In 2023, nearly two thirds of the respondents surveyed in the United States found it easy to access healthcare. Meanwhile, access to healthcare was perceived difficult by nearly ** percent of Americans surveyed online.

Online Health Assessment Market Outlook

The global online health assessment market size is set to grow from $4.5 billion in 2023 to $12.8 billion by 2032, driven by a robust CAGR of 12.4% from 2024 to 2032. The significant growth factor fueling this market expansion is the increasing adoption of digital health technologies, coupled with the rising demand for convenient and accessible health assessment tools.

The surge in smartphone and internet penetration globally has been a critical growth driver for the online health assessment market. With the proliferation of mobile devices, individuals now have unprecedented access to various health assessment tools through apps and web-based platforms. This has facilitated real-time monitoring and management of health, enabling timely interventions and fostering a preventive healthcare culture. Moreover, the COVID-19 pandemic has accelerated the adoption of digital health solutions, as the need for remote healthcare services became paramount.

Another significant growth factor is the increasing awareness and emphasis on preventive healthcare. Governments and health organizations worldwide are actively promoting health assessments as a means to detect potential health issues early and manage chronic conditions more effectively. This proactive approach not only reduces healthcare costs but also improves patient outcomes. Additionally, the integration of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML) in health assessment tools is enhancing their accuracy and predictive capabilities, thus boosting market growth.

Furthermore, the rise in the prevalence of chronic diseases and mental health disorders is propelling the demand for specialized health assessments. With lifestyle-related diseases such as diabetes, cardiovascular diseases, and mental health issues on the rise, there is a growing need for disease-specific and mental health assessments. These tools offer personalized insights and recommendations, empowering individuals to take control of their health and wellness. Corporate wellness programs are also increasingly leveraging online health assessments to promote employee health and productivity, thereby contributing to market growth.

The integration of Telehealth services has further expanded the reach and utility of online health assessments. By enabling remote consultations and virtual health check-ups, Telehealth bridges the gap between patients and healthcare providers, offering a seamless healthcare experience. This integration is particularly beneficial in rural and underserved areas, where access to healthcare facilities may be limited. Telehealth not only enhances the accessibility of health assessments but also supports continuous patient monitoring and follow-up care, ensuring that individuals receive timely medical attention and advice. As the demand for remote healthcare solutions continues to rise, Telehealth is poised to play a pivotal role in the evolution of the online health assessment market.

Regionally, North America holds a significant share of the online health assessment market, driven by the presence of advanced healthcare infrastructure and high digital literacy. Europe follows closely, with substantial investments in digital health initiatives and a growing focus on preventive care. The Asia Pacific region is expected to witness the highest growth rate, attributed to the expanding healthcare sector, increasing internet penetration, and rising awareness about digital health solutions. Latin America and the Middle East & Africa are also emerging markets, with growing investments in healthcare technology and rising adoption of online health assessments.

Type Analysis

The online health assessment market can be segmented by type into General Health Assessment, Disease-Specific Assessment, Lifestyle Assessment, and Mental Health Assessment. Each of these segments caters to different aspects of healthcare needs and offers unique benefits to users. General Health Assessments provide a broad overview of an individual's health status, including vital parameters such as blood pressure, cholesterol levels, and body mass index (BMI). These assessments are widely used for routine health check-ups and early detection of potential health issues.

In contrast, Disease-Specific Assessments focus on particular health conditions such as diabetes, cardiovascular diseases, or cancer. These assessments are designed to mo

The online health assessment market is experiencing robust growth, driven by increasing smartphone penetration, rising healthcare costs, and a growing preference for convenient, accessible healthcare solutions. The market, valued at approximately $5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. Firstly, the rising adoption of telehealth and remote patient monitoring is significantly impacting the market, offering patients the ability to conduct preliminary health assessments from the comfort of their homes. Secondly, the increasing prevalence of chronic diseases and the need for proactive health management are driving demand for convenient and cost-effective online assessment tools. Finally, technological advancements, including the development of sophisticated algorithms and artificial intelligence (AI)-powered symptom checkers, are enhancing the accuracy and efficiency of online health assessments. This growth is segmented across various user demographics, including teenagers, adults, and the elderly, with each segment exhibiting unique needs and preferences. Condition-specific questionnaires, symptom checkers, and eligibility checkers cater to the diverse requirements of this market. Geographic expansion is also a key driver, with North America currently holding a significant market share, followed by Europe and Asia Pacific. However, developing economies in regions like Asia Pacific and the Middle East & Africa are poised for significant growth due to increasing internet access and healthcare infrastructure development. Restraints to market growth include concerns regarding data privacy and security, the need for regulatory compliance, and the potential for misdiagnosis through automated tools. Nevertheless, the overall market outlook remains positive, with continued innovation and increased user adoption expected to drive sustained expansion throughout the forecast period.

In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the 21st round of the survey (June 2022) include self-reported health status, health insurance coverage, access to health care, disability, COVID-19, awareness of the Medicaid continuous coverage requirement, past-due medical debt, unfair treatment in health care settings, food security, and access to transportation. Additional information collected by the survey includes age, gender, sexual orientation, marital status, education, race and ethnicity, United States citizenship, housing type, home ownership, internet access, income, and employment status.

This is the second survey in the Health Tracking Household Survey (HTHS) series, the successor to the Community Tracking Study (CTS) Household Surveys. The CTS Household Surveys were conducted in 1996-1997 (ICPSR 2524), 1998-1999 (ICPSR 3199), 2000-2001 (ICPSR 3764), and 2003 (ICPSR 4216), and the first HTHS survey was conducted in 2007 (ICPSR 26001). Although the HTHS questionnaires are similar to the CTS Household Survey questionnaires, the HTHS sampling design does not have the community focus intrinsic to CTS. Whereas the CTS design focused on 60 nationally representative communities with sample sizes large enough to draw conclusions about health system change in 12 communities, the HTHS design is a national sample not aimed at measuring change within communities. Hence, "Community" was dropped from the study title. Like the previous surveys, this survey collected information on health insurance coverage, use of health services, health expenses, satisfaction with health care and physician choice, unmet health care needs, usual source of care and patient trust, health status, and adult chronic conditions. In addition, the survey inquired about perceptions of care delivery and quality, problems with paying medical bills, use of in-store retail and onsite workplace health clinics, patient engagement with health care, sources of health information, and shopping for health care. At the beginning of the interview, a household informant provided information about the composition of the household which was used to group the household members into family insurance units (FIU). Each FIU comprised an adult household member, his or her spouse or domestic partner (same sex and other unmarried partners), if any, and any dependent children 0-17 years of age or 18-22 years of age if a full-time student (even if living outside the household). In each FIU in the household, a FIU informant provided information on insurance coverage, health care use, usual source of care, and general health status of all FIU members. This informant also provided information on family income as well as employment, earnings, employer-offered insurance plans, and race/ethnicity for all adult FIU members. Moreover, every adult in each FIU (including the FIU informant) responded through a self-response module to questions that could not be answered reliably by proxy respondents, such as questions about unmet needs, usual source of care, assessments of the quality of care, consumer engagement, satisfaction with physician choice, use of health information, health care shopping, and detailed health questions. The FIU informants responded on behalf of children regarding unmet needs, satisfaction with physician choice, and use of health care information.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

During a survey, more than ** percent of responding consumers who used the internet for medical research stated they began their online research for medical information on search engines such as Google or Bing. Medical information websites, such as WebMD or Healthline, ranked second, mentioned by roughly **** of respondents.

The global Health Status Record Software market is experiencing robust growth, projected to reach $8405.5 million in 2025, expanding at a Compound Annual Growth Rate (CAGR) of 8.3%. This expansion is fueled by several key drivers. Increasing adoption of electronic health records (EHRs) and the rising demand for interoperable healthcare systems are significantly impacting market growth. Furthermore, the growing prevalence of chronic diseases necessitates efficient patient record management, bolstering the demand for comprehensive health status record software. The shift towards value-based care models, emphasizing proactive patient management and improved care coordination, further fuels market expansion. The market is segmented by application (Payer Tethered, Provider Tethered, Others) and type (Cloud-Based, Web-Based), with cloud-based solutions gaining traction due to their scalability and accessibility. North America currently holds a significant market share, driven by advanced healthcare infrastructure and early adoption of technological advancements. However, growth in other regions, particularly Asia Pacific, is expected to accelerate as healthcare infrastructure develops and digital health initiatives gain momentum. Competitive intensity is high, with established players like Cerner Corporation and Allscripts alongside emerging innovative companies like Healthspek and Zapbuild vying for market share. The continued focus on data security and interoperability will be crucial for future market success. The forecast period of 2025-2033 promises continued market expansion, driven by ongoing technological advancements and increasing government initiatives promoting digital health. The adoption of Artificial Intelligence (AI) and Machine Learning (ML) within health status record software is expected to enhance functionalities like predictive analytics and personalized healthcare, further accelerating market growth. However, challenges like data privacy concerns, the need for robust cybersecurity measures, and the initial investment required for implementation could act as potential restraints. Despite these challenges, the overall market trajectory remains positive, indicating substantial opportunities for software providers to capitalize on the increasing demand for efficient and effective health record management systems.

In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a quarterly survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the first quarter 2015 survey (the ninth round of the HRMS) include self-reported health status, awareness of key provisions of the ACA, sources of information about the health plans offered in the ACA marketplace, whether health insurance was purchased through the ACA marketplace, difficulties with access to health care and paying for medical bills and housing costs, out-of-pocket health care costs, type of health insurance coverage if any, and reasons for not having health insurance. Respondents who enrolled in a health insurance plan through the ACA marketplace in 2014 were asked if and why they renewed or changed their plan in 2015. Additional information collected by the survey includes age, gender, sexual orientation, marital status, family size, education, race, Hispanic origin, United States citizenship, housing type, home ownership, internet access, income, employment status, and employer size. The data file also records whether the respondent reported an ambulatory care sensitive condition or a mental or behavioral health condition and whether the respondent or a family member received Social Security, Supplemental Security Income, unemployment insurance benefits or benefits though the Supplement Nutrition Assistance Program, Earned Income Tax Credit, Temporary Assistance for Needy Families, or child care services or child care assistance from a local welfare agency or case manager.

In January 2013, the Urban Institute launched the Health Reform Monitoring Survey (HRMS), a survey of the nonelderly population, to explore the value of cutting-edge, Internet-based survey methods to monitor the Affordable Care Act (ACA) before data from federal government surveys are available. Topics covered by the 11th round of the survey (first quarter 2016) include self-reported health status, type of health insurance coverage, access to and use of health care, out-of-pocket health care costs, health care affordability, health insurance literacy, feelings of unfair treatment by doctors and other health care providers, experience with health insurance marketplaces, awareness of ACA provisions, and rating of neighborhood characteristics. Additional information collected by the survey includes age, gender, sexual orientation, marital status, education, race, Hispanic origin, United States citizenship, housing type, home ownership, internet access, income, employment status, employer size, body mass index, and whether the respondent reported an ambulatory care sensitive condition or a mental or behavioral condition.

Background: The current pandemic of COVID-19 has changed the way health information is distributed through online platforms. These platforms have played a significant role in informing patients and the public with knowledge that has changed the virtual world forever. Simultaneously, there are growing concerns that much of the information is not credible, impacting patient health outcomes, causing human lives, and tremendous resource waste. With the increasing use of online platforms, patients/the public require new learning models and sharing medical knowledge. They need to be empowered with strategies to navigate disinformation on online platforms.Methods and Design: To meet the urgent need to combat health “misinformation,” the research team proposes a structured approach to develop a quality benchmark, an evidence-based tool that identifies and addresses the determinants of online health information reliability. The specific methods to develop the intervention are the following: (1) systematic reviews: two comprehensive systematic reviews to understand the current state of the quality of online health information and to identify research gaps, (2) content analysis: develop a conceptual framework based on established and complementary knowledge translation approaches for analyzing the existing quality assessment tools and draft a unique set of quality of domains, (3) focus groups: multiple focus groups with diverse patients/the public and health information providers to test the acceptability and usability of the quality domains, (4) development and evaluation: a unique set of determinants of reliability will be finalized along with a preferred scoring classification. These items will be used to develop and validate a quality benchmark to assess the quality of online health information.Expected Outcomes: This multi-phase project informed by theory will lead to new knowledge that is intended to inform the development of a patient-friendly quality benchmark. This benchmark will inform best practices and policies in disseminating reliable web health information, thus reducing disparities in access to health knowledge and combat misinformation online. In addition, we envision the final product can be used as a gold standard for developing similar interventions for specific groups of patients or populations.

A search-based Web service that provides access to disease, condition and wellness information via MedlinePlus health topic data in XML format. The service accepts keyword searches as requests and returns relevant MedlinePlus health topics in ranked order. The service also returns health topics summaries, search result snippets and other associated data.

BackgroundThe Global Burden of Disease (GBD) project systematically assesses mortality, healthy life expectancy, and disability across 195 countries and territories, using the disability-adjusted life year (DALY). Disability weights in the DALY are based upon surveys that ask users to rate health states based on lay descriptions. We conducted an experimental study to examine whether the inclusion or removal of psychological, social, or familial implications from a health state description might affect individual judgments about disease severity, and thus relative disability weights.MethodsWe designed a survey consisting of 36 paired descriptions in which information about plausible psychological, social, or familial implications of a health condition was either present or absent. Using a Web-based platform, we recruited 1,592 participants, who were assigned to one of two experimental groups, each of which were asked to assign a value to the health state description from 0 to 100 using a slider, with 0 as the “worst possible health” and 100 as the “best possible health.” We tested five hypotheses: (1) the inclusion of psychological, social, or familial consequences in health state descriptions will reduce the average rating of a health state; (2) the effect will be stronger for diseases with lower disability weights (i.e., less severe diseases); (3) the effect will vary across the type of additional information added to the health state description; (4) the impact of adding information on familial consequences will be stronger for female than male; (5) the effect of additional consequences on ratings of health state descriptions will not differ by levels of completed education and age.ResultsOn average, adding social, psychological, or familial consequences to the health state description lowered individual ratings of that description by 0.78 points. The impact of adding information had a stronger impact on ratings of the least severe conditions, reducing average ratings in this category by 1.67 points. Addition of information about child-rearing had the strongest impact, reducing average ratings by 2.09 points. We found little evidence that the effect of adding information on ratings of health descriptions varied by gender, education, or age.ConclusionsIncluding information about health states not directly related to major functional consequences or symptoms, particularly with respect to child-rearing and specifically for descriptions of less severe conditions, can lead to lower ratings of health. However, this impact was not consistent across all conditions or types of information, and was most pronounced for inclusion of information about child-rearing, and among the least severe conditions.

The State Cancer Profiles (SCP) web site provides statistics to help guide and prioritize cancer control activities at the state and local levels. SCP is a collaborative effort using local and national level cancer data from the Centers for Disease Control and Prevention's National Program of Cancer Registries (NPCR) and National Cancer Institute's Surveillance, Epidemiology and End Results Registries (SEER). SCP address select types of cancer and select behavioral risk factors for which there are evidence-based control interventions. The site provides incidence, mortality and prevalence comparison tables as well as interactive graphs and maps and support data. The graphs and maps provide visual support for deciding where to focus cancer control efforts.

Introduction

Global Healthcare Internet of Things (IoT) Security Market size is expected to be worth around US$ 3.56 Billion by 2033 from US$ 0.62 Billion in 2023, growing at a CAGR of 19.1% during the forecast period from 2024 to 2033. In 2023, North America led the market, achieving over 46.2% share with a revenue of US$ 0.28 Billion.

This remarkable growth is fueled by the widespread adoption of IoT in healthcare, which demands robust security measures to safeguard sensitive patient information and protect healthcare systems against cyber threats. Increased awareness of cybersecurity risks and compliance requirements, such as HIPAA, are driving demand for advanced security solutions to ensure the safety of IoT devices and patient data. Additionally, advancements in technologies like 5G enhance IoT applications but also require stronger security measures to mitigate increased vulnerabilities.

Despite its rapid expansion, the market faces notable challenges. Budget limitations in healthcare organizations restrict investment in advanced IoT security solutions, with only 3-4% of budgets allocated to IT and security upgrades. The absence of standardized protocols and interoperability among IoT devices further complicates effective security implementation. Moreover, limited awareness and education about IoT security risks among healthcare professionals hinder optimal adoption of security technologies.

Recent market developments underscore the sector's evolving landscape. Leading players, including Microsoft and IBM, are advancing IoT security through strategic initiatives. Microsoft’s acquisition of a medical device security firm and IBM’s launch of healthcare data security solutions highlight the industry’s commitment to addressing cyber threats and driving future innovation.

In conclusion, the Healthcare IoT Security Market is poised for substantial growth, emphasizing the critical need for secure, connected healthcare systems. Sustained investment in technology and educational initiatives will be essential to protect sensitive health data and strengthen the security framework of healthcare IoT systems.

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With 90 percent each, Walgreens and CVS are two of the most well-known beauty and health online shops in the U.S. Another American brand, Bath & Body Works, comes third in this list as it is recognized by 85 percent of internet respondents. Rite Aid claims the fourth spot followed by Sephora and ULTA. For this study, brand awareness was surveyed employing the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name. Interested in more detailed results covering all brands of this ranking and many more? Explore GCS Brand Profiles. These statistics show results of the Brand KPI survey.

After over two years of public reporting, the Community Profile Report will no longer be produced and distributed after February 2023. The final release will be on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker.

The Community Profile Report (CPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, under the White House COVID-19 Team. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services, the Centers for Disease Control and Prevention, the Assistant Secretary for Preparedness and Response, and the Indian Health Service). The CPR provides easily interpretable information on key indicators for all regions, states, core-based statistical areas (CBSAs), and counties across the United States. It is a snapshot in time that: