The dashboard below contains visualizations pulled from the Los Angeles Times’ Covid-19 GitHub for “places” Los Angeles County. 

Los Angeles County – Community and Trend Analyses

The three-page dashboard contains a basemap of cumulative cases and infection rates for most communities or neighborhoods in Los Angeles County, along with interactive graphs that permit users to view recent ‘curve’ trends by community and comparative ‘curves’ for multiple communities.  A third map shows the contribution of nursing homes and residential care facilities to the overall caseloads by community.  

Full-Screen Dashboard 

Southern California – Residential Care/Nursing Homes

Please check out my friend Lauren He’s map of Covid-19 cases in Nursing Homes and Residential Care Facilities.  It’s a very important angle on the disease that is both under-reported in the press and for which it is difficult to obtain useful data.  Bonus:  Lauren’s a high school senior from Austin Texas.  



9 thoughts on “LOS Angeles COVID-19 TREND MAPs”

  1. I don’t understand what the color dots mean can you please explain what the yellow and green are I know the red means hot spot.

  2. Thank you for such a detailed site! We live in Tucson and will be driving to Inglewood, CA. soon to attend a funeral. It’s nice to see that the spike in Covid cases appears to have subsided in that local area as opposed to only seeing L.A. County’s Covid surge numbers. This information was very helpful in determining our course of direction etc.. We will be wearing our masks and social distancing too, of course, as our area is also just slowly growing by single digits.

  3. Hi! Thank you for a great interactive map! Have a question: I’m monitoring the emergence of covid cases in the Melrose area and notice that on 7/6 2020 the new cases are a whooping 928 from a regular in the low double digits, indeed they equal the cumulative cases for that very date and I wonder if this perchance is a typo/data error. Thank you so much!


    1. It’s a data error associated with the lack of data over the July 4th Holiday. My inability to get the software to ignore days with zero information is the problem…so the algorithm assumes that there were zero cumulative cases on those dates, and then it appears as a big jump in cases when the data feed resumes.

      1. Steve, wouldn’t it be better to find dates with missing data then, and simply carry over the previous days data to avoid these issues. I’d be more than happy to provide you with some data cleanup scripts if you would like. Also, have you thought about changing the colors to indicate where things are growing most rapidly (averaged values over X days) instead of total cases. I found this page trying to find a heat map of where the spread is slowing down and where things are still out of control.

        1. Kyle – there’s a LOT of things I could do, but I’m up to my eyeballs in other things. If you want to eliminate missing dates, it’s easy to click on them and chose “exclude”. This is mostly proof of concept with a software that is experimental for me.

          There are various heat maps (nationally) using a variety of heatmaps. I provide a couple of links on this page. The ESRI maps are very good in that respect.

      2. Aaargh! Frustrating, I imagine.
        MANY thanks for all your diligence and problem-solving!
        We non-mathy mortals quail at the thought!

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