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アレルギー性鼻炎の疫学的予測

Allergic Rhinitis: Epidemiology Forecast to 2028

出版日: | 発行: GlobalData | ページ情報: 英文 44 Pages | 納期: 即納可能 即納可能とは

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アレルギー性鼻炎の疫学的予測
出版日: 2019年07月31日
発行: GlobalData
ページ情報: 英文 44 Pages
納期: 即納可能 即納可能とは
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  • 全表示
  • 概要
  • 図表
  • 目次
概要

当レポートでは、世界の主要7ヶ国 (米国、ドイツ、フランス、イタリア、スペイン、英国、日本) におけるアレルギー性鼻炎 (AR) の発症状況と今後の見通しについて分析し、疾患の特徴や、現在の有病者の発症状況、今後10年間の有病者数の予測値などを調査・推計しております。

第1章 目次

第2章 アレルギー性鼻炎:エグゼクティブ・サマリー

第3章 疫学

  • 疾患の背景事情
  • リスク要因と共存症
  • 過去の世界的傾向
  • 予測手法
    • 情報源
    • 予測の前提条件と手法
  • アレルギー性鼻炎 (AR) の疫学的予測 (今後11年間分)
    • アレルギー性鼻炎の受診済み発症件数
    • アレルギー性鼻炎の受診済み発症件数:年齢層別
    • アレルギー性鼻炎の受診済み発症件数:男女別
    • アレルギー性鼻炎の受診済み有病者数 (今後12ヵ月間の合計値)
    • アレルギー性鼻炎の受診済み有病者数 (今後12ヵ月間の合計値):年齢層別
    • アレルギー性鼻炎の受診済み有病者数 (今後12ヵ月間の合計値):男女別
    • アレルギー性鼻炎の受診済み有病者数 (今後12ヵ月間の合計値):重症度別
    • アレルギー性鼻炎の受診済み有病者数 (今後12ヵ月間の合計値):アレルゲンの種類別
    • アレルギー性鼻炎の有病者総数 (今後12ヵ月間の合計値)
    • アレルギー性鼻炎の有病者総数 (今後12ヵ月間の合計値):年齢層別
    • アレルギー性鼻炎の有病者総数 (今後12ヵ月間の合計値):男女別
  • 議論
    • 疫学的予測に関する考察
    • 分析の限界
    • 分析の強み

第4章 付録

図表

List of Tables

  • Table 1: Risk Factors and Comorbid Conditions Associated with AR
  • Table 2: 7MM, 12-Month Diagnosed Prevalent Cases of AR b Type of Allergen, N, Both Sexes, Ages ≥5 Years, 2018

List of Figures

  • Figure 1: 7MM, Diagnosed Incident Cases of AR, N, Both Sexes, Ages ≥5 Years, 2018 and 2028
  • Figure 2: 7MM, 12-Month Diagnosed Prevalent Cases of AR, N, Both Sexes, Ages ≥5 Years, 2018 and 2028
  • Figure 3: 7MM, 12-Month Total Prevalent Cases o
目次
Product Code: GDHCER213-19

Allergic rhinitis (AR) is a chronic inflammatory condition of the nasal mucosa, caused by immunoglobulin E (IgE)-mediated early-phase and late-phase hypersensitivity responses (Scadding, 2015). AR symptoms include rhinorrhea, nasal obstruction and blockage, nasal itching, and repetitive sneezing (Scadding, 2015; National Health Services, 2019). It is being increasingly recognized that if AR is poorly managed, it can have a major impact on quality of life, emotional well-being, sleep, daily activities, and productivity. AR is also associated with considerable economic burden (Linneberg et al., 2016)..

GlobalData epidemiologists utilized county-specific studies published in peer-reviewed journals to build the forecast for the The report includes a 10-year epidemiological forecast for the diagnosed incident, 12-month diagnosed prevalent, and 12-month total prevalent cases of AR in the 7MM.

The following data describes epidemiology of AR. GlobalData epidemiologists forecast an increase in the diagnosed incident cases of AR in the 7MM from 5,621,030 cases in 2018 to 5,660,994 cases by 2028, at an AGR of 0.07% during the forecast period. The 12-month diagnosed prevalent cases of AR in the 7MM are expected to increase from 76,455,380 cases in 2018 to 77,778,250 cases by 2028, at an AGR of 0.17%. The 12-month total prevalent cases of AR are also expected to increase from 149,371,883 cases in 2018 to 151,702,573 cases by 2028, at an AGR of 0.16%. AR is more common in women than men and is more common in the younger age groups. These trends are reflected in GlobalData's forecast for the diagnosed incident cases, and prevalent cases for the 7MM.

Scope

  • The Allergic Rhinitis (AR) Epidemiology Report and Model provide an overview of the risk factors and global trends of AR in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan).
  • The report includes a 10-year epidemiological forecast for the diagnosed incident cases, 12-month total prevalent cases, and 12-month diagnosed prevalent cases of AR segmented by sex, and age (ages ≥5 years) in these markets. The 12-month diagnosed prevalent cases of AR are further segmented by severity (mild and moderate/severe), by type of allergen (grass pollen, birch pollen, cypress pollen, other tree pollen, ragweed pollen, other weed pollen, house dust mite), by comorbdities (asthma, atopic dermatitis, allergic conjunctivitis, pharyngitis, sinusitis, anxiety, depression), and by type of AR (seasonal and perennial).
  • The allergic rhinitis epidemiology report and model were written and developed by Masters- and PhD-level epidemiologists.
  • The Epidemiology Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.
  • The Epidemiology Model is easy to navigate, interactive with dashboards, and epidemiology-based with transparent and consistent methodologies. Moreover, the model supports data presented in the report and showcases disease trends over a 10-year forecast period using reputable sources.

Reasons to buy

The Allergic Rhinitis Epidemiology series will allow you to -

  • Develop business strategies by understanding the trends shaping and driving the global allergic rhinitis market.
  • Quantify patient populations in the global allergic rhinitis market to improve product design, pricing, and launch plans.
  • Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for allergic rhinitis therapeutics in each of the markets covered.
  • Understand magnitude of allergic rhinitis population by severity at diagnosis.

Table of Contents

1 Table of Contents

  • 1.1 List of Tables
  • 1.2 List of Figures

2 Allergic Rhinitis: Executive Summary

  • 2.1 Related Reports
  • 2.2 Upcoming Reports

3 Epidemiology

  • 3.1 Disease Background
  • 3.2 Risk Factors and Comorbidities
  • 3.3 Global and Historical Trends
  • 3.4 Forecast Methodology
    • 3.4.1 Sources
    • 3.4.2 Forecast Assumptions and Methods
  • 3.5 Epidemiological Forecast for AR (2018-2028)
    • 3.5.1 Diagnosed Incident Cases of AR
    • 3.5.2 Age-Specific Diagnosed Incident Cases of AR
    • 3.5.3 Sex-Specific Diagnosed Incident Cases of AR
    • 3.5.4 12-Month Diagnosed Prevalent Cases of AR
    • 3.5.5 Age-Specific 12-Month Diagnosed Prevalent Cases of AR
    • 3.5.6 Sex-Specific 12-Month Diagnosed Prevalent Cases of AR
    • 3.5.7 12-Month Diagnosed Prevalent Cases of AR by Severity
    • 3.5.8 12-Month Diagnosed Prevalent Cases of AR by Type of Allergen
    • 3.5.9 12-Month Total Prevalent Cases of AR
    • 3.5.10 Age-Specific 12-Month Total Prevalent Cases of AR
    • 3.5.11 Sex-Specific 12-Month Total Prevalent Cases of AR
  • 3.6 Discussion
    • 3.6.1 Epidemiological Forecast Insight
    • 3.6.2 Limitations of Analysis
    • 3.6.3 Strengths of Analysis

4 Appendix

  • 4.1 Bibliography
  • 4.2 Primary Research - KOLs Interviewed for This Report
  • 4.3 About the Authors
    • 4.3.1 Epidemiologist
    • 4.3.2 Reviewers
    • 4.3.3 Global Director of Therapy Analysis and Epidemiology
    • 4.3.4 Global Head and EVP of Healthcare Operations and Strategy
  • 4.4 About GlobalData
  • 4.5 Contact Us
  • 4.6 Disclaimer
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