Edited by: Roger Hewson, Public Health England, United Kingdom
Reviewed by: Mohammed Alkhaldi, McGill University, Canada; Giuseppe Battaglia, University of Palermo, Italy; Mostafizur Rahman, Jahangirnagar University, Bangladesh
This article was submitted to Infectious Diseases – Surveillance, Prevention and Treatment, a section of the journal Frontiers in Public Health
†These authors have contributed equally to this work
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
On 11 March 2020, the WHO declared COVID-19 to be a pandemic (
According to the Center for Disease Control and Prevention (CDC), quarantine was adopted as an obligatory means to separate and restrict the movement of people who had potentially been exposed to a contagious disease. People also had to follow appropriate infection control measures which included bans on large social gatherings, school closures, the ban of weddings, parties, and funerals, closures of entertainment venues, various restrictions on restaurant dining areas and gyms, such as increasing the distance between tables and gym machines and improving ventilation to prevent the virus droplet transmission. Adding to this, travel restrictions and social distancing measures were introduced during quarantine (
The utility of quarantine is undetermined, and whether or not overusing it can be of any benefit lacks any scientific basis. However, one thing is certain according to a rapid review on how to improve adherence with quarantine: quarantine does not work if people do not adhere to it (
Previous surveys on factors that affect adherence to quarantine in outbreaks were reviewed. Multiple factors were studied to assess their effect on the adherence to quarantine and protective health behaviors such as hand washing, avoiding crowds, and maintaining social distance between individuals. Some of these factors were of direct influence and reflected higher adherence actions, such as knowledge about the infectious disease outbreak and quarantine protocol, the perceived benefits of quarantine, the grasped risks of the disease, and the social norms that pressured others to comply with the quarantine. Other factors were of alternative effects, such as where people got their knowledge of quarantine protocols from, with no difference in adherence rates between those who sourced information from official vs. non-official sources. In addition, practical issues such as financial consequences or employees in insecure jobs who lacked leave entitlement would result in individuals being less likely to comply with social distance measures (
A study in Norway found that adherence to quarantine has been low, especially after the initial surge of infections faded nationwide, which suggests that people are influenced by the perceived infection risk or that the population experiences quarantine fatigue and a wish to return to normality (
Recent studies on the topic of the associated predictors with quarantine and health measure compliance showed that gender, age, geographic area, and employment status, as well as the person's fear for themselves and others to contract COVID-19, were significantly predictive (
There is very limited data that evaluates the possible predictors which could influence the general population's staying home adherence and the understanding of quarantine and lockdown measures during the COVID-19 pandemic in Palestine. This study is dedicated to providing a clear vision regarding the situation by expanding on the limited knowledge about the possible implicated factors in quarantine compliance. Overall, this could allow the decision-makers to constantly monitor and maintain the balance between the implementation of quarantine and public health measures.
The target population comprised every Palestinian who lived in the West Bank, Gaza, or Jerusalem during coronavirus-2 quarantine and who was equal to or more than 18 years old. We adopted a cross-sectional web-based survey design to assess the public's adherence to quarantine and infection control instructions during the lockdown of coronavirus-2 pandemic by using an anonymous online questionnaire. Every person had a number that reflected their order by the time they finished the questionnaire. A snowball sampling technique was used and focused on recruiting any Palestinian who lived in Palestine during the pandemic. The online survey was disseminated on Facebook and Instagram to friends and local pages and they were encouraged to pass it on to others. A mandatory question was added on the first page of the questionnaire regarding current residency. Those who reported living outside Palestine were automatically excluded from the study. We were able to recruit 2,819 participants in this study who completely filled and returned the questionnaire, with an age range between 18 and 71 years old.
After reviewing related factors that affect adherence to quarantine in outbreaks (
As the Palestinian Government recommended the public to minimize face-to-face interaction and isolate themselves at home, the questionnaire was distributed electronically. Participants completed it in Arabic through an online survey. Expedited ethical approval was obtained from the Institutional Review Board (IRB) at An-Najah National University. Privacy was strictly protected during the procedure as we avoided any questions that could expose the identity of respondents. Information and the purpose of the study were posted on the first page of the questionnaire. All respondents provided electronic informed consent before starting the questionnaire. Data collection took place over 10 days (6–16 April 2020) which corresponded to almost the middle interval of the massive quarantine in Palestine where restriction measures were at their highest (22 March to 5 May 2020).
Quarantine understanding outcome reflects the knowledge and information the person has about the pandemic and quarantine regardless of the source. It was initially evaluated through five statements: (1) quarantine is needed where I live, (2) not committing to quarantine will raise the number of cases, (3) measures taken by the government are necessary, (4) quarantine should not only be limited to infected people and those who are in contact with them, and (5) hygiene measures in the house are part of quarantine. A 5-point Likert scale [strongly agree (4), agree (3), neutral (2), disagree (1), and totally disagree (0)] was used to respond to each statement. By summing the points of each statement, a scale from 0 to 20 was created for each respondent. We then used the median as a cutoff point to categorize this outcome into a low level (0–17) and a high level (18–20).
Staying home adherence outcome reflects the compliance of the individual to the main instruction given by the government: “Do not leave the house if it is not necessary.” It was initially evaluated through five statements: (1) going grocery shopping or to the bakery, (2) going out meeting friends or family, (3) going out to spend time and have fun, (4) attending social events, and (5) going to the pharmacy. The answer to each statement is composed of [never going out (3), some days (2), more than half of days (1), and every day (0)].
In-home precautions adherence outcome reflects the compliance to infection control measures while staying inside the home to decrease the spread of infection between family members. It was initially evaluated through five statements: (1) washing your hands for 20 seconds or more, (2) decrease the time of interaction with other family members, (3) washing hands after returning from outside, (4) sneezing appropriately according to guidelines (using a tissue or using elbow), and (5) not sharing towels and items between family members. The answer to each statement is composed of [never do them (0), do them sometimes (1), do them most of the time (2), and always do them (3)].
For these last two outcomes separately, we summed up the points of each statement. A scale from 0 to 15 was created for each respondent. Then the median was used as the cutoff point to categorize staying home adherence outcome to a low level (0–12) and a high level (13–15) while categorizing in-home precautions adherence outcome to a low level (0–10) and a high level (11–15).
The 27th version of IBM SPSS (IBM SPSS Statistics for Windows, Version 27.0. Armonk, NY: IBM Corp) was used for data coding, entry, and analysis. All parts of the analysis were performed by the authors themselves. Descriptive statistics (median, mean, standard deviation, and independent student
Statistically significant variables in bivariate analysis were included in the multivariate logistic regression model developed for each of the study outcomes.
In this study, the questionnaire was introduced to 2,819 individuals, all of whom completed and returned the questionnaire electronically (
Bivariate analysis of socio-demographic characteristics with dependent variables (Staying home adherence; In-home precautions adherence; Quarantine understanding;
18–35 | 2,083(73.9) | 825(39.6) | 1,258(60.4) | 0.106 | 979(47) | 1,104(53) | <0.001 |
897(43.1) | 1,186(56.9) | <0.001 |
36–53 | 624(22.1) | 276(44.2) | 348(55.8) | 247(39.6) | 377(60.4) | 329(52.7) | 295(47.3) | |||
>53 | 112(4) | 43(38.4) | 69(61.6) | 35(31.3) | 77(68.7) | 57(50.9) | 55(49.1) | |||
Male | 768(27.2) | 468(60.9) | 300(39.1) | <0.001 |
377(49.1) | 391(50.9) | 0.04 |
409(53.3) | 359(46.7) | <0.001 |
Female | 2,051(72.8) | 676(33) | 1,375(67) | 884(43.1) | 1,167(56.9) | 874(42.6) | 1,177(57.4) | |||
Single | 1,449(51.4) | 539(37.2) | 910(62.8) | <0.001 |
669(46.2) | 780(53.8) | 0.114 | 593(40.9) | 856(59.1) | <0.001 |
Relationship | 1,370(48.6) | 605(44.2) | 765(55.8) | 592(43.2) | 778(56.8) | 690(50.4) | 680(49.6) | |||
Village | 1,380(49) | 618(44.8) | 762(55.2) | <0.001 |
631(45.7) | 749(54.3) | 0.113 | 657(47.6) | 723(52.4) | 0.01 |
City | 1,292(45.8) | 463(35.8) | 829(64.2) | 576(44.6) | 716(55.4) | 550(42.6) | 742(57.4) | |||
Camp | 147(5.2) | 63(42.9) | 84(57.1) | 54(36.7) | 93(63.3) | 76(51.7) | 71(48.3) | |||
West bank | 2,354(83.5) | 969(41.6) | 1,385(58.4) | 0.03 |
1,060(45) | 1,294(55) | 0.768 | 1,059(45) | 1,295(55) | 0.014 |
Gaza strip | 270(9.6) | 118(43.7) | 152(56.3) | 116(43) | 154(57) | 144(53.3) | 126(46.7) | |||
Jerusalem | 195(6.9) | 57(29.2) | 138(71.8) | 85(43.6) | 110(56.4) | 80(41) | 115(59) | |||
Secondary or less | 326(11.6) | 166(50.9) | 160(49.1) | <0.001 |
151(46.3) | 175(53.7) | 0.068 | 207(63.5) | 119(36.5) | <0.001 |
Collage | 2,211(78.4) | 865(39.1) | 1,346(60.9) | 1,002(45.3) | 1,209(54.7) | 964(43.6) | 1,247(56.4) | |||
Master or doctorate | 282(10) | 113(40.1) | 169(59.9) | 108(38.3) | 174(61.7) | 112(39.7) | 170(60.3) | |||
Yes | 332(11.8) | 131(39.5) | 201(60.5) | 0.657 | 139(41.9) | 193(58.1) | 0.264 | 141(42.5) | 191(57.5) | 0.236 |
No | 2,487(88.2) | 1,013(40.7) | 1,474(59.3) | 1,122(45.1) | 1,365(54.9) | 1,142(45.9) | 1,345(54.1) | |||
<2,000 | 568(20.1) | 240(42.3) | 328(57.7) | 0.512 | 232(40.9) | 336(59.) | 0.032 |
297(52.3) | 271(47.7) | <0.001 |
2,000–5,000 | 1,552(55.1) | 631(40.7) | 921(59.3) | 692(44.6) | 860(55.4) | 706(45.5) | 846(54.5) | |||
>5,000 | 699(24.8) | 273(39.1) | 426(60.9) | 337(48.2) | 362(51.8) | 280(40.1) | 419(59.9) | |||
Yes | 693(24.6) | 350(50.5) | 343(49.5) | <0.001 |
328(47.3) | 365(52.7) | 0.113 | 363(52.4) | 330(47.6) | <0.001 |
No | 2,126(75.4) | 794(37.4) | 1,332(62.6) | 933(43.9) | 1,193(56.1) | 920(43.3) | 1,266(56.7) | |||
Yes | 1,283(45.5) | 539(42) | 744(58) | 0.158 | 536(41.8) | 747(58.2) | 0.004 |
705(55) | 831(45) | 0.653 |
No | 1,536(54.5) | 605(39.4) | 931(60.6) | 725(47.2) | 811(52.8) | 578(37.6) | 705(62.4) |
It was found that 1,144 (40.6%), 1,261 (44.7%), and 1,283 (45.5%) of respondents had low levels of staying home adherence, in-home precautions adherence, and quarantine understanding, respectively.
As shown in
Bivariate analysis of quarantine characteristics with dependent variables (Staying home adherence; In-home precautions adherence; Quarantine understanding;
Yes | 2,763(98) | 1,116(40.4) | 1,647(59.6) | 0.147 | 1,232(44.6) | 1,531(55.4) | 0.248 | 1,238(44.8) | 1,525(55.2) | <0.001 |
No | 56(2) | 28(50) | 28(50) | 29(51.8) | 27(48.2) | 45(80.4) | 11(19.6) | |||
Obliged to stay at home | 2,398(85.1) | 902(37.6) | 1,496(62.4) | <0.001 |
1,046(43.6) | 1,334(56.4) | 0.356 | 1,060(44.2) | 1,338(55.8) | 0.001 |
I have to work outside home | 421(14.9) | 242(57.5) | 179(42.5) | 197(46.8) | 224(35.2) | 223(53) | 198(47) | |||
Yes | 85(3) | 34(40) | 51(60) | 0.912 | 40(47.1) | 45(52.9) | 0.661 | 39(45.9) | 46(54.1) | 0.945 |
No | 2,734(97) | 1,110(40.6) | 1,624(59.4) | 1,221(44.7) | 1,513(55.3) | 1,244(45.5) | 1,490(54.5) | |||
Yes | 2,173(77.1) | 852(39.2) | 1,321(60.8) | 0.006 |
950(43.7) | 1,223(56.3) | 0.047 |
897(41.3) | 1,276(58.7) | <0.001 |
No | 646(22.9) | 292(45.2) | 354(54.8) | 311(48.1) | 335(51.9) | 386(59.8) | 260(40.2) | |||
Yes | 2,262(80.2) | 884(39.1) | 1,378(60.9) | 0.001 |
976(43.2) | 1,286(56.8) | 0.001 |
984(43.5) | 1,278(56.5) | <0.001 |
No | 557(19.8) | 260(46.7) | 279(53.3) | 285(51.2) | 272(48.8) | 299(53.7) | 258(46.3) | |||
Television or radio | 525(18.6) | 219(41.7) | 306(58.3) | 0.027 |
221(42.1) | 304(57.9) | <0.001 |
259(49.3) | 266(50.7) | <0.001 |
Official government agencies | 359(12.7) | 134(37.3) | 225(62.7) | 120(33.4) | 239(66.6) | 132(36.8) | 227(63.2) | |||
A health care worker | 159(5.6) | 67(42.1) | 92(57.9) | 58(36.5) | 101(63.5) | 63(39.6) | 96(60.4) | |||
Social media | 1,676(59.5) | 669(39.9) | 1,007(60.1) | 806(48.1) | 870(51.9) | 770(45.9) | 906(54.1) | |||
Conversation with other people | 100(3.6) | 55(55) | 45(45) | 56(56) | 44(44) | 59(59) | 41(41) | |||
Yes | 1,994(70.7) | 750(37.6) | 1,244(62.4) | <0.001 |
876(43.9) | 1,118(56.1) | 0.184 | 855(42.9) | 1,139(57.1) | <0.001 |
No | 825(29.3) | 394(47.8) | 431(52.2) | 385(46.7) | 440(53.3) | 428(51.9) | 397(48.1) | |||
1–2 weeks | 187(6.6) | 98(52.4) | 89(47.6) | <0.001 |
86(46) | 101(54) | 0.103 | 102(54.5) | 85(45.5) | 0.023 |
2–3 weeks | 847(30.1) | 355(41.9) | 847(58.1) | 357(42.2) | 490(57.8) | 396(46.8) | 847(53.2) | |||
3–4 weeks | 786(27.9) | 331(42.1) | 786(57.9) | 378(48.1) | 408(51.9) | 357(45.4) | 786(54.6) | |||
>4 weeks | 999(35.4) | 360(36) | 639(67) | 440(44) | 559(56) | 428(42.8) | 571(57.2) | |||
<2 h | 584(20.7) | 206(35.3) | 378(64.7) | <0.001 |
261(44.7) | 323(55.3) | 0.851 | 289(49.5) | 295(50.5) | 0.020 |
2–6 h | 776(27.5) | 337(43.4) | 439(56.6) | 356(45.9) | 776(54.1) | 344(44.3) | 432(55.7) | |||
6–10 h | 1,075(38.2) | 415(38.6) | 660(61.4) | 478(44.5) | 1,075(55.5) | 460(42.8) | 615(57.2) | |||
>10 h | 384(13.6) | 186(48.4) | 198(51.6) | 166(43.2) | 384(56.8) | 190(49.5) | 194(50.5) |
However, most people (38.2%) used to spend between 6 and 10 h outside the home before the quarantine. Most respondents (94.1%) correctly identified that quarantine aimed to protect society. Only 52.6% understood that quarantine restrictions aimed to protect members of their household. Nearly 59.4% correctly reported that quarantine would not protect them.
Staying home adherence outcome was found to have statistically significant associations with the following socio-demographic variables [(sex, social status, residency, geographic area, educational level, and smoking);
Regarding in-home precautions adherence outcome, statistically significant associations were found with the following socio-demographics [(age, sex, monthly income, and high-risk group in the home);
On the other side, quarantine understanding outcome was found to be significantly associated with these socio-demographics [(age, sex, social status, residency, geographic area, educational level, monthly income, and smoking);
As shown in
A histogram chart built for the distribution of participants' self-rating of adherence to quarantine among the high and low levels of staying home adherence (
The multivariate logistic regression model for staying home adherence outcome predictors is shown in
Multivariate logistic regression model for factors associated with staying home adherence (
Female | 1.02 | 0.10 | 2.77 | 2.27–3.37 | <0.001 |
Male |
– | – | – | – | – |
Relationship | −0.36 | 0.09 | 0.70 | 0.59–0.83 | <0.001 |
Single |
– | – | – | – | – |
City | 0.32 | 0.09 | 1.37 | 1.16–1.64 | <0.001 |
Camp | 0.27 | 0.19 | 1.31 | 0.90–1.92 | 0.162 |
Village |
– | – | – | – | – |
West bank | −0.34 | 0.17 | 0.71 | 0.51–1.0 | 0.053 |
Gaza | −0.63 | 0.22 | 0.54 | 0.35–0.82 | 0.004 |
Jerusalem |
– | – | – | – | – |
Collage | 0.24 | 0.13 | 1.27 | 0.98–1.64 | 0.070 |
Master or doctorate | 0.41 | 0.18 | 1.51 | 1.06–2.16 | 0.023 |
Secondary or less |
– | – | – | – | – |
Yes | −0.12 | 0.10 | 0.89 | 0.73–1.09 | 0.246 |
No |
– | – | – | – | – |
I am obliged to stay at home | 0.63 | 0.12 | 1.87 | 1.49–2.34 | <0.001 |
My work requires that I stay outdoors |
– | – | – | – | – |
Yes | 0.18 | 0.10 | 1.2 | 0.99–1.45 | 0.063 |
No |
– | – | – | – | – |
Yes | 0.18 | 0.10 | 1.19 | 0.98–1.46 | 0.087 |
No |
– | – | – | – | – |
Official government agencies | 0.32 | 0.15 | 1.38 | 1.03–1.86 | 0.031 |
A health care worker | 0.02 | 0.20 | 0.02 | 0.70–1.51 | 0.903 |
Social media | 0.09 | 0.11 | 1.09 | 0.89–1.35 | 0.405 |
Conversations with other people | −0.31 | 0.24 | 0.74 | 0.46–1.17 | 0.193 |
Television or radio |
– | – | – | – | – |
Yes | 0.21 | 0.09 | 1.23 | 1.03–1.47 | 0.023 |
No |
– | – | – | – | – |
2–3 Weeks | 0.23 | 0.17 | 1.26 | 0.90–1.77 | 0.186 |
3–4 Weeks | 0.15 | 0.18 | 1.16 | 0.82–1.63 | 0.407 |
>4 Weeks | 0.30 | 0.17 | 1.35 | 0.97–1.90 | 0.080 |
1–2 Weeks |
– | – | – | – | – |
<2 h | 0.27 | 0.15 | 1.32 | 0.99–1.76 | 0.063 |
2–6 h | −0.13 | 0.14 | 0.88 | 0.67–1.15 | 0.338 |
6–10 h | 0.11 | 0.13 | 1.11 | 0.86–1.44 | 0.421 |
>10 h |
– | – | – | – | – |
In-home precautions adherence model shown in
Multivariate logistic regression model for factors associated with in-home precautions adherence (
Female | 0.30 | 0.09 | 1.35 | 1.14–1.61 | 0.001 |
Male |
– | – | – | – | – |
36–53 | 0.32 | 0.10 | 1.37 | 1.14–1.66 | 0.001 |
54–71 | 0.77 | 0.22 | 2.17 | 1.42–3.30 | <0.001 |
18–35 |
– | – | – | – | – |
2,000–5,000 | −0.19 | 0.10 | 0.83 | 0.68–1.01 | 0.066 |
>5,000 | −0.33 | 0.12 | 0.72 | 0.57–0.90 | 0.005 |
<2,000 |
– | – | – | – | – |
Yes | 0.21 | 0.08 | 1.23 | 1.06–1.43 | 0.008 |
No |
– | – | – | – | – |
Yes | 0.14 | 0.09 | 1.15 | 0.96–1.38 | 0.120 |
No |
– | – | – | – | – |
Yes | 0.21 | 0.10 | 1.23 | 1.01–1.49 | 0.036 |
No |
– | – | – | – | – |
Official government agencies | 0.46 | 0.15 | 1.58 | 1.19–2.10 | 0.002 |
A health care worker | 0.33 | 0.19 | 1.40 | 0.96–2.03 | 0.080 |
Social media | −0.19 | 0.10 | 0.83 | 0.68–1.02 | 0.070 |
Conversations with other people | −0.36 | 0.23 | 0.70 | 0.45–1.09 | 0.113 |
Television or radio |
– | – | – | – | – |
Furthermore, female sex, having a high-risk group in the home, and considering official government agencies as a source of information were significantly associated with a higher level of in-home precautions adherence [OR (95%CI) = 1.35 (1.14–1.61), 1.23 (1.06–1.43), and 1.58 (1.19–2.10); respectively]. Being properly informed about quarantine was also a significant positive predictor. On the other hand, higher monthly income (>5,000 Shekels) was inversely related to in-home precautions adherence [OR (95%CI) = 0.72 (0.57–0.90)].
The multivariate logistic regression model for quarantine understanding outcome predictors is shown in
Multivariate logistic regression model for factors associated with quarantine understanding (
Female | 0.26 | 0.10 | 1.29 | 1.06–1.58 | 0.012 |
Male |
– | – | – | – | – |
36–53 | −0.30 | 0.11 | 0.74 | 0.60–0.93 | 0.008 |
54–71 | −0.05 | 0.22 | 0.95 | 0.62–1.45 | 0.817 |
18–35 |
– | – | – | – | – |
Relationship | −0.35 | 0.10 | 0.71 | 0.59–0.85 | <0.001 |
Single |
– | – | – | – | – |
City | 0.19 | 0.09 | 1.21 | 1.02–1.44 | 0.025 |
Camp | −0.00 | 0.19 | 0.10 | 0.69–1.45 | 0.984 |
Village |
– | – | – | – | – |
West bank | 0.03 | 0.16 | 1.03 | 0.75–1.42 | 0.858 |
Gaza | −0.45 | 0.21 | 0.64 | 0.42–0.97 | 0.035 |
Jerusalem |
– | – | – | – | – |
Collage | 0.53 | 0.13 | 1.69 | 1.30–2.19 | <0.001 |
Master or doctorate | 0.83 | 0.18 | 2.29 | 1.60–3.27 | <0.001 |
Secondary or less |
– | – | – | – | – |
2,000–5,000 | 0.16 | 0.11 | 1.17 | 0.95–1.45 | 0.146 |
>5,000 | 0.27 | 0.13 | 1.31 | 1.01–1.69 | 0.041 |
<2,000 |
– | – | – | – | – |
Yes | −0.23 | 0.10 | 0.80 | 0.66–0.97 | 0.025 |
No |
– | – | – | – | – |
Yes | 1.28 | 0.36 | 3.61 | 1.79–7.25 | <0.001 |
No |
– | – | – | – | – |
I am obliged to stay at home | 0.28 | 0.11 | 1.33 | 1.06–1.66 | 0.012 |
My work requires that I stay outdoors |
– | – | – | – | – |
Yes | 0.71 | 0.10 | 2.03 | 1.68–2.45 | <0.001 |
No |
– | – | – | – | – |
Yes | 0.28 | 0.10 | 1.32 | 1.08–1.62 | 0.007 |
No |
– | – | – | – | – |
Official government agencies | 0.50 | 0.15 | 1.64 | 1.23–2.20 | 0.001 |
A health care worker | 0.36 | 0.20 | 1.44 | 0.98–2.11 | 0.061 |
Social media | 0.12 | 0.11 | 1.12 | 0.91–1.38 | 0.276 |
Conversations with other people | −0.30 | 0.24 | 0.74 | 0.46–1.17 | 0.200 |
Television or radio |
– | – | – | – | – |
Yes | 0.09 | 0.09 | 1.10 | 0.92–1.32 | 0.309 |
No |
– | – | – | – | – |
2–3 Weeks | 0.19 | 0.17 | 1.20 | 0.86–1.68 | 0.279 |
3–4 Weeks | 0.20 | 0.17 | 1.22 | 0.87–1.71 | 0.240 |
>4 Weeks | 0.23 | 0.17 | 1.26 | 0.91–1.76 | 0.169 |
1–2 Weeks |
– | – | – | – | – |
<2 h | −0.04 | 0.14 | 0.96 | 0.73–1.28 | 0.785 |
2–6 h | 0.10 | 0.14 | 1.10 | 0.84–1.44 | 0.488 |
6–10 h | 0.11 | 0.13 | 1.12 | 0.87–1.44 | 0.378 |
>10 h |
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The present study aimed to assess staying home adherence, in-home precautions adherence, and quarantine understanding among Palestinian society during the COVID-19 pandemic lockdown.
Females, city residents, those with a higher level of education, those obliged to stay at home as a type of quarantine, and those considering official government agencies as a source of information were associated with a higher level of staying home adherence and quarantine understanding. This could be explained by the cultural background of Palestinian society where males usually spend more time working outside the home. In our study, 47% of females and 64.4% of males reported more than 6 h on average outside the home before the quarantine. Police forces are usually more distributed in city centers compared to villages, and cities are usually more crowded; therefore the risk of COVID-19 is higher. On one hand, higher educated-people understand the risk of transmission and infection more which could affect their understanding and adherence compared to less-educated individuals. On the other hand, higher-educated people usually have jobs that can be performed from the home through online applications, whereas less-educated people usually have craft jobs that require them to leave the home. In a study in Israel during the same pandemic, it was noted that the compliance rate to self-isolation was affected by loss of income, as the compliance rate dropped from 94 to 57% when income was not compensated through the government (
Having an adequate food supply in the home was associated with a higher level of staying home adherence. It is reasonable that those who secure their food resources before the quarantine can avoid leaving the home easily in contrast to others who will be worried about protect their family from starving. However, monthly income (>5,000 Shekels), fear of getting COVID-19 or transmitting it, and being properly informed about quarantine were associated with a high-level of quarantine understanding. These again reinforce the importance of proper delivery of information to the public and the underlying fears from COVID-19 transmission and infection rate. An Australian study during the H1N1 pandemic reported that people who understand quarantine were more compliant with it compared to people who reported inadequacy of information (
However, being in a relationship (engaged or married) was inversely related to a higher level of both staying home adherence and quarantine understanding. This may be in part due to more responsibilities toward household members to supply the home with what is needed during the quarantine. On the other side, anxiety and stress might play a role in this due to over-stress between family members during the quarantine. Therefore, going out could be an opportunity to relax and to avoid more stress. Smoking (cigarette or Shisha) was inversely associated with quarantine understanding. Cigarette/Shisha smokers usually seek meeting friends more than nonsmokers. They are usually stressed and might not be able to handle and understand quarantine intentionally due to their carelessness and under-estimation of the risk. Moreover, the effect of financial status on their ability of smoking due to job loss may make them more stressed.
The elderly and those with a high-risk group living with them were more likely to have higher in-home precautions adherence. It is worth mentioning that the elderly are usually considered a high-risk group if infected with COVID-19, and by the time of the study, the only two deaths from COVID-19 in Palestine were two elderly patients with co-morbidities (
It should be noted that only two factors (females and those who consider official government agencies as a source of information) were significantly associated with a higher level of the three study outcomes. Average hours spent outside of the home before quarantine and duration of quarantine did not affect any of the study outcomes. This is in accordance with other studies during the H1N1 pandemic in Australia (
This study could have some limitations. Selection bias could have occurred due to the sampling technique. Due to social distancing during quarantine, we disseminated the survey on social media, and this might in part exclude people who do not have access to the internet and social media, and also limit access to children and the elderly. Any participant who was younger than 18-years-old was excluded. Furthermore, only 4% of the participants were older than 53 years old. However, according to Index Mundi, only 8% of the Palestinian population were older than 55 years old, and around 36% of the population were younger than 15 years in 2020 (
It was seen that major effects depend mainly on the socio-economic and financial status of the general population and the coordination between the major information resources (official government), social media, and the press. Hence, addressing such factors could enable the country to achieve higher adherence rates that can effectively decrease the spread of infection. It is important for policymakers to reach out to the community by every possible means during the lockdown to prevent the spread of false news, enhance their understanding, and update them with new measures. Policymakers' clear communication with the people is crucial for their reassurance, as such communication minimizes their fears of the unknown future. As financial status has a great role in the level of adherence, compensation of income loss and giving access to online jobs may decrease the burden of these lockdown measures on the population and ensure higher compliance.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by IRB of An-Najah National University. The ethics committee waived the requirement of written informed consent for participation.
HA, NY, TA, and MH-Y designed study protocol and drafting the manuscript. HA coordinated the study protocol and conducted the statistical analysis. NY, TA, and MH-Y collected the data. All authors read and approved the final manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MA declared a shared affiliation with the authors to the handling editor at time of review.
We are grateful to all participants in this study for the time they devoted and their understanding.