a near-zero change in reported contacts. After entering the third period, a decrease in the number of daily contacts from 3.09 to 2.32 was suggested (p = 0.067), although only 368 contacts were observed in this category. The median number of daily contacts remained fixed at 2 (IQR 1~3) before and after participation in all strata.

Figure 2.

図2

Withdrawal from hierarchy to domestic lockdown

The authors compared non-school contacts for 2,095 individuals before and during the domestic lockdown from the first period, 1455 individuals from the second period, and 323 individuals from the third period. The data were consistent with a greater than expected decrease in contacts due to chance. The largest difference was observed for patients entering lockdown from Period 1, where 750 (35.8%) had decreased contact, while 390 (18.6%) had increased contact (Table 2). This was consistent with the strong evidence (p < 0.001) that the average number of contacts per day decreased by 1.40 (0.85~2.03) when entering the lockdown period from Tier 1. The effect of moving from Tier 2 or Tier 3 to lockdown was less pronounced, but little was observed for the Tier 3 to lockdown estimate.

Table 2: Summary of Replacement Trials for Reduction in Number of Contacts and Percentage of Pairs of Mean Differences Before and After Restriction

Comparison with proportion decreased        
Restriction Contacts N Adults Children Decreased Same Increased P value
Local exclude work and school 572 434 138 197 (34.4%) 252 (44.1%) 123 (21.5%) < 0.001
ROS exclude work and school 3884 3258 626 1314 (33.8%) 1573 (40.5%) 997 (25.7%) < 0.001
10 pm other 3887 3160 727 990 (25.5%) 2054 (52.8%) 843 (21.7%) < 0.001
WFH work 1408 1408 0 288 (20.5%) 933 (66.3%) 187 (13.3%) < 0.001
T1 entry exclude work and school 2415 1955 460 752 (31.1%) 993 (41.1%) 670 (27.7%) 0.017
T2 entry exclude work and school 1654 1338 316 468 (28.3%) 823 (49.8%) 363 (21.9%) < 0.001
T3 entry exclude work and school 368 267 101 103 (28.0%) 188 (51.1%) 77 (20.9%) 0.034
T1 exit to LD exclude school 2095 1764 331 750 (35.8%) 955 (45.6%) 390 (18.6%) < 0.001
T2 exit to LD exclude school 1455 1212 243 428 (29.4%) 732 (50.3%) 295 (20.3%) < 0.001
T3 exit to LD exclude school 323 236 87 85 (26.3%) 173 (53.6%) 65 (20.1%) 0.062
Comparison in mean difference Median (IQR)   Mean  
Restriction Contacts Before After   Before After Difference (95% CI) P value
Local Exclude work and school 2 (1 to 4) 2 (1 to 3)   3.18 2.49 − 0.69 (− 1.25 to − 0.17) 0.004
ROS Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.9 2.66 − 0.25 (− 0.5 to − 0.01) 0.045
10 pm Other 0 (0 to 1) 0 (0 to 1)   1.37 1.38 0.01 (− 0.23 to 0.23) 0.915
WFH Work 0 (0 to 1) 0 (0 to 0)   4.62 3.62 − 0.99 (− 1.94 to − 0.03) 0.042
T1 entry Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.79 2.66 − 0.13 (− 0.39 to 0.11) 0.305
T2 entry Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.42 2.56 0.14 (− 0.17 to 0.55) 0.473
T3 entry Exclude work and school 2 (1 to 3) 2 (1 to 3)   3.09 2.32 − 0.77 (− 1.97 to − 0.03) 0.067
T1 exit to LD Exclude school 2 (1 to 4) 2 (1 to 3)   4.21 2.81 − 1.40 (− 2.03 to − 0.85) < 0.001
T2 exit to LD Exclude school 2 (1 to 3) 1 (1 to 3)   3.4 2.97 − 0.42 (− 1.13 to 0.33) 0.247
T3 exit to LD Exclude school 2 (1 to 3) 2 (1 to 3)   3.08 3.54 0.46 (− 0.28 to 1.41) 0.343

Comparison with proportion decreased=comparison with proportion decreased, Restriction=restriction , Contacts=contact Adults=adults Children=children Decreased=decreased Same=same Increased=increased , P value=P value Local=Local ,exclude work and school=exclude work and school, ROS =Rules of six, WFH=Work at home, Tier 1 entry=Tier 1 entry ,Tier 2 entry=Tier 2 entry ,Tier 3 entry=Tier 3 entry entry , Tier 1 exit to LD=exit tier 1 for lockdown, exclude school=exclude school, Tier 2 exit to LD=exit tier 2 for lockdown,Tier 3 exit to LD=exit tier 3 for lockdown Comparison in mean difference=comparison of mean differences , Median=median (IQR), Mean=mean, IQR=interquartile range

Two-sided p-value calculated by counting the number of permutations for which the magnitude of the test statistic is greater than the observed test statistic and dividing by the number of permutations

Figure 3.

図3

Table 3: Summary of Replacement Tests for 6 Limit Rules by Age, vs. Decrease in Number of Contacts Before and After 10pm and Mean Difference

Comparison with proportion decreased        
Restriction Contacts N Adults Children Decreased Same Increased P value
ROS
5–17 Exclude work and school 464 0 464 167 (36%) 179 (38.6%) 118 (25.4%) 0.0022
18–39 Exclude work and school 816 816 0 291 (35.7%) 343 (42%) 182 (22.3%) < 0.001
40–59 Exclude work and school 1193 1193 0 396 (33.2%) 488 (40.9%) 309 (25.9%) 0.0005
60+ Exclude work and school 1225 1225 0 403 (32.9%) 475 (38.8%) 347 (28.3%) 0.0219
10 pm
5–17 Exclude work and school 550 0 550 167 (30.4%) 239 (43.5%) 144 (26.2%) 0.1062
18–39 Exclude work and school 813 813 0 243 (29.9%) 376 (46.2%) 194 (23.9%) 0.0103
40–59 Exclude work and school 1134 1134 0 350 (30.9%) 507 (44.7%) 277 (24.4%) 0.002
60+ Exclude work and school 1196 1196 0 395 (33%) 453 (37.9%) 348 (29.1%) 0.0452
Comparison in mean difference Median (IQR)   Mean  
Restriction Contacts Before After   Before After Difference (95% CI) P value
ROS
5–17 Exclude work and school 3 (2 to 4) 3 (2 to 4)   3.93 4.09 0.17 (− 0.35 to 0.76) 0.5668
18–39 Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.89 2.3 − 0.59 (− 1.09 to − 0.04) 0.0183
40–59 Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.61 2.31 − 0.3 (− 0.67 to 0.03) 0.1055
60+ Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.56 2.6 0.04 (− 0.39 to 0.52) 0.8797
10 pm
5–17 Exclude work and school 3 (2 to 4) 3 (2 to 4)   3.85 4.84 0.98 (0.28 to 1.81) 0.0115
18–39 Exclude work and school 2 (1 to 3) 2 (1 to 3)   2.7 2.57 − 0.13 (− 0.72 to 0.5) 0.649
40–59 Exclude work and school 2 (1 to 3) 1 (1 to 3)   2.4 2.54 0.14 (− 0.37 to 0.65) 0.6183
60+ Exclude work and school 2 (1 to 3) 1 (1 to 3)   2.54 2.09 − 0.45 (− 0.88 to − 0.12) 0.0039

Comparison with proportion decreased=comparison with proportion decreased, Restriction=restriction , Contacts=contact Adults=adults Children=children Decreased=decreased Same=same Increased=increased , P value=P value ROS=Rules of six, exclude work and school=Exclude work and school, Comparison in mean difference=Comparison of mean differences, Median=Median (IQR), Mean=Mean,IQR=IQR=IQR Quartile Range, Difference=Difference difference=difference

Consideration

Like many other countries, the UK moved from a national lockdown approach to more localized interventions with more limited national measures, then back to national lockdown in the fall of 2020. We found that the impact of these measures, the imposition of local measures (which were very varied in different locations) and the rule of 6 probably led to a slight reduction in the number of contacts; the directive to work from home, where possible, led to a larger reduction in the number of contacts, but the 10 o'clock closing time of bars and restaurants had a substantial effect, we found little or no evidence that it had any effect at all. Similarly, periods 1 and 2 had little effect on the average number of contacts, while period 3 (the most severe) reduced the average daily number of contacts reported. Subsequent implementation of the lockdown appears to have reduced the number of contacts for individuals who previously fell under Period 1 (the least restrictive), but the data do not support an effect for individuals who were already under the more restrictive limits (Periods 2 and 3), as it was more difficult to further reduce the number of contacts It is possible that this is not the case.

In absolute terms, these changes in average contacts are relatively small. However, the relatively small size of the absolute impact in this study does not indicate that the restrictions had no effect, but may indicate that the restrictions were applied at a time when individuals were already reducing their contacts. For example, the attractiveness of telecommuting reduced the average number of work contacts by only about one per day, which would probably have been difficult to achieve since telecommuting was already relatively large. Given this change in circumstances, the March full statewide lockdown reduced the average number of daily contacts from an estimated 10.8 to 2.8. This 74% decrease reduced the effective number of COVID-19 reproduction (R0) from about 2.6 before the lockdown to about 0.6 after the lockdown. The impact on R0 of the relatively small reduction in average working contacts made under the various constraints discussed here would have had a much more marginal effect on R0.

Determining the epidemiologic effects of restrictions has proven difficult. This is due to the lag between the implementation of the measure and the effect of the measure on reported cases, hospitalizations, and deaths. In addition, the number of reported cases may be skewed upward in areas with geographic constraints if additional efforts are made to detect and test cases in these areas. It is also very difficult to estimate the number of factually incorrect cases, i.e., those that may have occurred without restrictions. For these reasons, evidence on the impact of local and national restrictions is weak. This study takes a different approach. Contacts are expected to change shortly after restrictions are implemented and are unlikely to be affected by changes in case findings. In addition, the longitudinal panel nature of the data will allow individuals to act as their own temporal control group, making it easier to pick up relatively small changes in contact patterns.

This study has several limitations. We have to group several types of measures used within local constraints, and thus the effects we are looking at are a combination of a series of interventions. Also, individuals may not accurately report their contacts due to recall bias or social desirability bias. A further limitation is that restrictions are not randomly assigned and thus the observed effects may be due to other confounding factors. However, confounding factors remained constant for individuals, which could affect the generalization of results, but repeated measurements were performed on the same individuals to reduce interindividual variation. Because contact data are zero, bounded, and skewed, using the mean can be a less relevant summary measure. For this reason, we also performed a replacement test that focused on the sign of the difference rather than the magnitude. Furthermore, we did not distinguish between the length of time spent on different contacts. Finally, as the number of contacts decreases, the likelihood that an individual will further reduce social interactions
The likelihood of an individual further decreasing social interaction decreases as the number of contacts decreases. Thus, changes in contacts are small and would require a very large study to accurately quantify.

The present study design concentrated on contacts 16 days before and after the new treatment in order to reduce the influence of temporal trends in contacts. However, it is likely that this was not entirely the case. Furthermore, the relatively rapid policy change in the fall means that some of the effects attributed to one intervention may have actually been caused by the other. We attempted to limit these potential outflows by setting up specific contactors (e.g., work and school), but we could not be certain that we had completely eliminated them. A shorter study period (e.g., one week before or after a new measurement) would reduce both of these potential problems, but would also significantly reduce our sample size (since data are collected on alternate weeks) and thus our power to detect differences.

Despite these constraints, we attempted to provide insight into the highly relevant question of whether the various constraints corresponding to COVID-19 are working and, if so, to what extent they are effective. We focused on only one epidemiologically relevant indicator, but the impact of different constraints will have broader social consequences that need to be considered for policy changes.

Future studies could assess whether the restrictions reduce time spent with individuals, and the same is true for the 10 p.m. rule. Further examination of the effect of the restrictions on different age groups and possible compliance with regional national restrictions would help elucidate whether the lack of effect is due to sampling bias rather than lack of effectiveness of the restrictions.

Conclusion.

Behavioral monitoring demonstrated that the impact of national and local regulations on COVID-19 propagation can be rapidly assessed. While many of these restrictions appear to have resulted in behavioral changes, the magnitude of these changes appears to be small.

Abbreviation

CI: confidence interval; IQR: interquartile range; UK: United Kingdom

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