Frequently asked questions about the Johns Hopkins COVID-19 United States Cases by County map.
The U.S. map dashboard reflects a collaboration led by the Johns Hopkins Centers for Civic Impact, with participation from the Applied Physics Laboratory, Bloomberg School of Public Health, and the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Technical support is provided by ESRI and the JHU Sheridan Libraries.
The JHU COVID-19 Tracking Map, first shared publicly on Jan. 22, has served as a valuable global resource to track the outbreak as it unfolds.
The JHU COVID-19 U.S. Map and County Dashboard Infographics have been developed to provide local leaders, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds within the U.S. All data collected and displayed are made freely available through a GitHub repository, along with the feature layers of the dashboard, which are now included in the ESRI Living Atlas.
Yes, but please provide credit by citing “Johns Hopkins University” or “Johns Hopkins Centers for Civic Impact.”
The embed code is provided below:
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Using the filters in the top right-hand corner of the map, select the state and county in which you have an interest. The map will “zoom to” that county and highlight the county border. Click on the county to open a pop-up that contains the county confirmed cases and deaths total. Click on the Infographic Details image to pull up a county dashboard, on which you will find county confirmed cases and deaths, county new cases since the previous day, cumulative state information, and other significant baseline data points—such as typically available hospital beds, at-risk population percentages, and poverty levels.
Positivity Rates: Our calculation, which is applied consistently across the site and predates most state's test positivity tracking efforts, looks at number of cases divided by number of negative tests plus number of cases. We feel that the ideal way to calculate positivity would be number of people who test positive divided by number of people who are tested. We feel this is currently the best way to track positivity because some states include in their testing totals duplicative tests obtained in succession on the same individual, as well as unrelated antibody tests. However, many states are unable to track number of people tested, so they only track number of tests. Because states do not all publish number of positive and number of negative tests per day, we have no choice but to calculate positivity via our approach.
7-Day Averages: The CRC calculates the rolling 7-day average separately for daily cases and daily tests, and then for each day calculate the percentage over the rolling averages. Some states may be calculating the positivity percentage for each day, and then doing the rolling 7-day average. The reason why we use our approach is because testing capacity issues and uneven reporting cadences create a lot of misleading peaks and valleys in the data. Since we want to give a 7-day average, it is more fair to average the raw data and then calculate the ratios. Otherwise, days when a large number of negative tests are released all at once—and positivity is going to be very low—will have the same weight as days when data was steadily released, and the overall result is going to be lower. Our approach is applied to all our testing data to correct for these uneven data release patterns.
There are several reasons the data looks different.
If you are a government agency, you may use the data for your purposes provided credit is attributed to the Johns Hopkins University. Please provide credit by citing “Johns Hopkins University” or “Johns Hopkins Centers for Civic Impact.” All data, mapping and analysis (website, copyright 2020 Johns Hopkins University, all rights reserved) is provided to the public strictly for educational and academic research purposes.
Screen shots of the website are permissible provided credit is attributed to the Johns Hopkins University.
The map is updated daily. The time of the latest update is noted on the bottom of the dashboard, as well as in a footer on county infographic. Occasional maintenance can result in slower updates.
The data sources include the Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University; the Red Cross; the Census American Community Survey; and the Bureau of Labor and Statistics.
The website and its contents, including all data, mapping, and analysis, copyright 2020 Johns Hopkins University, all rights reserved, is provided to the public strictly for educational and academic research purposes.
The website relies upon publicly available data from multiple sources that do not always agree. More frequent updates of the map often result in higher case numbers than may be available from other sources that are updated less frequently.
Reliance on the website for medical guidance or use of the website in commerce is strictly prohibited. The Johns Hopkins University hereby disclaims any and all representations and warranties with respect to the website, including accuracy, fitness for use, and merchantability.
No. Johns Hopkins University has learned about the existence of malware designed to look like the university’s coronavirus tracking map in an effort to steal information from users who visit the fake site. The university’s website does not contain malware and is safe to navigate. The malicious application requires users to download software or launch the fake map, which opens the malware. The Johns Hopkins dashboard is hosted by Esri as part of its ArcGIS Online offering. According to Esri, “a malicious person created a Windows-based application containing malware whose display is practically identical to the Hopkins dashboard.” If you receive an email containing a link to download such an item or come across the code for the malicious app please report it immediately to the Esri incident response team through ArcGIS Trust Center security concern page.
General questions about the map should be directed to COVID19map@jhu.edu. Members of the media with questions should contact the Johns Hopkins University Office of Communications at 443-997-9009 or at email@example.com.
American Indian and Alaska Native (AIAN) communities are experiencing some of the highest rates of COVID-19 in the country. There are, however, substantial gaps in the availability of COVID-19 data from Tribal communities in publicly available data sources and data displays. This map is designed to begin to address those data gaps and improve visualization of cases occurring in AIAN settings.
Developed in collaboration with Center for American Indian Health, this map identifies counties in the U.S. that intersect with federally recognized Native land reservations and displays the most up-to-date COVID data that are available for those counties. This depiction of data will not be a perfect representation of COVID-19 burden in specific Tribal communities where borders do not align directly with county lines. Our intention in presenting data this way is to bring attention to the unequal burden of COVID-19 in AIAN settings while also respecting Tribal sovereignty and individual privacy. For the most accurate data on COVID rates in a given community, we recommend contacting Tribal, regional, or Urban Indian health program representatives in the community of interest.
This map has been adapted from two sources: the Indian Health Service (continental United States) and Esri (Alaska Native Village lands). It is not a perfect or inclusive representation of all land boundaries for American Indians or Alaska Natives and is limited to federally recognized Tribal nations in the continental U.S. and Alaska Village lands – this map does not include Urban Indian populations though we recognize that there is also a need to represent Urban Indian data. Please note that there may be Native communities not represented in this visualization, and that this map does not include any individuals living outside of the counties that intersect with these land boundaries who may identify as AIAN. This map is not meant to serve as a complete representation of COVID data for all AIAN individuals in the United States. Finally, this map does not represent or intend to represent official or legal boundaries of any Indigenous communities.
For information on definitive land boundaries, please contact the specific tribal nation or Urban Indian community in question. If you see an error in this map, please contact Covid19map@jhu.edu. For questions about tribal data content, please contact the Center for American Indian Health.