Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours
Abstract
:1. Introduction
2. Materials and Methods
2.1. Ethics Statement
2.2. Study Objectives
2.3. Conceptual Framework
2.4. Data Collection
2.5. Questionnaire
2.6. Data Analysis
3. Results
3.1. Sample Characteristics
3.2. Effects of COVID-19 on Mobility Aspirations
3.3. From Mobility Aspirations to Behaviours
4. Discussion
4.1. Policy Implications
4.2. Limitations
4.3. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Total n = 4448 | Greece n = 596 | India n = 803 | Italy n = 653 | Kenya n = 371 | Nigeria n = 322 | Portugal n = 546 | Serbia n = 181 | Spain n = 329 | US n = 647 | |
---|---|---|---|---|---|---|---|---|---|---|
Age median (IQR) | 35.0 (22.0) | 35.0 (16.0) | 31.0 (21.0) | 40.0 (25.0) | 32.0 (13.0) | 28.0 (11.0) | 38.0 (21.0) | 29.0 (9.0) | 42.0 (18.0) | 42.0 (33.0) |
Gender % | ||||||||||
Female | 59.5 | 50.3 | 47.8 | 64.0 | 52.6 | 55.0 | 66.8 | 61.9 | 62.6 | 75.4 |
Male | 40.2 | 49.7 | 51.4 | 35.7 | 46.9 | 45.0 | 33.2 | 38.1 | 37.1 | 24.1 |
Other | 0.3 | 0.0 | 0.8 | 0.3 | 0.5 | 0.0 | 0.0 | 0.0 | 0.3 | 0.5 |
Education % | ||||||||||
None | 1.3 | 0.2 | 3.7 | 0.0 | 6.2 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5 |
Primary | 2.3 | 0.3 | 5.4 | 0.2 | 7.5 | 0.0 | 0.2 | 0.0 | 3.6 | 2.2 |
Lower secondary | 4.5 | 1.5 | 6.8 | 9.5 | 4.3 | 0.0 | 3.5 | 4.4 | 4.9 | 2.2 |
Higher secondary | 24.0 | 22.7 | 19.8 | 38.1 | 15.9 | 26.4 | 25.6 | 33.2 | 12.8 | 21.8 |
Vocational | 9.1 | 7.2 | 11.7 | 9.5 | 11.1 | 2.5 | 8.6 | 8.3 | 19.8 | 4.5 |
University | 58.8 | 68.1 | 52.6 | 42.7 | 55.0 | 71.1 | 62.1 | 54.1 | 58.4 | 68.8 |
Current health status % and number of diseases and health-related gaps mean (SD) | ||||||||||
Very bad | 1.0 | 1.7 | 1.4 | 0.2 | 0.8 | 1.3 | 1.1 | 0.5 | 1.2 | 0.8 |
Bad | 3.1 | 3.2 | 4.5 | 3.2 | 0.5 | 0.9 | 6.2 | 3.9 | 1.8 | 1.7 |
Fair | 20.5 | 15.0 | 21.4 | 21.9 | 22.4 | 14.9 | 29.5 | 23.8 | 20.1 | 16.5 |
Good | 52.5 | 46.0 | 60.4 | 56.5 | 51.2 | 46.9 | 49.3 | 48.6 | 56.8 | 49.8 |
Very good | 22.9 | 34.1 | 12.3 | 18.2 | 25.1 | 36.0 | 13.9 | 23.2 | 20.1 | 31.2 |
Number of diseases a | 0.5 (0.9) | 0.3 (0.9) | 0.5 (0.7) | 0.5 (0.9) | 0.3 (1.0) | 0.3 (0.9) | 0.6 (1.0) | 0.3 (0.7) | 0.5 (1.1) | 0.6 (1.0) |
Health gap b | 0.1 (0.6) | 0.0 (0.6) | 0.1 (0.5) | −0.1 (0.5) | 0.2 (0.6) | 0.2 (0.7) | −0.1 (0.5) | 0.1 (0.6) | 0.0 (0.6) | 0.1 (0.5) |
Healthcare gap c | 0.6 (2.3) | 0.9 (2.5) | 1.0 (2.1) | −0.3 (2.1) | 1.0 (2.1) | 2.7 (3.1) | 0.2 (2.2) | 2.0 (2.7) | 0.0 (1.4) | −0.2 (1.5) |
COVID-19 knowledge mean (SD) and experience % | ||||||||||
Knowledge d | 4.1 (1.1) | 4.5 (0.9) | 2.8 (0.9) | 4.6 (0.7) | 4.0 (0.9) | 3.6 (0.9) | 4.7 (0.7) | 3.8 (1.4) | 4.6 (0.7) | 4.6 (0.7) |
No experience e | 51.8 | 66.3 | 57.4 | 51.1 | 39.3 | 80.4 | 50.9 | 55.2 | 45.9 | 27.8 |
Had experience f | 42.8 | 30.5 | 33.1 | 46.9 | 36.4 | 17.1 | 47.1 | 44.2 | 50.8 | 70.6 |
Missing experience g | 5.4 | 3.2 | 9.5 | 2.0 | 24.3 | 2.5 | 2.0 | 0.6 | 3.3 | 1.6 |
Mobility aspiration in response to COVID-19 % | ||||||||||
Weak | 58.6 | 71.3 | 11.5 | 68.3 | 45.5 | 53.7 | 74.6 | 68.0 | 69.6 | 84.2 |
Moderate | 18.8 | 13.8 | 30.6 | 20.4 | 17.8 | 29.2 | 12.8 | 15.9 | 16.1 | 9.6 |
Strong | 17.2 | 11.7 | 48.4 | 9.3 | 12.4 | 14.6 | 10.6 | 15.5 | 11.0 | 4.6 |
Missing aspiration g | 5.4 | 3.2 | 9.5 | 2.0 | 24.3 | 2.5 | 2.0 | 0.6 | 3.3 | 1.6 |
Moderate Mobility Aspiration | Strong Mobility Aspiration | |||
---|---|---|---|---|
B (SE) | OR | B (SE) | OR | |
Fixed-effects intercept | −0.648 (1.113) | 0.523 | −1.330 (1.115) | 0.264 |
Female | 0.011 (0.094) | 1.012 | −0.010 (0.094) | 0.990 |
Age | 0.001 (0.005) | 1.001 | 0.002 (0.005) | 1.002 |
Lives in a big city | 0.111 (0.094) | 1.117 | 0.061 (0.094) | 1.063 |
Changed residence in 2020 | 0.062 (0.121) | 1.064 | 0.150 (0.120) | 1.161 |
Single and never married | 0.075 (0.116) | 1.078 | 0.012 (0.116) | 1.012 |
Social status: 1st quintile | −0.106 (0.283) | 0.899 | −0.392 (0.282) | 0.675 |
Social status: 2nd quintile | 0.062 (0.231) | 1.064 | −0.136 (0.227) | 0.873 |
Social status: 3rd quintile | −0.026 (0.217) | 0.974 | −0.171 (0.211) | 0.843 |
Social status: 4th quintile | −0.040 (0.222) | 0.961 | −0.065 (0.215) | 0.937 |
Has university education | −0.007 (0.100) | 0.993 | 0.064 (0.100) | 1.066 |
Works 30 or less hours/week | −0.009 (0.137) | 0.991 | −0.010 (0.138) | 0.990 |
Student | 0.068 (0.147) | 1.070 | 0.120 (0.147) | 1.128 |
Houseworker | −0.072 (0.199) | 0.931 | 0.068 (0.195) | 1.070 |
Unemployed | 0.094 (0.174) | 1.098 | 0.160 (0.173) | 1.173 |
Retired | 0.024 (0.216) | 1.025 | −0.009 (0.219) | 0.991 |
Unable to work | 0.095 (0.432) | 1.100 | −0.108 (0.442) | 0.897 |
Possesses land, house, or business | −0.112 (0.103) | 0.894 | −0.111 (0.103) | 0.895 |
Health gap index | 0.013 (0.082) | 1.013 | −0.011 (0.083) | 0.989 |
Diagnosed cancer | 0.088 (0.225) | 1.091 | −0.111 (0.233) | 0.895 |
Diagnosed cardiovascular disease | 0.063 (0.181) | 1.065 | 0.078 (0.180) | 1.081 |
Diagnosed depression | 0.013 (0.126) | 1.013 | 0.040 (0.128) | 1.041 |
Diagnosed diabetes | 0.044 (0.211) | 1.044 | −0.047 (0.211) | 0.954 |
Diagnosed HIV/AIDS | 0.111 (0.551) | 1.118 | 0.067 (0.569) | 1.069 |
Diagnosed kidney disease | −0.048 (0.293) | 0.953 | −0.097 (0.296) | 0.907 |
Diagnosed liver disease | 0.005 (0.319) | 1.005 | 0.141 (0.312) | 1.151 |
Diagnosed lung disease | −0.061 (0.208) | 0.941 | 0.153 (0.206) | 1.165 |
Healthcare gap index | −0.002 (0.021) | 0.998 | 0.037 (0.021) | 1.038 |
COVID-19 knowledge index | 0.310 (0.525) | 1.364 | 0.616 (0.530) | 1.851 |
COVID-19 knowledge index squared | −0.132 (0.0203) | 0.876 | −0.241 (0.204) | 0.786 |
COVID-19 knowledge index cubic | 0.012 (0.023) | 1.013 | 0.024 (0.023) | 1.025 |
Had COVID-19 or has contacts that had COVID-19 | −0.058 (0.094) | 0.944 | 0.046 (0.093) | 1.047 |
The severity of COVID-19 damages on people’s health | 0.009 (0.024) | 1.009 | 0.016 (0.024) | 1.016 |
The severity of COVID-19 damages on people’s finances | −0.052 (0.029) | 0.949 | 0.005 (0.029) | 1.005 |
Respondent’s vulnerability to the health effects of COVID-19 | 0.018 (0.021) | 1.018 | 0.014 (0.021) | 1.014 |
Respondent’s vulnerability to the financial effects of COVID-19 | 0.028 (0.019) | 1.028 | 0.015 (0.019) | 1.015 |
The current area of residence feels like home | −0.187 (0.146) | 0.830 | −0.397 ** [−0.652, −0.143] (0.146) | 0.672 |
Knows healthcare staff in their current area of residence | −0.056 (0.094) | 0.946 | 0.047 (0.095) | 1.048 |
Most of the known people intend to move because of COVID-19 | 0.155 (0.165) | 1.168 | 0.401 * [0.117, 0.685] (0.162) | 1.494 |
Worried for family and friends because of COVID-19 | 0.050 (0.109) | 1.051 | 0.077 (0.109) | 1.080 |
Agrees that they would avoid catching COVID-19 by moving | 0.201 (0.113) | 1.223 | 0.256 * [0.054, 0.457] (0.113) | 1.291 |
Agrees that they would not die of COVID-19 by moving | 0.140 (0.096) | 1.150 | 0.042 (0.096) | 1.043 |
Agrees that moving would maintain pre-pandemic lifestyle | 0.069 (0.102) | 1.071 | 0.024 (0.102) | 1.025 |
Finds moving easy | 0.034 (0.095) | 1.034 | 0.081 (0.096) | 1.084 |
Competent and capable in important activities | −0.179 (0.144) | 0.836 | −0.205 (0.143) | 0.814 |
Moved in the last 10 years at least once without financial difficulties | 0.097 (0.095) | 1.102 | 0.019 (0.095) | 1.019 |
Would live with no family or friends if moved | −0.023 (0.095) | 0.978 | 0.007 (0.095) | 1.007 |
Resides in Greece | 0.056 (1.314) | 1.058 | 0.150 (1.314) | 1.161 |
Resides in India | 0.828 (1.323) | 2.289 | 1.342 (1.323) | 3.828 |
Resides in Italy | 0.310 (1.312) | 1.364 | 0.204 (1.313) | 1.227 |
Resides in Kenya | 0.164 (1.321) | 1.178 | 0.130 (1.322) | 1.139 |
Resides in Nigeria | 0.343 (1.323) | 1.410 | 0.128 (1.324) | 1.136 |
Resides in Portugal | 0.057 (1.313) | 1.059 | 0.133 (1.313) | 1.143 |
Resides in Serbia | 0.027 (1.326) | 1.027 | 0.175 (1.326) | 1.192 |
Resides in Spain | −0.306 (1.320) | 0.736 | −0.204 (1.321) | 0.816 |
Included observations | 4002 | 4002 |
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Testa, D.J.; Nagarwala, Z.A.S.H.; Vale, J.P.; Carrillo, A.E.; Sargent, C.T.; Amollo, S.; Nyamai, M.; Carballo-Leyenda, B.; Onyima, B.N.; Afolabi, I.; et al. Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours. COVID 2024, 4, 261-275. https://doi.org/10.3390/covid4020018
Testa DJ, Nagarwala ZASH, Vale JP, Carrillo AE, Sargent CT, Amollo S, Nyamai M, Carballo-Leyenda B, Onyima BN, Afolabi I, et al. Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours. COVID. 2024; 4(2):261-275. https://doi.org/10.3390/covid4020018
Chicago/Turabian StyleTesta, Davide J., Zaheer A. S. H. Nagarwala, João P. Vale, Andres E. Carrillo, Cagney T. Sargent, Sharon Amollo, Mutono Nyamai, Belén Carballo-Leyenda, Blessing N. Onyima, Ibukun Afolabi, and et al. 2024. "Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours" COVID 4, no. 2: 261-275. https://doi.org/10.3390/covid4020018
APA StyleTesta, D. J., Nagarwala, Z. A. S. H., Vale, J. P., Carrillo, A. E., Sargent, C. T., Amollo, S., Nyamai, M., Carballo-Leyenda, B., Onyima, B. N., Afolabi, I., Mayor, T. S., Hargreaves, S., Marković, M., & Flouris, A. D. (2024). Measuring the Impact of the Coronavirus Disease 2019 Pandemic on Mobility Aspirations and Behaviours. COVID, 4(2), 261-275. https://doi.org/10.3390/covid4020018