[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-112823-en":3,"doc-seo-112823-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},112823,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Predicting Dynamic Patterns of Short-Term Movement","Short-term human mobility has major health implications, yet measuring it through survey data is expensive and logistically difficult, and mobile-phone data access is often limited. This study uses Senegal as a case study to predict short-term movement by combining several accessible data sources. Economic and social drivers explain about 70% of short-term movement variation. Predictions are compared with real movement to estimate effects on malaria spread.","Pub lic Disclosure Authorized Pub lic Disclosure Authorized  \nThe World Bank Economic Review, 34(Supplement), 2020, S26–S34 doi: 10.1093/wber/lhz036 Supplementary Article  \nPredicting Dynamic Patterns of Short-Term Movement Sveta Milusheva  \nAbstract  \nShort-term human mobility has important health consequences, but measuring short-term movement using survey data is difficult and costly, and use of mobile phone data to study short-term movement is only possible in locations that can access the data. Combining several accessible data sources, Senegal is used as a case study to predict short-term movement within the country. The focus is on two main drivers of movement—economic and social—which explain almost 70 percent of the variation in short-term movement. Comparing real and predicted short-term movement to measure the impact of population movement on the spread of malaria in Senegal, the predictions generated by the model provide estimates for the effect that are not significantly different from the estimates using the real data. Given that the data used in this paper are often accessible in other country settings, this paper demonstrates how predictive modeling can be used by policy makers to estimate short-term mobility.  \nJEL classification: R23, J18, O15  \nKeywords: mobility, predictive modeling, telecommunications data, policy planning, health policy  \n1. Introduction  \nShort-term human mobility has important health consequences, as it has been linked to the propagation of diseases such as influenza, malaria, and HIV/AIDS (Balcan et al. 2009; Oster 2012; Adda 2016; Tatemand Smith 2010; Wesolowski et al. 2012) . Yet measuring short-term movement, especially in low-income countries, has been difficult, requiring expensive surveys that cannot be implemented over a wide geographic area. More recently, mobile phone data have made it possible to study short-term movement fora whole country at a higher spatial and temporal granularity (Blumenstock 2012) . But the proprietary nature of the data and privacy concerns can prohibit long-term use by researchers or policy makers. This paper is the first to study how the temporal dynamics of short-term movement measured by cell phone data can be predicted.  \nTo study short-term movement, this paper focuses on two main drivers: economic and social. Two types of economic factors are individuals traveling for seasonal work or traveling to a big market or commercial center. People also take short trips to visit family or friends during religious holidays and  \nSveta Milusheva is an economist at the World Bank’s Development Impact Evaluation Group, part of the World Bank’s Development Economics Vice-presidency (DEC); her email address is [smilusheva@worldbank.org. The](smilusheva@worldbank.org. The) author is grateful to Andrew Foster, Jesse Shapiro, and Daniel Bjorkegren for their continuous guidance. Anonymous mobile phone data have been made available by Orange and Sonatel within the framework of the D4D-Senegal challenge. Thanks are extended to the National Agency of Statistics and Demography of Senegal (ANSD), the National Malaria Control Program, and MACEPA for providing the census data and data on malaria incidence. This work was supported by the Bill & Melinda Gates Foundation (grant OPP1114791) and the National Institute of Child Health and Human Development (grant T32 HD 7338-29) .  \n© The Author(s) 2019 . Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK.  \nAll rights reserved. For permissions, please e-mail: [journals.permissions@oup.com](journals.permissions@oup.com)  \nDownloaded from [https://academic.oup.com/wber/article/34/Supplement_1/S26/5651212 by guest on 23 June 2021](https://academic.oup.com/wber/article/34/Supplement_1/S26/5651212 by guest on 23 June 2021)  \nvacations. In past literature, long-term migration networks measured through census data were used to study short-term movement (Wesolow","cbCainJf45IJoEYR","https://ap.wps.com/l/cbCainJf45IJoEYR","pdf",1042277,1,9,"English","en",105,"# Introduction\n## Data and Empirical Specification","[{\"question\":\"Why is measuring short-term human mobility difficult in many settings?\",\"answer\":\"Survey-based measurement is costly and hard to deploy over wide geographic areas. Mobile-phone data can also be constrained by proprietary access and privacy concerns.\"},{\"question\":\"What drivers does the study use to predict short-term movement?\",\"answer\":\"The model focuses on two main drivers: economic and social factors that capture travel for seasonal work, market visits, and short social or holiday-related trips.\"},{\"question\":\"How is the predicted movement evaluated for health policy relevance?\",\"answer\":\"The study compares real and predicted short-term movement to estimate the impact of population movement on malaria spread, and uses those results to demonstrate how policy makers can estimate mobility effects.\"}]",1784497407,23,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"predicting-dynamic-patterns-of-short-term-movement","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/predicting-dynamic-patterns-of-short-term-movement/112823/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-19",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why is measuring short-term human mobility difficult in many settings?","Question",{"text":74,"@type":75},"Survey-based measurement is costly and hard to deploy over wide geographic areas. Mobile-phone data can also be constrained by proprietary access and privacy concerns.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What drivers does the study use to predict short-term movement?",{"text":79,"@type":75},"The model focuses on two main drivers: economic and social factors that capture travel for seasonal work, market visits, and short social or holiday-related trips.",{"name":81,"@type":72,"acceptedAnswer":82},"How is the predicted movement evaluated for health policy relevance?",{"text":83,"@type":75},"The study compares real and predicted short-term movement to estimate the impact of population movement on malaria spread, and uses those results to demonstrate how policy makers can estimate mobility effects.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":45,"category_name":123,"show_sort_weight":124,"slug":125},"Religion & Spirituality",20,"religion-spirituality",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":124,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]