INTRODUCTION
In December 2019, a novel strain of coronavirus was detected in Wuhan, the capital city of the Hubei province in China. This coronavirus was designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This current iteration of the coronavirus has many similar characteristics to its earlier ancestor SARS-CoV-1,[1] which was first detected in 2003 and known simply as SARS. According to a recent study, clinical characteristics of patients in China who were infected with SARS-CoV-2 included fever (up to 88.7% who were hospitalized) and cough (67.8%).[2] The median age of patients infected was 47.0 years (IQR: 35.0-58.0) with a large distribution of 58.3% over the age of 50 years having severe symptoms. Additionally, the case fatality rate was reported to be 1.4%.
In January 2020, the World Health Organization (WHO) in regards to the SARS-CoV-2 outbreak declared a global health emergency.[3] Regardless, as SARS-CoV-2 spread across the globe into a pandemic, many countries started to report the attributable number of cases and deaths. According to the WHO, the global total of confirmed cases is at 191,127 and global deaths is at 7,807 (as reported on March 18, 2020).[4]
One of the most important tools in understanding the SARS-CoV-2 epidemic course is the epidemic curve. Epidemic curves allow epidemiologists to visualize the progression of an outbreak by surveilling the number of cases across time.[5] The epidemic curve informs epidemiologists about the pattern of the outbreak’s spread, magnitude, time to exposure, and outliers. Moreover, the epidemic curve is constantly updated as more data become available.
As the SARS-CoV-2 pandemic spreads to other countries, many data visualizations have been developed to help educate and inform people. Johns Hopkins University has developed a real-time dashboard with epidemic curves on the SARS-CoV-2 pandemic that is an excellent source of global cases and mortality. The Centers for Disease Control and Prevention (CDC) also has a series of data visualizations on the SARS-CoV-2 outbreak in the United States including an epidemic curve.
This article will review the features of an epidemic curve and provide a tutorial on creating one based on the available data from the CDC on the SARS-CoV-2 outbreak in the United States.
EPIDEMIC CURVE
When an outbreak happens, there is an urgency to determine when it first occurred. Epidemiologists carefully, collect data to determine who patient zero is and when the case was first identified. This gives them a starting point for when the outbreak occurred. Epidemic curves provide information on the outbreaks’ spread, magnitude, incubation period, outliers, and time trend. Key features of the epidemic curve include the number of cases on the Y-axis and the date of illness on the X-axis. Figure 1 illustrates the key features of the epidemic curve for a point-source outbreak.
Figure 1. Key features of the epidemic curve for a point-source outbreak.
Epidemic curves can tell us information about the outbreak’s pattern of spread. Figure 1 illustrates the pattern of spread for a point-source outbreak. In a point-source outbreak, a single source of contamination affects a group of people at a single event (e.g., rotten potato salad at a dinner party). Other patterns include continuous-source and propagated-source outbreaks. Continuous-source outbreak occurs when the group of people are exposed to a source of contamination for a period of time (e.g., lead poisoning in children). Propagated-source outbreak occurs when the contamination is spread from person-to-person (e.g., flu). The SARS-CoV-2 is an example of a mixed-source outbreak where the early outbreak was due to a common-source (e.g., possibly from zoonotic transmission from animal to human) followed by a propagated-source outbreak where the virus is spread from person-to-person via air droplets or physical contact.[6] Based on a recent study, the mean incubation period for SARS-CoV-2 is 5.1 days (95% CI: 4.5 to 5.8 days).[6]
Motivating example
The SARS-CoV-2 outbreak in the United States was first reported in January 14, 2020. Data on the number of cases can be downloaded from the CDC’s SARS-CoV-2 surveillance site (Note: CDC data are updated daily; hence, the data for this exercise will not reflect these changes). We will use these data to create an epidemic curve of the SARS-CoV-2 outbreak in the United States using Excel. You can download the data files used in this exercise here.
The data are arranged in a wide format where the date (time) is represented by columns and the number of cases is represented by rows. This makes it much easier to generate the epidemic curve in Excel.
Step 1. Highlight the data and Insert a bar chart.
Select the data and insert a clustered column chart. The default version will provide a simple epidemic curve. However, we want to remove the spaces between the bars. To do that, we will need to format the
Step 2. Changing the size of the bars.
To change the size of the bars, we need to right-click one of them to bring up the editing menu. Then we select the Format Data Series… to bring up the options. We set the Gap Width of the bars to 0% so that their sides are in contact with each other. But to distinguish them, we can change the outline’s color to White. Increasing the width of the border’s color will increase gaps between each bar.
After a few more changes (e.g., color and labels), the final epidemic curve will represent the CDC’s data on SARS-CoV-2 on March 18, 2020 (Figure 2). Since data are constantly changing and require validation during an outbreak, this epidemic curve will eventually change. It is recommended that you constantly update this exercise’s data in order to have the most recent, accurate, and valid data from the CDC on SARS-CoV-2. You can also compare your findings to those of the CDC at their website.
Figure 2. Cases of SARS-CoV-2 in the United States.
Conclusions
Epidemic curves are helpful in understanding a disease outbreak in a community. They provide us with a visual representation of the outbreak’s magnitude, pattern, and time period, which will allow us to implement public health policy to stem, reduce, and eventually eradicate the contagion from our population. Although this is a short introduction on epidemic curves, it will, hopefully, be enough for you to review and interpret other epidemic curves in the news or literature.
Files related to this exercise are available here.
References
van Doremalen N, Bushmaker T, Morris DH, et al. Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1. N Engl J Med. 2020;0(0):null. doi:10.1056/NEJMc2004973
Guan W, Ni Z, Hu Y, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020;0(0):null. doi:10.1056/NEJMoa2002032
World Health Organization. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov). Accessed March 19, 2020.
World Health Organization. Coronavirus Disease 2019 (COVID-19) Situation Report –58.; 2020. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200318-sitrep-58-covid-19.pdf?sfvrsn=20876712_2. Accessed March 19, 2020.
Centers for Disease Control and Prevention. Interpretation of Epidemic (Epi) Curves during Ongoing Outbreak Investigations | Foodborne Outbreaks | Food Safety | CDC. https://www.cdc.gov/foodsafety/outbreaks/investigating-outbreaks/epi-curves.html. Published November 16, 2018. Accessed March 19, 2020.
Lauer SA, Grantz KH, Bi Q, et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application. Ann Intern Med. March 2020. doi:10.7326/M20-0504