[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-240596-105":53,"doc-detail-240596-en":127},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":120,"head_meta":122,"extra_data":124,"updated_unix":126},105,"en","disseminating-emergency-preparedness-planning-models-as-automatically-generated-custom-spreadsheets","Disseminating Emergency Preparedness Planning Models as Automatically Generated Custom Spreadsheets","","Operations research models were requested by public health officials to help county agencies plan the dispensing of medications and vaccines. The work developed capacity planning and queueing network models, then addressed how to distribute them to users with limited operations research experience and no ability to buy or learn new software. Spreadsheets were chosen to remove key barriers, with macros generating models from user input. Public health emergency preparedness planners can download the associated software.",{"@graph":63,"@context":119},[64,80,102],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/disseminating-emergency-preparedness-planning-models-as-automatically-generated-custom-spreadsheets/240596/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/disseminating-emergency-preparedness-planning-models-as-automatically-generated-custom-spreadsheets/240596.png","ImageObject",442,249,{"name":88,"@type":89},"Angel","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-25","2026-09-11",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",10,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"Why were spreadsheets used to distribute the planning models?","Question",{"text":109,"@type":110},"Spreadsheets removed major obstacles for users with limited operations research experience and no resources to acquire or learn new software.","Answer",{"name":112,"@type":107,"acceptedAnswer":113},"What kinds of operations research models were developed for dispensing and vaccination planning?",{"text":114,"@type":110},"The project developed capacity planning and queueing network models, including discrete-event simulation and related queueing network approaches.",{"name":116,"@type":107,"acceptedAnswer":117},"What planning factors influence the design of mass dispensing and vaccination clinics (PODs)?",{"text":118,"@type":110},"Plans must assign the right number of workers to roles and account for clinic capacity and the time residents spend in the system, which together affect clinic count, total vaccination time, and crowding.","https://schema.org",{"og:url":78,"og:type":121,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":123,"canonical":78},"index,follow",{"doc_id":125,"site_id":56},240596,1791719553,{"code":4,"msg":5,"data":128},{"doc_id":125,"user_id":129,"nickname":88,"user_avatar":130,"doc_module":9,"category_id":8,"category_name":11,"doc_title":59,"doc_description":61,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":101,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":20,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":47},687207412472,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Disseminating Emergency Preparedness Planning Models as Automatically Generated Custom Spreadsheets  \nJeffrey W. Herrmann  \nDepartment of Mechanical Engineering and Institute for Systems Research, University of Maryland, College Park, MD 20742  \nPhone: (301) 405-5433  \nFax: (301) 314-9477  \nElectronic mail: [jwh2@umd.edu](jwh2@umd.edu)  \nABSTRACT  \nWhen public health officials requested operations research models to help county health departments across the United States create plans for dispensing medications and vaccines, we developed capacity planning and queueing network models. We then faced the challenge of distributing these models to a set of persons who have unknown experience with operations research techniques and no resources for acquiring and learning new software. We decided to use spreadsheets, which eliminated the most significant obstacles. To allow users to evaluate a wide variety of plans, we created software that runs macros to generate spreadsheet models based on user input. Public health emergency preparedness planners can download the software from our web site. Developing spreadsheets for this type of application is very different from end-user modeling and typical spreadsheet applications.  \nIntroduction  \nMontgomery County, Maryland, is home to one of eight Advanced Practice Centers (APCs) for Public Health Preparedness. The APCs customize and package innovative tools for other local public health agencies to strengthen bioterrorism planning and response capabilities. The Centers for Disease Control and Prevention (CDC) funds the APC program. The National Association of County and City Health Officials (NACCHO) administers the program and maintains an online clearinghouse of APC preparedness tools for local public health agencies (NACCHO 2005) . The long-term goal is to create and disseminate a broad set of methods and guidelines to help county health departments create, assess, and improve their emergency preparedness and response plans.  \nEmergency preparedness includes carefully planning mass dispensing and vaccination clinics, also known as points of dispensing (PODs) . The health department must assign the right number of workers to various roles when the clinic begins operations. They must consider the capacity of each clinic (the number of residents it can serve per hour) and the number of minutes residents would spend in the clinic (the time in system, the flow time, or the throughput time) . Clinic capacity affects the number of clinics needed and the total time needed to vaccinate the affected population. The time in system affects the number of residents who would be inside the clinic waiting for treatment; too many residents in the clinic can cause crowding and confusion.  \nEvaluating clinic plans clearly requires the use of operations research models such as capacity planning and queueing. We developed discrete-event simulation models and capacity planning and queueing network models to improve clinic planning in an ongoing collaboration between the University of Maryland, College Park, and the Montgomery County (Maryland) Public Health Services (PHS) . Aaby et al. (2006b) provide more information about these models.  \nIn this paper we discuss the challenge of distributing these models to a set of persons who have unknown experience with operations research techniques and no resources for acquiring and learning new software. Providing the models in a useful format was a critical problem. The possible choices included publishing a report that presented the mathematical models, developing an original piece of software, creating spreadsheets for common clinic layouts, and providing discrete-event simulation models. We decided on developing software that creates spreadsheets based on user input.  \nEmergency Preparedness Planning  \nAfter the September 11, 2001, terrorist attacks, public health officials at the federal, state, and county level accelerated efforts to plan their response to event","cbCaidW0Q4PNgfEQ","https://ap.wps.com/l/cbCaidW0Q4PNgfEQ","pdf",70581,"English","# Abstract\n# Introduction\n## Emergency Preparedness and PODs\n## Need for Operations Research Models\n# Emergency Preparedness Planning\n## Post-9/11 Planning Context\n## Mass Vaccination Clinic Workflow","[{\"question\":\"Why were spreadsheets used to distribute the planning models?\",\"answer\":\"Spreadsheets removed major obstacles for users with limited operations research experience and no resources to acquire or learn new software.\"},{\"question\":\"What kinds of operations research models were developed for dispensing and vaccination planning?\",\"answer\":\"The project developed capacity planning and queueing network models, including discrete-event simulation and related queueing network approaches.\"},{\"question\":\"What planning factors influence the design of mass dispensing and vaccination clinics (PODs)?\",\"answer\":\"Plans must assign the right number of workers to roles and account for clinic capacity and the time residents spend in the system, which together affect clinic count, total vaccination time, and crowding.\"}]","Disseminating Emergency Preparedness Planning Models as Automatically Generated Custom Spreadsheets | PDF",1789163152]