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Global Artificial Intelligence in Epidemiology Market

Artificial Intelligence in Epidemiology Market Size, Share & Trends Analysis Report By Deployment (Web-Based, Cloud-Based), By Application (Infection Prediction and Forecasting, Disease and Syndromic Surveillance), By End-Use, By Region, And by Segment Forecasts, 2024-2031

Report ID : 1450 | Published : 2024-04-15 | Pages: 180 | Format: PDF/EXCEL

The Artificial Intelligence in Epidemiology Market Size is valued at 380.58 Million in 2023 and is predicted to reach 3,496.11 Million by the year 2031 at an 28.62 % CAGR during the forecast period for 2024-2031.

Key Industry Insights & Findings from the Report:

  • Artificial intelligence enables us to efficiently process and analyze large and complex data sets, including electronic health records, genomic data, and social determinants of health. This skill is essential for epidemiologists to discover patterns, trends, and relationships.
  • Artificial intelligence will facilitate real-time monitoring of health data, allowing epidemiologists to detect and respond to disease outbreaks more quickly. This is particularly important for infectious diseases, where early detection can lead to effective containment measures.
  • North America dominated the market and accounted for a revenue share of global revenue in 2023.
  • Incomplete or biased data AI models rely heavily on the quality and representativeness of the data used for training. Incomplete or biased data sets can cause models to not generalize well to various populations, leading to biased predictions.

Epidemioogy

Artificial intelligence (AI) is an intelligent system that performs various human intelligence-based operations in domains such as biology, computer science, mathematics, linguistics, psychology, and engineering. These talents include reasoning, learning, and problem-solving. In the healthcare industry, artificial intelligence is used to analyze complex medical data using algorithms and software. Rising public awareness of the significance of technology in chronic disease diagnosis and monitoring will be a significant driving force in the progress of AI applications in epidemiology. As healthcare research and development efforts expand, so will the demand for artificial intelligence in epidemiology labs.

The extensive usage and use of AI in drug research and discovery activities is a critical motivator. Pharmaceutical and biotech companies have also increased their R&D investments. This investment interest is driving the adoption of AI systems to follow the progression of syndromic diseases. The growing burden of chronic diseases has increased the need for effective control measures and the development of feasible treatment solutions. Government-backed programs, more significant investment from private investors and venture capitalists, and the creation of AI-focused start-ups worldwide are driving market expansion. Despite the prevalence of the diseases, the high cost of these techniques may impede the growth of the worldwide AI-based critical care market.

Market Segmentation:

Artificial intelligence in the epidemiology market is segmented on the deployment, applications and end users. Based on deployment, the market is segmented into web-based and cloud-based. Based on application, artificial intelligence in the epidemiology market is segmented into infection prediction & forecasting and disease & syndromic surveillance. Based on the end user, artificial intelligence in the epidemiology market is segmented into government & state agencies, research labs, pharmaceutical & biotechnology companies, and healthcare providers.

Based on end users, the healthcare providers segment is accounted as a significant contributor to artificial intelligence in the epidemiology market

The market's leading segment is healthcare providers. As a result of recent increases in awareness and correction of some common misconceptions about the intake of certain veggies, consumer acceptance and widespread application for equestrian and cow feeding are expected to drive demand for GMO veggies, strengthening segmental development.

The web-based segment witnessed growth at a rapid rate

Web-based grabbed the highest revenue share, and it is anticipated that they will continue to hold that position during the expected time. Adopting web-based software in epidemiology provides various advantages, including the possibility of integrating with other interoperable platforms. Web-based resources are also being developed to give health information and aid decision-making quickly. Such advancements will accelerate the use of AI in web-based epidemiological data analysis.

The North American artificial intelligence in epidemiology market holds a significant revenue share in the region

The North American artificial intelligence in epidemiology market is expected to register the highest market share in revenue shortly. Because of developments in healthcare IT infrastructure, rising healthcare expenditures, widespread technology use, favourable government efforts, and the presence of numerous key market competitors, The region has seen an increase in the use of AI technologies by federal authorities. The presence of key technology players will also facilitate the efficient integration of AI in epidemiology. Countries such as the United States and Canada are home to big pharmaceutical and biotechnology corporations that invest heavily in research, indicating a promising future for North American AI solution suppliers. Besides, Asia-Pacific is predicted to increase due to significant breakthroughs and development in IT infrastructure and entrepreneurial initiatives specialized in AI-based technologies. Artificial intelligence (AI) is an intelligent system that performs various functions.

Competitive Landscape

Some major key players in the Artificial Intelligence in Epidemiology Market:

  • Cognizant Technology Solutions Corporation,
  • Cerner Corporation (Oracle),
  • Epic Systems Corporation,
  • eClinicalWorks LLC,
  • Alphabet Inc.,
  • Komodo Health,
  • Microsoft Corporation,
  • Meditech,
  • Predixion Software,
  • Siemens Healthineers AG,
  • Intel Corporation,
  • Bayer Healthcare,
  • Artificial Intelligence for Medical Epidemiology (AIME),
  • Cardiolyse,
  • SAS Institute, Inc

Artificial Intelligence in Epidemiology Market Report Scope: 

Report Attribute

Specifications

Market size value in 2023

USD 480.58 Million

Revenue forecast in 2031

USD 3,496.11 Million

Growth rate CAGR

CAGR of 28.62 % from 2024 to 2031

Quantitative units

Representation of revenue in US$ Million and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report coverage

The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends

Segments covered

Deployment, Application, End-Use

Regional scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico ;The UK; France; Italy; Spain; China; Japan; India; South Korea; South East Asia; South Korea; South East Asia

Competitive Landscape

Cognizant Technology Solutions Corporation, Cerner Corporation (Oracle), Epic Systems Corporation, eClinicalWorks LLC, Alphabet Inc., Komodo Health, Microsoft Corporation, Meditech, Predixion Software, Siemens Healthineers AG, Intel Corporation, Bayer Healthcare, Artificial Intelligence for Medical Epidemiology (AIME), Cardiolyse, and SAS Institute, Inc

Customization scope

Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing and available payment methods

Explore pricing alternatives that are customized to your particular study requirements.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Artificial Intelligence In Epidemiology Market Snapshot

Chapter 4. Global Artificial Intelligence In Epidemiology Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Deployment Type Estimates & Trend Analysis

5.1. by Deployment Type & Market Share, 2019 & 2031

5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Deployment Type:

5.2.1. On-premise

5.2.2. Cloud-based

5.2.3. Web-based

Chapter 6. Market Segmentation 2: by Application Estimates & Trend Analysis

6.1. by Application & Market Share, 2019 & 2031

6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:

6.2.1. Infection Prediction and Forecasting

6.2.2. Disease and Syndromic Surveillance

Chapter 7. Market Segmentation 3: by End-use Estimates & Trend Analysis

7.1. by End-use & Market Share, 2019 & 2031

7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-use:

7.2.1. Government and State Agencies

7.2.2. Research Labs

7.2.3. Pharmaceutical and Biotechnology Companies

7.2.4. Healthcare Providers

Chapter 8. Artificial Intelligence In Epidemiology Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America

8.1.1. North America Artificial Intelligence In Epidemiology Market Revenue (US$ Million) Estimates and Forecasts by Deployment Type, 2019-2031

8.1.2. North America Artificial Intelligence In Epidemiology Market Revenue (US$ Million) Estimates and Forecasts by Application, 2019-2031

8.1.3. North America Artificial Intelligence In Epidemiology Market revenue (US$ Million) by End-use, 2019-2031

8.1.4. North America Artificial Intelligence In Epidemiology Market Revenue (US$ Million) Estimates and Forecasts by country, 2019-2031

8.2. Europe

8.2.1. Europe Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Deployment Type, 2019-2031

8.2.2. Europe Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Application, 2019-2031

8.2.3. Europe Artificial Intelligence In Epidemiology Market revenue (US$ Million) by End-use, 2019-2031

8.2.4. Europe Artificial Intelligence In Epidemiology Market revenue (US$ Million) by country, 2019-2031

8.3. Asia Pacific

8.3.1. Asia Pacific Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Deployment Type, 2019-2031

8.3.2. Asia Pacific Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Application, 2019-2031

8.3.3. Asia-Pacific Artificial Intelligence In Epidemiology Market revenue (US$ Million) by End-use, 2019-2031

8.3.4. Asia Pacific Artificial Intelligence In Epidemiology Market revenue (US$ Million) by country, 2019-2031

8.4. Latin America

8.4.1. Latin America Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Deployment Type, 2019-2031

8.4.2. Latin America Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Application, 2019-2031

8.4.3. Latin America Artificial Intelligence In Epidemiology Market revenue (US$ Million) by End-use, 2019-2031

8.4.4. Latin America Artificial Intelligence In Epidemiology Market revenue (US$ Million) by country, 2019-2031

8.5. Middle East & Africa

8.5.1. Middle East & Africa Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Deployment Type, 2019-2031

8.5.2. Middle East & Africa Artificial Intelligence In Epidemiology Market revenue (US$ Million) by Application, 2019-2031

8.5.3. Middle East & Africa Artificial Intelligence In Epidemiology Market revenue (US$ Million) by End-use, 2019-2031

8.5.4. Middle East & Africa Artificial Intelligence In Epidemiology Market revenue (US$ Million) by country, 2019-2031

Chapter 9. Competitive Landscape

9.1. Major Mergers and Acquisitions/Strategic Alliances

9.2. Company Profiles

9.2.1. Cognizant Technology Solutions Corporation

9.2.2. Cerner Corporation (Oracle)

9.2.3. Epic Systems Corporation

9.2.4. eClinicalWorks LLC

9.2.5. Alphabet Inc.

9.2.6. Komodo Health

9.2.7. Microsoft Corporation

9.2.8. Meditech

9.2.9. Predixion Software

9.2.10. Siemens Healthineers AG

9.2.11. Intel Corporation

9.2.12. Bayer Healthcare

9.2.13. Artificial Intelligence for Medical Epidemiology (AIME)

9.2.14. Cardiolyse

9.2.15. SAS Institute, Inc.

9.2.16. Other Prominent Players

 

By Deployment

  • Cloud-based
  • Web-based

epidemiology

By Application

  • Infection Prediction and Forecasting
  • Disease and Syndromic Surveillance

By End-use

  • Government and State Agencies
  • Research Labs
  • Pharmaceutical and Biotechnology Companies
  • Healthcare Providers"

By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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Frequently Asked Questions

How big is the Artificial Intelligence in Epidemiology Market?

Artificial Intelligence in Epidemiology Market expected to grow at a 28.62 % CAGR during the forecast period for 2024-2031

Cognizant Technology Solutions Corporation, Cerner Corporation (Oracle), Epic Systems Corporation, eClinicalWorks LLC, Alphabet Inc., Komodo Health, M

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