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In epidemiology, an outbreak is a sudden increase in occurrences of a disease when cases are in excess of normal expectancy for the location or season. It may affect a small and localized group or impact upon thousands of people across an entire continent.
An epidemic curve, or “epi curve,” is a visual display of the onset of illness among cases associated with an outbreak. The epi curve is represented by a graph with two axes that intersect at right angles. The horizontal is the date or time of illness onset among cases. The vertical is the number of cases.
- Using Different Scales For The X-Axis
- Dealing with Missing Onset Dates
- Stratification – Separating Cases Into Categories
- Events of Significance to The Outbreak
- Size
- Time Trend
- Outliers
- Pattern of Spread
The unit of time on the x-axis is usually based on the incubation period of the disease and the length of time over which cases are distributed. For example, for a disease with a short incubation period (e.g., Bacilius cereus) and cases distributed over a short period of time (hours), the scale for the x-axis may be more meaningful by hour rather t...
A case may have many dates associated with their illness: illness onset date, report date, hospital admission date, specimen collection date, laboratory testing date, etc. While the general practice is to use illness onset date for all cases, these may not be readily available – for example, when a case could not be reached for an interview. To add...
For some outbreaks, cases can be stratified (or separated) in the epi curve to help the reader understand the outbreak, particularly when there may be an interesting difference between the groups. There are often many ways to organize or separate outbreak cases into categories, such as: 1. Exposures (e.g., those who attended an event versus those t...
Key events that occur during an outbreak can be added to the epi curve as a way to tell a more comprehensive story about why cases are distributed in a particular way. The timing of these events may help describe visible changes on the epidemic curve. Some examples include: 1. Exposures (e.g., mass gathering event, implicated dinner) 2. Public heal...
The size of your epidemic curve can help validate whether you are in an outbreak by showing an increased number of cases over the baseline visually. Knowing the number of cases affected may also help you generate and refine your hypothesis.
The epi curve can provide information on the progression of the outbreak (e.g., if the outbreak is ongoing, increasing in size, stabilizing, decreasing, over, etc.). The epi curve will also depict the rate of increase or decrease of cases over time. When you are at a point where you would like to declare the outbreak over, it is important to ensure...
The outbreak curve can also identify outliers – cases that stand apart from the overall pattern such as the first, or index case thereby providing important clues about the source of the outbreak. Outliers can also result from secondary transmission.
The overall shape of the epi curve may help identify the mode of transmission of the outbreak. There are several well-described types of epi curves: point source, continuous common source, propagated source, and intermittent source. 1. Point source– Persons are exposed to the same common source over a brief period of time, such as through a single ...
An epidemic curve, also known as an epi curve or epidemiological curve, is a statistical chart used in epidemiology to visualise the onset of a disease outbreak. It can help with the identification of the mode of transmission of the disease.
May 5, 2017 · Epidemic Curves. An "epidemic curve" shows the frequency of new cases over time based on the date of onset of disease. The shape of the curve in relation to the incubation period for a particular disease can give clues about the source. There are three basic types of epidemic curve.
The WHO Outbreak Toolkit responds to the need for standardization of tools to improve comparability and sharing of data collected between investigation teams, locations, and time frames. The WHO Outbreak Toolkit is especially designed for complex emergencies and limited resource settings.
Dec 13, 2018 · Uncovering the spatial patterns of virus spread during outbreaks is a key objective that has been transformed by genomic epidemiology.
