2022 Fiscal Year Research-status Report
Mapping seasonal demography and mobility for malaria elimination
Project/Area Number |
20K10447
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Research Institution | The University of Tokyo |
Principal Investigator |
新井 亜弓 東京大学, 空間情報科学研究センター, 特任助教 (10788574)
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Co-Investigator(Kenkyū-buntansha) |
金杉 洋 東京大学, 空間情報科学研究センター, 協力研究員 (00526907)
ウィタヤンクーン アピチョン 東京大学, 空間情報科学研究センター, 客員研究員 (90726407)
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Project Period (FY) |
2020-04-01 – 2024-03-31
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Keywords | mobile phone data / human mobility / developing country / representativeness / population statistics |
Outline of Annual Research Achievements |
As we planned we conducted the analysis to characterize the attributes of highly-mobile population. We also examined how we could generalize our model to one of west African countries. We obtained the following findings: 1) Mobility and population distribution patterns, including access to job opportunities, vary across different socio-economic groups. The highly-mobile population are often geographically concentrated on informal areas. This could be part of factors determining other types of accessibility such as access to services and infrastructure. 2) There are specific areas and timing where high-risk population start to concentrate and leave towns, which are closely related to agricultural calendar/seasonality.
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Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We managed to have discussion with local stakeholders regarding the use of statistics generated from CDR data. Through the discussion we figured that local stakeholders concern about data representativeness that could potentially affect extracted patterns. So, we additionally investigated how data representativeness could vary across regions and if there is a certain indicator/variable which could potentially enable us to estimate the variation.
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Strategy for Future Research Activity |
コロナの影響で、昨年度は大学だけでなく、多くの国際機関やNGOの活動が制約を受け、特に調査については対面を介さない形態の調査が優先して行われた。 これに伴い、もともと想定していたマラリア患者のデータ更新が限定的であることは否めない。このため、同じく感染症としてCOVID-19関連のデータを用いて分析を進めることも併せて検討する。 今年度は最終年度のため、研究成果の発表を積極的に行う。また、他国でのスケールの実現を視野に入れた、成果の整理を行うことを目指す。
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Causes of Carryover |
前年度未使用額があり、現地への出張の際の経費として使用したが、大規模なワークショップ等はまだ実施ができなかったため、その一部が支出しきれなかった。
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