Modelling interventions to control COVID-19 outbreaks in a refugee camp
Background In the absence of effective treatments or vaccines, non-pharmaceutical interventions are the mainstay of control in the COVID-19 pandemic. Refugee populations in displacement camps live under adverse conditions that are likely to favour the spread of disease. To date, only a few cases of...
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BMJ Publishing Group
2020-12-01
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| Series: | BMJ Global Health |
| Online Access: | https://gh.bmj.com/content/5/12/e003727.full |
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| author | Robert Tucker Gilman Siyana Mahroof-Shaffi Andrew T Chamberlain |
| author_facet | Robert Tucker Gilman Siyana Mahroof-Shaffi Andrew T Chamberlain |
| author_sort | Robert Tucker Gilman |
| collection | DOAJ |
| description | Background In the absence of effective treatments or vaccines, non-pharmaceutical interventions are the mainstay of control in the COVID-19 pandemic. Refugee populations in displacement camps live under adverse conditions that are likely to favour the spread of disease. To date, only a few cases of COVID-19 have appeared in refugee camps, and whether feasible non-pharmaceutical interventions can prevent the spread of the SARS-CoV-2 virus in such settings remains untested.Methods We constructed the first spatially explicit agent-based model of a COVID-19 outbreak in a refugee camp, and applied it to evaluate feasible non-pharmaceutical interventions. We parameterised the model using published data on the transmission rates and progression dynamics of COVID-19, and demographic and spatial data from Europe’s largest refugee camp, the Moria displacement camp on Lesbos, Greece. We simulated COVID-19 epidemics with and without four feasible interventions.Results Spatial subdivision of the camp (‘sectoring’) was able to ‘flatten the curve’, reducing peak infection by up to 70% and delaying peak infection by up to several months. The use of face masks coupled with the efficient isolation of infected individuals reduced the overall incidence of infection, and sometimes averted epidemics altogether. These interventions must be implemented quickly in order to be maximally effective. Lockdowns had only small effects on COVID-19 dynamics.Conclusions Agent-based models are powerful tools for forecasting the spread of disease in spatially structured and heterogeneous populations. Our findings suggest that feasible interventions can slow the spread of COVID-19 in a refugee camp setting, and provide an evidence base for camp managers planning intervention strategies. Our model can be modified to study other closed populations at risk from COVID-19 or future epidemics. |
| format | Article |
| id | doaj-art-e0677a5fe34f453a94e27e552eb2a592 |
| institution | OA Journals |
| issn | 2059-7908 |
| language | English |
| publishDate | 2020-12-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Global Health |
| spelling | doaj-art-e0677a5fe34f453a94e27e552eb2a5922025-08-20T01:59:30ZengBMJ Publishing GroupBMJ Global Health2059-79082020-12-0151210.1136/bmjgh-2020-003727Modelling interventions to control COVID-19 outbreaks in a refugee campRobert Tucker Gilman0Siyana Mahroof-Shaffi1Andrew T Chamberlain2Centre for Crisis Studies and Mitigation, The University of Manchester, Manchester, UKKitrinos Healthcare, Lesbos, GreeceDepartment of Earth and Environmental Sciences, The University of Manchester, Manchester, UKBackground In the absence of effective treatments or vaccines, non-pharmaceutical interventions are the mainstay of control in the COVID-19 pandemic. Refugee populations in displacement camps live under adverse conditions that are likely to favour the spread of disease. To date, only a few cases of COVID-19 have appeared in refugee camps, and whether feasible non-pharmaceutical interventions can prevent the spread of the SARS-CoV-2 virus in such settings remains untested.Methods We constructed the first spatially explicit agent-based model of a COVID-19 outbreak in a refugee camp, and applied it to evaluate feasible non-pharmaceutical interventions. We parameterised the model using published data on the transmission rates and progression dynamics of COVID-19, and demographic and spatial data from Europe’s largest refugee camp, the Moria displacement camp on Lesbos, Greece. We simulated COVID-19 epidemics with and without four feasible interventions.Results Spatial subdivision of the camp (‘sectoring’) was able to ‘flatten the curve’, reducing peak infection by up to 70% and delaying peak infection by up to several months. The use of face masks coupled with the efficient isolation of infected individuals reduced the overall incidence of infection, and sometimes averted epidemics altogether. These interventions must be implemented quickly in order to be maximally effective. Lockdowns had only small effects on COVID-19 dynamics.Conclusions Agent-based models are powerful tools for forecasting the spread of disease in spatially structured and heterogeneous populations. Our findings suggest that feasible interventions can slow the spread of COVID-19 in a refugee camp setting, and provide an evidence base for camp managers planning intervention strategies. Our model can be modified to study other closed populations at risk from COVID-19 or future epidemics.https://gh.bmj.com/content/5/12/e003727.full |
| spellingShingle | Robert Tucker Gilman Siyana Mahroof-Shaffi Andrew T Chamberlain Modelling interventions to control COVID-19 outbreaks in a refugee camp BMJ Global Health |
| title | Modelling interventions to control COVID-19 outbreaks in a refugee camp |
| title_full | Modelling interventions to control COVID-19 outbreaks in a refugee camp |
| title_fullStr | Modelling interventions to control COVID-19 outbreaks in a refugee camp |
| title_full_unstemmed | Modelling interventions to control COVID-19 outbreaks in a refugee camp |
| title_short | Modelling interventions to control COVID-19 outbreaks in a refugee camp |
| title_sort | modelling interventions to control covid 19 outbreaks in a refugee camp |
| url | https://gh.bmj.com/content/5/12/e003727.full |
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