By Shazia Farooqui, Valérie Balvert and Candela Iglesias Chiesa
Have you heard phrases like these in the news or on social media?
- The incidence of COVID-19 cases in the US has doubled in the past two weeks.
- The prevalence of cervical cancer among Belgian women was higher in 2014 than in 2022.
- The mortality rate due to heart attack is higher amongst those 65 and older.
- Cancer is a leading cause of morbidity worldwide.
Especially during the COVID-19 pandemic terms such as “incidence”, “prevalence”, “mortality”, or “morbidity” have become very common in the news, and have been used by experts and non-experts alike (sometimes incorrectly!)
In case you got confused by these terms, we got you covered!
Incidence vs. prevalence
What is incidence?
Incidence refers to the number of new cases of a disease/condition in a certain population, over a specified timeframe.
Imagine you are looking at a high school and there is a virus going around (e.g. the flu). On Monday, only 4 students were sick but the next day you hear that there are 16 new cases of infected students. This means that the incidence of flu cases (new cases) over the last 24 hours was 16.
In our COVID-19 example, “the incidence of COVID-19 cases in the US has doubled in the past two weeks”, incidence refers to the new infections that have risen in the past two weeks.
What is prevalence?
Prevalence does not differentiate between old and new cases, it refers to all current cases of a disease/condition in a certain population, at a specified point in time or over a specified period.
Let’s go back to our high school example where students are getting sick from the flu. The prevalence, in this case, refers to how many students in total, on a specific day, have the flu. So, the prevalence of flu cases on Tuesday was 20 (4 kids that were sick on Monday + 16 kids that got sick the next day).
In our example of cervical cancer, this means that there are currently less Belgian women with that type of cancer compared to in 2014, due to less incident cases (e.g. HPV vaccination) or early screening programs that detect/treat the condition.
So for chronic conditions( e.g. HIV, diabetes), as incident cases accumulate, the prevalence will go up. Whereas for acute conditions (e.g. COVID-19, flu, measles), prevalence will go down once the outbreak dies out and people recover.
Why do we need these indicators?
Knowing the incidence and prevalence of a health condition allows us to:
- Detect a new outbreak and taking immediate action
- Evaluate health interventions (e.g. fewer cases)
- Have a better understanding of the burden of the condition
- Evaluate where, to whom and how often the condition occurs
- Compare communities, identifying risk groups where the condition occurs more often, and allocating necessary resources
Overall, both indicators are used in combination.
The Epidemiologist’s bathtub
Have you heard of the “Epidemiologist’s bathtub”? It’s a fun visual representation to better understand the concepts of incidence, prevalence, as well as recovery and death in a community. Take a look!
In this visualization, you can see that incidence (the new drops of water entering the tub) represent the number of new cases of a disease or a condition. This adds to the prevalence (the water that is already in the bathtub) which represents the total number of cases of that same condition. The prevalence rate may vary as people can recover from the disease (water evaporating from the tub) or pass away from it (drops leaking out of the bathtub).
Morbidity vs. Mortality
You’ve probably heard these terms when talking about diseases/health conditions or their burden. For example:
- Unhealthy lifestyles increase morbidity rates
- In 2020, one of the leading cause of mortality among the elderly, in many countries across the globe, was COVID-19
Both terms sound like bad news, right? But what exactly do they mean?
What is morbidity?
Remember when we talked about the incidence and prevalence of a disease? Both terms are used to describe morbidity!
“Morbidity” simply means having a disease/condition. Common morbidities include: diabetes, depression, hypertension, COVID-19, etc. Whereas “morbidity rate” refers to how many people, in a certain population, are suffering from a certain medical condition. So:
Morbidity rate = number of people affected by disease or condition / total number of people in a specific population
Going back to our example, adopting unhealthy lifestyles increases disease (morbidity) rates. For instance, drinking and smoking increases the risk of different types of cancers.
How about “co-morbidity”?
You can have more than one health condition, at the same time. For example, people with Type II diabetes are more likely to also develop conditions such as obesity, hypertension, heart disease, etc. When an individual has several conditions, we talk about “comorbidities”.
What is mortality?
A synonym for “mortality” is “death”. Mortality rate refers to how many people in a certain population have died as a result of a certain disease or condition. So for example, morbidities (diseases) with high mortality (death) rates include: stroke, lung cancers, chronic obstructive pulmonary disease, etc.
There are different types of mortality rates (e.g. crude mortality rate, cause-specific rate, etc.). To determine the overall mortality rate of a population (per 1000 people), we calculate:
Crude mortality rate = number of all deaths / total number of people in a specific population
In our COVID-19 example, it means that at that specific period of time, the leading cause of death (among all deaths) in that population was COVID-19.
Why do we need these indicators?
Knowing the morbidity and mortality rates of a disease helps with:
- Understanding the severity of a condition (e.g. How fatal is this condition? Does it have a high mortality rate?)
- Determining the overall health status of a population overtime (e.g. Is the morbidity rate of a certain disease going down after the implementation of a public health intervention?)
- Comparing health status between/among countries, communities, age groups, by sex, etc. (e.g. Are there higher morbidity rates in a specific group? Why does a certain condition seem to affect this group more than others?)
- Learning about risk factors of diseases (e.g. Has a certain lifestyle/exposure to a certain hazard increased the morbidity rate of a disease?)
Mortality in and around infancy
Let’s go a bit more in depth into the concept of “mortality rates” and have a look at different indicators to describe child mortality, specifically.
Since 1990, child mortality across the globe has dropped by almost 60% in 2021. This decrease was caused by low-cost interventions such as vaccination, improved nutrition, different sanitary measures, etc. However, there’s still a lot of work to do. In 2020, an estimated 5 million children, under the age of 5 died, mostly from preventable and treatable causes. Almost half of those deaths occurred among newborns.
Understanding when, where and why these deaths occur, and who is affected, help us understand how to prevent these early deaths. A common way of measuring deaths is as mortality rates (number of deaths in a given year per 1000 live births in a population).
We do this to make comparisons easier. If a country has a large population, the total number of child deaths may be higher than in a country with a smaller one, so comparing the number of deaths is not useful.
For example, in 2021, India had a child mortality rate of 31 deaths per 1000 live births. Whereas Burundi, in that same time period, had a child mortality rate of 53 per 1000 live births. However, India’s population is more than 100 times larger than that of Burundi. If you would then compare the total number of child deaths, we would conclude that the child mortality rate is higher in India than in Burundi, which is not the case.
Why are these mortality rates useful?
These mortality rates measure outcomes not inputs. It’s the main thing we want to change. For example, the percent of children immunized or the number of doctors in a given country both measure a means to an end—doctors and immunizations help keep kids healthy. But ultimately if mortality rates are not declining, we know that something is not working right.
Splitting mortality rates into different categories is useful because the cases of death in different age groups (even among children) can vary. Let’s have a look at child mortality rate and infant mortality rate as an example.
Child Mortality Rate (also called under five mortality rate, U5MR) is most commonly used and is defined as the probability of a child’s death before reaching the age of five, expressed per 1000 live births. The 5-year cut-off is useful as children’s deaths decline sharply after this age.
High under-five mortality is typically a result of a combination of poor nutrition, low immunization rates, poor maternal health and education, etc. For this reason, it is a powerful indicator of inequity and systemic health challenges in a country or region.
Infant Mortality Rate (IMR) is the number of deaths of infants under age 1 per 1000 live births in a given year. It is described as the probability of a newborn dying between birth and age one. Infant mortality makes up a big bulk of the under 5 mortality. Since mortality is higher at early ages of infancy than at later ages, it is useful to break up the IMR into neonatal mortality and post-neonatal mortality.
Neonatal Mortality Rate is the number of newborns dying in the first 28 days of life per 1000 live births in a specific geographic area and for a given period of time. These deaths are often caused by factors such as childbirth-related complications (lack of breathing at birth), birth defects, or infections.
Overall, these mortality rates not only help us measure survival, but also reflect social, economic and environmental conditions in which children –and others in society– live, including their health care. Since data on the number of diseases (morbidity) is frequently unavailable, mortality rates are often used to identify vulnerable populations and better understand key health issues among newborns, infants, children and mothers.
Good news: child mortality rates have been steadily declining worldwide over the last 30 years. But much more remains to be done. Addressing these challenges requires good data (including for these indicators), evidence-based interventions, and strategies that ensure successful rollout and uptake among populations. Successful implementation involves accounting for contextual factors such as female empowerment, nutrition, healthcare, etc.
Below you can have a look at other indicators of mortality in and around infancy:
We hope that this blogpost gives you better clarity on these different indicators that are commonly used in public and global health. Share in the comments if there are any other health indicators you’d like to know more about!