Wednesday, 10 July 2019




The study of viruses can be likened to a set of concentric circles. The most basic studies in virology comprise the detailed analyses of the genome and the structures of viral particles and proteins, which are crucial to understanding the biochemical consequences of the interaction of viral with host cell proteins. How infection of individual cells affects the tissue in which the infected cells reside and how that infected tissue disturbs the biology of the host defines the landscape of the field of viral pathogenesis (discussed in the next four articles). But if a viral population is to survive, the transmission must occur from an infected host to susceptible, uninfected hosts. The study of infections of populations is the discipline of epidemiology, the cornerstone of public health research.

An epidemiologist investigates outbreaks by undertaking careful data collection in the field (that is, where the infections occur) and performing statistical analyses. Often, questions such as “how might the symptoms observed in an infected individual implicate one mode of viral transmission over another?” or “can a timeline be established to trace back the origins of an epidemic to a single event?” are asked. The answers help epidemiologists learn more about the pathogen that caused the epidemic. Social interactions, individual differences among prospective hosts, group dynamics and behaviors, geography, and weather, all influence how efficiently a virus can establish infection within a population. Epidemiologists lack the luxury of performing controlled experiments in which only one variable is manipulated. Consequently, they must consider many parameters simultaneously to identify the source and transmission potential of a viral pathogen within a host community. 

Fundamental Concepts

Incidence versus Prevalence

Determining the number of infected individuals is a primary goal of epidemiological studies. This information is required to establish both the incidence and the prevalence of infection. Incidence is defined as the number of new cases within a population in a specified period. Some epidemiologists use this term to determine the number of new cases in a community during a particular period of time, while others use incidence to indicate the number of new disease cases per unit of population per period. For example, the incidence of influenza can be stated as the number of reported cases in New York City per year or the number of new cases/1,000 people/ year. Disease prevalence, on the other hand, is a measure of the number of infected individuals at one moment in time divided by an appropriate measure of the population. 

A highly infectious and lethal disease (such as the 1793 epidemic of yellow fever in Philadelphia) may have a high incidence but a low prevalence because many of the infected individuals either died or cleared the infection. In contrast, a virus that can persist in a host for decades is likely to have a high prevalence. An example of high prevalence is provided by hepatitis B virus; of the 300 to 400 million people infected globally, one-third live in China, with 130 million carriers. For this reason, the incidence is an informative measure for acute infections, whereas prevalence is often used to describe persistent infections in which disease onset is not easily determined.

Prospective and Retrospective Studies

Infections of natural populations obviously differ from those under controlled conditions in the laboratory. Nevertheless, it is possible to determine if one or more variables affect disease incidence and viral transmission in nature. Two general experimental approaches are used: prospective (also called cohort or longitudinal) and retrospective (or case-controlled) studies. In prospective studies, a population is randomly divided into two groups (cohorts). One group then gets the “treatment of interest,” such as a vaccine or a drug, and the other does not. The negative-control population often receives a placebo. Whether a person belongs to the treatment or placebo cohort is not known to either the recipient or the investigator until the data are collected and the code is broken (“ double-blind ”). Th is strategy removes potential investigator bias and patient expectations that may otherwise skew the data. Once the data are collected, the code is broken, and the incidence of disease or side eff ect is determined for each cohort and compared. Prospective studies require a large number of subjects, who oft en are followed for months or years. The number of subjects and time required to depend on the incidence of the disease or side effect under consideration and the statistical power required to draw conclusions. 
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 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 or without 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 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.

Mortality, Morbidity, and Case Fatality Ratios

Three other measures used in epidemiology can cause confusion because of the similarity of their definitions: mortality, morbidity, and case fatality ratios. Mortality is expressed as a percentage of deaths in a known population of infected individuals. Thus, 40 deaths in a population of 2,000 infected individuals would be expressed as 2% mortality (40/2,000). The morbidity rate is similar but refers to the number of infected individuals in a given population that show symptoms of infection per unit of time. The morbidity percentage will always be higher than the mortality percentage, of course, because not all sick individuals will die of the infection.

In contrast, a case fatality ratio is a measure of the number of deaths among clinical cases of the disease, expressed as a percentage. As an example, if 200 people are diagnosed with a respiratory tract infection and 16 of them die, the case fatality ratio would be 16/200, or 8%. In a technical sense, the use of the word “ratio” is incorrect; a case fatality ratio is actually more a measure of relative risk than a ratio between two numbers. While statistics are crucial to all studies in virology, they are of particular value in viral epidemiology, in which outcomes and causes are rarely black or white.

Tools of Epidemiology

We have considered some of the terms that epidemiologists use, but how do these scientists monitor and develop strategies to control the spread of viruses in populations? An investigation begins at the site of an outbreak, whereas many descriptive data as possible about the infected cases and the environment are gathered. In cases of viral infections in humans, information on recent travel, lifestyle, and preexisting health conditions is considered, along with the medical records of infected individuals to generate a testable hypothesis about the origin of the outbreak. The word “descriptive” can have a negative connotation in virology and is often used to mean the opposite of “mechanistic.” However, in epidemiology, descriptive studies are essential to establish or exclude particular hypotheses about the origins of an outbreak. Indeed, descriptive epidemiology was the cornerstone for the discovery of the human immunodeficiency virus during the AIDS epidemic in the 1980s. Following the descriptive phase, analytical epidemiological methods are used to test hypotheses using control populations in either retrospectively or prospectively focused studies. Clinical epidemiology focuses on the collection of biospecimens, such as blood, sputum, urine, and feces, to search for viral agents or other pathogens and to help determine the potential route of transmission. Once specimens are collected, nucleic acid sequencing is often performed on the samples. In addition, such studies may include serological analyses, in which antibodies in the blood that implicate the previous infection are identified. A timeline of the discovery of the H1N1 strain of influenza virus in 2009 illustrates the speed and coordination of epidemiological efforts to identify and thwart widespread dissemination of this virus.


A final function of epidemiology is the establishment of vigilant surveillance procedures that can shorten the period between the beginning of an epidemic and its detection. One could argue that the development of worldwide surveillance programs and information sharing have had as profound an impact on limiting viral infections as antiviral medications and vaccines. The U.S. Centers for Disease Control and Prevention (CDC) was established in 1946 after World War II, with a primary mission to prevent malaria from spreading across the country. The scope of the CDC quickly expanded, and this institution is now a central repository for information and biospecimens available to epidemiologists; it also offers educational tools to foster awareness and ensure the safety of the public. The World Health Organization (WHO), founded in 1948 as an international agency of the United Nations, is charged with establishing priorities and guidelines for the worldwide eradication of viral agents. The WHO provides support to countries that may not have the resources to combat infectious diseases and coordinates results from a global network of participating laboratories. While the WHO provides coordination, the experimental work is performed in hundreds of laboratories throughout the world, often in remote locations which process samples and relay information back to the WHO. These WHO-certified laboratories adhere to stringent standards to ensure consistency of methods and interpretations. The laboratories conduct field surveillance using wild and sentinel animals and perform periodic blood screening for signs of infection or immunity. Sentinel animals (“canaries in the coal mine”) allow rapid identification of new pathogens that may have entered a particular ecosystem.

The chief successes of such global-surveillance efforts to date include the eradication of smallpox virus and Rinderpest virus, a relative of measles virus that causes disease in animals used in agriculture, such as cattle and sheep. The Internet is a powerful tool for data sharing and public education. Publications and websites help to distribute consistent and timely information to health care workers across the globe. The weekly Morbidity and Mortality Weekly Report , published by the CDC, provides a central clearinghouse for\ health care providers in the United States to communicate individual cases of infectious diseases or to report unusual observations. ProMED (Program for Monitoring Emerging Diseases), sponsored by the International Society for Infectious Diseases, is a worldwide effort to promote communication among members of “the international infectious disease community, including scientists, physicians, epidemiologists, public health professionals, and others interested in infectious diseases on a global scale” ( about us/). Reporting of individual cases, when considered by epidemiologists in the aggregate, may catch an epidemic in its earliest days, when intervention is most effective. Use of real-time data-gathering tools, such as Google Flu Trends, a Web-based application that surveys search queries from over 25 countries to predict influenza epidemics, have also emerged recently. While the predictions made from this application have been generally consistent with more-traditional surveillance data-gathering approaches, its accuracy and practical utility have not yet been proven. Nevertheless, the innovative use of keyword collection to monitor viral outbreaks underscores how collaboration between distinct fields (e.g., epidemiology and search engine design) can lead to creative ways to detect incipient outbreaks.

Discovery of the H1N1 strain of influenza virus (swine flu). Less than one month transpired between the first case (in San Diego County, CA) and the first press conference announcing the new strain. Adapted from ECDC Technical Emergency Team, Eurosurveillance 14(18):pii? 19204, 2009, with permission.

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