After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was 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 State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level. It is a weekly snapshot in time that: Focuses on recent outcomes in the last seven days and changes relative to the month prior Provides additional contextual information at the county level for each state, and includes national level information Supports rapid visual interpretation of results with color thresholds

This work is part of a larger longitudinal study of the impact of COVID-19 on the daily life of people living in remote Alaskan communities. The parent study began in September 2020, five and half months after the Governor of Alaska issued the first COVID-19 health mandate. At the start of the study, we conducted 23 key informant interviews with residents in remote Alaskan communities in leadership positions, who were involved in the COVID-19 response, and/or who could provide a cultural perspective of ongoing events in their community. These conversations, along with consultation of Tribal and state representatives involved in Alaska’s pandemic response, guided the development of three waves of online surveys for individuals living in remote Alaskan communities. Data were collected via three survey waves (Wave 1: November 9 through 15 December 2020; Wave 2: March 9 to 25 March 2021; Wave 3: September 2–27). The surveys included questions regarding life changes due to COVID-19, coping strategies, emotions and worries related to the virus, perceived risks, sources of information, vaccine and testing perceptions, and questions regarding age, gender, level of education, household income, occupation, healthcare access, number of people living in the household, and access to water and sanitation services. Survey questions are available upon request.

This dataset tracks the updates made on the dataset "COVID-19 State Profile Report - Alaska" as a repository for previous versions of the data and metadata.

The dataset contains COVID-19 data summary tables on confirmed cases of COVID-19, geographic distribution of cases, demographic distribution of confirmed cases, daily cases hospitalizations and deaths, and the geographic distribution of tests in Alaska.

Case Data D contains information on recorded out of state COVID-19 Cases for the state of Alaska.

United States SB: Alaska (AK): COVID-19 Impact: Large Negative Effect data was reported at 22.800 % in 11 Apr 2022. This records a decrease from the previous number of 30.100 % for 04 Apr 2022. United States SB: Alaska (AK): COVID-19 Impact: Large Negative Effect data is updated weekly, averaging 29.950 % from Nov 2020 (Median) to 11 Apr 2022, with 54 observations. The data reached an all-time high of 38.900 % in 12 Apr 2021 and a record low of 16.400 % in 16 Aug 2021. United States SB: Alaska (AK): COVID-19 Impact: Large Negative Effect data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S053: Small Business Pulse Survey: by State: West Region: Weekly, Beg Monday (Discontinued).

The data set contains written transcripts from 50 local key informant interviews in real time about the early phases of COVID-19 impacts and adaptive responses taken by the City and Borough of Juneau, Alaska USA. During the early phases of the pandemic (2020) key informants, including healthcare professionals, elected officials, local government managers, and Indigenous peoples, provided in-depth insights and local and Indigenous knowledge and information about their organizations and community response. Tlingit and Haida people interviewed for this project stressed the themes of resiliency, worldview, cultural values and knowledge, and adaptation. The transcripts served as primary sources and evidence for our research findings published in the State and Local Government Review.

Note: The cumulative case count for some counties (with small population) is higher than expected due to the inclusion of non-permanent residents in COVID-19 case counts.

Reporting of Aggregate Case and Death Count data was discontinued on 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.

Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported through a robust process with the following steps:

• Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
• If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
• A CDC data team reviewed counts for congruency prior to integration. CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
• Cases and deaths are based on date of report and not on the date of symptom onset. CDC calculates rates in this data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
• COVID-19 aggregate case and death data were organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts were calculated as the week-to-week change in reported cumulative cases and deaths (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the week before.

This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues. CDC also worked with jurisdictions after the end of the public health emergency declaration to finalize county data.

• Source: The weekly archived dataset is based on county-level aggregate count data
• Confirmed/Probable Cases/Death breakdown: Cumulative cases and deaths for each county are included. Total reported cases include probable and confirmed cases.
• Time Series Frequency: The weekly archived dataset contains weekly time series data (i.e., one record per week per county)

Important note: The counts reflected during a given time period in this dataset may not match the counts reflected for the same time period in the daily archived dataset noted above. Discrepancies may exist due to differences between county and state COVID-19 case surveillance and reconciliation efforts.

The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implement these case classifications. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

Confirmed and Probable Counts In this dataset, counts by jurisdiction are not displayed by confirmed or probable status. Instead, counts of confirmed and probable cases and deaths are included in the Total Cases and Total Deaths columns, when available. Not all jurisdictions reported probable cases and deaths to CDC. Confirmed and probable case definition criteria are described here: "https://ndc.services.cdc.gov/case-definitions/coronavirus-disease-2019-covid-19/">Coronavirus Disease 2019 (COVID-19) 2023 Case Definition | CDC Council of State and Territorial Epidemiologists (ymaws.com).

Deaths COVID-19 deaths were reported to CDC from several sources since the beginning of the pandemic including aggregate death data and NCHS Provisional Death Counts. Historic information presented on the COVID Data Tracker pages were based on the same source (Aggregate Data) as the present dataset until the expiration of the public health emergency declaration on May 11, 2023; however, the NCHS Death Counts are based on death certificate data that use information reported by physicians, medical examiners, or coroners in the cause-of-death section of each certificate. Counts from previous weeks were continually revised as more records were received and processed.

Number of Jurisdictions Reporting There were 60 public health jurisdictions that reported cases and deaths of COVID-19. This included 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. In total there were 3,222 counties for which counts were tracked within the 60 public health jurisdictions.

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

Note: In early 2020, Alaska enacted changes to their counties/boroughs due to low populations in certain areas:

Case and death counts for Yakutat City and Borough, Alaska, are shown as 0 by default. Case and death counts for Hoonah-Angoon Census Area, Alaska, represent total cases and deaths in residents of Hoonah-Angoon Census Area, Alaska, and Yakutat City and Borough, Alaska. Case and death counts for Bristol Bay Borough, Alaska, are shown as 0 by default. Case and death counts for Lake and Peninsula Borough, Alaska, represent total cases and deaths in residents of Lake and Peninsula Borough, Alaska, and Bristol Bay Borough, Alaska.

Historical cases and deaths are not tracked separately in the county level datasets, and differences in weekly new cases and deaths could exist when county-level data are aggregated to the state-level (i.e., when compared to this dataset: https://data.cdc.gov/Case-Surveillance/United-States-COVID-19-Cases-and-Deaths-by-State-o/9mfq-cb36).

Downloadable Excel file of COVID data summary tables. Managed by the State of Alaska Department of Health and Social Services.

IntroductionAmerican Indian/Alaska Native (AI/AN) communities are more likely to suffer negative consequences related to substance misuse. The COVID-19 pandemic exacerbated the opioid poisoning crisis, in combination with ongoing treatment barriers resulting from settler-colonialism, systemic oppression and racial discrimination. AI/AN adults are at greatest risk of COVID-19 related serious illness and death. In collaboration with an Indigenous community advisory board and Tribal leadership, this study explored AI/AN treatment provider perceptions of client-relatives’ (i.e., SUD treatment recipients) experiences during the pandemic from 2020 to 2022.MethodsProviders who underwent screening and were eligible to participate (N = 25) represented 6 programs and organizations serving rural and urban areas in Washington, Utah, and Minnesota. Participants engaged in audio-recorded 60–90 min semi-structured individual interviews conducted virtually via Zoom. The interview guide included 15 questions covering regulatory changes, guidance for telemedicine, policy and procedures, staff communication, and client-relatives’ reactions to implemented changes, service utilization, changes in treatment modality, and perceptions of impact on their roles and practice. Interview recordings were transcribed and de-identified. Members of the research team independently reviewed transcripts before reaching consensus. Coding was completed in Dedoose, followed by analyses informed by a qualitative descriptive approach.ResultsFive main domains were identified related to client-relative experiences during the COVID-19 pandemic, as observed by providers: (1) accessibility, (2) co-occurring mental health, (3) social determinants of health, (4) substance use, coping, and harm reduction strategies, and (5) community strengths. Providers reported the distinctive experiences of AI/AN communities, highlighting the impact on client-relatives, who faced challenges such as reduced income, heightened grief and loss, and elevated rates of substance use and opioid-related poisonings. Community and culturally informed programming promoting resilience and healing are outlined.ConclusionFindings underscore the impact on SUD among AI/AN communities during the COVID-19 pandemic. Identifying treatment barriers and mental health impacts on client-relatives during a global pandemic can inform ongoing and future culturally responsive SUD prevention and treatment strategies. Elevating collective voice to strengthen Indigenous informed systems of care to address the gap in culturally-and community-based services, can bolster holistic approaches and long-term service needs to promote SUD prevention efforts beyond emergency response efforts.

United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Alaska data was reported at 102.000 Number in 28 Jan 2023. This records an increase from the previous number of 101.000 Number for 21 Jan 2023. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Alaska data is updated weekly, averaging 88.000 Number from Jan 2017 to 28 Jan 2023, with 317 observations. The data reached an all-time high of 104.000 Number in 31 Dec 2022 and a record low of 75.000 Number in 15 Apr 2017. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Alaska data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G014: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted.

This dataset includes transcriptions of interviews with Indigenous Individuals from Alaska and the US Southwest conducted over Zoom between March and July 2021. The interviews focused on individual’s access to harvested traditional foods as well as store bought food during the first year of the COVID-19 pandemic as well as institutional responses to support food access during this period. 31 semi-structured interviews were recorded (with permission), transcribed, and anonymized. Audio recordings were deleted to maintain participant confidentiality. The transcribed interviews are being stored on a secure server at the University of Arizona and due to potential sensitivity of the data, are not publicly available.

The contents of this dataset include 20 cleaned, deidentified interview transcripts from the dissertation project titled: "Exploring the COVID-19 Infodemic in Alaska". The NSF grant # is 2309906. Interviews took place via Zoom between January and March 2024 and included participants from across Alaska. The COVID-19 pandemic has been accompanied by an unprecedented infodemic, characterized by the proliferation of both accurate and misleading information. Efforts to better describe the impacts of misinformation during the pandemic can facilitate the development of tools and policies aimed at managing future infodemics. We aimed to investigate the infodemic experiences of COVID-19 responders and identify themes that cut across sectors. This study explored how the circulation of false, incomplete, and excessive information affected individuals responding to the COVID-19 pandemic, including healthcare providers, public health professionals, leadership, members of the media, K-12 school staff, tribal organizations, and others. Using a One Health framework to guide recruitment, we conducted 20 semi-structured interviews over video conference and analyzed them using mixed inductive/deductive thematic analysis. Our findings coalesced around three principal themes: misinformation management, misinformation impacts and lessons learned. Building trust, promoting equity, and ensuring adequate resources (such as staffing and time) stood out as critical components to successfully combating misinformation. Conversely, a lack of communication/collaboration and intense politicization of COVID-19 made the response exceedingly difficult. The infodemic had direct impacts on the community, professional practice across fields and mental and physical health, many of which will have a continued effect moving forward. The lessons learned from this study can be applied towards efforts to better prepare us for the next public health emergency by enabling a more informed and agile response.

As of March 10, 2023, the state with the highest rate of COVID-19 cases was Rhode Island followed by Alaska. Around 103.9 million cases have been reported across the United States, with the states of California, Texas, and Florida reporting the highest numbers of infections.

From an epidemic to a pandemic The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. The term pandemic refers to multiple outbreaks of an infectious illness threatening multiple parts of the world at the same time; when the transmission is this widespread, it can no longer be traced back to the country where it originated. The number of COVID-19 cases worldwide is roughly 683 million, and it has affected almost every country in the world.

The symptoms and those who are most at risk Most people who contract the virus will suffer only mild symptoms, such as a cough, a cold, or a high temperature. However, in more severe cases, the infection can cause breathing difficulties and even pneumonia. Those at higher risk include older persons and people with pre-existing medical conditions, including diabetes, heart disease, and lung disease. Those aged 85 years and older have accounted for around 27 percent of all COVID deaths in the United States, although this age group makes up just two percent of the total population

The study on the COVID-19 gendered policy responses in the Arctic aims to improve understanding of the impacts of the COVID-19 pandemic on women in the New Arctic at regional and local levels. The dataset provides information on a wide range of policy measures introduced by Arctic countries' governments to tackle the COVID-19 pandemic in order to promote sustainability in the region, as well as identifies gender-responsive policies. These policies directly address women's economic and social security, including unpaid care, female-dominated sectors of the economy, and violence against women. In addition, the dataset includes information about COVID-19 Task Forces, highlighting gender composition. This study followed the methodology developed by the United Nations (UN) Development Programme and UN Women, yet the novelty of this study is that it is designed to aggregate COVID-19 measures implemented by various levels of governance. As a showcase of different levels of governance, the dataset uses the examples of the selected study sites – Iceland, Russia, and the United States – to test a new approach. For the United States, it highlights measures at the state (Alaska) level and municipal level (cities of Anchorage, Fairbanks, Juneau, and town of Nome). For Iceland – the municipal level (city of Akureyri and town of Húsavík). For Russia, it covers the regional (Nenets and Chukotka Regions) and municipal (city of Naryan-Mar and town of Pevek) levels. In addition, the dataset includes national policy measures for Canada, Finland, Greenland (data for Greenland are currently not readily accessible; thus, the dataset provides information about policy measures for the Kingdom of Denmark), Iceland, Norway, Russia, Sweden, and the United States, as identified by the UN. Based on this dataset, the COVID-GEA project developed the Arctic COVID-19 Gender Response Tracker (COVID-GEA Tracker). The COVID-GEA Tracker is available here: https://www.arcticcovidgender.org/tracker The study is based on publicly available data, including official documents, and the UN COVID-19 Global Gender Response Tracker data.

United States Excess Deaths excl COVID: Predicted: Upper Bound: Alaska data was reported at 119.000 Number in 16 Sep 2023. This stayed constant from the previous number of 119.000 Number for 09 Sep 2023. United States Excess Deaths excl COVID: Predicted: Upper Bound: Alaska data is updated weekly, averaging 104.000 Number from Jan 2017 (Median) to 16 Sep 2023, with 350 observations. The data reached an all-time high of 119.000 Number in 16 Sep 2023 and a record low of 98.000 Number in 02 Jun 2018. United States Excess Deaths excl COVID: Predicted: Upper Bound: Alaska data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G012: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted (Discontinued).

These data were collected through three online Qualtrics surveys in 2020 and 2021. Data are provided in STATA format and linked at the respondent level across three surveys (i.e. panel data). Surveys were conducted in the Bristol Bay region of Alaska and targeted fisheries participants and local residents for participation. Related data include individual and household demographics, and health information. Also included is information from several questions asking subjects how they perceive the COVID-19-related risks and the relative importance they place on local mitigation policies. Information from a lottery question, used to determine subject earnings, is also included and is based on an experiment used in Charness and Genicot (2009). The dataset contains 1,867 observations and 258 variables and represents information from 903 subjects. Alfred Allen provided extensive assistance in creating the merged data file.

United States COVID-19: No. of Deaths: To Date: Alaska data was reported at 1,485.000 Person in 11 Sep 2023. This stayed constant from the previous number of 1,485.000 Person for 10 Sep 2023. United States COVID-19: No. of Deaths: To Date: Alaska data is updated daily, averaging 1,100.000 Person from Mar 2020 (Median) to 11 Sep 2023, with 1275 observations. The data reached an all-time high of 1,485.000 Person in 11 Sep 2023 and a record low of 1.000 Person in 24 Mar 2020. United States COVID-19: No. of Deaths: To Date: Alaska data remains active status in CEIC and is reported by Alaska Department of Health and Social Services. The data is categorized under High Frequency Database’s Disease Outbreaks – Table US.D001: Center for Disease Control and Prevention: Coronavirus Disease 2019 (COVID-2019). As of Dec 17, 2022, source started reporting data on a weekly basis. As of Jun 05, 2023, source moved to a monthly basis of reporting data.

A. SUMMARY This dataset includes San Francisco COVID-19 tests by race/ethnicity and by date. This dataset represents the daily count of tests collected, and the breakdown of test results (positive, negative, or indeterminate). Tests in this dataset include all those collected from persons who listed San Francisco as their home address at the time of testing. It also includes tests that were collected by San Francisco providers for persons who were missing a locating address. This dataset does not include tests for residents listing a locating address outside of San Francisco, even if they were tested in San Francisco.

The data were de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected). If a person tested multiple times on the same date, only one test is included from that date. When there are multiple tests on the same date, a positive result, if one exists, will always be selected as the record for the person. If a PCR and antigen test are taken on the same day, the PCR test will supersede. If a person tests multiple times on the same day and the results are all the same (e.g. all negative or all positive) then the first test done is selected as the record for the person.

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco.

When a person gets tested for COVID-19, they may be asked to report information about themselves. One piece of information that might be requested is a person's race and ethnicity. These data are often incomplete in the laboratory and provider reports of the test results sent to the health department. The data can be missing or incomplete for several possible reasons:

• The person was not asked about their race and ethnicity.
• The person was asked, but refused to answer.
• The person answered, but the testing provider did not include the person's answers in the reports.
• The testing provider reported the person's answers in a format that could not be used by the health department.

For any of these reasons, a person's race/ethnicity will be recorded in the dataset as “Unknown.”

B. NOTE ON RACE/ETHNICITY The different values for Race/Ethnicity in this dataset are "Asian;" "Black or African American;" "Hispanic or Latino/a, all races;" "American Indian or Alaska Native;" "Native Hawaiian or Other Pacific Islander;" "White;" "Multi-racial;" "Other;" and “Unknown."

The Race/Ethnicity categorization increases data clarity by emulating the methodology used by the U.S. Census in the American Community Survey. Specifically, persons who identify as "Asian," "Black or African American," "American Indian or Alaska Native," "Native Hawaiian or Other Pacific Islander," "White," "Multi-racial," or "Other" do NOT include any person who identified as Hispanic/Latino at any time in their testing reports that either (1) identified them as SF residents or (2) as someone who tested without a locating address by an SF provider. All persons across all races who identify as Hispanic/Latino are recorded as “"Hispanic or Latino/a, all races." This categorization increases data accuracy by correcting the way “Other” persons were counted. Previously, when a person reported “Other” for Race/Ethnicity, they would be recorded “Unknown.” Under the new categorization, they are counted as “Other” and are distinct from “Unknown.”

If a person records their race/ethnicity as “Asian,” “Black or African American,” “American Indian or Alaska Native,” “Native Hawaiian or Other Pacific Islander,” “White,” or “Other” for their first COVID-19 test, then this data will not change—even if a different race/ethnicity is reported for this person for any future COVID-19 test. There are two exceptions to this rule. The first exception is if a person’s race/ethnicity value i