According to the data from 2025, some 16 percent of respondents said that rising health care costs were the most important health issue facing the United States. Cancer ranked second on the list with 15 percent. Issues with healthcare costsCurrently, the most urgent problem facing American healthcare is the high costs of care. The high expense of healthcare may deter people from getting the appropriate treatment when they need medical care or cause them to completely forego preventative care visits. Many Americans reported that they may skip prescription doses or refrain from taking medication as prescribed due to financial concerns. Such health-related behavior can result in major health problems, which may raise the long-term cost of care. Inflation, medical debt, and unforeseen medical expenses have all added to the burden that health costs are placing on household income. Gun violence issueThe gun violence epidemic has plagued the United States over the past few years, yet very little has been done to address the issue. In recent years, gun violence has become the leading cause of death among American children and teens. Even though more than half of Americans are in favor of tougher gun control regulations, there is little political will to strongly reform the current gun law. Gun violence has a deep traumatic impact on survivors and society, it is developing into a major public health crisis in the United States.

A 2024 survey found that over half of U.S. individuals indicated the cost of accessing treatment was the biggest problem facing the national healthcare system. This is much higher than the global average of 32 percent and is in line with the high cost of health care in the U.S. compared to other high-income countries. Bureaucracy along with a lack of staff were also considered to be pressing issues. This statistic reveals the share of individuals who said select problems were the biggest facing the health care system in the United States in 2024.

We asked U.S. consumers about "Prevalence of health conditions" and found that *************************************************************** takes the top spot, while ************************** is at the other end of the ranking.These results are based on a representative online survey conducted in 2025 among 13,690 consumers in the United States.

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

Changelog:

Update September 20, 2021: Data and overview updated to reflect data used in the September 15 story Over Half of States Have Rolled Back Public Health Powers in Pandemic. It includes 303 state or local public health leaders who resigned, retired or were fired between April 1, 2020 and Sept. 12, 2021. Previous versions of this dataset reflected data used in the Dec. 2020 and April 2021 stories.

Overview

Across the U.S., state and local public health officials have found themselves at the center of a political storm as they combat the worst pandemic in a century. Amid a fractured federal response, the usually invisible army of workers charged with preventing the spread of infectious disease has become a public punching bag.

In the midst of the coronavirus pandemic, at least 303 state or local public health leaders in 41 states have resigned, retired or been fired since April 1, 2020, according to an ongoing investigation by The Associated Press and KHN.

According to experts, that is the largest exodus of public health leaders in American history.

Many left due to political blowback or pandemic pressure, as they became the target of groups that have coalesced around a common goal — fighting and even threatening officials over mask orders and well-established public health activities like quarantines and contact tracing. Some left to take higher profile positions, or due to health concerns. Others were fired for poor performance. Dozens retired. An untold number of lower level staffers have also left.

The result is a further erosion of the nation’s already fragile public health infrastructure, which KHN and the AP documented beginning in 2020 in the Underfunded and Under Threat project.

Findings

The AP and KHN found that:

• One in five Americans live in a community that has lost its local public health department leader during the pandemic
• Top public health officials in 28 states have left state-level departments ## Using this data To filter for data specific to your state, use this query

To get total numbers of exits by state, broken down by state and local departments, use this query

Methodology

KHN and AP counted how many state and local public health leaders have left their jobs between April 1, 2020 and Sept. 12, 2021.

The government tasks public health workers with improving the health of the general population, through their work to encourage healthy living and prevent infectious disease. To that end, public health officials do everything from inspecting water and food safety to testing the nation’s babies for metabolic diseases and contact tracing cases of syphilis.

Many parts of the country have a health officer and a health director/administrator by statute. The analysis counted both of those positions if they existed. For state-level departments, the count tracks people in the top and second-highest-ranking job.

The analysis includes exits of top department officials regardless of reason, because no matter the reason, each left a vacancy at the top of a health agency during the pandemic. Reasons for departures include political pressure, health concerns and poor performance. Others left to take higher profile positions or to retire. Some departments had multiple top officials exit over the course of the pandemic; each is included in the analysis.

Reporters compiled the exit list by reaching out to public health associations and experts in every state and interviewing hundreds of public health employees. They also received information from the National Association of City and County Health Officials, and combed news reports and records.

Public health departments can be found at multiple levels of government. Each state has a department that handles these tasks, but most states also have local departments that either operate under local or state control. The population served by each local health department is calculated using the U.S. Census Bureau 2019 Population Estimates based on each department’s jurisdiction.

KHN and the AP have worked since the spring on a series of stories documenting the funding, staffing and problems around public health. A previous data distribution detailed a decade's worth of cuts to state and local spending and staffing on public health. That data can be found here.

Attribution

Findings and the data should be cited as: "According to a KHN and Associated Press report."

Is Data Missing?

If you know of a public health official in your state or area who has left that position between April 1, 2020 and Sept. 12, 2021 and isn't currently in our dataset, please contact authors Anna Maria Barry-Jester annab@kff.org, Hannah Recht hrecht@kff.org, Michelle Smith mrsmith@ap.org and Lauren Weber laurenw@kff.org.

As of August 2024, some 20 percent of Americans surveyed were of the opinion that opioids and fentanyl addiction is the number one public health threat in the U.S., a significant decrease from 24 percent in June 2024. Furthermore, obesity was viewed as a top public health issue by 19 percent of Americans in August 2024.
U.S. healthcare issues The United States has the highest healthcare spending globally. The majority of Americans considered rising healthcare costs as the most important healthcare problem facing the U.S. in January 2023. While COVID-19 and cancer were ranked second on the list. Due to unfortunate mass shooting incidents in the country, gun violence is typically related to homicide and is not considered a healthcare issue. Although the most popular method of suicide among Americans who attempted it was a gun or firearm, the link between gun access and suicide is frequently ignored as a public health crisis.

41,000 Americans lose their lives to suicide each yearIn 2016, suicide was the 9th leading cause of death among men and 16th leading cause of death among women in Pinal County.1 in 5 American adults have experienced a mental health issue.

Coronavirus (COVID-19) Data in the United States

[ U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real-time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists, and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

United States Data

Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.

Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.

Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

Download all the data or clone this repository by clicking the green "Clone or download" button above.

State-Level Data

State-level data can be found in the states.csv file. (Raw CSV file here.)

date,state,fips,cases,deaths
2020-01-21,Washington,53,1,0
...

County-Level Data

County-level data can be found in the counties.csv file. (Raw CSV file here.)

date,county,state,fips,cases,deaths
2020-01-21,Snohomish,Washington,53061,1,0
...

In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

Methodology and Definitions

The data is the product of dozens of journalists working across several time zones to monitor news conferences, analyze data releases and seek clarification from public officials on how they categorize cases.

It is also a response to a fragmented American public health system in which overwhelmed public servants at the state, county and territorial levels have sometimes struggled to report information accurately, consistently and speedily. On several occasions, officials have corrected information hours or days after first reporting it. At times, cases have disappeared from a local government database, or officials have moved a patient first identified in one state or county to another, often with no explanation. In those instances, which have become more common as the number of cases has grown, our team has made every effort to update the data to reflect the most current, accurate information while ensuring that every known case is counted.

When the information is available, we count patients where they are being treated, not necessarily where they live.

In most instances, the process of recording cases has been straightforward. But because of the patchwork of reporting methods for this data across more than 50 state and territorial governments and hundreds of local health departments, our journalists sometimes had to make difficult interpretations about how to count and record cases.

For those reasons, our data will in some cases not exactly match the information reported by states and counties. Those differences include these cases: When the federal government arranged flights to the United States for Americans exposed to the coronavirus in China and Japan, our team recorded those cases in the states where the patients subsequently were treated, even though local health departments generally did not. When a resident of Florida died in Los Angeles, we recorded her death as having occurred in California rather than Florida, though officials in Florida counted her case in their...

A survey of adults in the United States found that around ** percent of respondents identified mobility issues, cancer, and cognitive decline as their top aging-related health concerns. This statistic depicts the percentage of adults in the United States who had select health concerns related to the aging process as of 2024.

Note: DPH is updating and streamlining the COVID-19 cases, deaths, and testing data. As of 6/27/2022, the data will be published in four tables instead of twelve.

The COVID-19 Cases, Deaths, and Tests by Day dataset contains cases and test data by date of sample submission. The death data are by date of death. This dataset is updated daily and contains information back to the beginning of the pandemic. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-Deaths-and-Tests-by-Day/g9vi-2ahj.

The COVID-19 State Metrics dataset contains over 93 columns of data. This dataset is updated daily and currently contains information starting June 21, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-State-Level-Data/qmgw-5kp6 .

The COVID-19 County Metrics dataset contains 25 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-County-Level-Data/ujiq-dy22 .

The COVID-19 Town Metrics dataset contains 16 columns of data. This dataset is updated daily and currently contains information starting June 16, 2022 to the present. The data can be found at https://data.ct.gov/Health-and-Human-Services/COVID-19-Town-Level-Data/icxw-cada . To protect confidentiality, if a town has fewer than 5 cases or positive NAAT tests over the past 7 days, those data will be suppressed.

COVID-19 cases and associated deaths that have been reported among Connecticut residents, broken down by race and ethnicity. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected. Deaths reported to the either the Office of the Chief Medical Examiner (OCME) or Department of Public Health (DPH) are included in the COVID-19 update.

The following data show the number of COVID-19 cases and associated deaths per 100,000 population by race and ethnicity. Crude rates represent the total cases or deaths per 100,000 people. Age-adjusted rates consider the age of the person at diagnosis or death when estimating the rate and use a standardized population to provide a fair comparison between population groups with different age distributions. Age-adjustment is important in Connecticut as the median age of among the non-Hispanic white population is 47 years, whereas it is 34 years among non-Hispanic blacks, and 29 years among Hispanics. Because most non-Hispanic white residents who died were over 75 years of age, the age-adjusted rates are lower than the unadjusted rates. In contrast, Hispanic residents who died tend to be younger than 75 years of age which results in higher age-adjusted rates.

The population data used to calculate rates is based on the CT DPH population statistics for 2019, which is available online here: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Population/Population-Statistics. Prior to 5/10/2021, the population estimates from 2018 were used.

Rates are standardized to the 2000 US Millions Standard population (data available here: https://seer.cancer.gov/stdpopulations/). Standardization was done using 19 age groups (0, 1-4, 5-9, 10-14, ..., 80-84, 85 years and older). More information about direct standardization for age adjustment is available here: https://www.cdc.gov/nchs/data/statnt/statnt06rv.pdf

Categories are mutually exclusive. The category “multiracial” includes people who answered ‘yes’ to more than one race category. Counts may not add up to total case counts as data on race and ethnicity may be missing. Age adjusted rates calculated only for groups with more than 20 deaths. Abbreviation: NH=Non-Hispanic.

Data on Connecticut deaths were obtained from the Connecticut Deaths Registry maintained by the DPH Office of Vital Records. Cause of death was determined by a death certifier (e.g., physician, APRN, medical examiner) using their best clinical judgment. Additionally, all COVID-19 deaths, including suspected or related, are required to be reported to OCME. On April 4, 2020, CT DPH and OCME released a joint memo to providers and facilities within Connecticut providing guidelines for certifying deaths due to COVID-19 that were consistent with the CDC’s guidelines and a reminder of the required reporting to OCME.25,26 As of July 1, 2021, OCME had reviewed every case reported and performed additional investigation on about one-third of reported deaths to better ascertain if COVID-19 did or did not cause or contribute to the death. Some of these investigations resulted in the OCME performing postmortem swabs for PCR testing on individuals whose deaths were suspected to be due to COVID-19, but antemortem diagnosis was unable to be made.31 The OCME issued or re-issued about 10% of COVID-19 death certificates and, when appropriate, removed COVID-19 from the death certificate. For standardization and tabulation of mortality statistics, written cause of death statements made by the certifiers on death certificates are sent to the National Center for Health Statistics (NCHS) at the CDC which assigns cause of death codes according to the International Causes of Disease 10th Revision (ICD-10) classification system.25,26 COVID-19 deaths in this report are defined as those for which the death certificate has an ICD-10 code of U07.1 as either a primary (underlying) or a contributing cause of death. More information on COVID-19 mortality can be found at the following link: https://portal.ct.gov/DPH/Health-Information-Systems--Reporting/Mortality/Mortality-Statistics

Data are subject to future revision as reporting changes.

Starting in July 2020, this dataset will be updated every weekday.

Additional notes: A delay in the data pull schedule occurred on 06/23/2020. Data from 06/22/2020 was processed on 06/23/2020 at 3:30 PM. The normal data cycle resumed with the data for 06/23/2020.

A network outage on 05/19/2020 resulted in a change in the data pull schedule. Data from 5/19/2020 was processed on 05/20/2020 at 12:00 PM. Data from 5/20/2020 was processed on 5/20/2020 8:30 PM. The normal data cycle resumed on 05/20/2020 with the 8:30 PM data pull. As a result of the network outage, the timestamp on the datasets on the Open Data Portal differ from the timestamp in DPH's daily PDF reports.

Starting 5/10/2021, the date field will represent the date this data was updated on data.ct.gov. Previously the date the data was pulled by DPH was listed, which typically coincided with the date before the data was published on data.ct.gov. This change was made to standardize the COVID-19 data sets on data.ct.gov.

Conducted by the National Association of County and City Health Officials (NACCHO), the purpose of this survey of local health departments (LHDs) was to advance and support the development of a database for LHDs to describe and understand their structure, function, and capacities. A core set of questions was submitted to every LHD. In addition, some LHDs received one of two randomly assigned modules of supplemental questions. The core questions covered governance, funding, workforce (staffing levels, occupations employed, top executive education and licensure), LHD activities, community health assessment and health improvement planning, accreditation through the Public Health Accreditation Board, and policy-making and advocacy. The surveyed LHD activities include immunization, screening for diseases and conditions, treatment for communicable diseases, maternal and child health, epidemiology and surveillance activities, population-based primary prevention activities, and regulation, inspection and/or licensing activities. Topics covered by Module 1 included LHD interaction with academic institutions, Partnerships and collaboration, Cross-jurisdictional sharing of services, Emergency preparedness, and Access to healthcare services. Module 2 examined additional issues related to jurisdiction and governance, community health assessment and planning, human resources issues, quality improvement, public health informatics, and use of the Community Guide of Preventive Services.

Digital Health And Wellness Market Outlook

The global digital health and wellness market size was valued at approximately USD 150 billion in 2023 and is projected to reach nearly USD 600 billion by 2032, growing at a compound annual growth rate (CAGR) of 16.5% during the forecast period. This substantial growth is primarily driven by the increasing adoption of digital health technologies, the rising prevalence of chronic diseases, and the continuous advancements in healthcare IT infrastructure.

One of the major growth factors contributing to the expansion of the digital health and wellness market is the rising prevalence of chronic diseases such as diabetes, cardiovascular diseases, and respiratory disorders. With an aging global population and changing lifestyles, the burden of chronic diseases is escalating, necessitating efficient and innovative healthcare solutions. Digital health technologies, such as telehealth and remote monitoring, offer significant advantages in managing these conditions by facilitating timely interventions and continuous monitoring, thereby improving patient outcomes and reducing healthcare costs.

Another significant factor driving the market growth is the increasing penetration of smartphones and the internet, coupled with the growing awareness and acceptance of digital health solutions among consumers and healthcare providers. Mobile health (mHealth) applications are becoming essential tools for health management, providing users with easy access to health information, remote consultations, and personalized health tracking. The convenience and accessibility offered by these digital health tools are encouraging more individuals to adopt them, leading to a surge in demand and market expansion.

The continuous advancements in healthcare IT infrastructure and the integration of advanced technologies such as artificial intelligence (AI), big data analytics, and the Internet of Things (IoT) are further propelling the digital health and wellness market. These technologies enable more precise diagnostics, personalized treatment plans, and efficient healthcare delivery. For instance, AI-powered algorithms can analyze vast amounts of health data to identify patterns and predict potential health issues, while IoT devices facilitate seamless data exchange between patients and healthcare providers, enhancing the overall efficiency of healthcare services.

Regionally, North America is leading the digital health and wellness market, driven by the high adoption rate of advanced healthcare technologies, supportive government policies, and significant investments in healthcare IT infrastructure. The United States, in particular, is at the forefront, with numerous digital health startups and established firms actively innovating in this space. However, other regions such as Europe and Asia Pacific are also witnessing substantial growth, fueled by increasing healthcare expenditures, rising awareness about digital health solutions, and the expansion of telehealth services.

Connected Health Solutions are becoming increasingly pivotal in the digital health and wellness market, as they offer a seamless integration of various healthcare services through digital platforms. These solutions enable real-time communication and data sharing between patients and healthcare providers, enhancing the quality and efficiency of care. By leveraging technologies such as IoT and AI, Connected Health Solutions facilitate continuous monitoring and personalized healthcare, which is particularly beneficial for managing chronic conditions. The ability to connect different healthcare systems and devices ensures that patients receive comprehensive and coordinated care, reducing the risk of errors and improving overall health outcomes. As the demand for integrated healthcare solutions grows, Connected Health Solutions are set to play a crucial role in transforming the healthcare landscape.

Component Analysis

The digital health and wellness market is segmented by component into software, hardware, and services. Each component plays a crucial role in the functionality and efficiency of digital health solutions, and their interplay determines the overall effectiveness of digital health systems. Software, as a component, encompasses a wide array of applications, including electronic health records (EHRs), telehealth platforms, a

Reporting of new Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. This dataset will receive a final update on June 1, 2023, to reconcile historical data through May 10, 2023, and will remain publicly available.

Aggregate Data Collection Process Since the start of the COVID-19 pandemic, data have been gathered through a robust process with the following steps:

• A CDC data team reviews and validates the information obtained from jurisdictions’ state and local websites via an overnight data review process.
• If more than one official county data source exists, CDC uses a comprehensive data selection process comparing each official county data source, and takes the highest case and death counts respectively, unless otherwise specified by the state.
• CDC compiles these data and posts the finalized information on COVID Data Tracker.
• County level data is aggregated to obtain state and territory specific totals.

Methodology Changes Several differences exist between the current, weekly-updated dataset and the archived version:

• Source: The current Weekly-Updated Version is based on county-level aggregate count data, while the Archived Version is based on State-level aggregate count data.
• Confirmed/Probable Cases/Death breakdown:  While the probable cases and deaths are included in the total case and total death counts in both versions (if applicable), they were reported separately from the confirmed cases and deaths by jurisdiction in the Archived Version.  In the current Weekly-Updated Version, the counts by jurisdiction are not reported by confirmed or probable status (See Confirmed and Probable Counts section for more detail).
• Time Series Frequency: The current Weekly-Updated Version contains weekly time series data (i.e., one record per week per jurisdiction), while the Archived Version contains daily time series data (i.e., one record per day per jurisdiction).
• Update Frequency: The current Weekly-Updated Version is updated weekly, while the Archived Version was updated twice daily up to October 20, 2022.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions report probable cases and deaths to CDC.* Confirmed and probable case definition criteria are described here:

Council of State and Territorial Epidemiologists (ymaws.com).

Deaths CDC reports death data on other sections of the website: CDC COVID Data Tracker: Home, CDC COVID Data Tracker: Cases, Deaths, and Testing, and NCHS Provisional Death Counts. Information presented on the COVID Data Tracker pages is based on the same source (total case counts) as the present dataset; however, NCHS Death Counts are based on death certificates that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Data from each of these pages are considered provisional (not complete and pending verification) and are therefore subject to change. Counts from previous weeks are continually revised as more records are received and processed.

Number of Jurisdictions Reporting There are currently 60 public health jurisdictions reporting cases of COVID-19. This includes the 50 states, the District of Columbia, New York City, the U.S. territories of American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and the U.S Virgin Islands as well as three independent countries in compacts of free association with the United States, Federated States of Micronesia, Republic of the Marshall Islands, and Republic of Palau. New York State’s reported case and death counts do not include New York City’s counts as they separately report nationally notifiable conditions to CDC.

CDC COVID-19 data are available to the public as summary or aggregate count files, including total counts of cases and deaths, available by state and by county. These and other data on COVID-19 are available from multiple public locations, such as:

https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html

https://www.cdc.gov/covid-data-tracker/index.html

https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html

https://www.cdc.gov/coronavirus/2019-ncov/php/open-america/surveillance-data-analytics.html

Additional COVID-19 public use datasets, include line-level (patient-level) data, are available at: https://data.cdc.gov/browse?tags=covid-19.

Archived Data Notes:

November 3, 2022: Due to a reporting cadence issue, case rates for Missouri counties are calculated based on 11 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 3, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Due to a reporting cadence change, case rates for Alabama counties are calculated based on 13 days’ worth of case count data in the Weekly United States COVID-19 Cases and Deaths by State data released on November 10, 2022, instead of the customary 7 days’ worth of data.

November 10, 2022: Per the request of the jurisdiction, cases and deaths among non-residents have been removed from all Hawaii county totals throughout the entire time series. Cumulative case and death counts reported by CDC will no longer match Hawaii’s COVID-19 Dashboard, which still includes non-resident cases and deaths. 

November 17, 2022: Two new columns, weekly historic cases and weekly historic deaths, were added to this dataset on November 17, 2022. These columns reflect case and death counts that were reported that week but were historical in nature and not reflective of the current burden within the jurisdiction. These historical cases and deaths are not included in the new weekly case and new weekly death columns; however, they are reflected in the cumulative totals provided for each jurisdiction. These data are used to account for artificial increases in case and death totals due to batched reporting of historical data.

December 1, 2022: Due to cadence changes over the Thanksgiving holiday, case rates for all Ohio counties are reported as 0 in the data released on December 1, 2022.

January 5, 2023: Due to North Carolina’s holiday reporting cadence, aggregate case and death data will contain 14 days’ worth of data instead of the customary 7 days. As a result, case and death metrics will appear higher than expected in the January 5, 2023, weekly release.

January 12, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0. As a result, case and death metrics will appear lower than expected in the January 12, 2023, weekly release.

January 19, 2023: Due to a reporting cadence issue, Mississippi’s aggregate case and death data will be calculated based on 14 days’ worth of data instead of the customary 7 days in the January 19, 2023, weekly release.

January 26, 2023: Due to a reporting backlog of historic COVID-19 cases, case rates for two Michigan counties (Livingston and Washtenaw) were higher than expected in the January 19, 2023 weekly release.

January 26, 2023: Due to a backlog of historic COVID-19 cases being reported this week, aggregate case and death counts in Charlotte County and Sarasota County, Florida, will appear higher than expected in the January 26, 2023 weekly release.

January 26, 2023: Due to data processing delays, Mississippi’s aggregate case and death data will be reported as 0 in the weekly release posted on January 26, 2023.

February 2, 2023: As of the data collection deadline, CDC observed an abnormally large increase in aggregate COVID-19 cases and deaths reported for Washington State. In response, totals for new cases and new deaths released on February 2, 2023, have been displayed as zero at the state level until the issue is addressed with state officials. CDC is working with state officials to address the issue.

February 2, 2023: Due to a decrease reported in cumulative case counts by Wyoming, case rates will be reported as 0 in the February 2, 2023, weekly release. CDC is working with state officials to verify the data submitted.

February 16, 2023: Due to data processing delays, Utah’s aggregate case and death data will be reported as 0 in the weekly release posted on February 16, 2023. As a result, case and death metrics will appear lower than expected and should be interpreted with caution.

February 16, 2023: Due to a reporting cadence change, Maine’s

A survey of men in the United States from 2022 found that 82 percent of Gen Z respondents said mental health was their leading health concern, compared to just 38 percent of Boomers. This statistic shows the leading health concerns among men in the United States as of 2022, by generation.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Digital Health Platforms Market Outlook

According to our latest research, the global digital health platforms market size reached USD 173.2 billion in 2024, reflecting the sector’s rapid evolution and increasing adoption across healthcare ecosystems worldwide. The market is projected to grow at a robust CAGR of 15.6% from 2025 to 2033, resulting in a forecasted market size of USD 545.8 billion by 2033. This impressive growth trajectory is being driven by the convergence of digital technology and healthcare, a surge in remote care demand, and the ongoing digital transformation initiatives across both public and private healthcare sectors.

The primary growth factor fueling the digital health platforms market is the increasing need for efficient healthcare delivery and cost containment. Healthcare systems globally are grappling with aging populations, rising chronic disease burdens, and the imperative to deliver patient-centered care while managing escalating costs. Digital health platforms, encompassing telemedicine, remote patient monitoring, and healthcare analytics, have emerged as critical enablers for improving care outcomes, enhancing patient engagement, and optimizing resource allocation. The integration of artificial intelligence, big data analytics, and cloud computing into these platforms has further amplified their potential, allowing for real-time data-driven decision-making and personalized healthcare interventions. The pandemic underscored the value of digital health, accelerating investments and policy support for virtual care solutions—momentum that continues to shape the market’s expansion.

Another significant driver is the rapid proliferation of mobile health (mHealth) applications and wearable devices, which empower patients to actively participate in their own health management. The widespread adoption of smartphones and advancements in sensor technology have made it possible for individuals to monitor vital signs, access medical records, and communicate with healthcare professionals from virtually anywhere. This patient-centric approach not only improves adherence to treatment regimens but also facilitates early detection of health issues, leading to better outcomes and reduced healthcare expenditures. Moreover, governments and regulatory bodies are increasingly recognizing the value of digital health platforms, enacting supportive policies and reimbursement frameworks that encourage their widespread implementation.

Interoperability and data integration capabilities have also become pivotal in driving the digital health platforms market forward. As healthcare organizations transition from siloed systems to interconnected digital ecosystems, the ability to seamlessly exchange and analyze health information across disparate platforms is paramount. Digital health platforms are evolving to support standardized data formats and secure data sharing, fostering collaboration among stakeholders and enabling holistic patient care. The emergence of cloud-based solutions has further democratized access to advanced digital health tools, allowing even resource-constrained providers to leverage sophisticated analytics and telehealth functionalities. This paradigm shift is expected to catalyze market growth, particularly in emerging economies where healthcare infrastructure modernization is a top priority.

From a regional perspective, North America continues to dominate the digital health platforms market, underpinned by robust healthcare IT infrastructure, high digital literacy, and substantial investments from both public and private sectors. The United States, in particular, has witnessed widespread adoption of telemedicine and electronic health records, driven by favorable reimbursement policies and a strong emphasis on value-based care. Europe follows closely, benefiting from coordinated digital health strategies and cross-border interoperability initiatives. Meanwhile, the Asia Pacific region is poised for the fastest growth over the forecast period, fueled by large, tech-savvy populations, increasing smartphone penetration, and government-led digital health campaigns. Latin America and the Middle East & Africa are also making significant strides, albeit at a more gradual pace, as they address infrastructure and regulatory challenges to unlock the full potential of digital health platforms.

According to Cognitive Market Research, the global Mobile Health Apps Market size is USD 44151.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 12.20 % from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 17660.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.4 % from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 13245.36 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 10154.78 million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.2 % from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 2207.56 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.6 % from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 883.02 million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.9 % from 2024 to 2031.
The Monitoring Services segment had the largest share in the global Mobile Health Apps Market by application

Market Dynamics of Mobile Health Apps Market

Key Drivers of Mobile Health Apps Market

Rising popularity and benefits of mobile health apps drive growth in the mobile health apps market

The growing visibility of mHealth applications, attributed to their significant advantages in enhancing patient health outcomes, is anticipated to drive the expansion of the mHealth app market. An increasing number of individuals are embracing health applications, contributing to their rising popularity. These applications offer numerous benefits for monitoring patients' health conditions. For instance, data from Business of Apps, a UK-based B2B media and information platform focused on the global app industry, indicates that health app downloads rose from 367 million in 2022 to 375 million in 2023. Consequently, the increased awareness of mHealth applications, due to their effectiveness in improving patient care, is propelling market growth. As smartphones become more affordable and widely available, a broader segment of the population can now access mHealth apps for various functions, ranging from fitness tracking to chronic disease management. In 2021, 44% of U.S. consumers utilized digital tools to monitor their health, while 33% owned a wearable health or wellness device. In 2022, wellness management emerged as the most popular app category, followed by disease and treatment management. The incorporation of advanced sensors and health-tracking features in smartphones further enhances their functionality, enabling users to effortlessly monitor a variety of health metrics. The ongoing enhancement of mobile internet connectivity is essential for enabling users to access applications at any time and from any location, thereby increasing their popularity and usage. A key driver of the mHealth app market is the rising prevalence of chronic illnesses, including diabetes, hypertension, and cardiovascular diseases. For instance, data released by the Centers for Disease Control and Prevention (CDC) in 2023 indicated that coronary heart disease was the leading heart condition in the United States, resulting in approximately 375,476 fatalities in 2021. These health issues necessitate ongoing monitoring and management, which mHealth applications can effectively support. Such applications facilitate real-time data tracking, remote consultations, and tailored care plans, ultimately enhancing patient outcomes and decreasing the frequency of hospital visits. Additionally, the growing awareness of preventive healthcare among consumers is further fueling market expansion, as individuals increasingly look for proactive methods to monitor and enhance their health.

Advancements in Wearable Technology to Boost the Market Growth

Wearable technologies, such as fitness trackers and smartwatches, are now essential components of the mobile health apps market. These gadgets enable the live tracking of diverse health metrics, including heart rate, sleep quality, and physical activity levels. By seamlessly integrating with mobile health applications, these wearables extend their capabilities, offering users valuable insights and tailored suggestions to enhance their overall health and wellness. This i...

Background The United States has experienced high surge in COVID-19 cases since the dawn of 2020. Identifying the types of diagnoses that pose a risk in leading COVID-19 death casualties will enable our community to obtain a better perspective in identifying the most vulnerable populations and enable these populations to implement better precautionary measures. Objective To identify demographic factors and health diagnosis codes that pose a high or a low risk to COVID-19 death from individual health record data sourced from the United States. Methods We used logistic regression models to analyze the top 500 health diagnosis codes and demographics that have been identified as being associated with COVID-19 death. Results Among 223,286 patients tested positive at least once, 218,831 (98%) patients were alive and 4,455 (2%) patients died during the duration of the study period. Through our logistic regression analysis, four demographic characteristics of patients; age, gender, race and region, were deemed to be associated with COVID-19 mortality. Patients from the West region of the United States: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming had the highest odds ratio of COVID-19 mortality across the United States. In terms of diagnoses, Complications mainly related to pregnancy (Adjusted Odds Ratio, OR:2.95; 95% Confidence Interval, CI:1.4 - 6.23) hold the highest odds ratio in influencing COVID-19 death followed by Other diseases of the respiratory system (OR:2.0; CI:1.84 – 2.18), Renal failure (OR:1.76; CI:1.61 – 1.93), Influenza and pneumonia (OR:1.53; CI:1.41 – 1.67), Other bacterial diseases (OR:1.45; CI:1.31 – 1.61), Coagulation defects, purpura and other hemorrhagic conditions(OR:1.37; CI:1.22 – 1.54), Injuries to the head (OR:1.27; CI:1.1 - 1.46), Mood [affective] disorders (OR:1.24; CI:1.12 – 1.36), Aplastic and other anemias (OR:1.22; CI:1.12 – 1.34), Chronic obstructive pulmonary disease and allied conditions (OR:1.18; CI:1.06 – 1.32), Other forms of heart disease (OR:1.18; CI:1.09 – 1.28), Infections of the skin and subcutaneous tissue (OR: 1.15; CI:1.04 – 1.27), Diabetes mellitus (OR:1.14; CI:1.03 – 1.26), and Other diseases of the urinary system (OR:1.12; CI:1.03 – 1.21). Conclusion We found demographic factors and medical conditions, including some novel ones which are associated with COVID-19 death. These findings can be used for clinical and public awareness and for future research purposes.

Treatment for Mental Health Market Outlook

As of 2023, the global market size for mental health treatment was valued at approximately $250 billion and is anticipated to reach $400 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 5.5%. The increasing recognition of mental health issues as critical components of overall health, along with technological advancements in treatment methodologies, is propelling the growth of this market.

A significant growth factor for the mental health treatment market is the rising prevalence of mental health disorders worldwide. The World Health Organization (WHO) reports that depression affects more than 264 million people globally, making it one of the leading causes of disability. The increasing awareness campaigns and educational programs aimed at reducing stigma and encouraging individuals to seek help are also contributing significantly to market growth. Furthermore, governments and private organizations are increasingly investing in mental health infrastructure, policies, and research, thereby boosting the market.

Technological advancements in mental health treatment are another crucial growth driver. The adoption of telemedicine and telepsychiatry has surged, especially in the wake of the COVID-19 pandemic. These technologies offer easier access to mental health services, which is particularly beneficial for individuals in remote areas. Additionally, the development of mobile apps and platforms for cognitive behavioral therapy (CBT) and other therapeutic techniques is making mental health care more accessible and efficient. Innovations in pharmacotherapy, including personalized medicine and the development of new drugs with fewer side effects, are also contributing to market expansion.

Another driving factor is the growing societal acceptance and reduced stigma surrounding mental health issues. Historically, mental health was a taboo topic in many cultures, leading to reluctance in seeking treatment. However, public figures and widespread media campaigns advocating for mental health awareness have significantly shifted public perception. This change is resulting in higher diagnosis rates and more individuals seeking professional help, thereby bolstering market growth. The role of community and peer support groups should not be underestimated, as these social structures encourage individuals to seek and maintain treatment.

When considering the regional outlook, North America holds the largest share of the mental health treatment market due to its advanced healthcare infrastructure and significant investments in mental health. The region also benefits from high levels of awareness and a strong presence of leading market players. Europe follows closely, driven by concerted efforts to integrate mental health services into primary care systems. The Asia Pacific region is expected to witness the highest CAGR, attributed to rapidly developing healthcare infrastructure, increasing awareness, and rising disposable incomes. Latin America and the Middle East & Africa are also seeing growth, though at a slower rate, due to improving healthcare policies and increasing international collaborations.

Psychotherapy Analysis

Psychotherapy remains one of the most commonly employed treatment modalities for mental health disorders. It encompasses various approaches, such as cognitive-behavioral therapy (CBT), dialectical behavior therapy (DBT), psychodynamic therapy, and more. The versatility of psychotherapy in addressing a wide range of mental health issues—from depression and anxiety to more severe conditions like schizophrenia—makes it a cornerstone of mental health treatment. The increasing endorsement of psychotherapy by medical professionals and its proven efficacy in numerous studies are major factors driving its adoption. Additionally, insurance companies are increasingly covering psychotherapy sessions, making them more accessible to a broader population.

The rise of online therapy platforms has revolutionized the psychotherapy segment. Companies like BetterHelp and Talkspace offer virtual therapy sessions, breaking geographical barriers and making mental health treatment accessible from the comfort of one’s home. This trend has gained additional traction during the COVID-19 pandemic, as lockdowns and social distancing measures necessitated remote solutions. Online therapy platforms also offer anonymity, which can be particularly appealing to individuals reluctant to seek in-person therapy due to stigma or privacy concerns.

Cognitive-behavioral therapy (CBT) is partic

Introduction

Global Chatbots for Mental Health & Therapy Market size is expected to be worth around US$ 2.2 Billion by 2033, from US$ 1.3 Billion in 2023, growing at a CAGR of 5.6% during the forecast period from 2024 to 2033. In 2023, North America led the market, achieving over 41.6% share with a revenue of US$ 0.5 Billion.

This growth is fueled by several key drivers, including the increasing prevalence of mental health conditions globally, advancements in natural language processing (NLP) technology, and the growing demand for accessible mental health support solutions.

Rising awareness and the reduction of stigma surrounding mental health issues have encouraged individuals to seek help, accelerating the adoption of chatbots. These tools provide a private and non-judgmental platform for users to express their emotions and receive support, making them an attractive alternative for those hesitant to pursue traditional therapy. Additionally, chatbots are scalable and accessible, offering mental health support to underserved and remote areas with limited healthcare resources. Their 24/7 availability ensures immediate assistance, irrespective of location or time, further enhancing their appeal.

Despite these advantages, the market faces notable challenges. Current chatbot technologies still struggle to fully replicate human emotions and address complex mental health issues, leading to potential shortcomings in the quality of care provided. Advancements in NLP have improved capabilities but remain insufficient to handle nuanced mental health scenarios, which can sometimes result in inappropriate responses. Ethical concerns around data privacy and user consent also pose significant hurdles, emphasizing the need for transparency and user empowerment in chatbot development.

Recent developments highlight growing investment and innovation within the sector. Companies such as Wysa and Woebot Health have secured substantial funding to improve chatbot functionalities and expand their market presence. Additionally, the integration of chatbots with wearable devices and other digital health tools represents a significant trend, enabling more personalized and context-aware mental health support.

In summary, the Chatbots for Mental Health and Therapy Market is expected to experience steady growth, driven by technological progress and increasing demand for accessible mental health solutions, despite facing challenges in emotional comprehension and ethical considerations.