Читать книгу Principles of Virology, Volume 2 - Jane Flint, S. Jane Flint - Страница 37

The terminology used to calculate the number of people who are infected and/or who become ill following a viral outbreak can be confusing. The following fictional example will be used to clarify these definitions.

Imagine that, in a city of 200,000 residents, a virus causes infection of 50,000 persons (as determined by serology). Of these, 20,000 develop signs of illness and 10,000 die of the infection.

 The incidence of this infection is the number of people infected divided by the population (50,000/200,000, or 25%).

 Morbidity rate is the number of individuals who became ill divided by the number of individuals at risk (20,000/200,000, or 10%).

 Mortality rate is the number of deaths divided by the number of individuals who are at risk (10,000/200,000, or 5%).

 The case fatality ratio is the proportion of deaths within a population of infected individuals. This value is typically expressed as a percentage. Case fatality ratios are most often used for diseases with discrete, limited time courses, such as outbreaks of acute infections. In the above example, the case fatality ratio is the number of deaths divided by the number of individuals with illness (10,000/20,000, or 50%).

Representation of incidence, morbidity, and mortality rates in a population. Each person represents 10,000 members of a community, as in the example above. Orange individuals are those who are infected; red are those who show symptoms of infection; the coffin indicates those who have died of the infection.

As a real-world example, Nipah virus infection and resulting encephalitis in Southeast Asia in 2011–12 resulted in 280 cases and 211 deaths, a staggering case fatality ratio of 75%.

In contrast, retrospective studies are not encumbered by the need for large numbers of subjects and long study times. Instead, some number of subjects with the disease or side effect under investigation is selected, as is an equal number of subjects who do not have the disease. The presence of the variable under study is then determined for each group. For example, in one retrospective study of measles virus vaccine safety and childhood autism, a cohort of vaccinated children and an equivalent cohort of age-matched, unvaccinated children were chosen randomly. The proportion of children with autism was then calculated for each group to determine if the rate of occurrence of autism in the vaccinated group was higher, lower, or the same as in the unvaccinated group. The incidence of the side effect in each group is then calculated; the ratio of these values between groups is the relative risk associated with vaccination. In this example, the rate of autism was not found to be different in the two groups, showing that vaccination is not a risk factor for the development of this disorder (Chapter 7).