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.

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

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 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

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).

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.

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).

Feature layer generated from running the Join Features solution

IntroductionThe COVID-19 pandemic exacerbated mental health concerns and stress among American Indians and Alaska Natives (AI/ANs) in the United States, as well as among frontline workers responding to the pandemic. Psychological First Aid (PFA) is a promising intervention to support mental wellbeing and coping skills during and after traumatic events, such as the COVID-19 pandemic. Since PFA is often implemented rapidly in the wake of a disaster or traumatic event, evidence evaluating its impact is lacking. This paper reports pilot evaluation results from a culturally adapted PFA training designed to support COVID-19 frontline workers and the AI/AN communities they serve during the pandemic.MethodsThis study was designed and implemented in partnership with a collaborative work group of public health experts and frontline workers in AI/AN communities. We conducted a pre-post, online pilot evaluation of a culturally adapted online PFA training with COVID-19 frontline workers serving AI/AN communities. Participants completed a baseline survey and two follow-up surveys 1 week and 3 months after completing the PFA training. Surveys included demographic questions and measures of anxiety, burnout, stress, positive mental health, communal mastery, coping skills, PFA knowledge, confidence in PFA skills, and satisfaction with the PFA training.ResultsParticipants included N = 56 COVID-19 frontline workers in AI/AN communities, 75% were AI/AN, 87% were female, and most (82%) were between the ages of 30–59. Participants reported high satisfaction with the training and knowledge of PFA skills. Pilot results showed significant increases in positive mental health and social wellbeing and reductions in burnout from baseline to 3 months after completing the PFA training among frontline workers. There were no changes in communal mastery, coping skills, stress, or anxiety symptoms during the study period.DiscussionTo our knowledge, this is the first pilot evaluation of a PFA training designed and culturally adapted with and for AI/AN communities. Given that many AI/AN communities were disproportionately impacted by COVID-19 and prior mental health inequities, addressing acute and chronic stress is of crucial importance. Addressing traumatic stress through culturally adapted interventions, including Indigenous PFA, is crucial to advancing holistic wellbeing for AI/AN communities.

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.

This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Overview

As coronavirus cases have exploded across the country, states have struggled to obtain sufficient personal protective equipment such as masks, face shields, gloves and ventilators to meet the needs of healthcare workers. FEMA began distributing PPE from the national stockpile as well as PPE obtained from private manufacturers to states in March.

Initially, FEMA distributed materials based primarily on population. By late March, Its methods changed to send more PPE to hotspot locations, and FEMA claimed these decisions were data-driven and need-based. By late spring, the agency was considering requests from states as well.

Although all U.S. states and territories have received some amount of PPE from FEMA, the amounts of PPE states have per capita and per positive COVID-19 case vary widely.

The AP used this data in a story that ran July 7.

Findings

• Overall, low population, rural states have the most PPE per positive case as of mid-June. This generally held true across types of equipment.
• The states that had the highest number of total PPE items per coronavirus case as of mid-May were, in descending order: Alaska, Montana, Vermont, Hawaii, Wyoming, and North Dakota. The highest was Alaska with 1,579 PPE items per coronavirus case.
• The states that had the highest number of total items per case as of mid-June were largely the same states — Montana, Alaska, Hawaii, Vermont, Wyoming, and West Virginia. The highest was Montana with 1,125 PPE items per coronavirus case.
• Conversely, the states that had the lowest amounts of PPE per positive case in mid-May included hotspot states — Massachusetts, New York, Virginia, California, Nebraska, and Iowa. New Jersey was just a couple spots further down. The lowest was Massachusetts with 36 PPE items per coronavirus case.
• The states that had the lowest amounts of PPE per case as of mid-June were largely the same as well — Massachusetts, New York, Iowa, California, and Nebraska. The lowest was Massachusetts with 32 PPE items per coronavirus case.
• When evaluated on a per-capita basis rather than per positive coronavirus case, the picture is different. The District of Columbia received the most PPE per capita in both May and June, although the vast majority of the PPE it received was distributed as of mid-May. Vermont, Kansas, New Jersey, and North Dakota had the next highest numbers of PPE per capita as of both mid-May and mid-June.
• There is no clear pattern of FEMA distribution by party control of states.

About the data

These numbers include material distributed by FEMA and also those sold by private distributors under direction from FEMA. They include materials both delivered to and en route to states.

States have purchased PPE directly in addition to receiving PPE from FEMA or directed there by the agency, and this data only includes the latter categories.

FEMA also distributed and directed the distribution of gear to U.S. territories in addition to states, which are included in FEMA’s release linked below, but not are not included in this data.

FEMA has publicly distributed its breakdown of PPE delivery by state for May and June. FEMA did not provide comprehensive numbers for each state before May.

These numbers are cumulative, meaning that the numbers for May include items of PPE distributed prior to May 14, dating to when the agency began allocations on March 1. The June numbers include the May numbers and any new PPE distributions since then.

The population column, which was used to calculate the numbers of PPE items per state, came from data from the U.S Census Bureau. Since the Census releases annual population data, population data from 2019 was used for each state.

The numbers of coronavirus cases were pulled from the data released daily by Johns Hopkins University as of the dates that FEMA released its distribution numbers — May 14 and June 10.

Caveats

The data includes amounts of gear that had been delivered to the states or were en route as of the reporting dates.

All PPE item numbers above 1 million were rounded to the nearest hundred thousand by FEMA, but numbers lower than that were not rounded.

In some cases, gear headed to a state was rerouted because it was needed more somewhere else or a state decided it did not need it. In some instances, that resulted in states having higher numbers for certain supplies in May than in June.

From July 2021 to June 2022, American Indians or Alaska Natives were the ethnic group reporting the highest death rate from Long COVID per million population in the United States. Among this ethnic group, the mortality rate from COVID-19 was about 1,795 deaths per million population, while nearly 15 individuals per million died due to Long COVID. This statistic shows the death rates from COVID-19 and Long COVID per million population in the U.S. from July 2021 to June 2022, by race and ethnicity.

In 2020, due to the COVID-19 pandemic, only 32,000 people traveled aboard Alaska Railroad's railcars, a decline from 522,000 in 2019. Passenger numbers began recovering in 2020 and rose to 540,000 in 2023, reaching its highest ever level.

0.2 (%) in 2025 2 16. All the rates compare that day vs. the median for that day of the week for the period Jan 4, 2020 – Jan 31, 2020.

Crude, age-specific, and age-standardized COVID-19 mortality rates per 100,000 person-years for non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic American Indian or Alaska Native, and non-Hispanic Asian or Pacific Islander populations, and age-specific mortality rate ratios and rate differences per 100,000 person-years.

Hours worked by hourly employees in transportation of Alaska rose by 3.71% from 382.8 % in 02/12/2025 to 397.0 % in 02/13/2025. Since the 3.34% decline in 02/10/2025, hours worked by hourly employees in transportation leapt by 5.67% in 02/13/2025. All the rates compare that day vs. the median for that day of the week for the period Jan 4, 2020 – Jan 31, 2020.

-25,2 (%) in 2025 feb. 19. All the rates compare that day vs. the median for that day of the week for the period Jan 4, 2020 – Jan 31, 2020.