South of the stark downtown and governmental edifices of Tiananmen Square and the smiling image of Chairman Mao hanging above the red gates of the Forbidden City, the narrow streets of the curio district were bustling. The shops lining the street were filled with shelves offering rarities of every description, from Japanese bayonets to year-old porcelain, most of it shameless fakery.
The 5W's of descriptive epidemiology: Epidemiologists strive for similar comprehensiveness in characterizing an epidemiologic event, whether it be a pandemic of influenza or a local increase in all-terrain vehicle crashes. However, epidemiologists tend to use synonyms for the five W's listed above: Descriptive epidemiology covers time, place, and person.
Compiling and analyzing data by time, place, and person is desirable for several reasons.
First, by looking at the data carefully, the epidemiologist becomes very familiar with the data. He or she can see what the data can or cannot reveal based on the variables available, its limitations for example, the number of records with missing information for each important variableand its eccentricities for example, all cases range in age from 2 months to 6 years, plus one year-old.
Second, the epidemiologist learns the extent and pattern of the public health problem being investigated — which months, which neighborhoods, and which groups of people have the most and least cases.
Third, the epidemiologist creates a detailed description of the health of a population that can be easily communicated with tables, graphs, and maps. Fourth, the epidemiologist can identify areas or groups within the population that have high rates of disease. This information in turn provides important clues to the causes of the disease, and these clues can be turned into testable hypotheses.
Time The occurrence of disease changes over time. Some of these changes occur regularly, while others are unpredictable. Two diseases that occur during the same season each year include influenza winter and West Nile virus infection August—September. In contrast, diseases such as hepatitis B and salmonellosis can occur at any time.
For diseases that occur seasonally, health officials can anticipate their occurrence and implement control and prevention measures, such as an influenza vaccination campaign or mosquito spraying.
For diseases that occur sporadically, investigators can conduct studies to identify the causes and modes of spread, and then develop appropriately targeted actions to control or prevent further occurrence of the disease.
In either situation, displaying the patterns of disease occurrence by time is critical for monitoring disease occurrence in the community and for assessing whether the public health interventions made a difference. Time data are usually displayed with a two-dimensional graph.
The vertical or y-axis usually shows the number or rate of cases; the horizontal or x-axis shows the time periods such as years, months, or days. The number or rate of cases is plotted over time. Graphs of disease occurrence over time are usually plotted as line graphs Figure 1.
Centers for Disease Control and Prevention. Summary of notifiable diseases—United States, Surveillance Summaries, January 24, Sometimes a graph shows the timing of events that are related to disease trends being displayed.
For example, the graph may indicate the period of exposure or the date control measures were implemented. Studying a graph that notes the period of exposure may lead to insights into what may have caused illness.
Studying a graph that notes the timing of control measures shows what impact, if any, the measures may have had on disease occurrence. As noted above, time is plotted along the x-axis. Depending on the disease, the time scale may be as broad as years or decades, or as brief as days or even hours of the day.
For some conditions — many chronic diseases, for example — epidemiologists tend to be interested in long-term trends or patterns in the number of cases or the rate. For other conditions, such as foodborne outbreaks, the relevant time scale is likely to be days or hours.
Some of the common types of time-related graphs are further described below. These and other graphs are described in more detail in Lesson 4. Graphing the annual cases or rate of a disease over a period of years shows long-term or secular trends in the occurrence of the disease Figure 1.
Health officials use these graphs to assess the prevailing direction of disease occurrence increasing, decreasing, or essentially flathelp them evaluate programs or make policy decisions, infer what caused an increase or decrease in the occurrence of a disease particularly if the graph indicates when related events took placeand use past trends as a predictor of future incidence of disease.
Disease occurrence can be graphed by week or month over the course of a year or more to show its seasonal pattern, if any. Some diseases such as influenza and West Nile infection are known to have characteristic seasonal distributions.
Seasonal patterns may suggest hypotheses about how the infection is transmitted, what behavioral factors increase risk, and other possible contributors to the disease or condition.
All three diseases display consistent seasonal distributions, but each disease peaks in different months — rubella in March to June, influenza in November to March, and rotavirus in February to April. The rubella graph is striking for the epidemic that occurred in rubella vaccine was not available untilbut this epidemic nonetheless followed the seasonal pattern.
Day of week and time of day. For some conditions, displaying data by day of the week or time of day may be informative. Analysis at these shorter time periods is particularly appropriate for conditions related to occupational or environmental exposures that tend to occur at regularly scheduled intervals.This is believed to be the mechanism underlying the appearance of SARS (severe acute respiratory syndrome) in The disease was characterised by an abrupt-onset of respiratory symptoms, which progressed rapidly to severe respiratory compromise often requiring ventilatory support.
Although it only sickened about 8, people, resulting in close to deaths, this SARS (Severe Acute Respiratory Syndrome) virus offered an example of how quickly infectious diseases can move across borders and disrupt travel and commerce.
The global nonmedical response to severe acute respiratory syndrome (SARS) and experiences in various states like China, Vietnam, Singapore or Canada with large – scale quarantine, raised ethical questions in seeking the right balance between the tension of protecting the public`s health and human rights and human needs.
Health, Science, Environment. Government Views of SARS (Severe Acute Respiratory Syndrome) - Several online primary resources about SARS, including government documents. TIME Asia Magazine: China's Failing Health System, "in China's hinterlands, medical facilities remain woefully unprepared for the SARS outbreak, hobbled by years of government neglect".
Acute respiratory distress syndrome is an inﬂammatory disease characterized by dysfunction of pulmonary epithelial and capillary endothelial cells, infiltration of alveolar macrophages and neutrophils, cell apoptosis, necroptosis, NETosis, and fibrosis.
Essay – Preventing Accidental Disease Outbreaks: Biosafety in East Asia. to examine the lessons from three recent accidents involving the virus that causes severe acute respiratory syndrome (SARS), and to assess the state of biosafety in East Asia.
Basics of Biosafety.