Sosyal sürdürülebilirlik kapsamında aşı soğuk zincir ağ tasarımı için matematiksel model önerisi

Year 2023, Volume: 12 Issue: 2, 376 - 385, 15.04.2023

Nur Hivda Yıldız , Nadide Aktaş , Neslihan Demirel

https://doi.org/10.28948/ngumuh.1180457

Abstract

Aşıların tabii olduğu soğuk zincirde meydana gelebilecek kırılmalar; ciddi ekonomik, çevresel ve sosyal maliyetlerin yanında insan ve halk sağlığı açısından da önemli risklere neden olmaktadır. Bu nedenle etkili, sağlam ve güçlü bir aşı soğuk zincir ağının tasarlanması gerekmektedir. Diğer yandan, “Sağlıklı Bireyler” başlıklı Sürdürülebilir Kalkınma Hedefi 3, çocukların sağlığına vurgu yapmakta ve beş yaş altı ölüm oranlarının düşürülmesini hedeflemektedir. Bu çalışmada, Türkiye'deki Genişletilmiş Bağışıklama Programı EPI aşı tedarik zinciri ele alınarak Sürdürülebilir Kalkınma Hedefi 3 ışığında çok ürünlü, çok dönemli, çok aşamalı bir aşı soğuk zincir ağı için doğrusal programlama modeli geliştirilmiştir. Çalışma, beş yaşa kadar tam bağışıklanmış çocuk sayısını en üst düzeye çıkarmayı ve aşı soğuk zincir ağ tasarımı için bir çerçeve önermeyi amaçlamaktadır. Önerilen model vaka çalışmasına uygulanmıştır. Son olarak, çeşitli senaryo analizleri ile model sonuçları değerlendirilmiştir.

Keywords

Genişletilmiş bağışıklama programı, Doğrusal programlama, Ağ tasarımı, Sosyal sürdürülebilirlik, Aşı soğuk zinciri

A mathematical model for vaccine cold chain network design considering social sustainability

Abstract

Breakages that may occur in the cold chain cause serious economic, environmental, and social costs, as well as a substantial risk for human and public health. Therefore, it is necessary to design an effective, robust, and strong vaccine cold chain network. Sustainable Development Goal 3 titled “Good Health and Well Being” emphasizes children's health and specifies reducing the mortality rate for under five ages. In this study, we consider the Expanded Programme on Immunization (EPI) vaccine cold chain in Türkiye and develop a linear programming model for a multi-product, multi-period, multi-stage vaccine cold chain network in light of Sustainable Development Goal 3. The study aims to maximize fully immunized children for up to five years and propose a framework for a vaccine cold chain network design. The proposed model is applied to a real case. Finally, various scenario analyzes are applied to show the results of the model under different conditions.

Keywords

Expanded Program on Immunization, Linear Programming, Network Design, Social sustainability, Vaccine cold chain

References

• World Health Organization, Children: improving survival and well-being, 08/09/2020. https://www.who.int/news-room/fact-sheets/detail/ children-reducing-mortality. Accessed: 19 April 2022.
• World Health Organization, Vaccines and immunization, 2021. https://www.who.int/health-topics/vaccines-and-immunization#tab=tab_1. Accessed: 19 April 2022.
• UNICEF, Immunization, 2021. https://www.unicef. org/immunization. Accessed: 16 November 2021.
• Sustainable Development Goals, Goal 3: Ensure healthy lives and promote well-being for all at all ages, 2022. https://www.un.org/sustainabledevelopment/ health/. Accessed: 14 April 2022.
• Statista, Infant mortality rate (under one year old) in Turkey from 1950 to 2020, 2022. https://www.statista.com/statistics/1073263/infant-mortality-rate-turkey-historical/. Accessed: 18 April 2022.
• UNICEF, Trends in under-five mortality rate in Turkey, 2022. https://data.unicef.org/country/tur/. Accessed: 18 April 2022.
• World Bank, Mortality rate under-5 (per 1,000 live births), 2022. https://data.worldbank.org/indicator/SH. DYN.MORT?locations=TR. Accessed: 18 April 2022.
• United Nations High Commissioner for Refugees, Refugees and Asylum Seekers in Turkey, 2022. https://www.unhcr.org/tr/en/refugees-and-asylum-seekers-in-turkey. Accessed: 18 April 2022.
• World Bank, Mortality rate under-5 (per 1,000 live births), 2022. https://data.worldbank.org/indicator/SH. DYN.MORT?most_recent_value_desc=true. Accessed: 18 April 2022.
• E. E. Günay, K. Park, S. Aydoğan and G. E. Okudan Kremer. Vaccine Distribution Strategies against Polio: An Analysis of Turkey Scenario. Industrial and manufacturing systems engineering conference proceeding and posters, Orlando, Florida, USA, 2019.
• UNICEF, Immunizaton, 2022. https://www.unicef.org/ turkey/en/immunization. Accessed: 16 November 2022.
• K. Shafaat, A. Hussain and B. Kumar, An Overview: Storage of pharmaceutical products. World J Pharm Sci, 2499-515, 2013.
• B. Y. Lee and L. A. Haidari, The importance of vaccine supply chains to everyone in the vaccine world. Vaccine, 35(35): 4475-4479, 2020. https://doi.org/ 10.1016/j.vaccine.2017.05.096
• S. I. Chen, B. Norman, j. Rajgopal, T. M. Assi, B. Y. Lee and S. T. Brown, A planning model for the WHO-EPI vaccine distribution network in developing countries. IIE Transactions, 46(8): 853-865, 2014. https://doi.org/10.1080/0740817X.2013.813094
• S. H. Jacobson, E. C. Sewell, R. Deuson and B. G. Weniger, An integer programming model for vaccine procurement and delivery for childhood immunization: A pilot study. Health Care Management Science, 2(1): 1-9, 1999. https://doi.org/10.1023/A:1019011106198
• S. Hovav and D. Tsadikovich, A network flow model for inventory management and distribution of influenza vaccines through a healthcare supply chain. Operations Research for Health Care, 5: 49-62, 2015. https://doi.org/10.1016/j.orhc.2015.05.003
• H. K. Smalley, P. Keskinocak, J. Swann and A. Hinman, Optimized oral cholera vaccine distribution strategies to minimize disease incidence: A mixed integer programming model and analysis of a Bangladesh scenario. Vaccine, 33(46): 6218-6223, 2015. https://doi.org/10.1016/j.vaccine.2015.09.088
• A. Saif, and S. Elhedhli, Cold supply chain design with environmental considerations: A simulation-optimization approach. European Journal of Operational Research, 251(1): 274-287, 2016. https://doi.org/10.1016/j.ejor.2015.10.056
• S. Hovav and A. Herbon, Prioritizing high-risk sub-groups in a multi-manufacturer vaccine distribution program. The International Journal of Logistics Management, 28(2): 311-331, 2017. https://doi.org/10.1108/IJLM-12-2015-0227
• M. I. D. Carvalho, D. Ribeiro and A. P. Barbosa-Povoa, Design and planning of sustainable vaccine supply chain. Pharmaceutical Supply Chains- Medicines Shortages, Springer, 2019. http://dx.doi.org/10.1007/ 978-3-030-15398-4_2
• J. Lim, B. A. Norman and J. Rajgopal, Redesign of vaccine distribution networks. International Transactions in Operational Research, 29(1): 200-225, 2019. https://doi.org/10.1111/itor.12758
• S. J. Sadjadi, Z. Ziaei and M. S. Pishvaee, The design of the vaccine supply network under uncertain condition: A robust mathematical programming approach. Journal of Modelling Management, 841-871, 2019. https://doi.org/10.1108/JM2-07-2018-0093
• B. Abbasi, M. Fadaki, O. Kokshagina, N. Saeed and P Chhetri, Modeling vaccine allocations in the COVID-19 pandemic: A case study in Australia, 2020. http://dx.doi.org/10.2139/ssrn.3744520
• S. Enayati and O. Y. Özaltın, Optimal influenza vaccine distribution with equity. European Journal Operational Research, 283(2): 714-725, 2020. https://doi.org/10.1016/j.ejor.2019.11.025
• Y. Yang, H. Bidkhori and J. Rajgopal, Optimizing vaccine distribution networks in low and middle-income countries. Omega, 99, 2020. https://doi.org/ 10.1016/j.omega.2020.102197
• A. G. Qasem, A. Shamsan and F. Aqlan, Optimal Cholera Vaccine Allocation Policies in Developing Countries: A Case Study. Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroit, Michigan, USA, pp. 2279-2287, 2020.
• M. Alizadeh, M. M. Paydar, S. M. Hosseini, and A. Makui, Influenza vaccine supply chain network design during the COVID-19 pandemic considering dynamical demand, Scientia Iranica, 2021. https://doi.org/10.24200/sci.2021.58365.5694
• G. P. Georgiadis and M. C. Georgiadis, Optimal planning of the COVID-19 vaccine supply chain. Vaccine, 39(37): 5302-5312, 2021. https://doi.org/ 10.1016/j.vaccine.2021.07.068
• M. Rastegar, M. Tavana, A. Meraj and H. Mina, An inventory-location optimization model for equitable infuenza vaccine distribution in developing countries during the COVID-19 pandemic. Vaccine, 495-504, 2021. https://doi.org/10.1016/j.vaccine.2020.12.022
• M. Tavana, K. Govindan, A. K. Nasr, M. S. Heidary and H. Mina, A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries. Annals of Operations Research, 1-34, 2021. https://doi.org/10.1007/s10479-021-04130-z
• H. Gilani and H. Sahebi, A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain. Omega, 110: 1-21, 2022. https://doi.org/10.1016/j. omega.2022.102637
• B. Balcik, E. Yucesoy, B. Akca, S.Karakaya, A. A.Gevsek, H. Baharmand and F. Sgarbossa, A mathematical model for equitable in-country COVID-19 vaccine allocation. International Journal of Production Research, 1-25, 2022. https://doi.org/10.1080/00207543.2022.2110014
• V. Khodaee, V. Kayvanfar and A. Haji, A humanitarian cold supply chain distribution model with equity consideration:The case of COVID-19 vaccine distribution in the European union. Decision Analytics Journal, 4, 100126. https://doi.org/10.1016/j.dajour. 2022.100126
• Z. Azadi, S. D. Eksioglu and H. N. Geismar, Optimization of Distribution Network Configuration for Pediatric Vaccines using Chance Constraint Programming, 2020. https://doi.org/10.48550/arXiv. 2006.05488
• World Health Organization, 1998, Safe vaccine handling, cold chain and immunizations: A manual for the Newly Independent States. https://apps. who.int/iris/handle/10665/64776
• S. Guichard, K. Hymbaugh, B. Burkholder, S. Diorditsa, C. Navarro, S. Ahmed and M. Rahman, Vaccine wastage in Bangladesh. Vaccine, 28(3): 858-863, 2010. https://doi.org/10.1016/j.vaccine.2009.08. 035