AI in Epidemiology Market Size & Share 2022 to 2030
Market Size by Deployment (On-premise, Web-based, Cloud-based), by Application (Infection Prediction & Forecasting, Disease & Syndromic Surveillance, Monitoring Population Health & Incidence/Prevalence), End Use & Forecast.
Report ID: GMI5364
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Published Date: September 2022
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Report Format: PDF
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Authors:
Monali Tayade, Jignesh Rawal
AI in Epidemiology Market Size
Artificial Intelligence in Epidemiology Market size was valued at USD 310 million in 2021 and is set to exhibit a CAGR of more than 27% from 2022 to 2030. This growth is a result of the surge in healthcare expenditures fueling the integration of AI and other optimization technologies in epidemiology.
A steady increase in healthcare costs and premiums continues to pose challenges for government organizations worldwide. Many constituents are facing higher out-of-pocket expenses and premiums as a result of this increase. In order to address such issues, artificial intelligence is being deployed to help curb overhead costs through the automation of processes and tasks. The requirement for lowering incremental healthcare costs will thus stimulate the demand for AI in epidemiology, to help reduce supply expenditures.
Growing risks of data theft may hamper the industry development
Artificial intelligence technology is deployed to analyze large amounts of patient data. The technology can allow healthcare providers to ensure seamless health service management, disease diagnosis, and care delivery. However, this data contains sensitive personal information, increasing the risks of theft and security breaches. The rising susceptibility to data breaches may pose concerns regarding the use of AI-powered health solutions and in turn, assert a negative influence on the artificial intelligence in epidemiology market dynamics.
AI in Epidemiology Market Analysis
Based on the mode of deployment, the artificial intelligence in epidemiology market is bifurcated into web-based and cloud-based segments. The web-based segment is poised to depict a CAGR of more than 26% through 2022-2030. The adoption of web-based software in epidemiology offers numerous benefits, including the ability to merge with other platforms that are interoperable. Web-based resources are also developed to provide health information quickly and support decision-making. Developments such as these will escalate the use of AI in web-based epidemiological data analysis.
In terms of applications, the AI in epidemiology market value from the disease & syndromic surveillance segment is anticipated to reach USD 1.8 billion by 2030. There is an increasing focus on monitoring and management of infectious and chronic diseases. Moreover, availability and high access to patient data are some of the benefits of AI across the application.
Based on end-users, the artificial intelligence in epidemiology market is categorized into healthcare providers, pharmaceutical and biotechnology companies, research labs, and government & state agencies. The research labs segment accounted for over 29% business share in 2021 and will be valued at over USD 935 million by 2030. An increase in the number of grants-in-aid and other support from governments has been observed, to carry out research studies and identify the knowledge gaps in the healthcare sector. Research labs are also using AI technology to conduct epidemiology studies and advance disease detection & prognosis.
North America artificial intelligence in epidemiology market is slated to exhibit a CAGR of 26.5% through 2030. The region has witnessed an escalating usage of AI solutions by federal agencies. The robust presence of major tech players, including Alphabet, IBM, Cerner Corporation, and Microsoft Corporation, will also foster efficient integration of AI in epidemiology. Countries like the U.S. and Canada boast of major pharmaceutical and biotechnology companies which investment significant amounts in research, representing strong potential for AI solution providers in North America.
AI in Epidemiology Market Share
are some of the key companies across AI in epidemiology industry. These companies are introducing strategic programs to drive awareness about the benefit of AI in healthcare.
Impact of COVID-19 Pandemic
The COVID-19 outbreak had an unprecedented impact on the global economy. While this impact has manifested in the form of challenges for many factions of the global economy, for some, such as the AI in epidemiology industry, it has also unearthed new opportunities. In healthcare sector, the pandemic has led to a rise in the deployment of AI, due to the extensive need for digital solutions.
The artificial intelligence in epidemiology market research report includes an in-depth coverage of the industry with estimates & forecast in terms of revenue in USD from 2017 to 2030, for the following segments:
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By Deployment
By Application
By End-use
The above information is provided for the following regions and countries:
Research methodology, data sources & validation process
This report draws on a structured research process built around direct industry conversations, proprietary modelling, and rigorous cross-validation and not just desk research.
Our 6-step research process
1. Research design & analyst oversight
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2. Primary research
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Data mining is a key part of our research process, contributing nearly 20% to the overall methodology. It involves analysing market structure, identifying industry trends, and assessing macroeconomic factors through revenue share analysis of major players. Relevant data is collected from both paid and unpaid sources to build a reliable database. This information is then integrated to support primary research and market sizing, with validation from key stakeholders such as distributors, manufacturers, and associations.
4. Market sizing
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5. Forecast model & key assumptions
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✓ Key growth drivers and their assumed impact
✓ Restraining factors and mitigation scenarios
✓ Regulatory assumptions and policy change risk
✓ Technology adoption curve parameter
✓ Macroeconomic assumptions (GDP growth, inflation, currency)
✓ Competitive dynamics and market entry/exit expectations
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