Use of wearable sensors to assess compliance of asthmatic children in response to lockdown measures for the COVID-19 epidemic

Abstract

Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels of public health interventions to control the COVID-19 pandemic. We quantified compliance of 108 asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries to intervention levels, using wearable sensors to continuously track personal location and physical activity. Changes in ‘fraction time spent at home’ and ‘total steps/day’ were assessed with a mixed-effects model adjusting for confounders. We observed significant mean increases in ‘fraction time spent at home’ in Cyprus and Greece, during each intervention level by 41.4% and 14.3% (level 1), 48.7% and 23.1% (level 2) and 45.2% and 32.0% (level 3), respectively. Physical activity in Cyprus and Greece demonstrated significant mean decreases by − 2,531 and − 1,191 (level 1), − 3,638 and − 2,337 (level 2) and − 3,644 and − 1,961 (level 3) total steps/day, respectively. Significant independent effects of weekends and age were found on ‘fraction time spent at home’. Similarly, weekends, age, humidity and gender had an independent effect on physical activity. We suggest that wearable technology provides objective, continuous, real-time location and activity data making possible to inform in a timely manner public health officials on compliance to various tiers of public health interventions during a pandemic.

Full text

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Use of wearable sensors to assess
compliance of asthmatic children
in response to lockdown measures
for the COVID‑19 epidemic
Panayiotis Kouis1, Antonis Michanikou1, Pinelopi Anagnostopoulou 1,2,
Emmanouil Galanakis3, Eleni Michaelidou3, Helen Dimitriou3, Andreas M. Matthaiou1,
Paraskevi Kinni1, Souzana Achilleos4, Harris Zacharatos5,6, Stefania I. Papatheodorou 7,
Petros Koutrakis8, Georgios K. Nikolopoulos9 & Panayiotis K. Yiallouros1*
Between March and April 2020, Cyprus and Greece health authorities enforced three escalated levels
of public health interventions to control the COVID‑19 pandemic. We quantied compliance of 108
asthmatic schoolchildren (53 from Cyprus, 55 from Greece, mean age 9.7 years) from both countries
to intervention levels, using wearable sensors to continuously track personal location and physical
activity. Changes in ‘fraction time spent at home’ and ‘total steps/day’ were assessed with a mixed‑
eects model adjusting for confounders. We observed signicant mean increases in ‘fraction time
spent at home’ in Cyprus and Greece, during each intervention level by 41.4% and 14.3% (level 1),
48.7% and 23.1% (level 2) and 45.2% and 32.0% (level 3), respectively. Physical activity in Cyprus and
Greece demonstrated signicant mean decreases by − 2,531 and − 1,191 (level 1), − 3,638 and − 2,337
(level 2) and − 3,644 and − 1,961 (level 3) total steps/day, respectively. Signicant independent eects
of weekends and age were found on ‘fraction time spent at home’. Similarly, weekends, age, humidity
and gender had an independent eect on physical activity. We suggest that wearable technology
provides objective, continuous, real‑time location and activity data making possible to inform in a
timely manner public health ocials on compliance to various tiers of public health interventions
during a pandemic.
Following several coronavirus outbreaks during the last years1, a novel coronavirus named SARS-CoV-2 pre-
sented in Wuhan, China in December 2019, causing severe disease (COVID-19) with high fatality rates, espe-
cially, amongst the elderly and people with comorbidities2. e virus rapidly spread all over the world and on
the 11th of March 2020, WHO characterized COVID-19 outbreak as a pandemic3.
In the absence of an eective vaccine or specic antiviral drugs against COVID-194, it seems that the only
strategy to control the pandemic are public health interventions implemented at the community or national
level. e interventions may range from simple isolation of disease carriers, quarantine of contacts and hand
hygiene measures to ban of mass gatherings, social distancing and nally to complete lockdown and community
quarantine (cordon sanitaire)5–7. ese measures coupled with extraordinary travel restrictions from national
governments are oen in disaccord with international and human rights law8. During the rst peak of the pan-
demic, aected countries chose dierent levels of interventions based, among others, on national risk assessments
of estimated number of patients and capacity for hospitalization and critical care support9,10. e evolution of
the pandemic over the last months demonstrated that timely interventions were eective to delay the spread of
COVID-1911,12, as it was also shown in previous u and SARS epidemics13–15.
OPEN
Respiratory Physiology Laboratory, Medical School, Shacolas Educational Center of Clinical Medicine,
           Institute
       Medical School, University of Crete, Heraklion, Crete,
Greece. Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology,
Limassol, Cyprus.          Department of
           Department
            Medical
 *email: yiallouros.panayiotis@ucy.ac.cy
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e compliance of the population to non-pharmaceutical interventions plays a catalytic role in the success-
ful containment of the virus16. However, it is dicult to monitor and understand population’s compliance to
behavioural changes forced by interventions during an emerging pandemic17–19. To date, several parameters have
been used as indirect indicators of societal behaviour and compliance to public health measures, such as the
reduction of outdoor pollution20,21, decrease in trac accidents22 or even quietening of human activity signals
as measured by seismometers worldwide23. In the context of complete lockdown measures, where citizens are
advised to reduce their mobility and stay at home, wearable sensors measuring physical activity levels and time
spent at home may serve as a direct indicator for citizens’ compliance to the measures.
Patients with chronic respiratory disorders, like asthma, are considered to be at increased risk for severe
COVID-19 disease24,25 and from the beginning of the pandemic they were advised to meticulously comply to
restriction measures. In the pediatric population, asthma is the most common chronic disorder and although
COVID-19 is milder in children, the burden of the disease on public health may be signicant26. Furthermore,
it is known that children may have more diculties to comply to restriction measures27, with their compliance
depending substantially on the whole family’s attitude towards the measures. e aim of our study was to quantify
mobility changes in response to COVID-19 lockdown measures of schoolchildren with asthma in Cyprus and
Greece, by continuously tracking their location and activity, using wearable sensors.
Results
Participants’ characteristics. For 2020 study period, a total of 108 (57% males) asthmatic children, 53
in Cyprus and 55 in Greece, with an average age of 9.2years were enrolled in the study, and contributed data
between February 3rd and April 26th, 2020. All children had a physician’s diagnosis of asthma, while 53% also
reported wheezing episode(s) during the past 12months, 45% unscheduled medical visit(s) for asthma, 26%
emergency room visits for asthma, and 20% daily preventive anti-asthma medication during the past 12months.
Among study participants, 43% were characterized as having asthma severity 1, 43% asthma severity 2 and 15%
asthma severity 3 (Table1). For the 2019 study period, from February 3rd to April 26th, we measured mobil-
ity for 39 and 52 asthmatic children (59% males) in Cyprus and Greece, respectively, with an average age of
9.3years.
Unadjusted analysis. Overall, in both countries there were signicant changes in the observed fraction
time spent at home and total steps/day with introduction of public health intervention levels for the study year
2020. e observed mean fraction time spent at home among asthmatic children in Cyprus and Greece during
baseline period was 43.8% (95%CI: 40.5–47.1%) and 52.4% (95%CI: 49.4–55.4%) respectively. In Cyprus, the
observed fraction time spent at home signicantly increased to 88.9% (95%CI: 85.7–92.1%) during level 1, to
95.5% (95%CI: 93.8–97.2%) during level 2 and 94.1% (95%CI: 92.5–95.7%) during level 3 of interventions. In
Greece, introduction of level 1 public health interventions was characterized by an increase in the observed frac-
tion time spent at home to 71.4% (95%CI: 60.4–82.5%), while during level 2 and 3 interventions the fraction time
spent at home increased further to 84.9% (95%CI: 80.3–89.4%) and 89.6% (95%CI: 87.0–92.3%) respectively
(Table2, Fig.1). In Cyprus, the observed total steps/day reduced signicantly with introduction of each level
of public health interventions from 8,996 (95%CI: 8,567–9,425) at baseline, to 6,499 (95%CI: 5,832–7,166) at
Table 1. Basic demographic and clinical characteristics of asthmatic children in Cyprus and Greece included
in the study for the 2020 study period. *Values are presented as Mean (Standard Deviation). †ER: Emergency
Department. ‡ Asthma Severity 1: Physician diagnosis plus one other eligibility criterion, Asthma Severity 2:
Physician diagnosis plus two other eligibility criteria, Asthma Severity 3: Physician diagnosis plus three or
more other eligibility criteria.
Parameter Asthmatic children (Cyprus, n = 53) Asthmatic children (Greece, n = 55)
Demographic
M (%) 35 (66%) 27 (49%)
Age, years* 9.3 (1.7) 9.11 (1.8)
Weight, kg* 39.3 (19.0) 35.9 (9.6)
Height, cm* 137.2 (21) 134.8 (10.2)
BMI, kg/m2* 20.3 (8.3) 19.5 (3.3)
Asthma eligibility criteria
Physician diagnosis of Asthma 53 (100%) 55 (100%)
Wheezing episodes 35 (66%) 22 (40%)
Daily preventive medication 10 (19%) 12 (22%)
Unscheduled physician visits for Asthma 34 (64%) 15 (27%)
ER† visits for Asthma 10 (19%) 18 (33%)
Asthma severity status‡
Asthma severity 1 25 (47%) 21 (38%)
Asthma severity 2 20 (38%) 26 (47%)
Asthma severity 3 8 (15%) 8 (15%)
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Table 2. Observed fraction time spent at home and total steps per day across levels of intervention for Covid-
19 in Cyprus and Greece. Values are presented as mean (95% Condence Interval).
Intervention
Parameter Statistical signicance Parameter Statistical signicance
Fraction time spent at
home Compared to baseline Compared to
previous le vel Steps per day Compared to baseline Compare d to
previous le vel
Asthmatic children (Cyprus) (n = 53)
Baseline (Level 0) 43.8% (40.5%; 47.1%) – – 8996 (8567; 9425) – –
Level 1 88.9% (85.7%; 92.1%) < 0.001 < 0.001 6499 (5832; 7166) < 0.001 < 0.001
Level 2 95.5% (93.8%; 97.2%) < 0.001 0.151 6248 (5683; 6812) < 0.001 0.999
Level 3 94.1% (92.5%; 95.7%) < 0.001 0.999 6270 (5814; 6727) < 0.001 0.999
Fraction time spent at home Steps per day
Asthmatic children (Greece) (n = 55)
Baseline (Level 0) 52.4% (49.4%; 55.4%) – – 8527 (8145; 8908) – –
Level 1 71.4% (60.4%; 82.5%) 0.003 0.003 6864 (5689; 8040) 0.060 0.060
Level 2 84.9% (80.3%; 89.4%) < 0.001 0.357 5533 (4769; 6297) < 0.001 0.613
Level 3 89.6% (87.0%; 92.3%) < 0.001 0.999 5439 (5051; 5829) < 0.001 0.999
Figure1. Changes in mobility in response to public health interventions among asthmatic children.
Weekly averages of fraction time spent at home and steps/day, before and during three levels of public health
interventions in asthmatic children in Cyprus (A) and Greece (B).
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level 1, 6,248 (95%CI: 5,683–6,812) at level 2 and 6,270 (95%CI: 5,814–6,727) at level 3. Similarly, in Greece, the
observed total steps/day reduced with each level of public health interventions from 8,527 (95%CI: 8,145–8,908)
at baseline, to 6,864 (95%CI: 5,689–8,040) at level 1, 5,533 (95%CI: 4,769–6,297) at level 2 and 5,439 (95%CI:
5,051–5,829) at level 3 (Table2, Fig.1). e same trend was also observed for fraction time spent at home and
total steps per day in both countries when the change across levels of intervention were calculated separately
for each category of asthma severity. Data are presented in detail in Supplementary Table1. is pattern was in
sharp contrast to the normal mobility pattern of the asthmatic children cohorts in Cyprus and Greece during the
same study period for the study year 2019, where the fraction time spent at home and total steps per day were
quite stable throughout the same weeks of the year (Fig.2).
Adjusted analysis. Based on the mixed eects model, aer controlling for several confounders, the adjusted
mean increase in time-fractions spent at home in Cyprus were: 41.4% (95%CI: 34.5–48.2%, pvalue < 0.001 com-
pared to baseline) during level 1, 48.7% (95%CI: 42.0–55.5%, pvalue < 0.001 compared to baseline) during level
2, and 45.2% (95%CI: 39.3–51.2%, pvalue < 0.001 compared to baseline) during level 3 of interventions (Table3).
ere was no signicant increase between level 2 and 3 periods (pvalue = 0.298), while the increase between level
1 and 2 periods was almost signicant (pvalue = 0.055). In Greece, the adjusted mean changes in fraction time
spent at home were more gradual and moderate, increasing by 14.3% (95%CI: 2.2–26.3%, pvalue = 0.02 com-
pared to baseline) during level 1, 23.1% (95%CI: 11.2–34.9%, pvalue < 0.001 compared to baseline) during level 2,
and 32.0% (95%CI: 24.8–39.3%, pvalue < 0.001 compared to baseline) during level 3 interventions (Table4). e
changes between levels 1 and 2 as well as levels 2 and 3 were not statistically signicant.
In Cyprus, physical activity, expressed in total steps per day, demonstrated an adjusted mean decrease of − 2,531
(95%CI: − 3,364; − 1,698, pvalue < 0.001 compared to baseline) during level 1, − 3,638 (95%CI: − 4,521; − 2,755,
Figure2. Comparison of mobility of asthmatic children recorded in February–April 2019 and February–April
2020 in Cyprus and Crete. Weekly averages of fraction time spent at home and steps/day during the same period
of 2019 and 2020 in Cyprus (A) and Greece (B) (February–April).
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pvalue < 0.001 compared to baseline) during le vel 2, and − 3,644 (95%CI: − 4,428; − 2,859, pvalue < 0.001 compared
to baseline) during level 3 (Table3). e decreases in total steps per day for levels 1 and 2 were statistically sig-
nicant (pvalue = 0.019), but not for levels 2 and 3 (pvalue = 0.954). In Greece, the adjusted mean decrease of physical
activity during level 1 period was − 1,191 (95%CI: − 2,641; − 259, pvalue = 0.108 compared to baseline) steps per
day. During level 2 and 3 periods the corresponding decreases were − 2,337 (95%CI: − 3,679; − 995, pvalue = 0.001
compared to baseline) and − 1,961 (95%CI: − 2,933; − 990, pvalue < 0.001 compared to baseline) steps/day, respec-
tively (Table4). e dierences in total steps decreases per day between levels 1 and 2 (pvalue = 0.212) and levels
2 and 3 (pvalue = 0.576) did not reach statistical signicance.
During the baseline period, in the cohort of asthmatic children in Cyprus, we found that fraction time
spent at home was signicantly higher during weekends as compared to weekdays (mean increase compared to
weekdays: 10.9%. 95%CI: 8.0; 13.8%) and with every year of increasing age (mean increase: 1.4%. 95%CI: 0.2;
2.6%). Furthermore, total steps per day were signicantly lower during weekends (mean decrease compared
to weekdays: − 1,002. 95%CI: − 1,374; − 630), with increasing age (mean decrease: − 378. 95% CI: − 615; − 143),
increasing humidity (mean decrease: − 29. 95%CI: − 42; − 15) and in year 2020 as compared to year 2019
(mean decrease: − 1,560. 95%CI: − 2,796; − 324). Finally, total steps per day were signicantly higher in males
as compared to females (mean increase: 1,024. 95%CI: 53; 1,944) (Table3). In asthmatic children in Greece,
Table 3. Fraction time spent at home and total steps per day in response to interventions for Covid-19 among
asthmatic children in Cyprus. *p < 0.001, compared to previous level. †p = 0.055, compared to the previous level.
‡p = 0.021, compared to the previous level, §p > 0.05, compared to the previous level.
Parameter
Fraction time spent at home Total Steps per day
β coecient (95% CI) Compared to baseline β coecient (95% CI) Compared to baseline
Baseline (Level 0) (intercept) 47.1% (18.2%; 76.0%) – 13,520 (9123–17,917) –
Level 1 41.4% (34.5%; 48.2%) < 0.001* − 2531 (− 3364; − 1698) < 0.001*
Level 2 48.7% (42.0%; 55.5%) < 0.001† − 3638 (− 4521; − 2755) < 0.001‡
Level 3 45.2% (39.3%; 51.2%) < 0.001§ − 3644 (− 4428; − 2859) < 0.001§
Gender (male) 1.7% (− 3.2%; 6.5%) 0.502 1024 (53;1944) 0.039
Age (per year increase) 1.4% (0.2%; 2.6%) 0.019 − 378 (− 615; − 143) 0.002
Year (2020) − 0.6% (− 6.4%; 5.1%) 0.826 − 1560 (− 2796; − 324) 0.013
Weekend 10.9% (8.0%; 13.8%) < 0.001 − 1002 (1374; − 630) < 0.001
Temperature (per degree C0
increase) − 0.03% (− 0.07%; 0.15%) 0.909 58.0 (− 6; 122) 0.075
Humidity (per % increase 0.04% (− 0.07%; 0.15%) 0.539 − 29 (− 42; − 15) < 0.001
Interaction term β coecient (95% CI) Compared to baseline β coecient (95% CI) Compared to baseline
Weekend # Level 1 − 22.8% (− 33.8%; − 11.8%) < 0.001 1870 (539; 3202) 0.006
Weekend # Level 2 − 13.0% (− 25.9%; − 0.1%) 0.047 1196 (− 535; 2927) 0.176
Weekend # Level 3 − 18.6% (− 27.4%; − 9.8%) < 0.001 1361 (191; 2531) < 0.001
Table 4. Fraction time spent at home and total steps per day in response to interventions for Covid-19 among
asthmatic children in Greece. *p = 0.020, compared to previous level. †p > 0.05, compared to the previous level.
Parameter
Fraction time spent at home Total Steps per day
β coecient (95% CI) Compared to baseline β coecient (95% CI) Compared to baseline
Baseline (Level 0) (intercept) 74.6% (52.3%; 97.0%) – 13,342 (9182; 17,501) –
Level 1 14.3% (2.2%; 26.3%) 0.020* − 1191 (− 2641; − 259) 0.108†
Level 2 23.1% (11.2%; 34.9%) < 0.001† − 2337 (− 3679; − 995) 0.001†
Level 3 32.0% (24.8%; − 39.3%) < 0.001† − 1961 (− 2933; − 990) < 0.001†
Gender (male) 2.2% (− 3.4%; 7.7%) 0.442 1064 (− 63; 2191) 0.064
Age (per year increase) − 1.0% (− 2.6%; 0.5%) 0.191 57 (− 257; 370) 0.722
Year (2020) − 0.7% (− 7.9%; 6.6%) 0.859 − 2791 (− 4090; − 1492) < 0.001
Weekend 8.32% (5.2%; 11.4%) < 0.001 − 1212 (1615; − 809) < 0.001
Temperature (per degree C0
increase) − 0.6% (− 1.3%; 0.0%) 0.059 21 (− 64; 107) 0.628
Humidity (per % increase) − 0.1% (− 0.2%; 0.0%) 0.061 − 2 (− 16; 12) 0.763
Interaction term β coecient (95% CI) Compared to baseline β coecient (95% CI) Compared to baseline
Weekend # Level 1 − 12.7% (− 37.2%; − 11.8%) 0.310 149 (− 2739; 3037) 0.006
Weekend # Level 2 − 9.5% (− 32.5%; 13.5%) 0.416 3704 (1115; 6292) 0.005
Weekend # Level 3 − 9.6% (− 19.8%; 0.5%) 0.063 1433 (96; 2772) 0.036
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the fraction of time spent at home was also found to be signicantly higher during weekends as compared
to weekdays (mean increase: 8.32%. 95%CI: 5.2; 11.4%), while steps per day were signicantly lower during
weekends (mean decrease: − 1,212. 95%CI: − 1,615; − 809) and in year 2020 as compared to year 2019 (mean
decrease: − 2,791. 95%CI: − 4,090; − 1,492) (Table4). In asthmatic children in Cyprus, we found a signicant
interaction eect of weekends across all levels of interventions on both the fraction time spent indoors and
total steps per day. e eect of weekends on fraction time spent indoors changed, signicantly, from positive
during level 0 (mean increase: 10.9%) to negative during level 1 (mean decrease: − 22.8%, pvalue: < 0.001), level 2
(mean decrease: − 13.0%, pvalue: 0.047) and level 3 (mean decrease: − 18.6%, pvalue: < 0.001). A similar interaction
eect was observed on the eect of weekends on total steps per day which changed from negative during level
0 (mean decrease: − 1002) to positive during level 1 (mean increase: 1863, pvalue: 0.006), level 2 (mean increase:
1180, pvalue: 0.181) and level 3 (mean increase: 1359, pvalue: < 0.023), (Table3). In asthmatic children in Greece
we found a signicant interaction eect for weekends only in regards to total steps per day. During the baseline
period, weekends were associated with a mean decrease of − 1212 steps per day while this eect was reversed in
level 1 (mean increase: 149, pvalue: 0.919), level 2 (mean increase: 3704, pvalue: 0.005) and level 3 (mean increase:
1434, pvalue: 0.036), (Table4).
Discussion
In this study, we have assessed changes in mobility of asthmatic children in Cyprus and Greece in response to
dierent levels of public health interventions for the COVID-19 pandemic using GPS tracking, pedometer and
heart rate sensors embedded in wearable watches. Our data imply that asthmatic children in both countries were
highly compliant to public health measures, by changing their everyday routine and limiting their activity and
mobility outside their homes.
In asthmatic children in Cyprus, we recorded a steep increase in the fraction of time spent at home from
44% to the very high 95% and a steep decrease in total steps per day from 8,996 to 6,270, demonstrating high
compliance to the implemented three levels of interventions. In asthmatic children in Greece, we observed a
more gradual, stepwise increase in fraction time spent at home from 52% at baseline to the also high 90% and
a similar pattern of gradual decrease of physical activity from 8,527 to 5,439 steps/day. e subtle dierences in
the ndings between the two countries can be explained by dierences in the actual measures implemented in
each country rather than by real dierences in the compliance of asthmatic children to the interventions. In fact,
intervention measures in Greece were slightly dierent to those in Cyprus. In Greece level 2 measures included
only ban of public gatherings and closure of shops and worship places, and escalated to include personal transport
and movement restrictions only in level 3 period. In Cyprus, personal mobility restrictions were implemented
from level 2 measures and became stricter (only one movement per day) in level 3, although the corresponding
changes in fraction time spent at home and steps per day between level 2 and level 3 periods were not signicant
in our study group.
e successful management of the pandemic spread in Cyprus and Greece is probably due to the early intro-
duction of lockdown measures in both countries by March 25 and 23, 2020 respectively, and the high compli-
ance of vulnerable groups, and possibly the general population, who spent the majority of their time at home.
e eectiveness of lockdown measures to reduce transmission of COVID-19 in several European countries
including Greece was previously reported28. A recent modelling study evaluated the impact of the sequence of
restrictions posed to mobility and human-to-human interactions on the virus transmission in Italy and found
that they have reduced transmission by 45%29. As of 26 April 2020, 1.43 and 1.22 deaths per 100,000 popula-
tion were reported for Cyprus and Greece respectively, which places them among the countries with the lowest
mortality rates for COVID-19 in the EU/EEA and UK30. Our ndings may also relate to those of several recent
studies that reported reduced asthma morbidity in children during the COVID-19 pandemic, attributed to the
reduction of the overall viral infections because of signicant changes in their daily activity31–34.
It is well documented that wearable technology is a reliable, objective tool for monitoring numerous dis-
eases and estimating adherence to medication35. However, to the best of our knowledge, there are no previ-
ous studies examining compliance to public health interventions using wearable devices. Previous reports on
adherence to public health interventions during epidemics were based on telephone or mailed interviews and
questionnaires17–19,36. ese conventional tools have inherent limitations such as non-response, recall biases, lack
of validation of self-reports, inuence by concerns about being recognized as breaching quarantine and low-level
spatio-temporal information. In contrast, the use of wearable devices provides objective, continuous, real-time
location and activity data making possible to timely inform public health ocials on the results of various tiers
of public health interventions and ensure adequate decision making in escalating or de-escalating interventions.
Using a mixed eects model, we were able to nd independent quantitative eects of several factors on the
time participants spent at home (weekends, increasing age) and their physical activity (weekends, increasing
age, humidity and gender). We also found an interaction eect of weekends on higher fraction of time spent
at home and lower physical activity, which was reversed during the implementation of intervention measures
in both countries. One possible explanation is that, under normal conditions, families spend more time out of
home on weekdays and more time at home during weekends. During the pandemic period this was reversed, as
working parents and children had to work or study at home during weekdays and spend more time for outdoor
activities on weekends. However, the change of participants’ daily behavior in both countries and the increase
in their mobility on weekends during the enforcement of the lockdown measures requires further investigation.
e independent eect of age on increasing fraction time spent at home and lower physical activity and female
gender on lower physical activity in asthmatic children in Cyprus, agree with previous studies that reported
lower physical activity in asthmatic girls37 and older asthmatic children38. Year 2020 has been associated with
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lower physical activity in asthmatic children in both countries, which may relate to a systematic eect of either
the recording devices used or implication of environmental factors we have not accounted for in the analysis.
Digital technology has been widely used in the COVID-19 management, including tracking positive cases,
informing citizens about the current epidemiological status in their region, performing virtual clinics and diag-
nostics through telemedicine and in disease modelling using big data analysis39,40. Our study presents another
promising application of digital technology in the ght against the pandemic, by employing wearable sensors to
provide objective and real-time information about population compliance to public health measures. erefore,
in a public health emergency, it is possible to employ wearable technology in a greater sample of the general
population and enable rapid measurements of the public reaction to a particular set of interventions. GPS and
physical activity data for example, are collected anonymously by telephone companies from their smartphone
customers and theoretically may provide information about population’s attitude and adherence to interventions
taken in pandemics and/or natural disasters. Towards this aim, in Israel a cell-phone tracking system was used
in SARS-CoV-2 positive individuals to facilitate contacts tracing41, while data from smartphone users in Italy
have been analysed to estimate citizen mobility during the lockdown42. In this direction, future applications of
wearable digital technology may include the development of appropriate tools and infrastructure for ecient,
systematic integration and interoperability of dierent health and behaviour data sources into existing public
health systems. is approach will facilitate the link between symptom-tracking apps, behavior-tracking apps,
contact tracing, aggregate population mobility monitoring, healthcare access and e-health monitoring40.
Nevertheless, this kind of monitoring raises important ethical issues, as it could be considered as limiting
individual freedoms and rights43–46. In our case, monitoring of these patients with wearable devices was already
established as part of the ongoing MEDEA project that started much before the spread of COVID-19, and thus
we had obtained timely ethical approval and written consent from participants. In the case of pandemics, where
decisions and measures are taken within days or even hours, it is extremely dicult to obtain fast-track consent
from individuals to record their attitudes with wearable technology. For this reason, future health surveillance
tracking and contact-tracing tools and applications should be designed in a way that can preserve individual
freedoms and assert patient autonomy in a socially responsible manner, while educating the population about
the positive eects of health surveillance47.
An important limitation of wearable technology is the loss of signal of GPS tracking, especially in indoor
environments, which introduces the challenge of how to treat missing values. As a response, automated micro-
environment classication algorithms that include spatial and temporal buering have been developed and
validated, especially for air pollution exposure studies48 and provide an eective way to account for missing
location data. Our ndings should be interpreted with caution and not be generalized directly to all children
or to the general population, because soon aer the appearance of the COVID-19 pandemic it became widely
known that asthmatic patients may be at increased risk for severe disease49. Furthermore, asthmatic patients
were more likely accustomed to protective behavioural changes even before the pandemic, as they were aware
of the negative health eects of poor air quality50,51 and the potential of atmospheric pollutants to further impair
the respiratory system and facilitate viral infection, as it has been suggested for SARS-CoV-252. ese factors
may have led to increased compliance to public health intervention measures for COVID-19, as compared to
the general population. Further studies, focusing on the general population are needed to better assess the full
extent of population compliance to public health intervention measures for COVID-19. Finally, our cohort lacks
information about family characteristics during the pandemic, such as parents’ employment status and time spent
working from home, which may aect the outcomes of our study.
Conclusion
In conclusion, we implemented novel wearable technology methods to assess personal compliance to public
health interventions aiming to contain the spread of a novel, highly contagious virus such as SARS-CoV-2. e
successful implementation of public health interventions in Cyprus and Greece, which minimized COVID-19
related mortality in both countries, was reected in the sharp mobility reductions recorded in the participants
of our study early in the course of the outbreak. Wearable devices provide objective, continuous, real-time data
that may timely inform public health ocials on compliance to various tiers of public health interventions and
ensure informed decision-making and strategic planning in the containment of epidemics, both at national and
cross-national levels.
Materials and methods
Study setting. Asthmatic children were recruited from primary schools in Cyprus and Greece (Heraklion
district, Crete) and were enrolled in the ongoing LIFE-MEDEA public health intervention project (Clinical.
Trials.gov Identier: NCT03503812). e LIFE-MEDEA project aims to evaluate the ecacy of behavioral rec-
ommendations to reduce exposure to particulate matter during desert dust storm (DDS) events and thus miti-
gate disease-specic adverse health eects in vulnerable groups of patients. Details of the study protocol and
methods are presented in Supplementary File 1. In order to assess adherence to recommendations, participants
are equipped with a wearable device (smartwatch) with several sensors. Participants are instructed to wear the
smartwatch throughout the study period, during both DDS and non-DDS days. During non-DDS days, all par-
ticipants carry out their usual daily activities. e rst MEDEA study period took place during February-June
2019, the second study period during February-June 2020.
Study populations and recruitment. In the asthma panel study the target population were children aged
from 6 to 11years with mild to moderate persistent asthma. e eligibility criteria included a physician’s diagno-
sis of asthma and at least one of the following: daily preventative asthma medication, wheezing episodes and/or
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unscheduled medical visits for asthma during the past 12months. Basic demographic and clinical information
from all participants was collected during the recruitment process. e number of eligibility criteria applying for
each participant were used to categorize participants into asthma severity groups. e groups were dened as
follows: Asthma Severity 1 (Physician diagnosis plus one other eligibility criterion), Asthma Severity 2 (Physi-
cian diagnosis plus two other eligibility criteria) and Asthma Severity 3 (Physician diagnosis plus three or more
other eligibility criteria). In Cyprus, study approvals were obtained from the Cyprus National Bioethics Commit-
tee (EEBK EΠ 2017.01.141), the Data Protection Commissioner (No. 3.28.223) and the Ministry of Education
(No 7.15.01.23.5). In Greece, approvals were obtained from the Scientic Committee (25/04/2018, No: 1748)
and the Governing Board of the University General Hospital of Heraklion (25/22/08/2018). Guardians of all
participants provided written informed consent and all methods described below were performed in accordance
with the relevant guidelines and regulations.
Physical activity and GPS tracking. Physical activity and global positioning system (GPS) data were
recorded between February 3 and April 26, for both study years (2019 and 2020) in Cyprus and Greece using
the smartwatch. Data from study year 2020 were extracted to assess the participants’ mobility before and during
the enforcement of COVID-19 lockdown measures while data from study year 2019 that represent a completely
restrictions-free mobility period were also used for comparison. e EMBRACE™ smartwatch (Embrace Tech
LTD, Cyprus) was used for data collection. e smartwatch works as a stand-alone device and is equipped with
multiple sensors such as pedometer, GPS and heart rate as well as an embedded sim-card for Wi-Fi data trans-
fer. e soware is capable of synchronizing the sensors, so the data are transferred to the cloud with the same
timestamp. Data on GPS coordinates and steps/time unit, and heart rate are collected per 5-min intervals. Data
synchronization with a cloud-based database is performed automatically when the smartwatch contacts the
Wi-Fi network inside the participants’ home. For each participant we recorded the total number of steps per day
(24-h period). In addition, we dened the fraction of time spent at home as the ratio of time with GPS signal
within a 100m radius around the participant’s residence divided by 24h. e 100m radius was dened as the
maximum barrier to account for the accuracy of GPS signal in commercially available GPS receivers53. As signal
accuracy in urban and especially indoor environments is further blocked or bounced repeatedly o buildings
prior to being received54, we also classied 5-min intervals with no GPS signal as either “at-home” or “out-home”,
depending on the signal of the most recent valid GPS recording. Lastly, the days that participants did not wear
the smartwatch were identied by absence of heart rate measurements, and were excluded from subsequent
analysis. We also excluded from the analysis GPS and pedometer data for DDS days in Cyprus (5days during
February-April 2020 and 4days during February-April 2019) and Crete-Greece (1day during February-April
2020 and 2days during February-April 2019) that may had further inuenced the mobility of the participants.
Public health (non‑pharmaceutical) interventions in Cyprus and Greece. Data collection period
spans for 12weeks from February 3 to April 26, 2020 and was divided into four levels based on the implemented
public health interventions in each country. In Cyprus, the rst COVID-19 cases were identied on March 9,
2020 and the study period is divided to: i) level 0 (baseline)—no public health interventions (Weeks 1–5: Febru-
ary 3, 2020–March 12, 2020), ii) level 1—social distancing measures, ban of public events with > 75 people, bars,
restaurants and schools closed (Weeks 6–7: March 13, 2020–March 24, 2020), iii) level 2—all retail shops and
worship places were closed, and mobility restrictions were implemented, except for subsistence and health needs
(3 permissions per person per day) (Week 8: March 25, 2020–March 31, 2020), iv) level 3—stringent lockdown
Figure3. Timeline of public health interventions in Cyprus and Greece. Timeline of the study recordings in
relation to introduction of public health interventions in Cyprus (A) and Greece (B) during March–April 2020.
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www.nature.com/scientificreports/
with only one mobility permission per person per day (Weeks 9–12: April 01, 2020–April 26, 2020) (Fig.3). In
Greece, the rst COVID-19 case was identied on February 26, 2020 and the study period is divided to: i) level
0 (baseline)— no public health interventions (Weeks 1–5: February 03, 2020–March 10, 2020), ii) level 1—social
distancing measures, ban of all public events, bars, restaurants and schools closed (Week 6: March 11, 2020–
March 15, 2020), iii) level 2—all retail shops and worship places closed, ban of gatherings of > 10 people (Week 7:
March 16, 2020–March 22, 2020), iv) level 3—mobility restrictions except for subsistence and health needs (no
daily limit) (Weeks 8–12: March 23, 2020-April 26, 2020) (Fig.3).
Statistical analysis. Basic demographics and clinical characteristics of the asthmatic children were sum-
marized using mean (standard deviation) for continuous variables and percentages for categorical variables.
In an unadjusted analysis, the mean fraction time spent at home and mean total steps per day were compared
between the dierent periods of public health interventions using ANOVA, while graphs were constructed in
order to demonstrate the weekly variation in mobility before and during the implementation of public health
interventions in Cyprus and Greece. Furthermore, the course of fraction time spent at home and total steps per
day in asthmatic children participating in the second MEDEA study period during February–April 2020 and
the same parameters’ course in asthmatic children participating in the rst MEDEA study period during Febru-
ary–April 2019 are displayed in separate graphs for Cyprus and Greece.
e changes in the daily levels of fraction time spent at home and total steps were further explored in a
mixed eect model, which included a xed eect term for the level of public health interventions and a random
intercept for each participant. e mixed eect model was adjusted for the eect of age, gender, temperature,
humidity, year, and weekend on mobility. In addition, sine and cosine functions were included to control for
monthly variability in our data. Finally, for each parameter, we used an interaction term to test for dierential
change of mobility across the levels of interventions measures.
All statistical comparisons were performed using STATA 12 (StataCorp, TX) and a p value lower than 0.05
was considered as statistically signicant.
Data availability
A preprint of the manuscript is available under https ://www.resea rchsq uare .co m/a rtic le/rs-37518 /v1. e original
data are available under https ://zenod o.org/recor d/39064 45#.XvUBh G5uI2 w (https ://doi.org/10.5281/zenod
o.39064 45).
Received: 1 July 2020; Accepted: 18 February 2021
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Acknowledgements
We are grateful to all LIFE-MEDEA participants, their families and school teachers for their cooperation.
Author contributions
PK: Conceptualization, Project administration, Methodology, Soware, Data curation, Visualisation, Formal
analysis ,Writing-Original dra preparation; AM: Methodology, Data curation, Visualisation, Formal analysis,
Writing-Original dra preparation; PA: Data curation, Visualisation, Writing-Original dra preparation; EG:
Data curation, Visualisation, Writing—Review & Editing; EM: Data curation, Writing—Review & Editing; HD:
Project administration, Data curation, Writing—Review & Editing; AM: Data curation, Visualisation, Writing—
Review & Editing; PK: Data curation, Visualisation, Writing—Review & Editing; SA: Data curation, Visualisation,
Writing—Review & Editing; HZ: Soware, Writing—Review & Editing; SIP: Conceptualization, Methodology,
Writing—Review & Editing; PK: Conceptualization, Methodology, Soware, Writing—Review & Editing; GKN:
Conceptualization, Methodology; Soware, Formal analysis, Writing—Review & Editing; PKY: Conceptualiza-
tion, Methodology; Writing—Review & Editing, Funding acquisition, Supervision.
Funding
is study was supported by the European Union LIFE Project MEDEA (LIFE16 CCA/CY/000041).
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