Ebola: Impact of hospital's admission policy in an overwhelmed scenario
Infectious disease outbreaks sometimes overwhelm healthcare facilities. A recent case occurred in West Africa in 2014 when an Ebola virus outbreak overwhelmed facilities in Sierra Leone, Guinea and Liberia. In such scenarios, how many patients can hospitals admit to minimize disease burden? This stu...
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AIMS Press
2018-11-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2018063 |
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| author | Mondal Hasan Zahid Christopher M. Kribs |
| author_facet | Mondal Hasan Zahid Christopher M. Kribs |
| author_sort | Mondal Hasan Zahid |
| collection | DOAJ |
| description | Infectious disease outbreaks sometimes overwhelm healthcare facilities. A recent case occurred in West Africa in 2014 when an Ebola virus outbreak overwhelmed facilities in Sierra Leone, Guinea and Liberia. In such scenarios, how many patients can hospitals admit to minimize disease burden? This study considers what type of hospital admission policy during a hypothetical Ebola outbreak can better serve the community, if overcrowding degrades the hospital setting. Our result shows that which policy minimizes loss to the community depends on the initial estimation of the control reproduction number, $R_0$. When the outbreak grows extremely fast ($R_0$$ \gg $1) it is better (in terms of total disease burden) to stop admitting patients after reaching the carrying capacity because overcrowding in the hospital makes the hospital setting ineffective at containing infection, but when the outbreak grows only a little faster than the system's ability to contain it ($R_0 \gtrsim 1$), it is better to admit patients beyond the carrying capacity because limited overcrowding still reduces infection more in the community. However, when $R_0$ is no more than a little greater than 1 (for our parameter values, 1.012), both policies result the same because the number of patients never exceeds the maximum capacity. |
| format | Article |
| id | doaj-art-d47b31bf42b84586804ab6e6789333e1 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2018-11-01 |
| publisher | AIMS Press |
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| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-d47b31bf42b84586804ab6e6789333e12025-01-24T02:41:08ZengAIMS PressMathematical Biosciences and Engineering1551-00182018-11-011561387139910.3934/mbe.2018063Ebola: Impact of hospital's admission policy in an overwhelmed scenarioMondal Hasan Zahid0Christopher M. Kribs1Deaprtment of Mathematics, University of Texas at Arlington, Arlington, TX 76019-0408, USADeaprtment of Mathematics, University of Texas at Arlington, Arlington, TX 76019-0408, USAInfectious disease outbreaks sometimes overwhelm healthcare facilities. A recent case occurred in West Africa in 2014 when an Ebola virus outbreak overwhelmed facilities in Sierra Leone, Guinea and Liberia. In such scenarios, how many patients can hospitals admit to minimize disease burden? This study considers what type of hospital admission policy during a hypothetical Ebola outbreak can better serve the community, if overcrowding degrades the hospital setting. Our result shows that which policy minimizes loss to the community depends on the initial estimation of the control reproduction number, $R_0$. When the outbreak grows extremely fast ($R_0$$ \gg $1) it is better (in terms of total disease burden) to stop admitting patients after reaching the carrying capacity because overcrowding in the hospital makes the hospital setting ineffective at containing infection, but when the outbreak grows only a little faster than the system's ability to contain it ($R_0 \gtrsim 1$), it is better to admit patients beyond the carrying capacity because limited overcrowding still reduces infection more in the community. However, when $R_0$ is no more than a little greater than 1 (for our parameter values, 1.012), both policies result the same because the number of patients never exceeds the maximum capacity.https://www.aimspress.com/article/doi/10.3934/mbe.2018063overcrowded hospitalebolaadmission policymathematical modeloverwhelmed healthcare facilitycontrol reproduction numberbasic reproduction number |
| spellingShingle | Mondal Hasan Zahid Christopher M. Kribs Ebola: Impact of hospital's admission policy in an overwhelmed scenario Mathematical Biosciences and Engineering overcrowded hospital ebola admission policy mathematical model overwhelmed healthcare facility control reproduction number basic reproduction number |
| title | Ebola: Impact of hospital's admission policy in an overwhelmed scenario |
| title_full | Ebola: Impact of hospital's admission policy in an overwhelmed scenario |
| title_fullStr | Ebola: Impact of hospital's admission policy in an overwhelmed scenario |
| title_full_unstemmed | Ebola: Impact of hospital's admission policy in an overwhelmed scenario |
| title_short | Ebola: Impact of hospital's admission policy in an overwhelmed scenario |
| title_sort | ebola impact of hospital s admission policy in an overwhelmed scenario |
| topic | overcrowded hospital ebola admission policy mathematical model overwhelmed healthcare facility control reproduction number basic reproduction number |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2018063 |
| work_keys_str_mv | AT mondalhasanzahid ebolaimpactofhospitalsadmissionpolicyinanoverwhelmedscenario AT christophermkribs ebolaimpactofhospitalsadmissionpolicyinanoverwhelmedscenario |