Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Study Area
2.3. Population
2.4. Study Design
2.5. Biological Analysis
2.6. Outcomes and Data Analysis
2.6.1. Socio-Demographic Factors and Living Areas
2.6.2. Relation between Mobility at the Individual Scale and Infection with SARS-CoV-2
2.6.3. Life Paths: Mobility at the Housing Scale
2.6.4. Mobility and Spatial Epidemiology at the Neighborhood Scale
2.7. Ethical Approval
3. Results
3.1. Socio-Demographic Factors and Living Areas
3.2. Relation between Mobility at the Individual Scale and Infection with SARS-CoV-2
3.3. Life Paths: Mobility at the Housing Scale
3.4. Mobility and Spatial Epidemiology at the Neighborhood Scale
4. Discussion
Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Variable. | CS1 | CS2 | |
---|---|---|---|
mdv.Isolated.adult | 0.318020814614317 | −0.138686155266092 | Household status: Isolated adult |
mdv.Family | −0.596581877218025 * | 0.268218556893136 | Household status: Family |
mdv.Isolated.parent | 0.371420323213889 | −0.189431086881132 | Household status: Isolated parent |
econ.No | 0.329645002280672 | −0.03784583794277 | Problems of economic resources during the period of health crisis: No |
econ.Yes | −0.118334103382805 | 0.0135856854153533 | Problems of economic resources during the period of health crisis: Yes |
comorb | 0.0601445363544964 | 0.143583595180596 | Number of Comorbidity |
age | 0.141722722286938 | 0.199677009063853 | Age in years |
count.France | 0.657142200949126 * | 0.565684402668609 * | Person’s country of birth: France |
count.UE | −0.461402761339287 | 0.565496784946139 | Person’s country of birth: country of European Union |
count.Europe.no.UE | 0.227542076216351 * | 0.227542076216351 | Person’s country of birth: country of Europe, not in European Union |
count.North.Africa | 0.30389661463267 | −0.445676499984632 | Person’s country of birth: country of North Africa |
count.Sub.Saharan Southern.Africa | −0.00692548059787189 | −0.693042068909341 * | Person’s country of birth: country of Sub−Saharan or Southern African countries |
count.Middle.East | 0.182154429482761 | −0.579650734253128 * | Person’s country of birth: country of Middle East |
count.Russia | −0.000515391122827311 | 0.063809437909346 | Person’s country of birth: Russia |
count.North.America | 0.194660784564911 | −0.989836831994614 * | Person’s country of birth: country of North America |
count.South.America | 0.0640708015214596 | −0.710434782575241 * | Person’s country of birth: country of South America |
sexe.Male | 0.193604145684412 | −0.0016711647920521 | Sex: Male |
sexe.Female | −0.457889169952026 | 0.00395243736533019 | Sex: Female |
finan.Yes | 0.050688018372308 | 0.172342681477751 | Financial resources: Yes |
finan.No | −0.101735526236618 | −0.34590765147662 | Financial resources: No |
educa.None | −0.273718530606828 | 0.103928647366441 | Education attainment: None |
educa.Lower.secondary | 0.415103314713079 | 0.0182723622263325 | Education attainment: Lower secondary |
educa.Upper.secondary | 0.138676787874378 | −0.285382577809815 | Education attainment: Upper secondary |
ealth.Yes | 0.0730428304542106 | 0.0286390463874196 | Health insurance: Yes |
ealth.No | −0.27363806632846 | −0.107289561839437 | Health insurance: No |
Tobac.No | −0.175282864892875 | −0.464552790157363 | Tobacco consumption: No |
Tobac.Yes | 0.128891492738417 | 0.341601574208484 | Tobacco consumption: Yes |
Alcool_D | 0.2129663952661 | 0.310894858612279 | Alcohol consumption in number of standard glasses per day |
drug.No | −0.120115203696184 | −0.119479595798671 | Drug consumption: No |
drug.Yes | 0.491030952710004 * | 0.488432587624964 | Drug consumption: Yes |
home.0 | −0.204960195548446 | −0.210235966368546 | Total length of homelessness: Less than 3 months |
home.1 | 0.226974290324227 | −0.351706113500525 | Total length of homelessness: Less than 1 year |
home.3 | 0.0607296491464919 | −0.191823511717764 | Total length of homelessness: 1 to 5 years |
home.6 | −0.158247979029243 | 0.4797275092935 | Total length of homelessness: More than 5 years |
ETHOS.1 | 0.377426671611134 | 0.538257285433284 | Housing situation: ETHOS 1 |
ETHOS.2 | 0.294737185619723 | −0.414156583347008 | Housing situation: ETHOS 2 |
ETHOS.8 | −0.527713370478378 * | 0.20237575177422 | Housing situation: ETHOS 8 |
ETHOS.3 | 0.354022532005372 | −0.0113341020402295 | Housing situation: ETHOS 3 |
Appendix B
Neighborhood | Neighborhood Number | District | Number of Tests | Number of Positive Tests | Prevalence | SatScan Cluster |
---|---|---|---|---|---|---|
Arenc | 1 | 2 | 17 | 0 | 0.000 | 1 |
Baille | 2 | 5 | 1 | 0 | 0.000 | |
Belle de Mai | 3 | 3 | 20 | 1 | 0.050 | 1 |
Belsunce | 4 | 1 | 8 | 0 | 0.000 | |
Bompard | 5 | 7 | 0 | 0 | ||
Bon-Secours | 6 | 14 | 24 | 1 | 0.042 | 1 |
Bonneveine | 7 | 8 | 0 | 0 | ||
Carpiagne | 8 | 9 | 0 | 0 | ||
Castellane | 9 | 6 | 2 | 1 | 0.500 | |
Chapitre | 10 | 1 | 1 | 0 | 0.000 | |
Chateau-Gombert | 11 | 13 | 0 | 0 | ||
Chutes-Lavie | 12 | 4 | 0 | 0 | 1 | |
Cinq-Avenues | 13 | 4 | 0 | 0 | ||
Endoume | 14 | 7 | 0 | 0 | ||
Éoures | 15 | 11 | 0 | 0 | ||
Grands-Carmes | 16 | 2 | 0 | 0 | ||
Hôtel-de-Ville | 17 | 2 | 2 | 0 | 0.000 | |
La Barasse | 18 | 11 | 0 | 0 | ||
La Blancarde | 19 | 4 | 19 | 0 | 0.000 | |
La Cabucelle | 20 | 15 | 0 | 0 | 1 | |
La Calade | 21 | 15 | 0 | 0 | 1 | |
La Capelette | 22 | 10 | 0 | 0 | ||
La Conception | 23 | 5 | 0 | 0 | ||
La Croix-Rouge | 24 | 13 | 0 | 0 | ||
La Delorme | 25 | 15 | 0 | 0 | 1 | |
La Fourragere | 26 | 12 | 0 | 0 | ||
La Joliette | 27 | 2 | 30 | 1 | 0.033 | |
La Milliere | 28 | 11 | 0 | 0 | ||
La Panouse | 29 | 9 | 0 | 0 | ||
La Plage | 30 | 8 | 0 | 0 | ||
La Pomme | 31 | 11 | 6 | 0 | 0.000 | |
La Rose | 32 | 13 | 17 | 0 | 0.000 | |
La Timone | 33 | 10 | 1 | 0 | 0.000 | |
La Treille | 34 | 11 | 0 | 0 | ||
La Valbarelle | 35 | 11 | 0 | 0 | ||
La Valentine | 36 | 11 | 40 | 0 | 0.000 | |
La Villette | 37 | 3 | 0 | 0 | 1 | |
La Viste | 38 | 15 | 0 | 0 | 1 | |
Le Cabot | 39 | 9 | 0 | 0 | ||
Le Camas | 40 | 5 | 0 | 0 | ||
Le Canet | 41 | 14 | 2 | 0 | 0.000 | 1 |
Le Merlan | 42 | 14 | 0 | 0 | ||
Le Pharo | 43 | 7 | 0 | 0 | ||
Le Redon | 44 | 9 | 0 | 0 | ||
Le Rouet | 45 | 8 | 1 | 0 | 0.000 | |
Les Accates | 46 | 11 | 0 | 0 | ||
Les Arnavaux | 47 | 14 | 0 | 0 | 1 | |
Les Aygalades | 48 | 15 | 2 | 0 | 0.000 | |
Les Baumettes | 49 | 9 | 0 | 0 | ||
Les Borels | 50 | 15 | 0 | 0 | ||
Les Caillols | 51 | 12 | 0 | 0 | ||
Les Camoins | 52 | 11 | 0 | 0 | ||
Les Chartreux | 53 | 4 | 0 | 0 | ||
Les Crottes | 54 | 15 | 39 | 1 | 0.026 | 1 |
Les Goudes | 55 | 8 | 0 | 0 | ||
Les Médecins | 56 | 13 | 0 | 0 | ||
Les Mourets | 57 | 13 | 0 | 0 | ||
Les Olives | 58 | 13 | 6 | 0 | 0.000 | |
Les Riaux | 59 | 16 | 0 | 0 | ||
Les Trois-Lucs | 60 | 12 | 0 | 0 | ||
L’Estaque | 61 | 16 | 1 | 0 | 0.000 | |
Lodi | 62 | 6 | 0 | 0 | ||
Malpasse | 63 | 13 | 0 | 0 | 1 | |
Mazargues | 64 | 9 | 0 | 0 | ||
Menpenti | 65 | 10 | 0 | 0 | ||
Montolivet | 66 | 12 | 3 | 0 | 0.000 | |
Montredon | 67 | 8 | 2 | 0 | 0.000 | |
Noailles | 68 | 1 | 8 | 0 | 0.000 | |
Notre-Dame-du-Mont | 69 | 6 | 10 | 0 | 0.000 | |
Notre-Dame-Limite | 70 | 15 | 0 | 0 | ||
Opéra | 71 | 1 | 3 | 0 | 0.000 | |
Palais-de-Justice | 72 | 6 | 0 | 0 | ||
Palama | 73 | 13 | 0 | 0 | ||
Périer | 74 | 8 | 0 | 0 | ||
Pointe-Rouge | 75 | 8 | 1 | 0 | 0.000 | |
Pont-de-Vivaux | 76 | 10 | 0 | 0 | ||
Préfecture | 77 | 6 | 2 | 0 | 0.000 | |
Roucas-Blanc | 78 | 7 | 0 | 0 | ||
Saint-Andre | 79 | 16 | 2 | 1 | 0.500 | 1 |
Saint-Antoine | 80 | 15 | 5 | 0 | 0.000 | |
Saint-Barnabé | 81 | 12 | 0 | 0 | ||
Saint-Barthélemy | 82 | 14 | 0 | 0 | 1 | |
Saint-Charles | 83 | 1 | 10 | 0 | 0.000 | |
Saint-Giniez | 84 | 8 | 3 | 0 | 0.000 | |
Saint-Henri | 85 | 16 | 0 | 0 | ||
Saint-Jean-du-Désert | 86 | 12 | 0 | 0 | ||
Saint-Jérôme | 87 | 13 | 0 | 0 | 1 | |
Saint-Joseph | 88 | 14 | 0 | 0 | 1 | |
Saint-Julien | 89 | 12 | 0 | 0 | ||
Saint-Just | 90 | 13 | 5 | 1 | 0.200 | 1 |
Saint-Lambert | 91 | 7 | 0 | 0 | ||
Saint-Lazare | 92 | 3 | 6 | 1 | 0.167 | 1 |
Saint-Louis | 93 | 15 | 16 | 1 | 0.063 | 1 |
Saint-Loup | 94 | 10 | 0 | 0 | ||
Saint-Marcel | 95 | 11 | 0 | 0 | ||
Saint-Mauront | 96 | 3 | 36 | 1 | 0.028 | 1 |
Saint-Menet | 97 | 11 | 7 | 0 | 0.000 | |
Saint-Mitre | 98 | 13 | 0 | 0 | ||
Saint-Pierre | 99 | 5 | 2 | 0 | 0.000 | |
Saint-Tronc | 100 | 10 | 0 | 0 | ||
Saint-Victor | 101 | 7 | 0 | 0 | ||
Sainte-Anne | 102 | 8 | 0 | 0 | ||
Sainte-Marguerite | 103 | 9 | 0 | 0 | ||
Sainte-Marthe | 104 | 14 | 1 | 0 | 0.000 | 1 |
Sormiou | 105 | 9 | 0 | 0 | ||
Thiers | 106 | 1 | 16 | 0 | 0.000 | |
Vauban | 107 | 6 | 0 | 0 | ||
Vaufrèges | 108 | 9 | 0 | 0 | ||
Verduron | 109 | 15 | 0 | 0 | ||
Vieille-Chapelle | 110 | 8 | 0 | 0 |
Neighborhood | Neighborhood Number | District | Number of Tests | Positif Test Number | Prevalence | SatScan Cluster |
---|---|---|---|---|---|---|
Arenc | 1 | 2 | 13 | 2 | 0.154 | |
Baille | 2 | 5 | 0 | 0 | 2 | |
Belle de Mai | 3 | 3 | 16 | 2 | 0.125 | |
Belsunce | 4 | 1 | 39 | 2 | 0.051 | |
Bompard | 5 | 7 | 0 | 0 | 1 | |
Bon-Secours | 6 | 14 | 33 | 2 | 0.061 | |
Bonneveine | 7 | 8 | 0 | 0 | ||
Carpiagne | 8 | 9 | 0 | 0 | ||
Castellane | 9 | 6 | 0 | 0 | ||
Chapitre | 10 | 1 | 35 | 3 | 0.086 | |
Château-Gombert | 11 | 13 | 0 | 0 | ||
Chutes-Lavie | 12 | 4 | 0 | 0 | ||
Cinq-Avenues | 13 | 4 | 4 | 1 | 0.250 | 2 |
Endoume | 14 | 7 | 0 | 0 | 1 | |
Éoures | 15 | 11 | 0 | 0 | ||
Grands-Carmes | 16 | 2 | 0 | 0 | ||
Hôtel-de-Ville | 17 | 2 | 1 | 1 | 1.000 | 1 |
La Barasse | 18 | 11 | 0 | 0 | ||
La Blancarde | 19 | 4 | 0 | 0 | 2 | |
La Cabucelle | 20 | 15 | 0 | 0 | ||
La Calade | 21 | 15 | 17 | 1 | 0.059 | |
La Capelette | 22 | 10 | 1 | 1 | 1.000 | 2 |
La Conception | 23 | 5 | 0 | 0 | 2 | |
La Croix-Rouge | 24 | 13 | 0 | 0 | ||
La Delorme | 25 | 15 | 0 | 0 | ||
La Fourragère | 26 | 12 | 0 | 0 | 2 | |
La Joliette | 27 | 2 | 75 | 3 | 0.040 | |
La Millière | 28 | 11 | 0 | 0 | ||
La Panouse | 29 | 9 | 0 | 0 | ||
La Plage | 30 | 8 | 0 | 0 | ||
La Pomme | 31 | 11 | 2 | 1 | 0.500 | 2 |
La Rose | 32 | 13 | 23 | 2 | 0.087 | |
La Timone | 33 | 10 | 0 | 0 | 2 | |
La Treille | 34 | 11 | 0 | 0 | ||
La Valbarelle | 35 | 11 | 0 | 0 | ||
La Valentine | 36 | 11 | 30 | 2 | 0.067 | |
La Villette | 37 | 3 | 5 | 2 | 0.400 | 3 |
La Viste | 38 | 15 | 0 | 0 | 3 | |
Le Cabot | 39 | 9 | 0 | 0 | ||
Le Camas | 40 | 5 | 1 | 1 | 1.000 | 2 |
Le Canet | 41 | 14 | 2 | 1 | 0.500 | |
Le Merlan | 42 | 14 | 0 | 0 | ||
Le Pharo | 43 | 7 | 1 | 1 | 1.000 | 1 |
Le Redon | 44 | 9 | 0 | 0 | ||
Le Rouet | 45 | 8 | 10 | 1 | 0.100 | |
Les Accates | 46 | 11 | 0 | 0 | ||
Les Arnavaux | 47 | 14 | 0 | 0 | ||
Les Aygalades | 48 | 15 | 0 | 0 | 3 | |
Les Baumettes | 49 | 9 | 0 | 0 | ||
Les Borels | 50 | 15 | 2 | 1 | 0.500 | 3 |
Les Caillols | 51 | 12 | 0 | 0 | 2 | |
Les Camoins | 52 | 11 | 0 | 0 | ||
Les Chartreux | 53 | 4 | 2 | 1 | 0.500 | 2 |
Les Crottes | 54 | 15 | 62 | 2 | 0.032 | |
Les Goudes | 55 | 8 | 0 | 0 | ||
Les Médecins | 56 | 13 | 0 | 0 | ||
Les Mourets | 57 | 13 | 0 | 0 | ||
Les Olives | 58 | 13 | 19 | 3 | 0.158 | |
Les Riaux | 59 | 16 | 0 | 0 | ||
Les Trois-Lucs | 60 | 12 | 0 | 0 | ||
L’Estaque | 61 | 16 | 32 | 2 | 0.063 | |
Lodi | 62 | 6 | 0 | 0 | ||
Malpasse | 63 | 13 | 0 | 0 | ||
Mazargues | 64 | 9 | 0 | 0 | ||
Menpenti | 65 | 10 | 0 | 0 | ||
Montolivet | 66 | 12 | 6 | 2 | 0.333 | 2 |
Montredon | 67 | 8 | 0 | 0 | ||
Noailles | 68 | 1 | 13 | 2 | 0.154 | |
Notre-Dame-du-Mont | 69 | 6 | 21 | 2 | 0.095 | |
Notre-Dame-Limite | 70 | 15 | 0 | 0 | ||
Opéra | 71 | 1 | 2 | 1 | 0.500 | |
Palais-de-Justice | 72 | 6 | 0 | 0 | ||
Palama | 73 | 13 | 0 | 0 | ||
Périer | 74 | 8 | 0 | 0 | ||
Pointe-Rouge | 75 | 8 | 0 | 0 | ||
Pont-de-Vivaux | 76 | 10 | 0 | 0 | 2 | |
Préfecture | 77 | 6 | 8 | 2 | 0.250 | |
Roucas-Blanc | 78 | 7 | 0 | 0 | ||
Saint-Andre | 79 | 16 | 11 | 3 | 0.273 | 3 |
Saint-Antoine | 80 | 15 | 2 | 1 | 0.500 | 3 |
Saint-Barnabé | 81 | 12 | 0 | 0 | 2 | |
Saint-Barthélemy | 82 | 14 | 6 | 1 | 0.167 | |
Saint-Charles | 83 | 1 | 42 | 3 | 0.071 | |
Saint-Giniez | 84 | 8 | 0 | 0 | ||
Saint-Henri | 85 | 16 | 1 | 1 | 1.000 | 3 |
Saint-Jean-du-Désert | 86 | 12 | 0 | 0 | 2 | |
Saint-Jérôme | 87 | 13 | 16 | 2 | 0.125 | |
Saint-Joseph | 88 | 14 | 0 | 0 | ||
Saint-Julien | 89 | 12 | 0 | 0 | ||
Saint-Just | 90 | 13 | 12 | 2 | 0.167 | |
Saint-Lambert | 91 | 7 | 2 | 2 | 1.000 | 1 |
Saint-Lazare | 92 | 3 | 15 | 2 | 0.133 | |
Saint-Louis | 93 | 15 | 4 | 2 | 0.500 | |
Saint-Loup | 94 | 10 | 0 | 0 | ||
Saint-Marcel | 95 | 11 | 0 | 0 | ||
Saint-Mauront | 96 | 3 | 85 | 2 | 0.024 | |
Saint-Menet | 97 | 11 | 39 | 2 | 0.051 | |
Saint-Mitre | 98 | 13 | 0 | 0 | ||
Saint-Pierre | 99 | 5 | 2 | 1 | 0.500 | 2 |
Saint-Tronc | 100 | 10 | 0 | 0 | ||
Saint-Victor | 101 | 7 | 1 | 1 | 1.000 | 1 |
Sainte-Anne | 102 | 8 | 0 | 0 | ||
Sainte-Marguerite | 103 | 9 | 0 | 0 | ||
Sainte-Marthe | 104 | 14 | 0 | 0 | ||
Sormiou | 105 | 9 | 0 | 0 | ||
Thiers | 106 | 1 | 8 | 1 | 0.125 | |
Vauban | 107 | 6 | 0 | 0 | ||
Vaufrèges | 108 | 9 | 0 | 0 | ||
Verduron | 109 | 15 | 0 | 0 | 3 | |
Vieille-Chapelle | 110 | 8 | 0 | 0 |
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Sociodemographic Characteristics | n (%) or Mean (SE) | |
---|---|---|
Gender | ||
Men | 894 | (70.29%) |
Women | 378 | (29.71%) |
Age (years) | 40.06 | (0.40) |
Household status | ||
Isolated adult | 672 | (52.83%) |
Family | 416 | (32.70%) |
Isolated parent | 130 | (10.22%) |
Missing | 54 | (4.25%) |
Financial resources | ||
No | 400 | (31.45%) |
Yes | 794 | (62.42%) |
Missing | 78 | (6.13%) |
Problems of economic resources during the period of health crisis | ||
No | 321 | (25.24%) |
Yes | 883 | (69.42%) |
Missing | 68 | (5.35%) |
Country of Birth 1 | ||
France | 236 | (18.55%) |
European Union | 199 | (15.64%) |
Europe, non-European Union | 212 | (16.67%) |
North Africa | 282 | (22.17%) |
Sub-Saharan/Southern Africa | 213 | (16.75%) |
Middle East | 15 | (1.18%) |
Russia | 31 | (2.44%) |
North America | 2 | (0.16%) |
South America | 17 | (1.34%) |
Missing | 65 | (5.11%) |
Education attainment | ||
No educational achievement | 607 | (47.72%) |
Lower secondary | 329 | (25.86%) |
Upper secondary or vocational | 246 | (19.34%) |
Missing | 90 | (7.08%) |
Health insurance | ||
No | 247 | (19.42%) |
Yes | 952 | (79.84%) |
Missing | 73 | (5.74%) |
Living Conditions | n (%) or Mean (SE) | |
Total length of homelessness | ||
<3 months | 90 | (7.08%) |
3 to 12 months | 240 | (18.87%) |
1 to 5 years | 452 | (35.53%) |
>5 years | 397 | (31.21%) |
Missing | 93 | (7.31%) |
ETHOS 2 Typology at baseline | ||
ETHOS 1: street | 166 | (13.05%) |
ETHOS 2: emergency shelters and hotel rooms | 447 | (35.14%) |
ETHOS 3: transitional shelters | 172 | (13.52%) |
ETHOS 8: squats, slums | 485 | (38.13%) |
Missing | 2 | (0.16%) |
Health Characteristics | n (%) or Mean (SE) | |
Tobacco consumption | ||
No | 486 | (38.21%) |
Yes | 655 | (51.49%) |
Missing | 131 | (10.3%) |
Alcohol consumption (glasses per day) | 0.48 | (0.03) |
Substance consumption | ||
No | 903 | (70.99%) |
Yes | 218 | (17.14%) |
Missing | 151 | (11.87%) |
Number of Comorbidities | 0.57 | (0.03) |
Serological test for SARS-CoV-2 | ||
Negative | 1157 | (90.96%) |
Positive | 74 | (5.82%) |
Missing | 41 | (3.22%) |
HR (IC95%) | p-Value | |
---|---|---|
Number of different accommodations in the past year | 1.2 (1.007–1.424) | 0.049 |
Cluster | Population | Number of Cases | Expected Cases | Observed/Expected | Relative Risk | Log Likelihood Ratio | p-Value | Gini Cluster |
---|---|---|---|---|---|---|---|---|
1 | 5 | 5 | 0.51 | 9.88 | 10.53 | 11.608803 | 0.00082 | yes |
2 | 18 | 8 | 1.82 | 4.39 | 4.81 | 7.329902 | 0.029 | yes |
3 | 20 | 8 | 2.02 | 3.95 | 4.31 | 6.429304 | 0.070 | no |
4 | 5 | 2 | 0.51 | 3.95 | 4.03 | 1.552775 | 0.991 | no |
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Allibert, A.; Tinland, A.; Landier, J.; Loubière, S.; Gaudart, J.; Mosnier, M.; Farnarier, C.; Auquier, P.; Mosnier, E. Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis. Int. J. Environ. Res. Public Health 2022, 19, 3129. https://doi.org/10.3390/ijerph19053129
Allibert A, Tinland A, Landier J, Loubière S, Gaudart J, Mosnier M, Farnarier C, Auquier P, Mosnier E. Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis. International Journal of Environmental Research and Public Health. 2022; 19(5):3129. https://doi.org/10.3390/ijerph19053129
Chicago/Turabian StyleAllibert, Agathe, Aurélie Tinland, Jordi Landier, Sandrine Loubière, Jean Gaudart, Marine Mosnier, Cyril Farnarier, Pascal Auquier, and Emilie Mosnier. 2022. "Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis" International Journal of Environmental Research and Public Health 19, no. 5: 3129. https://doi.org/10.3390/ijerph19053129
APA StyleAllibert, A., Tinland, A., Landier, J., Loubière, S., Gaudart, J., Mosnier, M., Farnarier, C., Auquier, P., & Mosnier, E. (2022). Residential Mobility of a Cohort of Homeless People in Times of Crisis: COVID-19 Pandemic in a European Metropolis. International Journal of Environmental Research and Public Health, 19(5), 3129. https://doi.org/10.3390/ijerph19053129