COVID-19 Blog

VDH COVID-19 Contact Tracing Indicators

Case investigations and contact tracing are trusted public health tools used to prevent further spread of contagious illnesses, including COVID-19. Laboratories and physicians notify the Virginia Department of Health (VDH) when patients test positive for COVID-19 or are diagnosed with the infection. Public health professionals then reach out to patients who are actively infected to conduct a confidential interview. This is part of the process of supporting patients with COVID-19 and allows VDH to make recommendations to individuals about how to limit the spread of the virus to others in the community. The interview includes helping the patient identify their close contacts during the time they were infectious.

Contact tracing involves public health professionals reaching out to alert individuals (close contacts) about their potential exposure. This is done as rapidly and sensitively as possible. To protect the identity of the patient, contacts are only informed about the exposure. They are not told who the person is who may have exposed them. During the interview, the public health professional provides information about COVID-19, symptoms to watch for and how to monitor for them, testing, the importance of quarantine, and supportive services that are available. Close contacts of actively infected COVID-19 patients are asked to self-quarantine; the duration is based on when the person was last exposed to the infectious patient.

VDH has been working hard to conduct case investigations and contact tracing since the beginning of the COVID-19 response. VDH is providing these indicators to describe the status of this work:

Percent of Cases Reached Within 24 Hours, 7 Day Average
This measure is the average percent of cases, in the preceding 7 days, that were contacted within 24 hours of the local health district receiving the case report.

Local health districts strive to contact 100% of cases within 24 hours of receiving notification of the case. Obstacles that prevent this from occurring include incorrect contact information provided to the health department, people not responding, and the volume of reports received in a given day.

Number of Contacts Under Public Health Monitoring
Contacts are only counted in this group while they are under monitoring; they are removed once their monitoring period has ended.

Of Contacts Able to Reach, Percent Reached Within 24 Hours
Local health districts strive to interview all contacts within 24 hours of public health identifying them as a close contact of a COVID-19 case. Obstacles that prevent this from occurring include incorrect contact information provided to the health department, people not responding, and the volume of reports received in a given day.

Percent of Contacts Unable to Reach to Date
This indicator includes contacts entered into the contact monitoring system but not yet reached at the time of the report (even if it has been less than 24 hours).

Local health districts strive to reach all contacts; however, it isn’t always possible. Obstacles that prevent this from occurring include incorrect contact information provided to the health department and people not responding.

To view Virginia’s contact tracing indicators, visit: VDH COVID-19 Contact Tracing Data.

More information about contact tracing is available on VDH’s COVID-19 website.

Race and Ethnicity Reporting Update

Click here to download a PDF version of this post

The Virginia Department of Health (VDH)  is changing the way it presents race and ethnicity data. Since COVID-19 has impacted some communities more than others, It is important for the public to understand these health disparities so they can respond appropriately. In some cases, reporting data in large groups, for large geographic areas, can mask disparities. However, reporting data at too fine detail can put individual privacy at risk. This is especially true for groups with relatively small numbers in Virginia such as Native Americans or Pacific Islanders. 

Previously, we published data for ethnicity and race separately. With the exception of the  “White” and “Black or African American” categories, all other races were combined into a single “Other Race” category. The new reporting categories are:

  • Asian or Pacific Islander – Non-Hispanics who identify as “Asian” or “Native Hawaiian or Pacific Islander”
  • Black – Non-Hispanics who identify as “Black or African American” 
  • Latino – Individuals of any race who identify as “Hispanic or Latino” 
  • Native American – Non-Hispanics who identify as “American Indian or Alaska Native” 
  • White – Non-Hispanics who identify as “White” alone
  • Other Race – Non-Hispanics who select “Other Race” alone
  • Two or More Races – Non-Hispanics who select more than one of the above race categories

The new reporting categories allow us to provide more detail on racial and ethnic health disparities while preserving individual privacy. Additionally, combining the ethnicity and race questions into a single reporting category reduces the amount of missing data from about 33% for both race and ethnicity questions, to about 26%. This is because we only need a response in one or the other categories for reporting purposes.

While these categories allow us to report data in most categories for the majority of local health districts, in a few cases, local health districts were combined for specific groups:

  • Asian or Pacific Islander
    • Lenowisco + Cumberland Plateau
    • Eastern Shore + Three Rivers
  • American Indian or Alaska Native 
    • Lenowisco + Cumberland Plateau + Mount Rogers 
    • Pittsylvania-Danville + Southside
    • Eastern Shore + Three Rivers
    • Alleghany + Roanoke

The Results

With these changes, some results stand out. For instance, It is clear that COVID-19 is disproportionately affecting Virginia’s Latino population. Although Latinos make up just 10% of Virginia’s population, current data suggest that they account for 45% of cases, 35% of hospitalizations, and 11% of deaths. It is important to note that there is no evidence that migration or travel from Central or South America played a role in bringing COVID-19 into the United States. While it is difficult to make direct comparisons due to some anomalies in the disease reporting system, it is clear that this population is being impacted significantly. 

What about the missing data?

Although this new reporting method is an improvement over previous methods, it is hard to ignore the elephant in the room: the large amount of missing data. This missing information makes it difficult to draw any firm conclusions about the cause(s) of these disparities. For example, it is possible that factors such as age and geography may play a more important role in the observed health, and related social and economic disparities, than race and ethnicity alone.

VDH is pursuing multiple strategies to address the problems caused by missing data. First, we are encouraging individuals, health providers, and laboratories to be more diligent in reporting race and ethnicity data. Second, we are trying to match records from multiple data systems to fill in some gaps. Finally, we are exploring statistical imputation methods that use existing information (e.g., census tract data, geolocation, surname) to impute missing data (Note: VDH will always report and label imputed data separately from official data). 

What does this mean?

Race and ethnicity are complex issues. A government organization like VDH reporting data using race and ethnicity groups can never fully reflect how individuals identify. While individuals select race and ethnicity categories themselves, we use r categories  based on Federal standards. This allows us to match with federal data and better measure disparities in health at the population level. 

Health disparities between populations are not caused by a group’s race or ethnicity. They reflect societal factors like geography, access to healthcare, poverty, and racism that may disproportionately affect people of color. Statisticians with the Office of Health Equity will use the data collected from the current pandemic to identify those health inequities and inform tracking and reporting guidelines so that Virginia will be better prepared to address similar crises in the future. 


How is VDH Calculating the Number of People Tested?

SARS-CoV-2 testing data are complex. There are several ways of looking at these numbers, and VDH has used several of these methods over the course of our COVID-19 response.

  1. Unique people tested
    The number of unique people tested is how we look at the overall number of individuals who have been tested for SARS-CoV-2 in Virginia. This method of looking at testing measures will only count a person once regardless of how many times they are tested over weeks or months. VDH used this method originally as a way to measure the number of opportunities to identify a new case.
  2. Testing encounters or Total people tested
    VDH has referred to this measure by two names – total people tested and testing encounters. Both of these names were our attempt to communicate that this is the number of people who have been tested per day. Over the course of the COVID-19 response, some people have been tested more than once. Some of these people are healthcare workers, some are at high-risk, and some are known cases who need to have negative tests to return to their normal life. VDH started reporting this method on May 1 as a better way to measure Virginia’s capacity to test people. It is included in the daily COVID-19 Cases in Virginia dashboard, the dashboard of cases and tests by ZIP code, and the Key Measures report. Regardless of how many times a person has been tested, they will only be counted as a case once.

Besides these two methods of measuring the number of tests Virginia has conducted, there are a few other things to keep in mind.

  • VDH is reporting test numbers that include people who do not live in Virginia. If we want to measure the state’s capacity to test for SARS-CoV-2, we need to include all tests that are conducted on people who are sick enough to pursue testing while they’re in Virginia.
  • Case data and test data are two different sources. Not all cases involve a positive test, and not all positive tests count as cases. Some cases are counted based on their clinical symptoms alone, so those people are not included in testing data. Some tests are in out-of-state residents, so those people would not be included in Virginia’s case numbers. Other tests are positive for antibodies or an antigen. These tests are not as accurate as RT-PCR, the gold standard, so VDH is not counting someone as a case with that information alone. 
  • Not all tests are equal. Sensitivity is the measure of how likely a test is to identify an infection. Specificity is how likely a positive result is to be due to the exact pathogen the test is designed for. The higher the sensitivity of a test, the lower the rate of false negatives. The higher the specificity, the lower the rate of false positives. RT-PCR tests look for the virus’ genome and are both highly sensitive and highly specific. Other tests, like antibody tests, are less accurate. These tests look for the antibodies that our immune system builds after infection with a new pathogen. These antibodies take a few days or weeks for form, so a test conducted too early may not have good sensitivity. These antibodies often look similar for related pathogens. Because there are several regularly-occurring coronaviruses in the human population, some public health officials are worried about cross-reactivity. Right now, antibody results may need to be confirmed using an RT- PCR test.
  • Some tests are FDA-approved and some are not. The FDA has issued an Emergency Use Authorization, or EUA, for a lot of tests when the manufacturer has been able to show good sensitivity and specificity. This is not as rigorous a process as new tests normally need to go through to be approved. There are some tests that are not FDA-approved at all being used as well. VDH is only reporting FDA-approved tests.

Five Things to Remember When Interpreting Epidemiologic Data

Five Things to Remember When Interpreting Epidemiologic Data

Data will change some over time.

VDH gets data on COVID-19 from a number of different sources. Laboratory results, morbidity reports, death certificates, medical records, and patient interviews are a few of the ways we collect data. Sometimes these different sources will disagree on something. For example, we may get a positive lab result that doesn’t have the patient’s address. To count this case, we use the address of the doctor who ordered the lab test. During the course of the interview, we may find out that the case-patient sought care from their doctor in one county, but actually lives in a different county. In another example, we may receive a report of a case- patient who has all of the symptoms of COVID-19 and meets the criteria for a ‘Probable’ case. If later laboratory testing comes back negative, then we won’t count that person as a case anymore. Every time that we report data, we are reporting the most up-to-date information we have, even if it’s different from what we reported before.

The data we share is an underrepresentation of COVID-19 in Virginia.

We know that the number of cases we have on record is an underrepresentation of the true burden for several reasons. Some underrepresentation is because testing for SARS-CoV-2 might not be available for the infected person.. Another factor is that not everyone will need to see a doctor for COVID-19. The World Health Organization (WHO) published a very detailed report about the outbreak of COVID-19 in China and found that 80% of cases were mild or moderate. Since then, there have been studies that have identified infections in people who never develop symptoms. If someone gets infected and recovers on their own, then public health may never find out about the case.

This data is based on a case definition.

Public health uses standardized case definitions to count cases. These case definitions make it easier to compare data over time, across states, or even between different counties. A case definition is different from a diagnosis, and is used for a different purpose. A diagnosis is helpful for treatment and medical billing while a case definition is used for public health surveillance. For COVID-19, Virginia uses the CDC COVID-19 confirmed and probable case definitions. These definitions suggests that we report two case statuses:

  1. Confirmed cases – Confirmed cases include anyone who tests positive for SARS-CoV-2 RNA in a clinical or autopsy specimen using a molecular amplification test.
  2. Probable cases – There are a few ways to identify a probable case. In Virginia, anyone who is positive using an approved antigen test or anyone who displays a specific set of symptoms and has an epidemiologic linkage (contact with another confirmed or probable case or part of a risk cohort), or anyone whose death certificate mentions COVID-19 or SARS-CoV-2 without a positive lab result counts as a probable case.

Our data are intended to answer questions about the epidemiology of COVID-19.

There are a few different sources that provide data on the COVID-19 pandemic, and the numbers may be different for things that sound the same. That’s because these different sources have different purposes. The Virginia Hospital and Healthcare Association (VHHA), for example, has a great dashboard that includes the number of hospitalizations for people who have tested positive for COVID-19 or who have tests pending. These data are intended to help measure the current burden on the healthcare system and to help hospitals prepare for a surge. These data do not have the same kind of rigorous case definition that epidemiologic case data do because they are not intended for the same purpose. For healthcare system preparation, an overestimation is better than an underestimation. VDH reports hospitalization data among identified cases so that we can measure the relative severity of the disease. For our purposes, it’s important that the same case definition be applied to the numerator (the number of cases that result in hospitalization) and the denominator (the total number of cases).

There are limitations to the data we share.

Public health epidemiologists work hard to make sure we can present the best data possible, but there are limitations to any data source. We’ve presented some of the issues above, but there are many other complexities that we work with on a daily basis. VDH has experts in infectious disease epidemiology, community health, data visualization, and public communication working to make the data we share as accurate, useful, and easy to understand as possible.

UVA COVID-19 Modeling Weekly Update

Key Takeaways

  • This is a shortened weekly report as we celebrate Juneteenth in Virginia.
  • Vaccination coverage continues to slowly but steadily increase across VA, but disparities and pockets of low coverage exist.
  • Cases continue to decline even as restrictions on vaccinated individuals are lifted.
  • The Delta variant, which has ravaged India, is gaining traction in the US and Virginia. Unvaccinated individuals, including those with a previous COVID infection, remain at risk from this variant.

Full Weekly Report.

UVA COVID-19 Model Dashboard.

UVA Biocomplexity Institute Slides.

RAND Corporation Situation & Research Update.

Quality Assurance Steps for COVID-19 Data

During the COVID-19 response in Virginia, the Virginia Department of Health (VDH) is reporting public health data in more detail and more quickly than ever before. VDH routinely performs ongoing and comprehensive quality assurance on COVID-19 cases, hospitalizations, and deaths, including those that have been previously reported to VDH. Performing data quality assurance, such as checking for correct addresses, re-classifying cases to align with national case definitions, and other efforts, is important for public health. It helps make sure that data that are reported and presented are as accurate and timely as possible. The data quality assurance steps VDH takes are not new. Public health professionals perform these data quality steps for many health conditions in addition to COVID-19. Because of these steps, it is important to note that

Checking for Locality of Residence:

One of the data quality assurance steps that VDH takes is checking for correct addresses. VDH initially assigns a case to a locality (county or independent city) based on the patient’s residential ZIP code. In Virginia, some ZIP codes cross between multiple localities. Upon further review of the case, which includes applying geocoding to the residential address, VDH may determine the original locality assigned to the case is not correct. In these scenarios, the case will be re-assigned to the appropriate locality, which may result in a negative count for the original locality and a positive case count in the re-assigned locality.

Classifying a COVID-19 Case: 

To determine if a person should be counted as a COVID-19 case, VDH uses criteria outlined in a national case surveillance definition by the Centers for Disease Control and Prevention (CDC). Disease surveillance is foundational to public health practice. It helps understand diseases and their spread and informs appropriate actions to control outbreaks. VDH performs several steps to ensure each COVID-19 case reported in a Virginia resident meets these specified criteria.

Not every COVID-19 case involves a positive test, and not every positive test reported to VDH is counted as a COVID-19 case. Some cases are counted because they show symptoms of COVID-19 and had close contact to another known COVID-19 case as described in the national case surveillance definition. Additionally, there are people in Virginia who have been tested more than once for COVID-19. Some of these people are in higher risk settings such as healthcare or nursing homes, and others are known COVID-19 cases who needed negative tests to return to their normal routine. When a person is tested many times over the course of their COVID-19 infection, VDH reviews all the test results to ensure multiple positive test results for the same infection in one person are not counted as multiple COVID-19 cases.

The data quality steps described above may result in changes to the number of cases, hospitalizations, and deaths in your community or within the state. Negative numbers in case counts by report date on the VDH COVID-19 data dashboards may be observed as quality assurance steps are completed. The dashboards most likely to be impacted are: Locality, School Metrics, and Locality Metrics.

Virginia COVID-19 Response: Meat and Poultry Processing Plants

This data will be updated at the beginning of each month.

The meat and poultry data blog looks different this month—why the change?

The number of COVID-19 cases, outbreaks, hospitalizations and deaths associated with meat and poultry processing plants continue to remain very low throughout Virginia. As long as there is community transmission of COVID-19, it is likely that we will continue to see occasional cases in meat and poultry processing plant workers over time. The focus of the COVID-19 response efforts for meat and poultry processing plant workers has shifted from supporting outbreak investigations to providing vaccine access to this essential workforce.

What efforts have been made to improve COVID-19 vaccine access to meat and poultry processing workers?

VDH and the food sector have been working on various ways to distribute COVID-19 vaccines to meat and poultry processing workers. These include working with occupational health providers and local health departments. In addition to these efforts community-based organizations have been working to share information about COVID-19 vaccines with workers in the food and agriculture sector.

  • The Lord Fairfax Health District (LFHD) has been working with local food processors to set up vaccination clinics. They’ve vaccinated local fruit growers and a few food processing plants and are continuing to reach out to businesses to arrange coming on site to get more people vaccinated. Since January 2021, LFHD has vaccinated at least:
    • 405 meat and poultry processing plant workers
    • 255 dairy workers
    • 170 produce workers
    • 130 other food production workers
    • 43 migrant workers
  • The Central Shenandoah Health District (CSHD) scheduled 15 clinics onsite at poultry plant facilities, administering over 2,770 1st and 2nd COVID-19 vaccine doses. The health district utilized Community Health Workers to work with poultry plant workers and their families to get connected to other clinics if they were unable to or uncomfortable with receiving the vaccine at the onsite clinics at their place of employment. These efforts supported the districts’ larger, weekly clinics at the Rockingham County Fairgrounds and James Madison University where essential workers, including poultry plant workers, food processing, and agricultural workers, were invited to come and receive a COVID-19 vaccine. Furthermore, CSHD engaged with poultry plant facilities to establish COVID-19 vaccine programs within their occupational health programs. So far, this effort has resulted in the establishment of one COVID-19 vaccine program at a local poultry plant.
  • The Eastern Shore Health District (ESHD) has:
    • Been offering COVID-19 vaccinations to seasonal workers as they arrive on the Shore and coordinating that effort with local farm managers and crew leaders.  Out of approximately 130 workers currently on the Shore, it is estimated that  80-85% have been vaccinated; some received the vaccine before they arrived.
    • Partnered with Eastern Shore Rural Health to provide three onsite vaccination events at poultry plant facilities. Hispanic and Haitian Creole outreach workers helped provide education to workers as part of these events. A total of 91 night shift workers were vaccinated during these events and similar events are planned for day shift workers in early June. The Elite Marketing Group will be helping to host a pre-vaccination “party” with snacks and educational information as part of these upcoming events.
    • Offered weekly walk-in vaccination clinics on Tuesdays and Wednesdays at the local health department.
    • Partnered with Legal Aid and Eastern Shore Rural Health to plan an upcoming outdoor event at the local YMCA, to specifically offer COVID-19 vaccines to the refugee, immigrant and migrant populations. There will be informational tables for organizations who provide services to this community and walk-up vaccine opportunities for anyone 12+ with all three authorized vaccines available to maximize vaccine uptake.
    • Hired one Hispanic and one Haitian Creole Community Health Worker who will be working primarily with poultry, agricultural, aquaculture and seasonal workers, which comprise a large part of the refugee, immigrant and migrant community.
Why is COVID-19 vaccination so important?

COVID-19 vaccination is an important tool to help us get back to normal; every vaccine administered helps us get closer to reaching population immunity. Population immunity means that enough people in a community are protected from getting a disease because they’ve already had the disease or because they’ve been vaccinated. Population immunity makes it hard for the disease to spread from person to person. It even protects those who cannot be vaccinated, like newborns or people who are allergic to the vaccine. Learn more about the benefits of getting vaccinated.

Why the focus on meat and poultry processing workers?

Initial cases of COVID-19 associated with meat and poultry processing plants were reported in Virginia in March of 2020. Cases peaked in April and May of 2020 with large outbreaks reported in several processing plants throughout the United States, including Virginia. Workers in these facilities need to work closely to one another, often for prolonged periods of time, making transmission of COVID-19 from one worker to another easy. Protecting this vulnerable workforce is important to protect both the workers, who produce the food we eat, and the communities in which they live.

In addition to vaccination, what other interventions were put in place to prevent the transmission of disease within these facilities and the wider communities in which they exist?

The Virginia Department of Health worked with affected facilities to put a variety of interventions in place to reduce disease transmission. The most common interventions implemented in Virginia included:

  • educating employees about the transmission of COVID-19
  • screening employees for signs and symptoms of illness
  • adding hand hygiene stations
  • adding physical barriers between workers where physical distancing was not possible, and
  • requiring universal face coverings

For more information about recommended interventions for meat and poultry processing facilities, check out the links below:

COVID-19 Death Disparities by Census Tract Poverty Level, Health Opportunity Index and Rurality

by Michael Landen & Rexford Anson-Dwamena

COVID-19 Death Disparities by Census Tract Poverty Level, Health Opportunity Index and Rurality

Disparities for key COVID-19 indicators by race/ethnicity in Virginia and the United States have been well documented (see March 8, 2021 COVID-19 Health and Disease Disparities by Race and Ethnicity in Virginia blog post). This report focuses on COVID-19 death rate disparities for adults 35-54 years of age in Virginia by census tract level poverty, health opportunity index and rurality. The entire age range was not used for this analysis because subpopulations, such as those with different poverty levels, have different age structures and therefore can’t be fairly compared for an outcome that is associated with age such as COVID-19 death. The 35-54 year age group was chosen for these comparisons because it is the youngest age group with sufficient numbers of deaths to allow for reasonable death rate comparisons at the census tract level.

Poverty Level Disparities

A person’s income is not included in their death records, however, the percentage of persons living below the federal poverty level by census tract is available. COVID-19 deaths among persons 35-54 years of age can be grouped by this percentage. The largest disparity in the COVID-19 death rate was found between those living in census tracts with the greatest percentage of persons living in poverty, >= 40%, and those living in census tracts with the lowest percentage of persons living in poverty, < 10%. Persons living in census tracts with the highest percentage of people in poverty were 2.3 times more likely to die of COVID-19 than those from the lowest poverty census tracts (Figure 1).

Figure 1.  COVID-19 Death Rates per 100,000 persons aged 35-54 years by Census Tract Percentage of Persons Living below the Federal Poverty Level, Virginia, March 2020 – April 2021


Health Opportunity Index Disparities

The Virginia Department of Health provides the Virginia Health Opportunity Index (HOI) which is a composite measure of the social determinants of health – the social, economic, educational and environmental factors that relate to a community’s well-being – at the census tract level. The index is divided into 5 levels – very high, high, moderate, low, and very low – and census tracts can be grouped into these 5 levels. In general, persons living in census tracts with a higher HOI tend to have lower disease and death rates.  COVID-19 deaths among persons 35-54 years of age can be grouped by the level of HOI for the census tract in which they reside. The largest disparity in the COVID-19 death rate for this age group was found between those living in census tracts with the lowest HOI and those living in census tracts with the highest HOI. Persons living in census tracts with the lowest HOI were 1.9 times more likely to die of COVID-19 than those from census tracts with the highest HOI (Figure 2).


Figure 2.  COVID-19 Death Rates per 100,000 persons aged 35-54 years by Census Tract HOI, Virginia, March 2020 – April 2021


Rurality Disparities

Persons living in rural areas, in general, tend to have higher disease and death rates than those living in metropolitan areas. Rural and urban census tracts can be classified by the Rural/Urban Community Area (RUCA) taxonomy and then further classified into groups – metropolitan, micropolitan, small town and rural.  COVID-19 deaths among persons 35-54 years of age can be grouped by these RUCA groups for the census tract in which they resided. The largest disparity in the COVID-19 death rate for this age group was found between those living in small town census tracts and those living in metropolitan census tracts. Persons living in small town census tracts were 1.5 times more likely to die of COVID-19 than those from metropolitan census tracts, and both persons from micropolitan census tracts and persons from rural census tracts were 1.4 times more likely to die of COVID-19 than those from metropolitan census tracts (Figure 3).

Figure 3.  COVID-19 Death Rates per 100,000 persons aged 35-54 years by Census Tract RUCA, Virginia, March 2020 – April 2021

COVID-19 death rates for those 35-54 years are higher in non-metropolitan communities and for persons living in communities with a higher percentage of people living in poverty in Virginia. This is not surprising since many health indicators are worse for communities with high poverty rates and for rural communities. In general, these communities may have fewer opportunities than communities with lower poverty and metropolitan communities. One approach to reducing these disparities is to increase social, economic, vocational and educational opportunities in these high poverty communities and rural communities. An “opportunity” specifically related to COVID-19 is vaccination, and these vaccinations should continue to be prioritized for persons in rural communities and those with high poverty rates or percentages.


UVA COVID-19 Modeling Weekly Update

Key Takeaways

  • Average daily cases per 100k Virginia residents declined to the single digits for the first time since last summer. Cases are declining or plateauing in all of Virginia’s Local Health Districts – a first since UVA began reporting trajectories.
  • New vaccinations have declined dramatically, while mitigation measures are being relaxed, heralding an new environment compared to April.
  • Scenarios have changed to include the dominance of the B1.1.7 variant, behavioral changes in response to surges, and different vaccination rates.
  • Masks and social distancing are still recommended for people who are unvaccinated, and masks are still recommended in certain situations for those who are vaccinated.

Full Weekly Report.

(Note: The Weekly Report was edited to reflect that recent data on vaccine administrations is preliminary.)

UVA COVID-19 Model Dashboard.

UVA Biocomplexity Institute Slides.

RAND Corporation Situation & Research Update.