Uveitis – Epidemiology Forecast to 2029

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Uveitis is a condition characterized by the inflammation of the uveal tract (iris, ciliary body, and choroid), but can also cause the inflammation of nearby tissues, such as the retina, the optic nerve, and the vitreous humor. Uveitis can affect one or both eyes. It primarily affects people ages 20-60 years, but can present at any age (National Eye Institute, 2019; Medscape, 2020). Uveitis is an important cause of blindness and visual loss in many communities (Wakefield and Chang, 2005). In most cases, the etiology remains elusive and is often of an autoimmune nature. In instances where the etiology is known, infectious agents or trauma are important causes.

The report includes a 10-year epidemiological forecast for the diagnosed incident and diagnosed prevalent cases of uveitis segmented by sex and age (ages ≥18 years). The diagnosed prevalent cases of uveitis are further segmented into anatomical site of inflammation (anterior, intermediate, posterior, and panuveitis), then by etiology (infectious, non-infectious, and idiopathic), severity (mild and moderate, and severe), and laterality (unilateral and bilateral). The following data describes epidemiology of uveitis. In the 9MM, GlobalData epidemiologists forecast an increase in the diagnosed incident cases of uveitis in adults from 719,115 cases in 2019 to 780,725 cases in 2029, at an AGR of 0.86%. The diagnosed prevalent cases of uveitis in adults in the 9MM are expected to increase from 1,687,303 cases in 2019 to 1,851,766 cases in 2029, at an AGR of 0.97%. Women accounted for more diagnosed incident and diagnosed prevalent cases of uveitis than men in the 9MM and it predominantly affects older adults. These findings are in line with the GlobalData estimates.

Scope

The Uveitis Epidemiology Report and Model provide an overview of the risk factors and global trends of uveitis in the nine major markets (9MM: US, France, Germany, Italy, Spain, UK, Japan, Australia, and Canada).

The report includes a 10-year epidemiological forecast for the diagnosed incident and diagnosed prevalent cases of uveitis segmented by sex and age (ages ≥18 years). The diagnosed prevalent cases of uveitis are further segmented into anatomical site of inflammation (anterior, intermediate, posterior, and panuveitis), then by etiology (infectious, non-infectious, and idiopathic), severity (mild and moderate, and severe), and laterality (unilateral and bilateral). The model associated with this report additionally provides diagnosed incident cases of uveitis segmented into anatomical site of inflammation, etiology, course of disease (acute, recurrent, and chronic), and severity.

The uveitis 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 9MM.

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 Uveitis Epidemiology series will allow you to:

Develop business strategies by understanding the trends shaping and driving the global uveitis market.

Quantify patient populations in the global uveitis 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 uveitis therapeutics in each of the markets covered.

Understand magnitude of uveitis population by anatomical site of inflammation, etiology, course of disease, severity, and laterality.

Table of Contents

Table of Contents

| About GlobalData

1 Uveitis: Executive Summary

1.1 Catalyst

1.2 Related Reports

1.3 Upcoming Reports

2 Epidemiology

2.1 Disease Background

2.2 Risk Factors and Comorbidities

2.3 Global and Historical Trends

2.4 9MM Forecast Methodology

2.4.1 Sources

2.4.2 Forecast Assumptions and Methods

2.4.3 Forecast Assumptions and Methods: Diagnosed Incident and Diagnosed Prevalent Cases of Uveitis – 9MM

2.4.4 Forecast Assumptions and Methods: Diagnosed Prevalent Cases of Uveitis by Anatomical Site of Inflammation

2.4.5 Diagnosed Prevalent Cases of Uveitis by Etiology

2.4.6 Diagnosed Prevalent Cases of Uveitis by Severity

2.4.7 Diagnosed Prevalent Cases of Uveitis by Laterality

2.5 Epidemiological Forecast for Uveitis

2.5.1 Diagnosed Incident Cases of Uveitis

2.5.2 Age-Specific Diagnosed Incident Cases of Uveitis

2.5.3 Sex-Specific Diagnosed Incident Cases of Uveitis

2.5.4 Diagnosed Prevalent Cases of Uveitis

2.5.5 Age-Specific Diagnosed Prevalent Cases of Uveitis

2.5.6 Sex-Specific Diagnosed Prevalent Cases of Uveitis

2.5.7 Diagnosed Prevalent Cases of Uveitis by Anatomical Site of Inflammation, Etiology, and Severity

2.5.8 Diagnosed Prevalent Cases of Uveitis by Laterality

2.6 Discussion

2.6.1 Epidemiological Forecast Insight

2.6.2 COVID-19 Impact

2.6.3 Limitations of Analysis

2.6.4 Strengths of the Analysis

3 Appendix

3.1 Bibliography

3.2 About the Authors

3.2.1 Epidemiologist

3.2.2 Reviewers

3.2.3 Global Director of Therapy Analysis and Epidemiology

3.2.4 Global Head and EVP of Healthcare Operations and Strategy

3.3 Contact Us

Table

Table 1: Summary of Newly Added Data Types

Table 2: Summary of Updated Data Types

Table 3: Risk Factors and Comorbidities for Uveitis

Table 4: Diagnosed Prevalent Cases of Uveitis by Anatomical Site of Inflammation, Etiology, and Severity

Table 5: Diagnosed Prevalent Cases of Uveitis by Laterality

Figures

Figure 1: 9MM, Diagnosed Incident Cases of Uveitis, Both Sexes, N, Ages ≥18 Years, 2019 and 2029

Figure 2: 9MM, Diagnosed Prevalent Cases of Uveitis, Both Sexes, N, Ages ≥18 Years, 2019 and 2029

Figure 3: 9MM, Diagnosed Incidence of Uveitis, Men and Women, Cases Per 100,000 Population, Ages ≥18 Years, 2019

Figure 4: 9MM, Diagnosed Prevalence of Uveitis, Men and Women, %, Ages ≥18 Years, 2019

Figure 5: 9MM, Sources Used and Not Used to Forecast the Diagnosed Incident and Diagnosed Prevalent Cases of Uveitis

Figure 6: 9MM, Sources Used to Forecast the Diagnosed Prevalent Cases of Uveitis by Anatomical Site of Inflammation

Figure 7: 9MM, Sources Used to Forecast the Diagnosed Prevalent Cases of Uveitis by Etiology

Figure 8: 9MM, Sources Used to Forecast the Diagnosed Prevalent Cases of Uveitis by Severity

Figure 9: 9MM, Sources Used to Forecast the Diagnosed Prevalent Cases of Uveitis by Laterality

Figure 10: 9MM, Diagnosed Incident Cases of Uveitis, N, Both Sexes, Ages ≥18 Years, 2019

Figure 11: 9MM, Diagnosed Incident Cases of Uveitis by Age, N, Both Sexes, 2019

Figure 12: 9MM, Diagnosed Incident Cases of Uveitis by Sex, N, Ages ≥18 Years, 2019

Figure 13: 9MM, Diagnosed Prevalent Cases of Uveitis, N, Both Sexes, Ages ≥18 Years, 2019

Figure 14: 9MM, Diagnosed Prevalent Cases of Uveitis by Age, N, Both Sexes, 2019

Figure 15: 9MM, Diagnosed Prevalent Cases of Uveitis by Sex, N, Ages ≥18 Years, 2019

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