慶應義塾研究者情報データベース

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• 国立がん研究センター, 社会と健康研究センター, 外来研究員

• 国立感染症研究所, 感染症疫学センター, 所外研究員

• 大阪大学, 感染症総合教育研究拠点 (CiDER), 連携研究員

• エコノミスト・インパクト, 新型コロナ後遺症に関する諮問委員会

• Center for Asia-Pacific Resilience and Innovation (CAPRI), シニアフェロー

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経歴 【 表示 ／ 非表示 】

経歴 【 表示 ／ 非表示 】

• 2012年08月

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  2012年10月

  国連開発計画（UNDP） タジキスタン共和国事務所, 災害リスク管理部, インターン

• 2013年04月

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  2013年09月

  東京大学, グローバルヘルス・リーダーシップ・プログラム, フェロー

• 2014年07月

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  2014年09月

  世界保健機関（WHO）, 災害リスク・人道支援部門政策実施評価局, インターン

• 2016年12月

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  2024年07月

  東京大学, 大学院医学系研究科 国際保健政策学教室, 特任助教

• 2017年07月

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  2020年03月

  独立行政法人国立国際医療研究センター, グローバルヘルス政策研究センター, 特任研究員

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• 2007年04月

  -

  2011年03月

  東京大学, 薬学部

  大学, 卒業

• 2011年04月

  -

  2013年03月

  東京大学, 大学院医学系研究科, , 国際保健政策学教室

  大学院, 修了, 修士

• 2013年09月

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  2019年02月

  インペリアル・カレッジ・ロンドン, 公衆衛生大学院, 疫学・生物統計学教室

  グレートブリテン・北アイルランド連合王国(英国), 大学院, 修了, 博士

学位 【 表示 ／ 非表示 】

学位 【 表示 ／ 非表示 】

• 保健学修士, 東京大学, 課程, 2013年03月

• 疫学・生物統計学博士, インペリアル・カレッジ・ロンドン, 課程, 2019年02月

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• パンデミックに対する予防、備え及び対応 (PPR)

• ユニバーサル・ヘルス・カバレッジ (UHC)

• 世界の疾病負荷 (GBD)

• 国際保健外交

• 国際保健政策

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研究テーマ 【 表示 ／ 非表示 】

• 国際保健政策​, 国際保健外交​, 世界の疾病負荷 (GBD)​, ユニバーサル・ヘルス・カバレッジ (UHC)​, 非感染性疾患の予防・管理​, 栄養科学と政策​, 災害・健康危機管理 (Health EDRM)​, パンデミックに対する予防、備え及び対応 (PPR), 

  2011年04月

  -

  継続中

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• 新型コロナウイルス感染症 対応記録（続編）〈2022年－2024年〉

  橋爪真弘, 野村周平, 鈴木基, 一般財団法人 日本公衆衛生協会, 2024年12月

  担当範囲: わが国における超過死亡の推定

• 第3期「健康・医療戦略」策定に向けた提言―求められるグローバルな視点—

  「グローバルヘルスと人間の安全保障」運営委員会 有志一同, 公益財団法人 日本国際交流センター, 2024年10月

• Financing Global Health 2023: The Future of Health Financing in the Post-Pandemic Era

  Angela Micah, Joseph Dieleman, Katherine Leach-Kemon, Enis Bariş, Ian E. Cogswell, Hans Elliot, Brendan Lidral-Porter, Christopher J.L. Murray, Seong Nam, Shuhei Nomura, Nishali K. Patel, Carolyn Shyong, Juan Solorio, Golsum Tsakalos, Wesley Warriner, Asrat A. Wolde, Dereje Y. Yada, Yingxi Zhao, Bianca Zlavog, 2024年05月

• An incomplete picture: understanding the burden of long Covid

  Economist Impact, Economist Impact, 2024年04月

• Modernizing Global Health Security to Prevent, Detect, and Respond

  Qudsia Huda, Erin L. Downey, Ali Ardalan, Shuhei Nomura, Ambrose Otau Talisuna, Ankur Rakesh, Elsevier, 2023年11月

  担当範囲: Rights-based Global Health Security through all-hazard risk management

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• The Unseen Aftermath: Associations Between the COVID-19 Pandemic and Shifts in Mortality Trends in Japan

  Hasan Jamil, Shuhei Nomura, Stuart Gilmour

  International Journal of Environmental Research and Public Health 22 （ 1 ） 74 2025年01月

  査読有り,  ISSN  16617827

  　概要を見る

  The COVID-19 pandemic disrupted healthcare systems globally, potentially altering mortality trends for non-COVID-19 diseases, particularly in aging populations like Japan’s. Assessing these impacts is essential for responsive healthcare planning. We analyzed Japanese vital registration mortality records from January 2018 to December 2021 for adults aged 25 and older, excluding COVID-19-related deaths. Data were stratified by sex and ICD-10 cause-of-death chapters. Poisson regression models assessed changes in mortality rates and trends, incorporating pandemic-related variables and interactions between time, age group, and the pandemic term. Among the 4,920,942 deaths analyzed, 2,456,750 occurred during the pandemic years. Significant sex-specific changes in mortality trends were observed. Women experienced increases in mortality rates and trends for endocrine, nutritional, and metabolic diseases; skin and subcutaneous tissue diseases; circulatory diseases; and genitourinary diseases, reversing some pre-pandemic declines. Men showed increases in mortality trends for endocrine, nutritional, and metabolic diseases and genitourinary diseases but no significant changes for skin or circulatory diseases. These findings indicate that the pandemic differentially affected mortality trends between sexes, with women experiencing broader increases across multiple disease categories. The COVID-19 pandemic was associated with significant changes in mortality trends for certain non-COVID-19 diseases in Japan, with notable sex differences. Increased mortality among women across multiple disease categories highlights the pandemic’s indirect health impacts and underscores the need for sex-specific healthcare strategies in the post-pandemic era.

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• Cost-Benefit Analysis of Pre-Entry Tuberculosis Screening Policy: Nepalese and Japanese Perspectives

  Y Iwaki, T Hayashi, S Nomura, S Shimamura, R Gauchan, MC Huang

  2025年

• Trading-Off Privacy and Willingness to Share Personal Health Information: A Survey of Municipal Employees in Fukuoka City, Japan

  Shuhei Nomura, Yasumasa Segawa, Cyrus Ghaznavi, Takanori Fujita, Keiko Maruyama-Sakurai, Manae Uchibori, Akifumi Eguchi, Masaharu Ishigaki, Kazuto Fujiwara, Masayuki Kido, Hiroaki Miyata, Takanori Yamashita, Naoki Nakashima

  Health （Scientific Research Publishing, Inc.）  16 （ 12 ） 1315 - 1331 2024年12月

  筆頭著者, 責任著者, 査読有り,  ISSN  1949-4998

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• Indirect and direct effects of nighttime light on COVID-19 mortality using satellite image mapping approach

  Yoneoka D., Eguchi A., Nomura S., Kawashima T., Tanoue Y., Hashizume M., Suzuki M.

  Scientific Reports 14 （ 1 ） 25063 - 25063 2024年12月

  ISSN  2045-2322

  　概要を見る

  The COVID-19 pandemic has highlighted the importance of understanding environmental factors in disease transmission. This study aims to explore the spatial association between nighttime light (NTL) from satellite imagery and COVID-19 mortality. It particularly examines how NTL serves as a pragmatic proxy to estimate human interaction in illuminated nocturnal area, thereby impacting viral transmission dynamics to neighboring areas, which is defined as spillover effect. Analyzing 43,199 COVID-19 deaths from national mortality data during January 2020 and October 2022, satellite-derived NTL data, and various environmental and socio-demographic covariates, we employed the Spatial Durbin Error Model to estimate the direct and indirect effect of NTL on COVID-19 mortality. Higher NTL was initially directly linked to increased COVID-19 mortality but this association diminished over time. The spillover effect also changed: during the early 3rd wave (December 2020 – February 2021), a unit (nanoWatts/sr/cm2) increase in NTL led to a 7.9% increase in neighboring area mortality (p = 0.013). In contrast, in the later 7th wave (July – September 2022), dominated by Omicron, a unit increase in NTL resulted in an 8.9% decrease in mortality in neighboring areas (p = 0.029). The shift from a positive to a negative spillover effect indicates a change in infection dynamics during the pandemic. The study provided a novel approach to assess nighttime human activity and its influence on disease transmission, offering insights for public health strategies utilizing satellite imagery, particularly when direct data collection is impractical while the collection from space is readily available.

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• Lifestyle Differences in the Metabolic Comorbidity Score of Adult Population From South Asian Countries: A Cross-Sectional Study

  Sultana S., Nomura S., Sheng C.F., Hashizume M.

  AJPM Focus （Elsevier BV）  3 （ 6 ） 100273 - 100273 2024年12月

  査読有り,  ISSN  2773-0654

  　概要を見る

  Introduction: Metabolic comorbidities are involved in the development and progression of noncommunicable diseases. There is convincing evidence that lifestyles are important contributors to metabolic comorbidities. This study measured the metabolic comorbidity score of South Asian adults and identified its relationship with lifestyles. Methods: The authors studied 5 South Asian countries, including Afghanistan, Bangladesh, Bhutan, Nepal, and Sri Lanka, using the World Health Organization's STEPwise approach to noncommunicable disease risk factor surveillance data between 2014 and 2019. This was a nationally representative and cross-sectional survey on participants aged 15–69 years. The sample size was 27,616. The outcome was metabolic comorbidity score, calculated on the basis of total cholesterol, fasting plasma glucose, blood pressure, and abdominal obesity. Total metabolic comorbidity score of each participant varied between 0 and 8. It was then divided into 3 ranges: the lowest range (total metabolic comorbidity score <3), medium range (total metabolic comorbidity score ≥3 and ≤5), and the highest range (total metabolic comorbidity score ≥6). On the basis of the outcome of nonparametric receiver operating characteristics analysis, the medium and the highest ranges together were considered as higher metabolic comorbidity score. The lowest range was considered as lower metabolic comorbidity score. The higher metabolic comorbidity score was coded as 1, and the lower metabolic comorbidity score was coded as 0. Thus, the outcome variable, metabolic comorbidity score, became a binary variable. Exposures included physical inactivity (<150 minutes of medium-to-vigorous physical activity/week), high daily sedentary time (≥9 hours/day), use of tobacco (present or past smoking or daily use of smokeless tobacco products), and consumption of alcohol (at least once per month in the last 1 year). Binomial logistic regression model produced the OR with corresponding 95% CIs. Results: The prevalence of higher metabolic comorbidity score was 34% among South Asian adults, 25% among the male respondents, and 41% among the female respondents. Participants who were physically inactive (OR=1.26; 95% CI= 1.17, 1.36), had high sedentary time (OR=1.24; 95% CI=1.11, 1.33), and consumed alcohol (OR=1.40; 95% CI=1.23, 1.53) showed higher metabolic comorbidity score than participants who were physically active, had low sedentary time, and did not consume alcohol respectively. However, the authors found an inverse association (OR=0.75; 95% CI=0.71, 0.81) between the use of tobacco and metabolic comorbidity score. Conclusions: One third of South Asian adults had higher metabolic comorbidity score. Physical inactivity, daily sedentary hours, and minimal alcohol consumption were associated with higher metabolic comorbidity score.

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• The importance of methodological vigilance: Reevaluating suicide trends in Japan post-2022

  Koda M., Harada N., Nomura S.

  Psychiatry and Clinical Neurosciences Reports 3 （ 2 ）  2024年06月

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• 空間スキャン統計量と高次元回帰モデルの接点

  川島孝行, 米岡大輔, 田上悠太, 江口哲史, 野村周平

  統計関連学会連合大会講演報告集 2023 2023年

• コロナ禍における迅速サーベイランスを用いたビッグデータ解析における機械学習・統計学的方法論の整備

  米岡大輔, 野村周平, ギルモー スチュアート, 斎藤英子, 田上悠太, 川島孝行, 史蕭逸, 江口哲史

  大和証券ヘルス財団研究業績集 46 2023年

• 日本のCOVID-19パンデミックにおける都道府県間移動とネットワーク接続性

  Ghaznavi Cyrus, Ghaznavi Cyrus, Yoneoka Daisuke, Yoneoka Daisuke, Tanoue Yuta, Tanoue Yuta, Gilmour Stuart, Kawashima Takayuki, Kawashima Takayuki, Eguchi Akifumi, Eguchi Akifumi, Kawamura Yumi, Miyata Hiroaki, Miyata Hiroaki, Nomura Shuhei, Nomura Shuhei, Nomura Shuhei

  Journal of Epidemiology (Web) 32 （ 11 ）  2022年

  ISSN  1349-9092

• Correction to: Tracking Japan’s development assistance for health, 2012–2016 (Globalization and Health, (2020), 16, 1, (32), 10.1186/s12992-020-00559-2)

  Nomura S., Sakamoto H., Sugai M.K., Nakamura H., Maruyama-Sakurai K., Lee S., Ishizuka A., Shibuya K.

  Globalization and Health 17 （ 1 ）  2021年12月

  　概要を見る

  Following publication of the original article [1], the authors reported a conversion error that concerned the estimated amounts of development assistance for health (DAH) for 2012–2015; when the authors converted the current prices of 2012–2015 to the constant prices of 2016 using the gross domestic product (GDP) deflator, they erroneously multiplied the current prices by the GDP deflator instead of dividing them. Please find the details of this error in this correction. Firstly, the ‘Results’ in the article’s Abstract stated that “Japan’s DAH was estimated at 1,472.94 (2012), 823.15 (2013), 832.06 (2014), 701.98 (2015), and 894.57 million USD (2016) in constant prices of 2016”, while it should state that “Japan’s DAH was estimated at 853.87 (2012), 718.16 (2013), 824.95 (2014), 873.04 (2015), and 894.57 million USD (2016) in constant prices of 2016”. Secondly, the first sentence of the article’s Results section stated that “Japan’s DAH was estimated at 1, 472.94 (2012), 823.15 (2013), 832.06 (2014), 701.98 (2015), and 894.57 million USD (2016) in constant prices of 2016”, while it should state that “Japan’s DAH was estimated at 853.87 (2012), 718.16 (2013), 824.95 (2014), 873.04 (2015), and 894.57 million USD (2016) in constant prices of 2016”. In addition to the above mentioned parts of the article, the conversion error affected Table 1, Fig. 1a, Fig. 2a, and Additional file 2, for the data of 2012–2015; please find (the corrected version of) these files in this correction. The errors have now been corrected in the original article. Furthermore, the authors would like to assure the reader that the discussions proposed in their article were based on the part of the results not related to the conversion by the GBD deflator (i.e. percentage value rather than amount) and, therefore, that the miscalculated amounts of DAH mentioned above do not affect the interpretation or conclusions of the study. The authors thank you for reading this correction, and apologize for any inconvenience caused.

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• 我が国の疾病負荷の再評価と活用：ポストコロナ時代の都道府県分析と新方法論への挑戦

  2024年04月

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  2027年03月

  日本学術振興会, 科学研究費助成事業, 野村 周平, 基盤研究(A), 補助金,  研究代表者

• 令和時代の自然災害と健康危機管理：WHOの研究手法ガイダンスを見据えた研究推進

  2024年04月

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  2027年03月

  厚生労働省, 健康安全・危機管理対 策総合研究事業, 野村周平, 研究分担者

• 医療デジタルトランスフォーメーション時代の重層的な感染症サーベイランス体制の整備に向けた研究

  2023年04月

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  2024年03月

  厚生労働省, 新興・再興感染症及び予防接種政策推進研究事業, 野村周平, 研究分担者

• with/postコロナ時代の保健医療課題への疾病負荷の活用と実証分析

  2021年04月

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  2024年03月

  文部科学省・日本学術振興会, 科学研究費助成事業, 野村 周平, 基盤研究(B), 補助金,  研究代表者

• 科学的根拠に基づくがんリスク評価とがん予防ガイドライン提言に関する研究

  2021年04月

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  2025年03月

  国立がん研究センター, 国立がん研究センター研究開発費, 野村周平, 研究分担者

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• 明日の象徴

  2014年09月, 「明日の象徴」組織委員会