COVID-19 Trends Methodology
Our goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the
Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.
Revisions added on 4/23/2020 are highlighted.
Revisions added on 4/30/2020 are highlighted.
Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020.
Correction on 6/1/2020
Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.
Reasons for undertaking this work:
- The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.
- The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.
- The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:
- U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online.
- Initial older guidance was also obtained online.
Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws.
Thus, the formula used to compute an estimate of active cases is:
Active Cases = 100% of new cases in past 14 days + 19% from past 15-30 days + 5% from past 31-56 days - total deaths.
We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose.
- We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase.
- Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.
- Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.
This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:
- Emergent: Early stages of outbreak.
- Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread.
- Epidemic: Uncontrolled spread.
- Controlled: Very low levels of new cases
- End Stage: No New cases
These trends can be applied at several levels of administration:
- Local: Ex., City, District or County – a.k.a. Admin level 2
- State: Ex., State or Province – a.k.a. Admin level 1
- National: Country – a.k.a. Admin level 0
Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.
Key Concepts and Basis for Methodology:
- 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources.
- 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source used as basis:
- Stephen A. Lauer, MS, PhD *; Kyra H. Grantz, BA *; Qifang Bi, MHS; Forrest K. Jones, MPH; Qulu Zheng, MHS; Hannah R. Meredith, PhD; Andrew S. Azman, PhD; Nicholas G. Reich, PhD; Justin Lessler, PhD. 2020. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Annals of Internal Medicine DOI: 10.7326/M20-0504.
- New Cases per Day (NCD) = Measures the daily spread of COVID-19. This is the basis for all rates.
- Back-casting revisions: In the Johns Hopkins’ data, the structure is to provide the cumulative number of cases per day, which presumes an ever-increasing sequence of numbers, e.g., 0,0,1,1,2,5,7,7,7, etc. However, revisions do occur and would look like, 0,0,1,1,2,5,7,7,6. To accommodate this, we revised the lists to eliminate decreases, which make this list look like, 0,0,1,1,2,5,6,6,6.
- Reporting Interval: In the early weeks, Johns Hopkins' data provided reporting every day regardless of change. In late April, this changed allowing for days to be skipped if no new data was available. The day was still included, but the value of total cases was set to Null. The processing therefore was updated to include tracking of the spacing between intervals with valid values.
- 100 News Cases in a day as a spike threshold: Empirically, this is based on COVID-19’s rate of spread, or r0 of ~2.5, which indicates each case will infect between two and three other people. There is a point at which each administrative area’s capacity will not have the resources to trace and account for all contacts of each patient. Thus, this is an indicator of uncontrolled or epidemic trend. Spiking activity in combination with the rate of new cases is the basis for determining whether an area has a spreading or epidemic trend (see below). Source used as basis:
- World Health Organization (WHO). 16-24 Feb 2020. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Obtained online.
- Mean of Recent Tail of NCD = Empirical, and a COVID-19-specific basis for establishing a recent trend. The recent mean of NCD is taken from the most recent fourteen days. A minimum of 21 days of cases is required for analysis but cannot be considered reliable. Thus, a preference of 42 days of cases ensures much higher reliability. This analysis is not explanatory and thus, merely represents a likely trend. The tail is analyzed for the following:
- Most recent 2 days: In terms of likelihood, this does not mean much, but can indicate a reason for hope and a basis to share positive change that is not yet a trend. There are two worthwhile indicators:
- Last 2 days count of new cases is less than any in either the past five or 14 days.
- Past 2 days has only one or fewer new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 5 days or 14 days.
- Most recent 5 days: In terms of likelihood, this is more meaningful, as it does represent at short-term trend. There are five worthwhile indicators:
- Past five days is greater than past 2 days and past 14 days indicates the potential of the past 2 days being an aberration.
- Past five days is greater than past 14 days and less than past 2 days indicates slight positive trend, but likely still within peak trend time frame.
- Past five days is less than the past 14 days. This means a downward trend. This would be an important trend for any administrative area in an epidemic trend that the rate of spread is slowing.
- If less than the past 2 days, but not the last 14 days, this is still positive, but is not indicating a passage out of the peak time frame of the daily new cases curve.
- Past 5 days has only one or two new cases – this is an extremely positive outcome if the rate of testing has continued at the same rate as the previous 14 days.
- Most recent 14 days: Represents the full tail of the curve and provides context for the past 2- and 5-day trends.
- If this is greater than both the 2- and 5-day trends, then a short-term downward trend has begun.
- Mean of Recent Tail NCD in the context of the Mean of All NCD, and raw counts of cases:
- Mean of Recent NCD is less than 0.5 cases per 100,000 = high level of control
- Mean of Recent NCD is less than 1.0 and fewer than 30 cases indicate continued emergent trend.
- 3.\tMean of Recent NCD is less than 1.0 and greater than 30 cases indicate a change from emergent to spreading trend.
- Mean of All NCD less than 2.0 per 100,000, and areas that have been in epidemic trends have Mean of Recent NCD of less than 5.0 per 100,000 is a significant indicator of changing trends from epidemic to spreading, now going in the direction of controlled trend.
- Similarly, in the context of Mean of All NCD greater than 2.0 per 100,000 and Mean of Recent NCD of over 3,300 indicates moving into epidemic trend. (See trends below for additional information as this is not the only determinant.)
Detailed Criteria for Trends:
Note, prolonged sequences of days in spreading or epidemic state represents a peak period within the pandemic. Shifts into either spreading level rates or to controlled levels are desirable. Each trend’s sub-items are stand-alone criteria for the trend, i.e., only one criteria need be met.
- General Rules =
- 10 or fewer days of cases is too early to analyze.
- Greater than 10 days and fewer than 21 days of cases will be analyzed but must be qualified as too soon to be reasonably reliable.
- Criteria are necessarily different for areas with population below 100,000 because rates per 100,000 become skewed. Thus, the assignment of trends is also based on whether a place has over 100,000. For example on April 18, 2020, only 1 U.S. County with fewer than 100,000 people was considered to be in epidemic trend using this first set of criteria, while 299 counties met the subsequent criteria for under 100,000 persons.
- Emergent =
- Fewer than 10 cases and Mean of Recent NCD between 0.5 to 33.334.
- Fewer than 30 cases, Fewer than 21 days of cases, and the rate of active cases in the tail is less than 1.0 per 100,000. (21 was incorrectly shown as 45)
- Spreading = Over 10 cases
- and Mean of Recent NCD between 0.5 and 33.334
- and Fewer than 30 cases and fewer than 21 days of and the rate of active cases in the tail is over than 1.0 per 100,000. (21 was incorrectly shown as 45)
- and Mean of Recent NCD is less than 100.0, and rate of active case is less than 2.0 per 100,000, and if the trend was at point epidemic, this signifies re-entry into spreading trend.
- Epidemic = Over 10 cases
- and Mean of Recent NCD over 33.334 and rate of active cases is over 2.0 per 100,000.
- and the mean of the rate new cases prior to the tail of the curve was ever greater than 33.334 and if the trend was at point epidemic, this signifies re-entry into spreading or a continuing epidemic trend.
- Controlled =
- Cases rate for last 14 days under 0.5 per 100,000. This also covers the trend scenario of emergent directly to controlled.
- Mean of Recent NCD less than 5.0 and at least 63 days of cases. This covers the trend scenario of spreading to controlled (noting epidemic trend should first evolve back to a spreading trend).
- Greater than 100 New Cases in Tail is not controlled and will result in trend becoming spreading.
- End Stage = Only occurs after more than 28 days with cases. 28 days is used based on first 14 days threshold for certainty that mild or asymptomatic cases have infected others, and an additional 14 days to ensure that serious cases lasting have not infected others, e.g., medical staff.
- Average less than 1 new case every five days over last 28 days.
When determining trends for places with small populations several accommodations are needed. Rural places require special consideration because their populations have higher risks, including reduced access to healthcare, lower likelihood of being able to stop working, and lower likelihood to fully implement social distancing. Thus, the following adjustments apply to places with fewer than 100,000 people:
- Emergent: 1-2 cases in 10-21 days.
- Spreading: Cases per 100,000 <= 100 OR 3-5 cases in 10-21 days (deals with <5,000 populations).
- Epidemic: Cases per 100,000 is over 100 (general case is 33.334)
- Controlled: Cases per 100,000 <= 5.0 OR 3 or fewer cases in past 14 days (general case is 0.5 per 100,000)
- End Stage: If:
- Population under 100,000: Zero cases in past 14 days AND (Days with Cases > 28 OR Total Cases <= 8).
- Population under 20,000: Zero cases in past 14 days AND (Days with Cases > 28 OR Total Cases <= 4)..
- Population under 5,000: Zero cases in past 14 days AND (Days with Cases > 28 OR Total Cases <= 2)..
Assumptions for assigning trends:
- The rate of testing is below capacity. If capacity has been reached, it is expected that the rate of new cases either stabilizes or only changes based on the rate of positive tests. In the latter case, slow increases indicate further spread and slow decreases indicates countermeasures such as isolation policies are slowing the spread.
- Tests are given to people with a full range of symptoms, ranging from asymptomatic persons who were in contact with people wo tested positively, through to those being admitted to hospital with severe or critical symptoms.
- Accurate reporting of all cases and mortalities. Integrity of testing results and reporting of those results is crucial to assigning trends.
Spikes in New Cases: Spikes indicate extreme changes new case counts. In the context of the most recent 2, 5, 21, and total case count days. Spikes should not to be confused with the peak of new cases rate during the event, which is an ‘after the fact’ point for analysis as there is no way to know whether any given day’s spike represents the peak.
The threshold used to indicate a spike is 100 new cases in one day. Whether this is only one locale with a large outbreak, or many locales with new instances of positive tests, 100 represents a challenge with regard to the capacity of health officials to contact and trace all individuals connected to the 100 new cases. At the level of countries with large populations, 100 may seem quite small, and if there are resources to handle 100 cases, this threshold could be revised to a higher number for those countries. However, as stated above, 100 new cases in one day is not a sign of control (4th of the trends), regardless of the size of the population.
Case Rates: There are four types of case rates:
- Total cases per 100,000 persons
- Active cases per 100,000 persons (ACR).
- Active Cases = (100% of new cases from last 14 days + 19% of days 15-30 + 5% of days 31-56) - Death Count
- This formula covers the findings (from the references below) that 81% of cases are mild, lasting 10-14 days, 14% are severe, lasting 15-30 days, and 5% are critical, lasting 31-56 days. This is imperfect and varies by locale but offers a more realistic estimate of the current situation.
- U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online.
- The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) — China, 2020[J]. China CDC Weekly, 2020, 2(8): 113-122.Deaths per 100,000 persons. Accessed online.
- There are assumptions underpinning this formula:
- Testing is below capacity. If testing is at capacity, there are likely unreported cases. As yet, there is no estimate of whether given areas are able to test all persons who should be tested.
- The rate of recoveries remains stable. We expect that over time severe and critical cases will resolve to healthy outcomes in progressively shorter time spans, and this will be monitored and adjusted as time spans change.
- Total Deaths per 100,000 persons – this work will not focus on mortality rate. Later, may provide the data point as additional information.
- Total Tests per 100,000 persons – this is largely missing. It would be useful to indicate the testing capacity of an administrative unit, as well as offer additional explanatory power to this work.
Discussion:
Initial feedback by regional public health experts on the look of the U.S. County Trends map included instances of skepticism that rural counties were assigned trends that were worse than actual conditions. We view this feedback as valid, primarily because we lack data to assign a trend with better accuracy. There are three data points that do not exist that would greatly help: - Number of sites with cases: To illustrate this point, we will use a hypothetical county with 5,000 people. We assert that resources likely exist to contact-trace as many as five cases within such a county. This is based places with 100,000 or more where we assert a new case rate of 33 per day or a spike in one day of cases of 100 or more will exceed local resources to contact-trace. If the 5,000 person county only has one site, the jobs of contact-tracing and quarantine are easier to accomplish, and the risk of spread to caregivers of all levels is much lower because we presume fewer caregivers are needed. However, if just six cases occur in three sites, all the caregiver jobs become more difficult with higher risk, particularly if caregivers are crossing between sites. Out of an abundance of caution we assume this latter case is occurring when assigning a trend.
- Level of and effectiveness of testing: If everyone who needs to be tested is tested it is presumed that policies can be implemented to stop, or greatly slow community spread of COVID-19. However, logical need to be tested is not the basis for many people’s decision to be tested. Emotions and trust play a role as well. Local health officials must weigh this information and act accordingly.
- In Efficient Mitigation Strategies for Epidemics in Rural Regions several factors are given that indicate rural communities and economies have higher risks. These include higher proportions of essential jobs, higher likelihood to continue with normal social contacts despite risks, and lower access to healthcare facilities compared to urban settings.
Generally, ad-hoc observation of day to day shifts in county trends is bearing out that an abundance of caution is necessary. The meat packaging plants around Sioux Falls SD and southwestern MN and their supply chains into Iowa flipped in a very short time from controlled low case counts to uncontrolled spread in less than two weeks.
This work is licensed under the Esri Master License Agreement.