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Data laboratory for supply chain response models during epidemic outbreaks. (English) Zbl 1434.90087
Summary: Disasters in developing countries tremendously affect the economy and long-term development. Recent years have seen an increase in epidemic outbreaks in countries like Haiti and in West Africa. However, there seems to be a lack of decision support to address epidemic outbreak challenges in developing countries compared to their developed counterparts. The lack of data to implement such models is a potential reason. This paper presents a data set that will permit to develop data-driven allocation models and policies for an epidemic outbreak in a developing country. The data set is for the cholera epidemic that occurred in the aftermath of the 2010 earthquake in Haiti. The detailed time-series patient data is intended to facilitate the development and evaluation of multi-period supply chain models that support emergency health response, allocate medical resources and staff, and design coordination mechanisms among humanitarian stakeholders. We also provide a simple model to illustrate how the data can be utilized to develop a basic epidemic outbreak response model. The data set will be made available online for researchers interested in developing models in this field.
90B90 Case-oriented studies in operations research
90B06 Transportation, logistics and supply chain management
92D30 Epidemiology
Google Maps API
Full Text: DOI
[1] Aaby, K.; Herrmann, JW; Jordan, CS; Treadwell, M.; Wood, K., Montgomery County’s public health service uses operations research to plan emergency mass dispensing and vaccination clinics, Interfaces, 36, 569-579, (2006)
[2] Anaya-Arenas, AM; Renaud, J.; Ruiz, A., Relief distribution networks: A systematic review, Annals of Operations Research, 223, 53-79, (2014) · Zbl 1306.90021
[3] Anparasan, A. A., & Lejeune, M. A. (2017). Data for epidemic outbreaks. http://www.milejeune.org/data.html.
[4] Apte, A.; Heidtke, C.; Salmerón, J., Casualty collection points optimization: A study for the district of Columbia, Interfaces, 45, 149-165, (2015)
[5] Bhattacharya, S.; Hasija, S.; Wassenhove, LN, Designing efficient infrastructural investment and asset transfer mechanisms in humanitarian supply chains, Production and Operations Management, 23, 1511-1521, (2014)
[6] Dasaklis, TK; Pappis, CP; Rachaniotis, NP, Epidemics control and logistics operations: A review, International Journal of Production Economics, 139, 393-410, (2012)
[7] Drezner, T., Location of casualty collection points, Environment and Planning C: Government and Policy, 22, 899-912, (2004)
[8] Farmer, P.; Almazor, CP; Bahnsen, ET; Barry, D.; Bazile, J.; Bloom, BR; Bose, N.; Brewer, T.; Calderwood, SB; Clemens, JD; etal., Meeting cholera’s challenge to Haiti and the world: A joint statement on cholera prevention and care, PLoS Neglected Tropical Diseases, 5, 1-13, (2011)
[9] Geohive. (2015). Haiti—General information. http://www.geohive.com/cntry/haiti.aspx.
[10] Geo Locator. (2015). http://tools.freeside.sk/geolocator/geolocator.html.
[11] Goentzel, J., & Heigh, I. (2015). Supply Chains in Crisis. Inside Logistic. July 2015: 16-18. Institute for Supply Management.
[12] Google. (2015). Google Maps Image APIs. Google Developers: https://developers.google.com/maps/documentation/staticmaps/. Accessed February 25, 2015.
[13] Green, LV, OM forum—The vital role of operations analysis in improving healthcare delivery, Manufacturing & Service Operations Management, 14, 488-494, (2012)
[14] Hazen, B.; Skipper, J.; Boone, C.; Hill, R., Back in business: Operations research in support of big data analytics for operations and supply chain management, Annals of Operations Research, (2016)
[15] IFRC. (2014). World Disasters Report 2014—Data: https://www.ifrc.org/en/publications-and-reports/world-disasters-report/world-disasters-report-2014/world-disasters-report-2014—data/. Accessed February 6, 2015.
[16] Koyuncu, M.; Erol, R., Optimal resource allocation model to mitigate the impact of pandemic influenza: A case study for Turkey, Journal of Medical Systems, 34, 61-70, (2010)
[17] Kraiselburd, S.; Yadav, P., Supply chains and global health: An imperative for bringing operations management scholarship into action, Production and Operations Management, 22, 377-381, (2013)
[18] Lee, EK; Smalley, HK; Zhang, Y.; Pietz, F., Facility location and multi-modality mass dispensing strategies and emergency response for biodefence and infectious disease outbreaks, International Journal of Risk Assessment and Management, 12, 311-351, (2009)
[19] Lemonick, DM, Epidemics after natural disasters, American Journal of Clinical Medicine, 8, 144-152, (2011)
[20] Maskery, B.; DeRoeck, D.; Levin, A.; Kim, YE; Wierzba, TF; Clemens, JD, Strategy, demand, management, and costs of an international cholera vaccine stockpile, Journal of Infectious Diseases, 208, s15-s22, (2013)
[21] McCoy, JH; Johnson, ME, Clinic capacity management: Planning treatment programs that incorporate adherence, Production and Operations Management, 23, 1-18, (2014)
[22] MSPP. (2011). Documentation. Ministry of Health and Population, Haiti. http://www.mspp.gouv.ht/site/index.php?option=com_content&view=article&id=57&Itemid=1.
[23] MSPP and CDC. (2011). Haiti cholera training manual: A full course for health care providers. http://www.cdc.gov/haiticholera/pdf/haiticholera_trainingmanual_en.pdf.
[24] Natarajan, KV; Swaminathan, JM, Inventory management in humanitarian operations: Impact of amount, schedule, and uncertainty in funding, Manufacturing & Service Operations Management, 16, 595-603, (2014)
[25] Prasad, S., Zakaria, R., & Altay, N. (2016). Big data in humanitarian supply chain networks: A resource dependence perspective. Annals of Operations Research. doi:10.1007/s10479-016-2280-7.
[26] Rachaniotis, NP; Dasaklis, TK; Pappis, CP, A deterministic resource scheduling model in epidemic control: A case study, European Journal of Operational Research, 216, 225-231, (2012)
[27] Rahman, S.; Smith, DK, Use of location-allocation models in health service development planning in developing nations, European Journal of Operational Research, 123, 437-452, (2000) · Zbl 0962.91514
[28] Russom, P. (2011). Big data analytics. TDWI best practices report, fourth quarter. http://www.tableau.com/sites/default/files/whitepapers/tdwi_bpreport_q411_big_data_analytics_tableau.pdf. Accessed November 5, 2016.
[29] Simchi-Levi, D., OM forum-OM research: From problem-driven to data-driven research, Manufacturing & Service Operations Management, 16, 2-10, (2014)
[30] UNDP. (2015). Multi-partner trust fund office gateway. UNDG Haiti Reconstruction Fund. http://www.lessonsfromhaiti.org/download/International_Assistance/2-overall-financing-data.pdf. Accessed October 4, 2015.
[31] UNISDR. (2015). Disaster statistics. The United Nations Office for Disaster Risk Reduction. http://www.unisdr.org/we/inform/disaster-statistics. Accessed May 6, 2015.
[32] WHO. (2004). Cholera outbreak: Assessing the outbreak response and improving preparedness. http://www.who.int/cholera/publications/OutbreakAssessment/en/.
[33] World Bank. (2014). The economic impact of the 2014 Ebola Epidemic: Short and medium term estimates for West Africa: http://www.worldbank.org/en/region/afr/publication/the-economic-impact-of-the-2014-ebola-epidemic-short-and-medium-term-estimates-for-west-africa. Accessed July 24, 2015.
[34] Xiang, Y.; Zhuang, J., A medical resource allocation model for serving emergency victims with deteriorating health conditions, Annals of Operations Research, 236, 177-196, (2016) · Zbl 1345.91015
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