Last Updated: April 28, 2020
The Covid-19 Graph (NYC) shows people arriving at the emergency department (case counts in the angled line), hospitalizations (bar graph), and deaths (dots below the base line). This graph uses syndromic surveillance to show the burden being placed on the NYC medical system. It is built with data from the NYC Health & Mental Hygiene Department.
In this graph we can see (potential!) new cases, people being treated via hospitalizations, and deaths in one visualization. We can see the relationship between actions, identification and treatment, and the societal burden of Covid-19 on New York City.
The data from EpiQuery is the angular, lighter weight solid line. These points are the sum of ILI and Respiratory case counts for each day. Triangular points on the lighter weight line enclose weekends. Knowing which days are weekends helps to identify days which are often low due to human weekend patterns vs days which are low due to some factor with coronavirus.
There are two case progression measuring sticks. One is aligned with the first death in NYC. The other is aligned with the current day. The measuring stick combines data from articles in Annals of Internal Medicine and The Lancet Infectious Diseases (see Resources, linked below). This tool is useful for understanding why deaths may increase for some time even though the case count of ILI + Respiratory are falling.
The bar chart shows new hospitalizations per day made by subtracting a given day’s total hospitalizations as reported in NYC Health & Mental Hygiene’s 2019 Novel Coronavirus (Covid-19) Daily Data Summary (Hospitalizations) and subtracting the measurement obtained in the previous day.
Dots along the bottom indicate one death each. These are gathered via NYC Health Department’s 2019 Novel Coronavirus (Covid-19) Daily Data Summary. Note: As of April 14, 2020, NYC Health Department reports on confirmed Covid-19 deaths (those who have tested positive) and probable Covid-19 deaths (Covid-19 or equivalent on their death certificate but have not been tested). On this graph, deaths after April 13th include both categories of deaths.
The baseline is the average of people 18 and older (summed from demographic data in Epiquery), presenting Influenza-like Illness and Respiratory cases at a NYC emergency department 2017-2019. All lines and bars are relative to this figure in order to show variation from normal seasonality. ILI usually has a February peak, Respiratory has similar peaks but also rises gently as Spring arrives.
The loadband is a series of shaded bands. The darkness of the band indicates the number of days with the amount cases of “ILI and Respiratory, all ages” were generated during the peak of the 2018 flu season ( Jan 5 2018-February 28, 2018). Median and peak lines are also present. This loadband summarizes the peak months of the 2018/19 flu season activity for emergency departments in NYC. The data source is EpiQuery.
FAQ on the NYC ER graph
- What’s the difference between confirmed deaths and probable deaths? Confirmed deaths are those who have been tested for coronavirus and confirmed positive. Usually confirmed deaths occur in a hospital or other medical system environment. Probable deaths are those with “covid-19” or equivalent listed as the cause of death on their birth certificate but have not been tested. Probable deaths most often occur at home. Due to unequal access to health care, crowding of the healthcare system at the peak of the March/April 2020 Covid-19 outbreak, and other factors, many New Yorkers may have chosen to forego medical assistance for Covid-19 and as a result died without being tested.
- Why do you combine ILI and Respiratory syndromes in this graph? My purpose in designing this chart is to show increased load on the medical system. Covid-19 has elements which present as either ILI or Respiratory and people arriving at the emergency department for either syndrome will need to be treated with the additional precautions of a Covid-19 case.
- Is this all the deaths caused by Covid-19 in NYC? No. Covid-19 response takes up staff resources and ventilators etc. There are people who do not have Covid-19 but will die because there are no more ventilators left for them, no clean rooms to perform emergency procedures, no staff available to take them in. Additionally, there are people who will die because they do not go to the emergency department out of fear of catching Covid-19. Finally, the unusual and unseasonal rise in cases for ILI and Respiratory begins around February 15th. It is quite likely that people were dying of Covid-19 during the time in which NYC was unable to test thoroughly. These people will not be represented on the Syndromic Surveillance Covid-19 Graph (NYC). Were authorities to go back to pneumonia/influenza deaths between February 15th and March 10th there would almost certainly be more deaths from Covid-19 identified. There will be many who won’t be counted due to the lack of testing.
- What do you mean “additional?” The angled data line represent how many more cases are showing up this year vs the average of 2017-2019. These numbers are only the additional–more than the average–that show up for the 18 and older people arriving at the ER reporting a respiratory (aka breathing) problem or an influenza-like illness (fever, coughing, sore throat).
- What do you mean “Respiratory” symptoms? This is defined by the data set I’m using to make this graph, EpiQuery: “Respiratory includes ED chief complaint mention of bronchitis, chest cold, chest congestion, chest pain, cough, difficulty breathing, pneumonia, shortness of breath, and upper respiratory infection.”
- What do you mean “ILI”? ILI is an acronym which, used in medical culture, stands for Influenza-like Illness. EpiQuery, the data source for syndromic surveillance aspect of this chart, defines ILI as “ILI includes ED chief complaint mention of flu, fever, and sore throat.”
- So it isn’t coronavirus for certain? No. Syndromic surveillance and Covid-19 are not an exact one-to-one match. It could be people just coming in because they are worried, for example. This project was initiated due to the lack of access, material, and permission for people in the United States to test and screen for coronavirus. This project is not helpful in a test/trace/treat system, unfortunately. It can only indicate what the burden of our medical infrastructure will be if it follows a given pattern.
- Is this the entirety of the increase? No. This is only people 18 and older. There will be a few people that are younger who show up as well (See Daniel Weinberger’s project in “Covid-19 Syndromic Surveillance Resources” to look into different age and borough configurations of this data). Also, this is only people who show up in the emergency department. There will be people who come in for treatment via other channels. Also, this is only people who report a respiratory (breathing) problem. There will almost certainly be people who show up with other concerns such as shortness of breath. This graph shows only one, very narrow and specific group of people.
- I saw a different version of this graph where the angled line was different, how come that is? After this data is entered it is continually refined for up to two weeks. Though I do not know why this is, my experience with data projects leads me to believe that any exhaustive data-gathering activity finds ands corrects errors afterwards. Each time I update the graph I use the most current data available in the web interface.
The Covid-19 Graph (NYC) is part of the Syndromic Surveillance and Covid–19 collection of articles at Thoughtfaucet. Please see the Caveats section in particular to better understand the limitations of data and methods.