Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies

Antiviral drugs have benefited public health officers to elucidate outbreak risks by controlling influenza pandemics efficacious, especially effective in the early stage of epidemic outbreaks. To limit explosive strain on hospitals, commercial pharmacies have joined, as antiviral drug-dispensing par...

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Main Authors: Zhang, Chijun, Du, Zhanwei, Cai, Qing, Yu, Limin, Li, Zhaohui, Bai, Yuan
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/141676
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1416762020-06-10T02:34:27Z Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies Zhang, Chijun Du, Zhanwei Cai, Qing Yu, Limin Li, Zhaohui Bai, Yuan School of Computer Science and Engineering Engineering::Computer science and engineering Urban Network Antiviral Drugs Antiviral drugs have benefited public health officers to elucidate outbreak risks by controlling influenza pandemics efficacious, especially effective in the early stage of epidemic outbreaks. To limit explosive strain on hospitals, commercial pharmacies have joined, as antiviral drug-dispensing partners, in governments’ pandemic response plans. Existing researches focus on site selection by optimizing the single objective of access to the target population. However, there are substantial inevitable but essential social factors (such as social unbalance, spatial unbalance and resource unbalance) needed to consider to benefit the society best. In this paper, we propose a network-perspective optimization model across multiple social scales (e.g, access, social unbalance, spatial unbalance and resource unbalance) to assign antiviral drugs to the urban dispensing pharmacies. In the network-based frame, we transfer these considerations to the constraints of group, edge, and node. The constrained optimization model is studied and solved using methods of willingness-to-travel model, L12 norm and network lasso, corresponding to each considerations. Taking Shanghai in a cohort of 11 million individuals as an example, we have shown the flexibility of the proposed multi-objective model, comparing with the traditional methods. For example, we found that there are 29 pharmacies needed with covering 81% districts by tradition single-objective method. In the contrast, only 12 pharmacies are needed with similar access ability but can still cover 75% districts. Or more pharmacies are assigned with covering 87% districts. This research can supply an initial exploration of pharmacy-based distribution of antiviral drugs for the studying construction of strategic national stockpile in some countries. 2020-06-10T02:34:27Z 2020-06-10T02:34:27Z 2018 Journal Article Zhang, C., Du, Z., Cai, Q., Yu, L., Li, Z., & Bai, Y. (2019). Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies. Journal of Ambient Intelligence and Humanized Computing, 10(8), 3067-3074. doi:10.1007/s12652-018-0872-6 1868-5137 https://hdl.handle.net/10356/141676 10.1007/s12652-018-0872-6 2-s2.0-85049585898 8 10 3067 3074 en Journal of Ambient Intelligence and Humanized Computing © 2018 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering::Computer science and engineering
Urban Network
Antiviral Drugs
spellingShingle Engineering::Computer science and engineering
Urban Network
Antiviral Drugs
Zhang, Chijun
Du, Zhanwei
Cai, Qing
Yu, Limin
Li, Zhaohui
Bai, Yuan
Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
description Antiviral drugs have benefited public health officers to elucidate outbreak risks by controlling influenza pandemics efficacious, especially effective in the early stage of epidemic outbreaks. To limit explosive strain on hospitals, commercial pharmacies have joined, as antiviral drug-dispensing partners, in governments’ pandemic response plans. Existing researches focus on site selection by optimizing the single objective of access to the target population. However, there are substantial inevitable but essential social factors (such as social unbalance, spatial unbalance and resource unbalance) needed to consider to benefit the society best. In this paper, we propose a network-perspective optimization model across multiple social scales (e.g, access, social unbalance, spatial unbalance and resource unbalance) to assign antiviral drugs to the urban dispensing pharmacies. In the network-based frame, we transfer these considerations to the constraints of group, edge, and node. The constrained optimization model is studied and solved using methods of willingness-to-travel model, L12 norm and network lasso, corresponding to each considerations. Taking Shanghai in a cohort of 11 million individuals as an example, we have shown the flexibility of the proposed multi-objective model, comparing with the traditional methods. For example, we found that there are 29 pharmacies needed with covering 81% districts by tradition single-objective method. In the contrast, only 12 pharmacies are needed with similar access ability but can still cover 75% districts. Or more pharmacies are assigned with covering 87% districts. This research can supply an initial exploration of pharmacy-based distribution of antiviral drugs for the studying construction of strategic national stockpile in some countries.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Zhang, Chijun
Du, Zhanwei
Cai, Qing
Yu, Limin
Li, Zhaohui
Bai, Yuan
format Article
author Zhang, Chijun
Du, Zhanwei
Cai, Qing
Yu, Limin
Li, Zhaohui
Bai, Yuan
author_sort Zhang, Chijun
title Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
title_short Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
title_full Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
title_fullStr Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
title_full_unstemmed Assignment optimization of pandemic influenza antiviral drugs in Urban pharmacies
title_sort assignment optimization of pandemic influenza antiviral drugs in urban pharmacies
publishDate 2020
url https://hdl.handle.net/10356/141676
_version_ 1681059691259494400