FemWIKI - User contributions [en]

Software for epidemiologists

2025-09-07T16:51:49Z

Bosmana fem:

==Statistical packages==
Statistical software is one of the most important software for epdiemiologists. For a detailed review see the list of [https://web.archive.org/web/20161220110100/http://en.wikipedia.org/wiki/Comparison_of_statistical_packages comparison of statistical packages from Wikipedia]. The most important ones are listed here:

* [https://web.archive.org/web/20161220110100/http://www.r-project.org/ R] = Open source statistics package
* [https://web.archive.org/web/20161220110100/http://www.stata.com/ Stata] = statistic software
* [https://web.archive.org/web/20161220110100/http://www-01.ibm.com/software/analytics/spss/ SPSS] =statistic software
* [https://web.archive.org/web/20161220110100/http://www.graphpad.com/scientific-software/prism/ GraphPad Prism] = statistic software focused on graphs
* [https://web.archive.org/web/20161220110100/http://www.openepi.com/v37/Menu/OE_Menu.htm Openepi] = Open Source Epidemiologic Statistics for Public Health
* [https://web.archive.org/web/20161220110100/http://www.atlasti.com/index.html Atlasti] = Qualitative statistics software
* [https://web.archive.org/web/20161220110100/http://surveillance.cancer.gov/joinpoint/ Joinpoint] = analysis of trends using joinpoint models
* [https://web.archive.org/web/20161220110100/http://www.palisade.com/risk/ Atrisk] = risk analysis using Monte Carlo simulation
* Quick guide for experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R. http://www.statmethods.net/index.html

==GIS software==
Geographical information systems are used for displaying and analysing geographic data. For a detailed list see the [https://web.archive.org/web/20161220110100/http://en.wikipedia.org/wiki/List_of_geographic_information_systems_software list of GIS-software from Wikipedia]. The most important ones are listed here

* [https://web.archive.org/web/20161220110100/http://www.esri.com/software/arcgis/ Acrgis] = frequently used program
* [https://web.archive.org/web/20161220110100/http://www.qgis.org/en/site/ Quantum GIS] = Open source GIS program
* [https://web.archive.org/web/20161220110100/http://www.gfk-regiograph.com/en/homepage.html Regiograph] = business mapping software

==Data entry software==
* [https://web.archive.org/web/20161220110100/http://www.epidata.dk/ Epidata] = data collection instrument released by the non-profit organisation "The EpiData Association"
* [https://www.who.int/tools/godata Go.Data]

==Field Epidemiology Packages==
* [https://web.archive.org/web/20161220110100/http://wwwn.cdc.gov/epiinfo/ Epiinfo] = The very first all-round Field Epidemiology Support Software by CDC<Ref>See also: The Rise and Fall of Epi Info https://fieldepi.eu/the-rise-and-fall-of-epi-info/</ref>
* [https://sormas.org/ SORMAS]

== Social network analysis==
* [https://web.archive.org/web/20161220110100/http://www.cytoscape.org/ Cytoscape] = Open source social network analysis tool

== Online questionnaires software==
* [https://web.archive.org/web/20161220110100/https://www.limesurvey.org/en/ Limesurvey] = Open source online questionnaire tool
* [https://web.archive.org/web/20161220110100/http://www.classapps.com/SelectSurveyNETOverview.asp Select survey]
* [https://web.archive.org/web/20161220110100/https://www.surveymonkey.com/ Survey monkey]
* [https://web.archive.org/web/20161220110100/https://portal.voozanoo.net/ Voozanoo]

==FEM PAGE CONTRIBUTORS 2007==
; Editor
: Arnold Bosman
; Contributors
: Vladimir Prikazsky
: Jakob Schumacher
: Arnold Bosman

=References=
</references>

[[Category:Public Health Informatics]]

Primary prevention

2025-07-08T08:13:08Z

Bosmana fem:

Within the framework of [[Field Epidemiology|field epidemiology]], primary prevention plays a vital role in averting the onset of communicable diseases and reducing their overall impact on public health.<ref>Centers for Disease Control and Prevention. (2012). Principles of Epidemiology in Public Health Practice, 3rd ed. Lesson 3: Measures of Risk. https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section2.html</ref><ref>This text was written by ChatGPT4.0 on 26 March 2023 and reviewed by Arnold Bosman.</ref>

Key strategies in primary prevention include [[Vaccination|immunisation]] programs, which protect populations from infectious agents such as [[Measles|measles]], polio, and influenza through vaccination.<ref>World Health Organisation. (2023). Immunisation coverage. https://www.who.int/news-room/fact-sheets/detail/immunization-coverage</ref>
Health education and promotion campaigns—such as handwashing initiatives and safe food handling practices—encourage behaviours that reduce the risk of disease [[Transmission routes|transmission]].

[[Vector Borne|Vector control measures]], including the use of insecticide-treated bed nets and environmental source reduction, help limit the spread of vector-borne diseases like malaria and dengue fever. Environmental interventions, such as improving access to clean water and sanitation, also play a critical role by reducing exposure to disease-causing pathogens.

Through these proactive efforts, field epidemiologists contribute to building resilient communities and establishing a strong foundation for communicable disease prevention.

== References ==
<references />

[[Category:Prevention]]

Category:Prevention

2025-07-08T08:11:13Z

Bosmana fem:

In the realm of communicable disease control, prevention strategies are classified into three distinct categories: [[Primary prevention|primary]], [[Secondary prevention|secondary]], and [[Tertiary prevention|tertiary]] prevention.
* Primary prevention focuses on preemptive measures to avoid the onset of disease, targeting healthy individuals through methods such as vaccinations, health education, and promoting hygienic practices.
* Secondary prevention aims to identify and treat the disease in its early stages to halt its progression, typically utilizing screening programs and early diagnosis interventions.
* On the other hand, tertiary prevention targets individuals with an established disease, seeking to minimize complications and improve the quality of life through rehabilitation, long-term care, and chronic disease management.

Collectively, these prevention strategies form a comprehensive approach to controlling communicable diseases, reducing morbidity, and mitigating the overall impact on public health.

=References=
* This text was written by ChatGPT4.0 on 26 March 2023 and reviewed by Arnold Bosman.

[[Category:Public Health Interventions]]

Category:Prevention

2025-07-08T08:10:35Z

Bosmana fem:

In the realm of communicable disease control, prevention strategies are classified into three distinct categories: [[Primary prevention|primary]], [[Secondary prevention|secondary]], and [[Tertiary prevention|tertiary]] prevention.
* Primary prevention focuses on preemptive measures to avoid the onset of disease, targeting healthy individuals through methods such as vaccinations, health education, and promoting hygienic practices.
* Secondary prevention aims to identify and treat the disease in its early stages to halt its progression, typically utilizing screening programs and early diagnosis interventions.
* On the other hand, tertiary prevention targets individuals with an established disease, seeking to minimize complications and improve the quality of life through rehabilitation, long-term care, and chronic disease management. Collectively, these prevention strategies form a comprehensive approach to controlling communicable diseases, reducing morbidity, and mitigating the overall impact on public health.

=References=
* This text was written by ChatGPT4.0 on 26 March 2023 and reviewed by Arnold Bosman.

[[Category:Public Health Interventions]]

Category:Assessing the burden of disease and risk assessment

2025-07-08T08:08:37Z

Bosmana fem:

Effective disease [[Prevention|prevention]] and control depends on several factors that must be present and work together in the community. It all starts with the ability to detect threats to the population's health. A threat can be seen as an undesirable situation that has not yet occurred but may happen unless protective measures are taken. The ability to detect a disease threat implies that we already have basic knowledge about the 'normal occurrence (or burden)' of this disease in the population.

Assessing the disease burden requires a public health workforce competent to collect, analyze and interpret health data from "your" population and the healthcare system infrastructure that allows access to relevant data. [[Field Epidemiology]] methods are central in assessing disease burden.

Detect health threats requires (in addition to the above) continuous monitoring of the burden of disease information of 'your own' and surrounding populations, trends in risk behaviour, characteristics of pathogens (e.g., development of antimicrobial resistance) plus competent staff responsible for the continuous collection, analysis, and interpretation of information. Detecting health threats is sometimes referred to as [[epidemic intelligence]].

Once health threats have been detected and validated, information must be shared with "those who need to know" in the health system. This usually requires translating specific epidemiology jargon into a format used by policy and decision-makers to decide on [[Public Health Interventions|public health interventions]] (preventive and control measures).

This part of this FEMWiki addresses methods that can be used to assess the population's health status and detect and assess health threats. Methods for [[Surveillance principles|Surveillance]], [[Formal Risk Assessment|Risk Assessment]], and [[Outbreak Investigations]] will be described in this section.

[[Public Health Interventions|Interventions]] (public health measures, policy-making, and decision-taking) are discussed in another part of the FEMWIKI. Communication is yet another topic.

<div style="display: inline-block; width: 25%; vertical-align: top; border: 1px solid #000; background-color: #d7effc; padding: 10px; margin: 5px;">
'''FEM PAGE CONTRIBUTORS 2007'''
;Editors
:Arnold Bosman
;FEM Contributors
:Patty Kostkova
</div>
[[Category:Root]]

Category:Assessing the burden of disease and risk assessment

2025-07-08T08:07:45Z

Bosmana fem:

Effective disease [[Category:Prevention|prevention]] and control depends on several factors that must be present and work together in the community. It all starts with the ability to detect threats to the population's health. A threat can be seen as an undesirable situation that has not yet occurred but may happen unless protective measures are taken. The ability to detect a disease threat implies that we already have basic knowledge about the 'normal occurrence (or burden)' of this disease in the population.

Assessing the disease burden requires a public health workforce competent to collect, analyze and interpret health data from "your" population and the healthcare system infrastructure that allows access to relevant data. [[Field Epidemiology]] methods are central in assessing disease burden.

Detect health threats requires (in addition to the above) continuous monitoring of the burden of disease information of 'your own' and surrounding populations, trends in risk behaviour, characteristics of pathogens (e.g., development of antimicrobial resistance) plus competent staff responsible for the continuous collection, analysis, and interpretation of information. Detecting health threats is sometimes referred to as [[epidemic intelligence]].

Once health threats have been detected and validated, information must be shared with "those who need to know" in the health system. This usually requires translating specific epidemiology jargon into a format used by policy and decision-makers to decide on [[Public Health Interventions|public health interventions]] (preventive and control measures).

This part of this FEMWiki addresses methods that can be used to assess the population's health status and detect and assess health threats. Methods for [[Surveillance principles|Surveillance]], [[Formal Risk Assessment|Risk Assessment]], and [[Outbreak Investigations]] will be described in this section.

[[Public Health Interventions|Interventions]] (public health measures, policy-making, and decision-taking) are discussed in another part of the FEMWIKI. Communication is yet another topic.

<div style="display: inline-block; width: 25%; vertical-align: top; border: 1px solid #000; background-color: #d7effc; padding: 10px; margin: 5px;">
'''FEM PAGE CONTRIBUTORS 2007'''
;Editors
:Arnold Bosman
;FEM Contributors
:Patty Kostkova
</div>
[[Category:Root]]

FEM-WIKI

2025-07-08T07:59:05Z

Bosmana fem: /* Field Epidemiology Manual */

= '''Field Epidemiology Manual''' =

The Field Epidemiology Manual was originally developed in [https://web.archive.org/web/20050315063110/http://www.epiet.org/index.html 2004-2005 by EPIET] as the Field Epidemiology Manual, where facilitators and scientific coordinators contributed chapters. This informal reference book was transformed in 2007 into a WIKI format by the [http://ecdc.europa.eu ECDC] and the City eHealth Research Centre (CeRC - City University, London) <Ref>KOSTKOVA, Patty; SZOMSZOR, Martin. The FEM Wiki Project: A Conversion of a Training Resource for Field Epidemiologists into a Collaborative Web 2.0 Portal. In: Electronic Healthcare: Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers 3. Springer Berlin Heidelberg, 2012. p. 119-126.</ref>, <Ref>KOSTKOVA, Patty; PRIKAZSKY, Vladimir; BOSMAN, Arnold. FEMwiki: Crowdsourcing Semantic Taxonomy and Wiki Input Todomain Experts While Keeping Editorial Control: Mission Possible! In: Proceedings of the 5th International Conference on Digital Health 2015. 2015. p. 27-34.</ref> to support the European Programme for Intervention Epidemiology Training ([https://www.ecdc.europa.eu/en/epiet-euphem EPIET]). Trainers, supervisors, scientific coordinators, and facilitators created draft chapters using the lectures they delivered during the EPIET introductory course. The philosophy of sharing and building knowledge (in particular training materials) led to creation of a collaborative information space for the epidemiological training community - The FEM Wiki.

Eventually, the ECDC decommissioned the FEM Wiki in 2022 and archived the last version as a [https://eva.ecdc.europa.eu/mod/resource/view.php?id=23002 PDF]. Since FEM Wiki content was developed under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons], the Dutch Public Health Learning Support Company [https://Transmissible.eu Transmissible] decided to reinstall the Field Epidemiology manual as it was intended: a professional collaborative platform.

The FEMWiki aims to create a library of training materials for field epidemiologists.

FEM Wiki is an open information-sharing platform for all professionals and the lay public interested in public health. It is hosted and funded by ECDC. Platform users provide the content of FEM Wiki and do not necessarily represent the official opinion of Transmissible BV. By contributing content to FEMWIKI, users agree to the conditions described under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons] and FEM Wiki users’ [[FEM Users code of conduct|code of conduct]].

Though this platform does not allow as many community activities besides maintaining the Field Epidemiology Manual, we have created an [[Talk:FEM-WIKI|open marketplace where users can discuss and exchange views]]: click on the 'Discussion' tab above. The FEMWIKI is organised into five main volumes. Below is a portal with links to each volume's main articles.

<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Methods Portal'''
<categorytree mode="all">Assessing the burden of disease and risk assessment</categorytree>
<categorytree mode="all">Statistical Concepts</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Public Health Portal'''
<categorytree mode="all">Introduction to Public Health and basic concepts</categorytree>
<categorytree mode="all">General Communication</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Infection Control'''
<categorytree mode="all">Infection control and hospital hygiene</categorytree>
</div>

=References=
<References/>

=FEMWiki Needs You!=
YES, you should contribute!
If you are a Field Epidemiologist who loves to manage and share knowledge, then you are the one FEMWiki needs. [https://fieldepi.eu/fem-editor/ Request an account here], and we will be delighted to include more Field Epidemiologists in the FEM-editor crew!
[[File:Aunt WIKI needs you2.jpg]]

Category:Public Health Law

2025-06-03T06:47:46Z

Bosmana fem:

Among the tools that governments have to influence the population's health, public health law is critical to reduce illness and preventing premature death. Public health law examines the government's authority at various jurisdictional levels to improve the general population's health within societal limits and norms.

Public health staff may encounter various legal and policy decisions during their public health work, including:

The need to apply isolation or quarantine measures in order to reduce public health threats
Closing schools and other public gatherings, temporarily or for longer periods to limit the spread of communicable diseases
The authority to mandate vaccinations for minors or autonomous adults, including health care workers
Licensing, credentialing and privileging health practitioners from abroad
Inter-disciplinary and inter-departmental management of resources, including personnel, vaccines, shelter etc
Concerns over the liability of public health practitioners during emergencies
Public health measures must be applied to contain and control events with potential health impact.

Public health law typically has three major areas of practice: police power, disease and injury prevention, and the law of populations.

==Police Power==
These areas perpetuate are employed by governmental agencies. Bioterrorism is a growing focus of this practice area in some jurisdictions, yet also more day to day law enforcement situations such as closing down restaurants or production facilities, giving fines to health care facilities and impounding suspected sources of infections fall under this area.

A specific part of this area deals with questions of case management of highly infectious individuals: what are the legal possibilities for restricting movement and treatment against the will of the individual? Public Health Doctors that encounter such situations do well to get in touch with public health law experts for guidance.

==Disease and Injury Prevention==
This broader area of public health law applies legal tools to public health problems associated with disease and injury. Practitioners apply legislation, regulation, litigation (private enforcement), and international law to public health problems using the law as an instrument of public health. Litigation against tobacco companies in the United States provides an excellent example.

==Law of Populations==
Population-based legal analysis is the theoretical foundation of public health law. The law of populations is a relatively new theoretical framework in jurisprudence that seeks to analyze legal problems using the tools of epidemiology. Population-based legal analysis can be applied to traditional public health problems but also has application in environmental law, zoning, evidence, and complex tort.

==Communicable Diseases and Law Enforcement==
Many countries have specific national laws on the control of communicable diseases. Internationally, there are many regulations that address this topic. The International Health Regulations (2005) offer global regulations concerning people and goods, aimed to reduce spread of 'public health events of international concern'. This IHR is one of the most recent in short history of global international health laws, aimed to reduce global spread of diseases. The EU has adopted a specific set of regulations, addressing communicable disease prevention and control in the European Union.

<<<EDITORS WANTED FOR PUBLIC HEALTH LAW CHAPTERS >>>>>
=References=
1. Public Health Law, Wikipedia, accessed 28 January 2011.

2. Centers for Disease Control and Prevention's Public Health Law Program

3. The network for public health law; https://www.networkforphl.org/

[[Category:Introduction to Public Health and basic concepts]]

FEM-WIKI

2025-05-22T12:51:19Z

Bosmana fem: /* Field Epidemiology Manual */

= '''Field Epidemiology Manual''' =

The Field Epidemiology Manual was originally developed in 2004-2005 by EPIET as the Field Epidemiology Manual, where facilitators and scientific coordinators contributed chapters. This informal reference book was transformed in 2007 into a WIKI format by the [http://ecdc.europa.eu ECDC] and the City eHealth Research Centre (CeRC - City University, London) <Ref>KOSTKOVA, Patty; SZOMSZOR, Martin. The FEM Wiki Project: A Conversion of a Training Resource for Field Epidemiologists into a Collaborative Web 2.0 Portal. In: Electronic Healthcare: Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers 3. Springer Berlin Heidelberg, 2012. p. 119-126.</ref>, <Ref>KOSTKOVA, Patty; PRIKAZSKY, Vladimir; BOSMAN, Arnold. FEMwiki: Crowdsourcing Semantic Taxonomy and Wiki Input Todomain Experts While Keeping Editorial Control: Mission Possible! In: Proceedings of the 5th International Conference on Digital Health 2015. 2015. p. 27-34.</ref> to support the European Programme for Intervention Epidemiology Training ([https://www.ecdc.europa.eu/en/epiet-euphem EPIET]). Trainers, supervisors, scientific coordinators, and facilitators created draft chapters using the lectures they delivered during the EPIET introductory course. The philosophy of sharing and building knowledge (in particular training materials) led to creation of a collaborative information space for the epidemiological training community - The FEM Wiki.

Eventually, the ECDC decommissioned the FEM Wiki in 2022 and archived the last version as a [https://eva.ecdc.europa.eu/mod/resource/view.php?id=23002 PDF]. Since FEM Wiki content was developed under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons], the Dutch Public Health Learning Support Company [https://Transmissible.eu Transmissible] decided to reinstall the Field Epidemiology manual as it was intended: a professional collaborative platform.

The FEMWiki aims to create a library of training materials for field epidemiologists.

FEM Wiki is an open information-sharing platform for all professionals and the lay public interested in public health. It is hosted and funded by ECDC. Platform users provide the content of FEM Wiki and do not necessarily represent the official opinion of Transmissible BV. By contributing content to FEMWIKI, users agree to the conditions described under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons] and FEM Wiki users’ [[FEM Users code of conduct|code of conduct]].

Though this platform does not allow as many community activities besides maintaining the Field Epidemiology Manual, we have created an [[Talk:FEM-WIKI|open marketplace where users can discuss and exchange views]]: click on the 'Discussion' tab above. The FEMWIKI is organised into five main volumes. Below is a portal with links to each volume's main articles.

<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Methods Portal'''
<categorytree mode="all">Assessing the burden of disease and risk assessment</categorytree>
<categorytree mode="all">Statistical Concepts</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Public Health Portal'''
<categorytree mode="all">Introduction to Public Health and basic concepts</categorytree>
<categorytree mode="all">General Communication</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Infection Control'''
<categorytree mode="all">Infection control and hospital hygiene</categorytree>
</div>

=References=
<References/>

=FEMWiki Needs You!=
YES, you should contribute!
If you are a Field Epidemiologist who loves to manage and share knowledge, then you are the one FEMWiki needs. [https://fieldepi.eu/fem-editor/ Request an account here], and we will be delighted to include more Field Epidemiologists in the FEM-editor crew!
[[File:Aunt WIKI needs you2.jpg]]

Category:Odds

2025-05-21T07:49:35Z

Bosmana fem: /* Absolute Number */

=Absolute Number=
Odds (no synonyms), are expressed as an absolute number.

The odds of an event ("odds", always plural) occurring is the probability (e.g. risk) that this event will occur divided by the probability that the event will not occur. It can also be expressed as the probability that an event will occur divided by "1 minus the probability that the event will occur"<ref>Porta, M. A Dictionary of Epidemiology, Fifth edition. Oxford University press, 2008.</ref>.

P
Odds of event = -----------
1 - P

Note that probabilities allow us to calculate the odds of an event: probabilities and odds are related, but they are not the same thing.

𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 expresses the chance of an event happening out of the total number of possible outcomes. Probability is the likelihood that an event will occur, expressed as a value between 0 and 1 (e.g., a 20% chance is a probability of 0.2).

𝐎𝐝𝐝𝐬 express the ratio of the event happening to the event not happening. For a 20% chance (probability of 0.2), the odds are 0.25 (i.e., the odds of having the disease is 0.25).

[[File:Prob Vs Odds.png|400px|frameless|Visual representation about the differences between probabilities and odds]]
Visual representation about the differences between probabilities and odds

Odds is a probability measure that is popular in the world of gambling. If we compute the number of people putting money on one horse winning and the number of people putting money on the horse not winning (i.e., putting money on other horses), we can compute the odds of winning. For example, among 3100 persons gambling on horses, 100 persons put money on horse "A" to win, and 3000 do not (they bet on other horses). The odds of winning are then 1/30 (100/3100 divided by 3000/3100 which can be simplified as 100/3000 or 1 / 30). In fact, in gambling, the odds of not winning are preferred and expressed as a ratio X/1. In our example, 30/1, or in words, "thirty to one". This means that for every Euro that you bet, you will receive 30 if you win.

Since we illustrate the population under investigation in epidemiology with a two-by-two table, we will use a table to describe how to calculate odds. In the two-by-two table, the concept of exposure is also included. However, to calculate the odds of disease, it is not necessary to consider that in our population, some might have been exposed to a particular exposure and some not.

===Example 1===
{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 30 || 70 || 100
|}
The table yields the following calculations:
[[File:0028.risk of dis.png-550x0.png|400px|frameless|left]]

[[File:2086.odds of dis.png-550x0.png|600px|frameless|left]]

Therefore to calculate the odds: divide the risk of getting the disease by the risk of not getting the disease. It is equal to the ratio of the number of people with the disease to the number of people without it in a particular population.

The odds is a measure rarely used in epidemiology. Most often the odds are used to express the odds ratio. A disease-odds ratio is the ratio of the odds of having the disease among the exposed and the odds of having the disease among the unexposed [1]. In other words, the odds ratio is the ratio of the odds of disease observed in 2 subsets of a population.

In you take again the table as an example, the disease-odds ratio will be equal to:

Odds of developing the disease among the exposed: a / b

Odds of developing the disease among the unexposed: c / d

Disease-odds ratio:
[[File:2330.or simple.png-550x0.png|400px|frameless|left]]

As you see by comparing example one, two and three, the risk and the odds approximate each other when the event is rare. When the event occurs frequently the odds overestimate the risk of disease.

For this reason, in many situations (when the disease is rare) the odds ratio can estimate the risk ratio.

===Example 2===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 50 || 99 950 || 100 000
|}

Risk of disease = 50 / 100000 = 0.00050000

Odds of disease (50 / 100000) / 1 - (50/100000) = 0.00050025

When getting the disease is rare, the risk of disease approximates the odds of disease.

===Example 3===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 59 || 950 || 1000
|}

Risk of disease = 50 / 1000 = 0.05000

Odds of disease (50 / 1000) / 1 - (50/1000) = 0.05263

=References=
<References/>

=Credits=
===FEM Editor 2007===
* Sabrina Bacci
===Original Authors===
* Alain Moren
* Marta Valenciano
* Arnold Bosman
===FEM Contributors===
* Arnold Bosman
* Naomi Boxall
* Vladimir Prikazsky
* Aileen Kitching
* Lisa Lazareck
* Sabrina Bacci

[[Category:Measures of Disease Occurrence]]

Category:Odds

2025-05-21T07:48:40Z

Bosmana fem: /* Absolute Number */

=Absolute Number=
Odds (no synonyms), are expressed as an absolute number.

The odds of an event ("odds", always plural) occurring is the probability (e.g. risk) that this event will occur divided by the probability that the event will not occur. It can also be expressed as the probability that an event will occur divided by "1 minus the probability that the event will occur"<ref>Porta, M. A Dictionary of Epidemiology, Fifth edition. Oxford University press, 2008.</ref>.

P
Odds of event = -----------
1 - P

Note that probabilities allow us to calculate the odds of an event: probabilities and odds are related, but they are not the same thing.

𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 expresses the chance of an event happening out of the total number of possible outcomes. Probability is the likelihood that an event will occur, expressed as a value between 0 and 1 (e.g., a 20% chance is a probability of 0.2).

𝐎𝐝𝐝𝐬 express the ratio of the event happening to the event not happening. For a 20% chance (probability of 0.2), the odds are 0.25 (i.e., the odds of having the disease is 0.25).

[[File:Prob Vs Odds.png|400px|frameless|Visual representation about the differences between probabilities and odds]]

Odds is a probability measure that is popular in the world of gambling. If we compute the number of people putting money on one horse winning and the number of people putting money on the horse not winning (i.e., putting money on other horses), we can compute the odds of winning. For example, among 3100 persons gambling on horses, 100 persons put money on horse "A" to win, and 3000 do not (they bet on other horses). The odds of winning are then 1/30 (100/3100 divided by 3000/3100 which can be simplified as 100/3000 or 1 / 30). In fact, in gambling, the odds of not winning are preferred and expressed as a ratio X/1. In our example, 30/1, or in words, "thirty to one". This means that for every Euro that you bet, you will receive 30 if you win.

Since we illustrate the population under investigation in epidemiology with a two-by-two table, we will use a table to describe how to calculate odds. In the two-by-two table, the concept of exposure is also included. However, to calculate the odds of disease, it is not necessary to consider that in our population, some might have been exposed to a particular exposure and some not.

===Example 1===
{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 30 || 70 || 100
|}
The table yields the following calculations:
[[File:0028.risk of dis.png-550x0.png|400px|frameless|left]]

[[File:2086.odds of dis.png-550x0.png|600px|frameless|left]]

Therefore to calculate the odds: divide the risk of getting the disease by the risk of not getting the disease. It is equal to the ratio of the number of people with the disease to the number of people without it in a particular population.

The odds is a measure rarely used in epidemiology. Most often the odds are used to express the odds ratio. A disease-odds ratio is the ratio of the odds of having the disease among the exposed and the odds of having the disease among the unexposed [1]. In other words, the odds ratio is the ratio of the odds of disease observed in 2 subsets of a population.

In you take again the table as an example, the disease-odds ratio will be equal to:

Odds of developing the disease among the exposed: a / b

Odds of developing the disease among the unexposed: c / d

Disease-odds ratio:
[[File:2330.or simple.png-550x0.png|400px|frameless|left]]

As you see by comparing example one, two and three, the risk and the odds approximate each other when the event is rare. When the event occurs frequently the odds overestimate the risk of disease.

For this reason, in many situations (when the disease is rare) the odds ratio can estimate the risk ratio.

===Example 2===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 50 || 99 950 || 100 000
|}

Risk of disease = 50 / 100000 = 0.00050000

Odds of disease (50 / 100000) / 1 - (50/100000) = 0.00050025

When getting the disease is rare, the risk of disease approximates the odds of disease.

===Example 3===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 59 || 950 || 1000
|}

Risk of disease = 50 / 1000 = 0.05000

Odds of disease (50 / 1000) / 1 - (50/1000) = 0.05263

=References=
<References/>

=Credits=
===FEM Editor 2007===
* Sabrina Bacci
===Original Authors===
* Alain Moren
* Marta Valenciano
* Arnold Bosman
===FEM Contributors===
* Arnold Bosman
* Naomi Boxall
* Vladimir Prikazsky
* Aileen Kitching
* Lisa Lazareck
* Sabrina Bacci

[[Category:Measures of Disease Occurrence]]

Category:Odds

2025-05-21T07:47:55Z

Bosmana fem: /* Absolute Number */

=Absolute Number=
Odds (no synonyms), are expressed as an absolute number.

The odds of an event ("odds", always plural) occurring is the probability (e.g. risk) that this event will occur divided by the probability that the event will not occur. It can also be expressed as the probability that an event will occur divided by "1 minus the probability that the event will occur"<ref>Porta, M. A Dictionary of Epidemiology, Fifth edition. Oxford University press, 2008.</ref>.

P
Odds of event = -----------
1 - P

Note that probabilities allow us to calculate the odds of an event: probabilities and odds are related, but they are not the same thing.

𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 expresses the chance of an event happening out of the total number of possible outcomes. Probability is the likelihood that an event will occur, expressed as a value between 0 and 1 (e.g., a 20% chance is a probability of 0.2).

𝐎𝐝𝐝𝐬 express the ratio of the event happening to the event not happening. For a 20% chance (probability of 0.2), the odds are 0.25 (i.e., the odds of having the disease is 0.25).

[[File:Prob Vs Odds.png|600px|frame|Visual representation about the differences between probabilities and odds]]

Odds is a probability measure that is popular in the world of gambling. If we compute the number of people putting money on one horse winning and the number of people putting money on the horse not winning (i.e., putting money on other horses), we can compute the odds of winning. For example, among 3100 persons gambling on horses, 100 persons put money on horse "A" to win, and 3000 do not (they bet on other horses). The odds of winning are then 1/30 (100/3100 divided by 3000/3100 which can be simplified as 100/3000 or 1 / 30). In fact, in gambling, the odds of not winning are preferred and expressed as a ratio X/1. In our example, 30/1, or in words, "thirty to one". This means that for every Euro that you bet, you will receive 30 if you win.

Since we illustrate the population under investigation in epidemiology with a two-by-two table, we will use a table to describe how to calculate odds. In the two-by-two table, the concept of exposure is also included. However, to calculate the odds of disease, it is not necessary to consider that in our population, some might have been exposed to a particular exposure and some not.

===Example 1===
{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 30 || 70 || 100
|}
The table yields the following calculations:
[[File:0028.risk of dis.png-550x0.png|400px|frameless|left]]

[[File:2086.odds of dis.png-550x0.png|600px|frameless|left]]

Therefore to calculate the odds: divide the risk of getting the disease by the risk of not getting the disease. It is equal to the ratio of the number of people with the disease to the number of people without it in a particular population.

The odds is a measure rarely used in epidemiology. Most often the odds are used to express the odds ratio. A disease-odds ratio is the ratio of the odds of having the disease among the exposed and the odds of having the disease among the unexposed [1]. In other words, the odds ratio is the ratio of the odds of disease observed in 2 subsets of a population.

In you take again the table as an example, the disease-odds ratio will be equal to:

Odds of developing the disease among the exposed: a / b

Odds of developing the disease among the unexposed: c / d

Disease-odds ratio:
[[File:2330.or simple.png-550x0.png|400px|frameless|left]]

As you see by comparing example one, two and three, the risk and the odds approximate each other when the event is rare. When the event occurs frequently the odds overestimate the risk of disease.

For this reason, in many situations (when the disease is rare) the odds ratio can estimate the risk ratio.

===Example 2===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 50 || 99 950 || 100 000
|}

Risk of disease = 50 / 100000 = 0.00050000

Odds of disease (50 / 100000) / 1 - (50/100000) = 0.00050025

When getting the disease is rare, the risk of disease approximates the odds of disease.

===Example 3===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 59 || 950 || 1000
|}

Risk of disease = 50 / 1000 = 0.05000

Odds of disease (50 / 1000) / 1 - (50/1000) = 0.05263

=References=
<References/>

=Credits=
===FEM Editor 2007===
* Sabrina Bacci
===Original Authors===
* Alain Moren
* Marta Valenciano
* Arnold Bosman
===FEM Contributors===
* Arnold Bosman
* Naomi Boxall
* Vladimir Prikazsky
* Aileen Kitching
* Lisa Lazareck
* Sabrina Bacci

[[Category:Measures of Disease Occurrence]]

Category:Odds

2025-05-21T07:46:43Z

Bosmana fem:

=Absolute Number=
Odds (no synonyms), are expressed as an absolute number.

The odds of an event ("odds", always plural) occurring is the probability (e.g. risk) that this event will occur divided by the probability that the event will not occur. It can also be expressed as the probability that an event will occur divided by "1 minus the probability that the event will occur"<ref>Porta, M. A Dictionary of Epidemiology, Fifth edition. Oxford University press, 2008.</ref>.

P
Odds of event = -----------
1 - P

Note that probabilities allow us to calculate the odds of an event: probabilities and odds are related, but they are not the same thing.

𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 expresses the chance of an event happening out of the total number of possible outcomes. Probability is the likelihood that an event will occur, expressed as a value between 0 and 1 (e.g., a 20% chance is a probability of 0.2).

𝐎𝐝𝐝𝐬 express the ratio of the event happening to the event not happening. For a 20% chance (probability of 0.2), the odds are 0.25 (i.e., the odds of having the disease is 0.25).

<gallery>
Prob Vs Odds.png| Visual representation about the differences between probabilities and odds
</gallery>

Odds is a probability measure that is popular in the world of gambling. If we compute the number of people putting money on one horse winning and the number of people putting money on the horse not winning (i.e., putting money on other horses), we can compute the odds of winning. For example, among 3100 persons gambling on horses, 100 persons put money on horse "A" to win, and 3000 do not (they bet on other horses). The odds of winning are then 1/30 (100/3100 divided by 3000/3100 which can be simplified as 100/3000 or 1 / 30). In fact, in gambling, the odds of not winning are preferred and expressed as a ratio X/1. In our example, 30/1, or in words, "thirty to one". This means that for every Euro that you bet, you will receive 30 if you win.

Since we illustrate the population under investigation in epidemiology with a two-by-two table, we will use a table to describe how to calculate odds. In the two-by-two table, the concept of exposure is also included. However, to calculate the odds of disease, it is not necessary to consider that in our population, some might have been exposed to a particular exposure and some not.

===Example 1===
{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 30 || 70 || 100
|}
The table yields the following calculations:
[[File:0028.risk of dis.png-550x0.png|400px|frameless|left]]

[[File:2086.odds of dis.png-550x0.png|600px|frameless|left]]

Therefore to calculate the odds: divide the risk of getting the disease by the risk of not getting the disease. It is equal to the ratio of the number of people with the disease to the number of people without it in a particular population.

The odds is a measure rarely used in epidemiology. Most often the odds are used to express the odds ratio. A disease-odds ratio is the ratio of the odds of having the disease among the exposed and the odds of having the disease among the unexposed [1]. In other words, the odds ratio is the ratio of the odds of disease observed in 2 subsets of a population.

In you take again the table as an example, the disease-odds ratio will be equal to:

Odds of developing the disease among the exposed: a / b

Odds of developing the disease among the unexposed: c / d

Disease-odds ratio:
[[File:2330.or simple.png-550x0.png|400px|frameless|left]]

As you see by comparing example one, two and three, the risk and the odds approximate each other when the event is rare. When the event occurs frequently the odds overestimate the risk of disease.

For this reason, in many situations (when the disease is rare) the odds ratio can estimate the risk ratio.

===Example 2===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 50 || 99 950 || 100 000
|}

Risk of disease = 50 / 100000 = 0.00050000

Odds of disease (50 / 100000) / 1 - (50/100000) = 0.00050025

When getting the disease is rare, the risk of disease approximates the odds of disease.

===Example 3===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 59 || 950 || 1000
|}

Risk of disease = 50 / 1000 = 0.05000

Odds of disease (50 / 1000) / 1 - (50/1000) = 0.05263

=References=
<References/>

=Credits=
===FEM Editor 2007===
* Sabrina Bacci
===Original Authors===
* Alain Moren
* Marta Valenciano
* Arnold Bosman
===FEM Contributors===
* Arnold Bosman
* Naomi Boxall
* Vladimir Prikazsky
* Aileen Kitching
* Lisa Lazareck
* Sabrina Bacci

[[Category:Measures of Disease Occurrence]]

Category:Odds

2025-05-21T07:46:09Z

Bosmana fem: /* Absolute Number */

=Absolute Number=
Odds (no synonyms), are expressed as an absolute number.

The odds of an event ("odds", always plural) occurring is the probability (e.g. risk) that this event will occur divided by the probability that the event will not occur. It can also be expressed as the probability that an event will occur divided by "1 minus the probability that the event will occur"<ref>Porta, M. A Dictionary of Epidemiology, Fifth edition. Oxford University press, 2008.</ref>.

P
Odds of event = -----------
1 - P

Note that probabilities allow us to calculate the odds of an event: probabilities and odds are related, but they are not the same thing.

𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 expresses the chance of an event happening out of the total number of possible outcomes. Probability is the likelihood that an event will occur, expressed as a value between 0 and 1 (e.g., a 20% chance is a probability of 0.2).

𝐎𝐝𝐝𝐬 express the ratio of the event happening to the event not happening. For a 20% chance (probability of 0.2), the odds are 0.25 (i.e., the odds of having the disease is 0.25).

<gallery>
Prob Vs Odds.png| Visual representation about the differences between probabilities and odds
</gallery>

[[File:Prob Vs Odds.png|frame|Visual representation about the differences between probabilities and odds]]

Odds is a probability measure that is popular in the world of gambling. If we compute the number of people putting money on one horse winning and the number of people putting money on the horse not winning (i.e., putting money on other horses), we can compute the odds of winning. For example, among 3100 persons gambling on horses, 100 persons put money on horse "A" to win, and 3000 do not (they bet on other horses). The odds of winning are then 1/30 (100/3100 divided by 3000/3100 which can be simplified as 100/3000 or 1 / 30). In fact, in gambling, the odds of not winning are preferred and expressed as a ratio X/1. In our example, 30/1, or in words, "thirty to one". This means that for every Euro that you bet, you will receive 30 if you win.

Since we illustrate the population under investigation in epidemiology with a two-by-two table, we will use a table to describe how to calculate odds. In the two-by-two table, the concept of exposure is also included. However, to calculate the odds of disease, it is not necessary to consider that in our population, some might have been exposed to a particular exposure and some not.

===Example 1===
{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 30 || 70 || 100
|}
The table yields the following calculations:
[[File:0028.risk of dis.png-550x0.png|400px|frameless|left]]

[[File:2086.odds of dis.png-550x0.png|600px|frameless|left]]

Therefore to calculate the odds: divide the risk of getting the disease by the risk of not getting the disease. It is equal to the ratio of the number of people with the disease to the number of people without it in a particular population.

The odds is a measure rarely used in epidemiology. Most often the odds are used to express the odds ratio. A disease-odds ratio is the ratio of the odds of having the disease among the exposed and the odds of having the disease among the unexposed [1]. In other words, the odds ratio is the ratio of the odds of disease observed in 2 subsets of a population.

In you take again the table as an example, the disease-odds ratio will be equal to:

Odds of developing the disease among the exposed: a / b

Odds of developing the disease among the unexposed: c / d

Disease-odds ratio:
[[File:2330.or simple.png-550x0.png|400px|frameless|left]]

As you see by comparing example one, two and three, the risk and the odds approximate each other when the event is rare. When the event occurs frequently the odds overestimate the risk of disease.

For this reason, in many situations (when the disease is rare) the odds ratio can estimate the risk ratio.

===Example 2===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 50 || 99 950 || 100 000
|}

Risk of disease = 50 / 100000 = 0.00050000

Odds of disease (50 / 100000) / 1 - (50/100000) = 0.00050025

When getting the disease is rare, the risk of disease approximates the odds of disease.

===Example 3===

{| class="wikitable"
! !! Developing the disease !! Not developing the disease !! Total
|-
| Exposed || a || b || a+b
|-
| Not exposed || c || d || c+d
|-
| Total || 59 || 950 || 1000
|}

Risk of disease = 50 / 1000 = 0.05000

Odds of disease (50 / 1000) / 1 - (50/1000) = 0.05263

=References=
<References/>

=Credits=
===FEM Editor 2007===
* Sabrina Bacci
===Original Authors===
* Alain Moren
* Marta Valenciano
* Arnold Bosman
===FEM Contributors===
* Arnold Bosman
* Naomi Boxall
* Vladimir Prikazsky
* Aileen Kitching
* Lisa Lazareck
* Sabrina Bacci

[[Category:Measures of Disease Occurrence]]

Key definitions in infectious diseases epidemiology

2025-05-19T15:09:38Z

Bosmana fem:

Infectious disease epidemiology shares the same general conceptual framework as ‘non-infectious disease’ epidemiology. It seeks to understand the causes and distribution of infectious diseases in populations with the aim of controlling them. However, there are specific epidemiological concepts/terms that are mainly related to infectious diseases:

== Infection ==

'''Infection''' refers to the entry and multiplication of an infectious agent in the body of humans or animals, where it may or may not lead to clinical symptoms.

An infection can be:
* '''Endogenous''' – originating from the host’s own microbial flora (e.g. urinary tract infection from intestinal flora)
* '''Exogenous''' – acquired from the environment, other individuals, animals, or contaminated objects

=== Source of infection ===
The term '''source of infection''' refers to the origin from which a susceptible host acquires the infectious agent.
It can be:
* An infected human (symptomatic or asymptomatic)
* An infected animal (reservoir or vector)
* A contaminated environment (e.g. surfaces, food, water)

''Example: A cholera patient excreting Vibrio cholerae in stools contaminates drinking water. The patient is the source of infection, the water is the vehicle of transmission.''

== Contamination ==

'''Contamination''' refers to the presence of infectious agents on inanimate objects, surfaces, food, or water, without any multiplication or clinical infection in the object or material.

Contamination may or may not lead to infection in a host. Contaminated materials can act as:
* '''Vehicles''' (e.g. contaminated food, water)
* '''Fomites''' (e.g. door handles, bedding)
* '''Environmental reservoirs''' (e.g. soil, surfaces)

''Example: A septic tank overflow that pollutes a drinking water well is a source of contamination. People drinking from the well may become infected, depending on exposure and susceptibility.''

== Comparison table ==

{| class="wikitable"
! Aspect !! Infection !! Contamination
|-
| Definition || Multiplication of pathogens in a host || Presence of pathogens on a surface or substance
|-
| Host involvement || Occurs in living organisms (humans/animals) || Occurs on inanimate objects or materials
|-
| Clinical symptoms || May or may not occur || Never occurs (non-biological host)
|-
| Role in outbreaks || Direct cause of disease || May facilitate transmission, but not always infectious
|}

==Agent==
A disease agent is a biological agent that causes a disease. This can be a virus, bacterium, fungus, parasite, or other type of microorganism, as well as certain toxins and other substances that can cause disease. Disease agents can be transmitted from person to person, or through contact with contaminated surfaces, food, water, or other sources. They can cause a wide range of diseases, ranging from mild to severe, and can have serious consequences for individuals and communities. Some examples of disease agents include the influenza virus, which causes the flu; the bacterium Escherichia coli, which can cause food poisoning; and the parasite Plasmodium, which causes malaria.

==Chain of transmission==
The chain of transmission refers to the steps or stages through which a disease agent is transmitted from one person or host to another. It involves a series of events that occur in a specific order, starting with the source of the disease agent and ending with the infection of a new host. The chain of transmission can be broken at any point, which can help to prevent the spread of the disease.
There are several key elements in the chain of transmission:
# The source: This is the source of the disease agent, which can be a person, animal, or environment.
# The reservoir: This is the place where the disease agent can survive and multiply.
# The mode of transmission: This is the way in which the disease agent is transmitted from the source to the host. This can be through direct contact (such as through touching, kissing, or sexual contact), indirect contact (such as through contaminated objects or surfaces), or through the air (such as through coughing or sneezing).
# The host: This is the person or animal that becomes infected with the disease agent.
#The environment: This includes the physical, social, and cultural factors that can influence the transmission of the disease agent.

Breaking the chain of transmission involves interrupting one or more of these elements, which can help to prevent the spread of the disease. This can be achieved through measures such as vaccination, hygiene practices, quarantine, and other public health interventions.

==Contagiousness==
Contagiousness refers to the ability of a disease to be transmitted from one person or animal to another. A disease that is highly contagious can be transmitted easily and quickly, often with just brief contact or through the air. A disease that is less contagious may require more prolonged or close contact in order to be transmitted.

The contagiousness of a disease can depend on several factors, including the type of disease agent (such as a virus or bacterium), the mode of transmission (such as through direct or indirect contact, or through the air), and the susceptibility of the host (such as a person or animal). Some diseases, such as the common cold, are highly contagious and can be transmitted easily through contact with respiratory secretions or contaminated surfaces. Other diseases, such as HIV, are less contagious and require more specific modes of transmission, such as through sexual contact or sharing needles.

Understanding a disease's contagiousness is important in preventing its spread and controlling outbreaks. Public health measures, such as vaccination and hygiene practices, can help reduce a disease's contagiousness and prevent its transmission.

==Epidemic curve==
An epidemic curve is a graphical representation of the number of cases of a specific disease that occur over time. It is used to understand the spread and impact of an outbreak, as well as to identify patterns and trends in the data.

The epidemic curve is usually plotted on a graph, with the x-axis representing time (often in days or weeks) and the y-axis representing the number of cases. The shape of the curve can provide important information about the nature of the outbreak, such as the rate at which the disease is spreading and the population groups that are most affected.

There are several types of epidemic curves that can be used to represent different types of outbreaks:
# A linear epidemic curve shows a constant rate of disease transmission over time.
# An exponential epidemic curve shows a rapid increase in cases over time, often indicating a highly contagious disease.
# A log-linear epidemic curve shows a slowing of the rate of disease transmission over time, often indicating that public health interventions are having an effect.
# A logistic epidemic curve shows a slowing of the rate of disease transmission, followed by a plateau and then a decline, often indicating that the outbreak has reached its peak and is starting to decline.
Understanding the shape of the epidemic curve can help public health officials to identify the most effective interventions for controlling the outbreak and preventing further transmission of the disease.

==Generation time==
The time that elapses between the onset of symptoms in the primary case and the onset of symptoms in the secondary case. Generation time is a term used to describe the time it takes for a disease to be transmitted from one person to another or from one generation of hosts to the next. In the context of an epidemic, generation time can be an important factor in understanding the spread and impact of the disease and in identifying strategies for controlling the outbreak.

The generation time of a disease can vary depending on the specific disease agent and the characteristics of the host population. Some diseases have a relatively short generation time, meaning that they can be transmitted quickly and can lead to rapid outbreaks. Other diseases have a longer generation time, meaning they may take longer to spread and may have a slower impact on the population.

Understanding the generation time of a disease can help public health officials to identify the most effective interventions for controlling the outbreak and preventing further transmission of the disease. This can include measures such as vaccination, quarantine, and hygiene practices, as well as strategies for reducing the number of contacts between individuals in the population.

==Herd immunity==
Herd immunity, also known as community immunity, refers to the protective effect that occurs when a high proportion of a population is immune to a specific disease. This can be achieved through natural immunity (for example, by recovering from the disease) or through vaccination.

When a large proportion of a population is immune to a disease, it is more difficult for the disease to spread, because there are fewer individuals who are susceptible to infection. This can provide protection for those who are not immune, including those who are too young to be vaccinated, those who are unable to be vaccinated due to underlying health conditions, and those who have not yet had the opportunity to be vaccinated.

Herd immunity can be an important factor in controlling the spread of infectious diseases and preventing outbreaks. The level of immunity needed to achieve herd immunity varies depending on the specific disease and the characteristics of the population. Some diseases, such as measles, require a relatively high level of immunity (around 95%) in order to achieve herd immunity, while others, such as pertussis (whooping cough), require a lower level of immunity (around 80%).

It is important to maintain high vaccination rates in order to protect the population from infectious diseases and to maintain herd immunity. This can help to prevent outbreaks and protect those who are most vulnerable to serious illness or complications from the disease.

==Host==
A host is an individual or animal that is infected with a disease agent, such as a virus or bacterium. The host serves as a source of the disease, and can transmit the disease to other individuals or animals through the process of transmission.

The term "host" can also refer to the individual or animal that provides a habitat or environment for a particular disease agent. For example, a mosquito may be the host for a parasite that causes malaria, while a human may be the host for a virus that causes the flu.
A primary host is where a parasite reaches maturity or passes its sexual stage. A secondary host is where a parasite is in a larval or asexual stage.

Understanding the role of hosts in the transmission of disease is an important aspect of epidemiology, as it helps public health officials to identify the sources of outbreaks and to develop strategies for preventing the spread of the disease. This can include measures such as vaccination, quarantine, and hygiene practices, as well as strategies for reducing the number of contacts between individuals in the population.

==Incubation period==
The incubation period is the time between when an individual is exposed to a disease agent (such as a virus or bacterium) and when they develop symptoms of the disease. The incubation period can vary depending on the specific disease, as well as the individual's age, immune system, and other factors.

During the incubation period, the disease agent may be multiplying and spreading in the body, but the individual is not yet experiencing any symptoms. This can make it difficult to identify the source of the infection, as the infected individual may not realize that they are carrying the disease and may be unknowingly spreading it to others.

Understanding the incubation period of a disease is important in terms of preventing the spread of the disease and controlling outbreaks. For example, if the incubation period is relatively long, public health officials may need to implement quarantine measures for a longer period of time in order to prevent the transmission of the disease. If the incubation period is shorter, more immediate interventions may be necessary to control the spread of the disease.

==Index case==
First case of a disease to be identified at the start of an outbreak. The index case is the first patient that indicates the existence of an outbreak. It does not necessarily mean that it was the outbreak's first case. Earlier cases may be found and are labeled primary case, secondary case, tertiary case, etc.

==Primary case==
The primary case (or source case, or patient zero), is the first case of a disease in an outbreak or epidemic. This individual introduced the disease agent to the population and gave rise to the outbreak or epidemic.

==Latent period==
The latent period is the time between the initial infection and the onset of infectiousness. In other words, it is the period during which the pathogen replicates within the infected individual's body, but the individual is not yet contagious.

==Outbreak==
Term used in epidemiology to describe an occurrence of disease greater than would otherwise be expected at a particular time and place. It may affect a small and localized group or impact upon thousands of people across an entire continent. Two linked cases of a rare infectious disease may be sufficient to constitute an outbreak.

==Epidemic==
Generally, ‘epidemic’ refers to large outbreak. But the difference between ‘epidemic’ and ‘outbreak’ remains subjective. Some have proposed that an epidemic is an outbreak that affects a region in a country of a group of countries.

==Pandemic==
Outbreak of disease around the globe.

==Pathogen==
A pathogen is any agent that can cause disease in a host organism. Pathogens are typically infectious agents such as viruses, bacteria, fungi, or parasites, but they can also be non-infectious agents such as physical agents (e.g., radiation) or chemical agents (e.g., toxins).

Pathogens can cause a wide range of diseases in humans and other animals, ranging from mild infections to serious, life-threatening illnesses. Some common examples of pathogens include the bacteria that cause tuberculosis and salmonella, the viruses that cause influenza and HIV, and the fungi that cause athlete's foot and ringworm.

Pathogens are able to enter the body of a host in a variety of ways, including through contact with infected bodily fluids (such as blood or saliva), through inhalation of respiratory secretions, or through ingestion of contaminated food or water. Once inside the body, the pathogen may begin to replicate and cause damage to cells and tissues, leading to the development of symptoms of disease.

==Reproductive rate==
The reproductive rate of an infection refers to the number of new infections that are generated by each infected individual during the course of their illness. It is often expressed as the basic reproductive number, or R0 (pronounced "R-naught"), which is the average number of new infections produced by a single infected individual in a population that is fully susceptible to the infection.

The reproductive rate is an important concept in the field of epidemiology, as it helps to predict the spread and potential impact of an infectious disease within a population. A high reproductive rate can indicate that an infection is highly contagious and may spread rapidly through a population, while a low reproductive rate may suggest that the infection is less easily transmitted.

The reproductive rate of an infection can vary widely depending on a number of factors, including the mode of transmission (e.g., respiratory droplets, contact with bodily fluids), the severity of the disease, and the effectiveness of control measures (such as vaccination or isolation of infected individuals).

To calculate the reproductive rate of an infection, epidemiologists use a variety of statistical and mathematical models that take into account the number of new infections, the length of the infectious period, and the size of the population. These models can help to identify the key drivers of transmission and inform the development of strategies to control the spread of the infection.

==Transmission route==
A transmission route refers to the way in which a pathogen (such as a virus or bacterium) is transmitted from one host to another. Transmission routes can vary depending on the specific pathogen and the characteristics of the host population.

Some common transmission routes for infectious diseases include:

* '''Respiratory droplets''': Many respiratory infections, such as the common cold and influenza, are transmitted through respiratory droplets that are released into the air when an infected person talks, coughs, or sneezes. Other people can inhale these droplets and then become infected.
* '''Contact with bodily fluids''': Some infections, such as HIV and hepatitis B, are transmitted through contact with infected blood or other bodily fluids. This can occur through sexual contact, injection drug use, or accidental exposure to contaminated needles or other medical equipment.
* '''Food and water''': Some infections, such as norovirus and salmonella, are transmitted through contaminated food or water. These pathogens can be present in undercooked or raw food, or water contaminated with feces.
* '''Insects''': Some infections, such as malaria and West Nile virus, are transmitted through the bites of infected insects, such as mosquitoes or ticks.
* '''Fomites''': Fomites are inanimate objects that can become contaminated with pathogens and serve as a means of transmission. Examples of fomites include towels, bedding, and other household items that can harbor pathogens and transmit them to other people.

Understanding the transmission route of an infection is important in the control and prevention of the disease, as it can inform the development of strategies such as vaccination, isolation of infected individuals, and the implementation of infection control measures.

==Direct transmission==
Direct and immediate transfer of infectious agents to a susceptible host. This may be through direct contact such as touching, biting, kissing or sexual intercourse, or by the direct projection of droplet (droplet spread) spraying onto eyes, nose or mouth of other people. Droplet spread is usually limited to short distances, such as 1 meter or less.

==Vertical transmission==
A specific direct transmission is between mother and child during pregnancy or childbirth.

==Indirect transmission==
Transmission of infectious organisms from a source through objects (vehicles) or insects (vectors).

==Vehicle-borne==
Infectious agents can reach susceptible hosts through transport on inanimate objects (=fomites) such as toys, handkerchiefs, soiled clothes, bedding, medical instruments, food, water, blood products or any other substance that can be contaminated. Some vehicles allow multiplication of the infectious agent (e.g. salmonella in food), though this is not always the case.

==Vector-borne==
When insects transfer infectious agents to susceptible hosts, they act as 'vectors' of the infection.

==Airborne transmission==
Microbial aerosols are suspensions of particles (fluid or solid) in the air consisting partially or wholly of microorganisms. They may remain suspended in the air for prolonged periods of time (as opposed to droplets that are too large in diameter and fall to the ground relatively fast). This transmission route works particularly efficiently for viruses such as the measles virus.

==Reservoir==
a reservoir is a place or host where a pathogen (such as a virus or bacterium) can survive, grow, and reproduce. A reservoir can be either a living organism (such as a human, animal, or plant) or an inanimate object (such as soil or water).

The concept of a reservoir is important in epidemiology because it helps to understand how infectious diseases are transmitted and how they can be controlled. For example, if the reservoir for a particular pathogen is an animal, such as a rodent or a bird, understanding the habits and habitats of that animal can help to identify potential sources of infection and implement control measures to reduce the risk of transmission to humans.

Some common examples of reservoirs for infectious diseases include:
* Humans: Many infectious diseases, such as influenza and measles, have humans as their primary reservoir.
* Animals: Many infections, such as rabies and West Nile virus, are transmitted to humans from animals. The animal reservoir for these infections may be wild animals, domestic pets, or livestock.
* Water: Some infections, such as cholera and typhoid fever, are transmitted through contaminated water. In these cases, the water can act as a reservoir for the pathogen.
* Soil: Some infections, such as tetanus and anthrax, are transmitted through contact with contaminated soil. In these cases, the soil can act as a reservoir for the pathogen.

Understanding the reservoir for an infectious disease is important for developing control measures and designing effective interventions to prevent the spread of the infection.

==Susceptibility==
A susceptible individual (sometimes known simply as a susceptible) is a population member at risk of becoming infected by a disease.

==Source==
The source is the place or host from which the pathogen is transmitted to another host.

To understand the difference between a reservoir and a source, it can be helpful to think of a reservoir as a place where the pathogen is "stored" and a source as a place where the pathogen is "released." For example, a person with an infection may act as a reservoir for the pathogen (storing it within their body), while the respiratory secretions they release when they sneeze or cough may act as the source of the infection (releasing the pathogen into the environment).

In some cases, the reservoir and the source for an infectious disease may be the same. For example, if a person with an infection sneezes or coughs, they may both act as the reservoir (storing the pathogen within their body) and the source (releasing the pathogen into the environment). In other cases, the reservoir and the source may be different. For example, a mosquito may act as the source of an infection by transmitting the pathogen to a human through its bite, while the human may act as the reservoir for the pathogen.

There are several ways this source can infect people:

===Common source outbreaks===
Outbreaks, where all (or most) cases were infected by the same source, are called common source outbreaks.

===Point source outbreaks===
Common source outbreaks where the source has infected cases at one particular geographical location and during a short period of time. In such situations, the source is located 'at a single point in time and place'. These outbreaks have a typical bell-shaped epidemic curve that increases sharply, peaks, and then declines sharply, reflecting the normal distribution of the incubation period of the causative agent in humans. For this reason, the epidemic curve of a point source outbreak can help identify the moment of transmission (i.e., when all cases have been exposed to the source).

===Continuing common source outbreaks===
Outbreaks where all (or most) cases have been infected by the same source over a prolonged period of time. The shape of the epidemic curve does not increase that sharply, it does not peak, yet reaches a plateau sustained over time until the source is removed.

===Propagated outbreaks===
Outbreaks of communicable infectious disease (i.e. can be transmitted from person to person) for which there is no single, common source. The causative agent is propagated within the population through human contact patterns. The shape of the epidemic curve in propagated outbreaks can vary and depends on the contact pattern and the proportion of susceptible individuals.

[[Category:Field Epidemiology]]

Source of infection

2025-05-19T15:08:37Z

Bosmana fem:

We refer to the source of [[Basic concepts: Infection and Contamination|infection]] as the origin from which a [[Host tracing|host]] acquires the infection, either endogenous (i.e. originating from a person's own commensal microbial flora) or exogenous (i.e. an individual, animal or object in the external environment of the host). Usually, the source can be identified as an individual, animal or object in a specific place and at a specific time.

Thus, a person can be a source of infection, either for him/herself (endogenous) or to other people (directly through personal contact or indirectly, e.g. by contaminating food or beverages).

In addition to people, also animals can be sources of infection.

Objects may be sources of infection; food, water, air-conditioning systems, showers, medical instruments, recreational waters, door knobs, cotton handkerchiefs etc. Such contaminated objects are also referred to as fomites. Most man-made products that may be sources of infection must be produced while limiting the risk of contamination.

In most outbreak investigations, the principal objective is to identify the source of the infection. Interestingly enough, this sometimes leads to semantic problems: an identified 'source' (e.g. a chocolate cake) is usually contaminated by some other source (e.g. the baker of the cake or the eggs used). Tracing back such a 'chain of transmission' usually leads back to the reservoir. In some articles, the concept of 'source' and 'reservoir' are used as synonyms, though strictly speaking, they are not.

Inanimate sources of infection are sometimes referred to as 'vehicles of infection' (e.g. the chocolate cake) or 'fomites' (e.g. the cotton handkerchief). Inanimate sources (vehicles, fomites) are part of the indirect transmission route.

The source of infection should be distinguished from the source of contamination (e.g. overflow of a septic tank, contaminating a water supply).

=References:=
* David L. Heymann (editor). Control of Communicable Diseases Manual. APHA, 2008

[[Category:Public Health Interventions]]

Primary prevention

2025-05-17T17:36:18Z

Bosmana fem:

Within the framework of [[Field Epidemiology|field epidemiology]], primary prevention plays a vital role in averting the onset of communicable diseases and reducing their overall impact on public health.<ref>Centers for Disease Control and Prevention. (2012). Principles of Epidemiology in Public Health Practice, 3rd ed. Lesson 3: Measures of Risk. https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section2.html</ref><ref>This text was written by ChatGPT4.0 on 26 March 2023 and reviewed by Arnold Bosman.</ref>

Key strategies in primary prevention include immunisation programs, which protect populations from infectious agents such as measles, polio, and influenza through vaccination.<ref>World Health Organisation. (2023). Immunisation coverage. https://www.who.int/news-room/fact-sheets/detail/immunization-coverage</ref>
Health education and promotion campaigns—such as handwashing initiatives and safe food handling practices—encourage behaviours that reduce the risk of disease transmission.

Vector control measures, including the use of insecticide-treated bed nets and environmental source reduction, help limit the spread of vector-borne diseases like malaria and dengue fever. Environmental interventions, such as improving access to clean water and sanitation, also play a critical role by reducing exposure to disease-causing pathogens.

Through these proactive efforts, field epidemiologists contribute to building resilient communities and establishing a strong foundation for communicable disease prevention.

== References ==
<references />

[[Category:Prevention]]

Secondary prevention

2025-05-17T17:30:24Z

Bosmana fem:

Secondary prevention<ref>This text was written by ChatGPT4.0 on 26 March 2023 and reviewed by Arnold Bosman</ref> focuses on the early detection and timely intervention of communicable diseases, aiming to halt or slow disease progression in its initial stages. In the context of [[Field Epidemiology|field epidemiology]], secondary prevention includes a range of strategies designed to identify infections before they become symptomatic or widely transmitted.

Screening programs for diseases such as tuberculosis or HIV are critical for identifying asymptomatic or pre-symptomatic individuals. Early diagnosis allows for prompt initiation of treatment, reducing the risk of complications and limiting further transmission within the community.

Another essential method is [[Contact tracing]], which involves identifying and monitoring individuals who have been exposed to a contagious disease—such as COVID-19—with the goal of ensuring timely testing, isolation, and treatment if necessary.

Field epidemiologists also contribute through [[Outbreak Investigations|outbreak investigations]] and ongoing surveillance. These systems help detect unusual patterns, emerging clusters, or sharp increases in incidence, allowing public health authorities to launch rapid containment and mitigation efforts.

In addition, targeted prophylactic interventions, such as post-exposure prophylaxis (PEP) for HIV or chemoprophylaxis for malaria, can prevent disease development in individuals who have been recently exposed to a pathogen.

Through these strategies, secondary prevention plays a vital role in curbing the spread of communicable diseases and minimizing their impact on individual and public health.

== References ==
<references />

[[Category:Prevention]]

Secondary prevention

2025-05-17T17:29:20Z

Bosmana fem:

Secondary prevention focuses on the early detection and timely intervention of communicable diseases, aiming to halt or slow disease progression in its initial stages. In the context of [[Field Epidemiology|field epidemiology]], secondary prevention includes a range of strategies designed to identify infections before they become symptomatic or widely transmitted.

Screening programs for diseases such as tuberculosis or HIV are critical for identifying asymptomatic or pre-symptomatic individuals. Early diagnosis allows for prompt initiation of treatment, reducing the risk of complications and limiting further transmission within the community.

Another essential method is [[Contact tracing]], which involves identifying and monitoring individuals who have been exposed to a contagious disease—such as COVID-19—with the goal of ensuring timely testing, isolation, and treatment if necessary.

Field epidemiologists also contribute through [[Outbreak Investigations|outbreak investigations]] and ongoing surveillance. These systems help detect unusual patterns, emerging clusters, or sharp increases in incidence, allowing public health authorities to launch rapid containment and mitigation efforts.

In addition, targeted prophylactic interventions, such as post-exposure prophylaxis (PEP) for HIV or chemoprophylaxis for malaria, can prevent disease development in individuals who have been recently exposed to a pathogen.

Through these strategies, secondary prevention plays a vital role in curbing the spread of communicable diseases and minimizing their impact on individual and public health.

== References ==
<references />

[[Category:Prevention]]

Tertiary prevention

2025-05-17T17:27:37Z

Bosmana fem:

Tertiary prevention aims to reduce the long-term impact of communicable diseases by alleviating complications, preventing disability, and improving quality of life for those already affected. In the context of field epidemiology, tertiary prevention goes beyond clinical care and includes strategic interventions that promote recovery, functionality, and psychosocial well-being. These efforts are often disease-specific and require collaboration across public health, clinical medicine, and social services.

For instance, in HIV/AIDS management, multidisciplinary rehabilitation programs play a vital role in addressing physical deconditioning, social stigma, mental health concerns, and vocational reintegration. These programs help individuals cope with the chronic nature of the disease and support their participation in society.<ref>Rebeiro, Peter F. (2021). "The Impact of HIV/AIDS on Quality of Life: A Global Perspective". ''Journal of the International AIDS Society''. https://doi.org/10.1002/jia2.25772</ref>

In tuberculosis (TB) control, adherence support strategies are central to tertiary prevention. The Directly Observed Treatment Short-course (DOTS) strategy, endorsed by the WHO, ensures completion of therapy, thus reducing the risk of relapse and drug resistance.<ref>World Health Organization. "The End TB Strategy". https://www.who.int/tb/strategy/en/</ref> Long-term support may also include rehabilitation from lung damage and re-integration into the workforce after extended treatment.

For viral hepatitis, particularly chronic hepatitis B and C, tertiary prevention encompasses patient education, regular monitoring of liver function, and antiviral therapies to prevent progression to cirrhosis or hepatocellular carcinoma. Psychosocial support is also essential to address stigma and facilitate lifestyle adjustments that reduce hepatic stress.<ref>EASL (2020). "EASL Clinical Practice Guidelines: Management of hepatitis C virus infection". ''Journal of Hepatology'', 73:1174–1211. https://doi.org/10.1016/j.jhep.2020.05.041</ref>

In the context of emerging infectious diseases such as COVID-19 or Ebola virus disease, tertiary prevention includes structured long-term follow-up to manage post-acute sequelae (e.g., “long COVID” or post-EVD syndrome), inform rehabilitation strategies, and guide future clinical preparedness.<ref>Carfi, Angelo et al. (2020). "Persistent Symptoms in Patients After Acute COVID-19". ''JAMA'', 324(6):603–605. https://doi.org/10.1001/jama.2020.12603</ref>

Field epidemiologists contribute to tertiary prevention by:
* Designing surveillance systems that capture long-term outcomes of infectious diseases.
* Coordinating with clinical and rehabilitation services to ensure comprehensive care.
* Conducting operational research to identify best practices for chronic disease management after infection.

These activities help minimize the burden of disease on individuals and society, strengthen health systems’ resilience, and close the loop between acute response and sustained recovery.

== References ==
<references />

[[Category:Prevention]]

Tertiary prevention

2025-05-17T17:19:20Z

Bosmana fem:

Tertiary prevention aims to reduce the long-term impact of communicable diseases by alleviating complications, preventing disability, and improving quality of life for those already affected. In the context of field epidemiology, tertiary prevention goes beyond clinical care and includes strategic interventions that promote recovery, functionality, and psychosocial well-being. These efforts are often disease-specific and require collaboration across public health, clinical medicine, and social services.

For instance, in HIV/AIDS management, multidisciplinary rehabilitation programs play a vital role in addressing physical deconditioning, social stigma, mental health concerns, and vocational reintegration. These programs help individuals cope with the chronic nature of the disease and support their participation in society {{Cite journal |last=Rebeiro |first=Peter F. |title=The Impact of HIV/AIDS on Quality of Life: A Global Perspective |journal=Journal of the International AIDS Society |year=2021 |doi=10.1002/jia2.25772}}.

In tuberculosis (TB) control, adherence support strategies are central to tertiary prevention. The Directly Observed Treatment Short-course (DOTS) strategy, endorsed by the WHO, ensures completion of therapy, thus reducing the risk of relapse and drug resistance {{Cite web |url=https://www.who.int/tb/strategy/en/ |title=The End TB Strategy |publisher=World Health Organization}}. Long-term support may also include rehabilitation from lung damage and re-integration into the workforce after extended treatment.

For viral hepatitis, particularly chronic hepatitis B and C, tertiary prevention encompasses patient education, regular monitoring of liver function, and antiviral therapies to prevent progression to cirrhosis or hepatocellular carcinoma. Psychosocial support is also essential to address stigma and facilitate lifestyle adjustments that reduce hepatic stress {{Cite journal |last=EASL |title=EASL Clinical Practice Guidelines: Management of hepatitis C virus infection |journal=Journal of Hepatology |year=2020 |volume=73 |pages=1174–1211 |doi=10.1016/j.jhep.2020.05.041}}.

In the context of emerging infectious diseases such as COVID-19 or Ebola virus disease, tertiary prevention includes structured long-term follow-up to manage post-acute sequelae (e.g., “long COVID” or post-EVD syndrome), inform rehabilitation strategies, and guide future clinical preparedness {{Cite journal |last=Carfi |first=Angelo |title=Persistent Symptoms in Patients After Acute COVID-19 |journal=JAMA |year=2020 |volume=324 |issue=6 |pages=603–605 |doi=10.1001/jama.2020.12603}}.

Field epidemiologists contribute to tertiary prevention by:

Designing surveillance systems that capture long-term outcomes of infectious diseases.

Coordinating with clinical and rehabilitation services to ensure comprehensive care.

Conducting operational research to identify best practices for chronic disease management after infection.

These activities help minimize the burden of disease on individuals and society, strengthen health systems’ resilience, and close the loop between acute response and sustained recovery.

== References ==
<references />

[[Category:Prevention]]

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Tertiary prevention

2025-05-17T16:29:15Z

Bosmana fem: /* Tertiary Prevention */

Tertiary prevention aims to reduce the long-term impact of communicable diseases by alleviating complications, preventing disability, and improving quality of life for those already affected. In the context of field epidemiology, tertiary prevention goes beyond clinical care and includes strategic interventions that promote recovery, functionality, and psychosocial well-being. These efforts are often disease-specific and require collaboration across public health, clinical medicine, and social services.

For instance, in HIV/AIDS management, multidisciplinary rehabilitation programs play a vital role in addressing physical deconditioning, social stigma, mental health concerns, and vocational reintegration. These programs help individuals cope with the chronic nature of the disease and support their participation in society {{Cite journal |last=Rebeiro |first=Peter F. |title=The Impact of HIV/AIDS on Quality of Life: A Global Perspective |journal=Journal of the International AIDS Society |year=2021 |doi=10.1002/jia2.25772}}.

In tuberculosis (TB) control, adherence support strategies are central to tertiary prevention. The Directly Observed Treatment Short-course (DOTS) strategy, endorsed by the WHO, ensures completion of therapy, thus reducing the risk of relapse and drug resistance {{Cite web |url=https://www.who.int/tb/strategy/en/ |title=The End TB Strategy |publisher=World Health Organization}}. Long-term support may also include rehabilitation from lung damage and re-integration into the workforce after extended treatment.

For viral hepatitis, particularly chronic hepatitis B and C, tertiary prevention encompasses patient education, regular monitoring of liver function, and antiviral therapies to prevent progression to cirrhosis or hepatocellular carcinoma. Psychosocial support is also essential to address stigma and facilitate lifestyle adjustments that reduce hepatic stress {{Cite journal |last=EASL |title=EASL Clinical Practice Guidelines: Management of hepatitis C virus infection |journal=Journal of Hepatology |year=2020 |volume=73 |pages=1174–1211 |doi=10.1016/j.jhep.2020.05.041}}.

In the context of emerging infectious diseases such as COVID-19 or Ebola virus disease, tertiary prevention includes structured long-term follow-up to manage post-acute sequelae (e.g., “long COVID” or post-EVD syndrome), inform rehabilitation strategies, and guide future clinical preparedness {{Cite journal |last=Carfi |first=Angelo |title=Persistent Symptoms in Patients After Acute COVID-19 |journal=JAMA |year=2020 |volume=324 |issue=6 |pages=603–605 |doi=10.1001/jama.2020.12603}}.

Field epidemiologists contribute to tertiary prevention by:

Designing surveillance systems that capture long-term outcomes of infectious diseases.

Coordinating with clinical and rehabilitation services to ensure comprehensive care.

Conducting operational research to identify best practices for chronic disease management after infection.

These activities help minimize the burden of disease on individuals and society, strengthen health systems’ resilience, and close the loop between acute response and sustained recovery.

[[Category:Prevention]]

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2025-05-17T16:07:46Z

Bosmana fem: 1 revision imported

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2025-05-17T16:07:46Z

Bosmana fem: 1 revision imported

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2025-05-17T16:07:46Z

Bosmana fem: 1 revision imported

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2025-05-17T16:07:46Z

Bosmana fem: 1 revision imported

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2025-05-17T16:07:46Z

Bosmana fem: 1 revision imported

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Tertiary prevention

2025-05-17T15:59:29Z

Bosmana fem:

== Tertiary Prevention ==

Tertiary prevention aims to reduce the long-term impact of communicable diseases by alleviating complications, preventing disability, and improving quality of life for those already affected. In the context of field epidemiology, tertiary prevention goes beyond clinical care and includes strategic interventions that promote recovery, functionality, and psychosocial well-being. These efforts are often disease-specific and require collaboration across public health, clinical medicine, and social services.

For instance, in HIV/AIDS management, multidisciplinary rehabilitation programs play a vital role in addressing physical deconditioning, social stigma, mental health concerns, and vocational reintegration. These programs help individuals cope with the chronic nature of the disease and support their participation in society {{Cite journal |last=Rebeiro |first=Peter F. |title=The Impact of HIV/AIDS on Quality of Life: A Global Perspective |journal=Journal of the International AIDS Society |year=2021 |doi=10.1002/jia2.25772}}.

In tuberculosis (TB) control, adherence support strategies are central to tertiary prevention. The Directly Observed Treatment Short-course (DOTS) strategy, endorsed by the WHO, ensures completion of therapy, thus reducing the risk of relapse and drug resistance {{Cite web |url=https://www.who.int/tb/strategy/en/ |title=The End TB Strategy |publisher=World Health Organization}}. Long-term support may also include rehabilitation from lung damage and re-integration into the workforce after extended treatment.

For viral hepatitis, particularly chronic hepatitis B and C, tertiary prevention encompasses patient education, regular monitoring of liver function, and antiviral therapies to prevent progression to cirrhosis or hepatocellular carcinoma. Psychosocial support is also essential to address stigma and facilitate lifestyle adjustments that reduce hepatic stress {{Cite journal |last=EASL |title=EASL Clinical Practice Guidelines: Management of hepatitis C virus infection |journal=Journal of Hepatology |year=2020 |volume=73 |pages=1174–1211 |doi=10.1016/j.jhep.2020.05.041}}.

In the context of emerging infectious diseases such as COVID-19 or Ebola virus disease, tertiary prevention includes structured long-term follow-up to manage post-acute sequelae (e.g., “long COVID” or post-EVD syndrome), inform rehabilitation strategies, and guide future clinical preparedness {{Cite journal |last=Carfi |first=Angelo |title=Persistent Symptoms in Patients After Acute COVID-19 |journal=JAMA |year=2020 |volume=324 |issue=6 |pages=603–605 |doi=10.1001/jama.2020.12603}}.

Field epidemiologists contribute to tertiary prevention by:

Designing surveillance systems that capture long-term outcomes of infectious diseases.

Coordinating with clinical and rehabilitation services to ensure comprehensive care.

Conducting operational research to identify best practices for chronic disease management after infection.

These activities help minimize the burden of disease on individuals and society, strengthen health systems’ resilience, and close the loop between acute response and sustained recovery.

[[Category:Prevention]]

File:Onderzeebootbunker waalhaven Kees Mout Fotos.jpg

2025-05-17T15:48:58Z

Bosmana fem:

test

Event-based Surveillance

2025-05-17T15:09:47Z

Bosmana fem: test

Event-based surveillance (EBS) is a vital component of the field of epidemiology, aimed at early detection, assessment, and response to public health threats. EBS is essential in monitoring and controlling emerging and re-emerging infectious diseases, as well as events that may lead to outbreaks, epidemics, or pandemics. In this chapter, we will delve into the concepts, methods, and significance of event-based surveillance in field epidemiology.

==Defining Event-Based Surveillance==
Event-based surveillance is a systematic approach to the collection, analysis, interpretation, and dissemination of information about health events or risks that may pose a threat to public health. This type of surveillance focuses on the detection and verification of events or signals, rather than relying solely on routinely collected health data. Events can include disease outbreaks, unusual clusters of illness, or exposure to hazardous agents.

==Key Components of Event-Based Surveillance==

The main components of EBS are:

* Detection: The process of identifying potential public health threats through various sources, including media, healthcare providers, community-based organizations, and public health agencies.

* Verification: The process of confirming the existence, nature, and extent of the public health event through investigation and analysis.

* Assessment: Evaluating the potential public health impact of the event and determining appropriate response measures.

* Response: Implementing appropriate interventions to prevent, control, or mitigate the impact of the event on public health.

* Communication: Sharing information and coordinating with relevant stakeholders, including the public, to ensure a timely and effective response.

==Methods for Event Detection and Data Collection==

EBS relies on a variety of data sources and methods to detect and collect information about potential public health events:

* Media monitoring: Analyzing local, national, and international media sources to identify reports of potential public health events.

* Community-based reporting: Engaging community members in the reporting of unusual health events or risk factors.

* Healthcare provider reporting: Collecting information from healthcare providers, including hospitals and clinics, about unusual health events or risk factors.

* Syndromic surveillance: Monitoring syndromes or groups of symptoms indicative of a potential public health event.

* Laboratory surveillance: Analyzing laboratory data to identify unusual patterns of disease or infection.

* Digital surveillance: Leveraging internet-based platforms, such as social media and online forums, to gather information about potential public health events.

==Importance of Event-Based Surveillance in Field Epidemiology==

Event-based surveillance plays a crucial role in field epidemiology for several reasons:

* Timeliness: EBS can provide early warning of potential public health threats, allowing for a rapid response and the possibility of preventing or mitigating their impact.

* Sensitivity: EBS can detect emerging diseases or unusual health events that may be missed by traditional routine surveillance systems.

* Flexibility: EBS can be adapted to different settings and contexts, making it a valuable tool for detecting public health threats in diverse environments.

* Integration: EBS can complement existing surveillance systems, providing additional information and insights to inform public health decision-making.

In summary, event-based surveillance is a critical aspect of field epidemiology that enhances the early detection and response to public health threats. By monitoring a wide range of data sources and employing various methods, EBS can provide valuable information to guide public health interventions, ultimately protecting the health and well-being of communities worldwide.

=Reference=
* World Health Organization (2018). Early Detection, Assessment and Response to Acute Public Health Events: Implementation of Early Warning and Response with a focus on Event-Based Surveillance. WHO/HSE/GCR/LYO/2014.4. World Health Organization. Geneva, Switzerland.

[[Category:Surveillance principles]]

MediaWiki:Confirmemail body

2025-05-16T20:59:33Z

Bosmana fem: Created page with "Hello and WELCOME as an editor to FemWIKI I have registered an account "$2" with this email address on {{SITENAME}}, since we received a registration form with your details a..."

Hello and WELCOME as an editor to FemWIKI

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To confirm that you requested an account at FemWiki and activate email features on {{SITENAME}}, open this link in your browser:

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This confirmation code will expire at $4.

I wish you lots of fun and good editing in the Femwiki community. To facilitate discussions among the editors, I have added you to the [https://fieldepi.eu/groups/femwiki-editors/ group FemWIKI] editors at the FieldEpi.eu platform.

Warm regards

Arnold Bosman

File:Screenshot 2023-08-15 150848.png

2025-05-16T07:43:54Z

Bosmana fem:

FEM-WIKI

2025-03-17T14:42:24Z

Bosmana fem: /* FEMWiki Needs You! */

= '''Field Epidemiology Manual''' =

The Field Epidemiology Manual was originally developed in 2007 by the [http://ecdc.europa.eu ECDC] and the City eHealth Research Centre (CeRC - City University, London) <Ref>KOSTKOVA, Patty; SZOMSZOR, Martin. The FEM Wiki Project: A Conversion of a Training Resource for Field Epidemiologists into a Collaborative Web 2.0 Portal. In: Electronic Healthcare: Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers 3. Springer Berlin Heidelberg, 2012. p. 119-126.</ref>, <Ref>KOSTKOVA, Patty; PRIKAZSKY, Vladimir; BOSMAN, Arnold. FEMwiki: Crowdsourcing Semantic Taxonomy and Wiki Input Todomain Experts While Keeping Editorial Control: Mission Possible! In: Proceedings of the 5th International Conference on Digital Health 2015. 2015. p. 27-34.</ref> to support the European Programme for Intervention Epidemiology Training ([https://www.ecdc.europa.eu/en/epiet-euphem EPIET]). Trainers, supervisors, scientific coordinators, and facilitators created draft chapters using the lectures they delivered during the EPIET introductory course. The philosophy of sharing and building knowledge (in particular training materials) led to creation of a collaborative information space for the epidemiological training community - The FEM Wiki.

Eventually, the ECDC decommissioned the FEM Wiki in 2022 and archived the last version as a [https://eva.ecdc.europa.eu/mod/resource/view.php?id=23002 PDF]. Since FEM Wiki content was developed under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons], the Dutch Public Health Learning Support Company [https://Transmissible.eu Transmissible] decided to reinstall the Field Epidemiology manual as it was intended: a professional collaborative platform.

The FEMWiki aims to create a library of training materials for field epidemiologists.

FEM Wiki is an open information-sharing platform for all professionals and the lay public interested in public health. It is hosted and funded by ECDC. Platform users provide the content of FEM Wiki and do not necessarily represent the official opinion of Transmissible BV. By contributing content to FEMWIKI, users agree to the conditions described under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons] and FEM Wiki users’ [[FEM Users code of conduct|code of conduct]].

Though this platform does not allow as many community activities besides maintaining the Field Epidemiology Manual, we have created an [[Talk:FEM-WIKI|open marketplace where users can discuss and exchange views]]: click on the 'Discussion' tab above. The FEMWIKI is organised into five main volumes. Below is a portal with links to each volume's main articles.

<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Methods Portal'''
<categorytree mode="all">Assessing the burden of disease and risk assessment</categorytree>
<categorytree mode="all">Statistical Concepts</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Public Health Portal'''
<categorytree mode="all">Introduction to Public Health and basic concepts</categorytree>
<categorytree mode="all">General Communication</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Infection Control'''
<categorytree mode="all">Infection control and hospital hygiene</categorytree>
</div>

=References=
<References/>

=FEMWiki Needs You!=
YES, you should contribute!
If you are a Field Epidemiologist who loves to manage and share knowledge, then you are the one FEMWiki needs. [https://fieldepi.eu/fem-editor/ Request an account here], and we will be delighted to include more Field Epidemiologists in the FEM-editor crew!
[[File:Aunt WIKI needs you2.jpg]]

FEM-WIKI

2025-03-17T14:30:58Z

Bosmana fem: /* FEMWiki Needs You! */

= '''Field Epidemiology Manual''' =

The Field Epidemiology Manual was originally developed in 2007 by the [http://ecdc.europa.eu ECDC] and the City eHealth Research Centre (CeRC - City University, London) <Ref>KOSTKOVA, Patty; SZOMSZOR, Martin. The FEM Wiki Project: A Conversion of a Training Resource for Field Epidemiologists into a Collaborative Web 2.0 Portal. In: Electronic Healthcare: Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers 3. Springer Berlin Heidelberg, 2012. p. 119-126.</ref>, <Ref>KOSTKOVA, Patty; PRIKAZSKY, Vladimir; BOSMAN, Arnold. FEMwiki: Crowdsourcing Semantic Taxonomy and Wiki Input Todomain Experts While Keeping Editorial Control: Mission Possible! In: Proceedings of the 5th International Conference on Digital Health 2015. 2015. p. 27-34.</ref> to support the European Programme for Intervention Epidemiology Training ([https://www.ecdc.europa.eu/en/epiet-euphem EPIET]). Trainers, supervisors, scientific coordinators, and facilitators created draft chapters using the lectures they delivered during the EPIET introductory course. The philosophy of sharing and building knowledge (in particular training materials) led to creation of a collaborative information space for the epidemiological training community - The FEM Wiki.

Eventually, the ECDC decommissioned the FEM Wiki in 2022 and archived the last version as a [https://eva.ecdc.europa.eu/mod/resource/view.php?id=23002 PDF]. Since FEM Wiki content was developed under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons], the Dutch Public Health Learning Support Company [https://Transmissible.eu Transmissible] decided to reinstall the Field Epidemiology manual as it was intended: a professional collaborative platform.

The FEMWiki aims to create a library of training materials for field epidemiologists.

FEM Wiki is an open information-sharing platform for all professionals and the lay public interested in public health. It is hosted and funded by ECDC. Platform users provide the content of FEM Wiki and do not necessarily represent the official opinion of Transmissible BV. By contributing content to FEMWIKI, users agree to the conditions described under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons] and FEM Wiki users’ [[FEM Users code of conduct|code of conduct]].

Though this platform does not allow as many community activities besides maintaining the Field Epidemiology Manual, we have created an [[Talk:FEM-WIKI|open marketplace where users can discuss and exchange views]]: click on the 'Discussion' tab above. The FEMWIKI is organised into five main volumes. Below is a portal with links to each volume's main articles.

<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Methods Portal'''
<categorytree mode="all">Assessing the burden of disease and risk assessment</categorytree>
<categorytree mode="all">Statistical Concepts</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Public Health Portal'''
<categorytree mode="all">Introduction to Public Health and basic concepts</categorytree>
<categorytree mode="all">General Communication</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Infection Control'''
<categorytree mode="all">Infection control and hospital hygiene</categorytree>
</div>

=References=
<References/>

=FEMWiki Needs You!=
YES, you should contribute!
If you are a Field Epidemiologist who loves to manage and share knowledge, then you are the one FEMWiki needs. Request an account here, and we will be delighted to include more Field Epidemiologists in the FEM-editor crew!
[[File:Aunt WIKI needs you2.jpg]]

File:Aunt WIKI needs you2.jpg

2025-03-17T14:29:49Z

Bosmana fem:

File:Aunt WIKI needs you1.jpg

2025-03-17T14:24:11Z

Bosmana fem:

File:Aunt WIKI needs you.jpg

2025-03-17T14:06:11Z

Bosmana fem:

FEM-WIKI

2025-03-17T14:02:54Z

Bosmana fem:

= '''Field Epidemiology Manual''' =

The Field Epidemiology Manual was originally developed in 2007 by the [http://ecdc.europa.eu ECDC] and the City eHealth Research Centre (CeRC - City University, London) <Ref>KOSTKOVA, Patty; SZOMSZOR, Martin. The FEM Wiki Project: A Conversion of a Training Resource for Field Epidemiologists into a Collaborative Web 2.0 Portal. In: Electronic Healthcare: Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers 3. Springer Berlin Heidelberg, 2012. p. 119-126.</ref>, <Ref>KOSTKOVA, Patty; PRIKAZSKY, Vladimir; BOSMAN, Arnold. FEMwiki: Crowdsourcing Semantic Taxonomy and Wiki Input Todomain Experts While Keeping Editorial Control: Mission Possible! In: Proceedings of the 5th International Conference on Digital Health 2015. 2015. p. 27-34.</ref> to support the European Programme for Intervention Epidemiology Training ([https://www.ecdc.europa.eu/en/epiet-euphem EPIET]). Trainers, supervisors, scientific coordinators, and facilitators created draft chapters using the lectures they delivered during the EPIET introductory course. The philosophy of sharing and building knowledge (in particular training materials) led to creation of a collaborative information space for the epidemiological training community - The FEM Wiki.

Eventually, the ECDC decommissioned the FEM Wiki in 2022 and archived the last version as a [https://eva.ecdc.europa.eu/mod/resource/view.php?id=23002 PDF]. Since FEM Wiki content was developed under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons], the Dutch Public Health Learning Support Company [https://Transmissible.eu Transmissible] decided to reinstall the Field Epidemiology manual as it was intended: a professional collaborative platform.

The FEMWiki aims to create a library of training materials for field epidemiologists.

FEM Wiki is an open information-sharing platform for all professionals and the lay public interested in public health. It is hosted and funded by ECDC. Platform users provide the content of FEM Wiki and do not necessarily represent the official opinion of Transmissible BV. By contributing content to FEMWIKI, users agree to the conditions described under [https://creativecommons.org/licenses/by-nc-sa/3.0/ Creative Commons] and FEM Wiki users’ [[FEM Users code of conduct|code of conduct]].

Though this platform does not allow as many community activities besides maintaining the Field Epidemiology Manual, we have created an [[Talk:FEM-WIKI|open marketplace where users can discuss and exchange views]]: click on the 'Discussion' tab above. The FEMWIKI is organised into five main volumes. Below is a portal with links to each volume's main articles.

<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Methods Portal'''
<categorytree mode="all">Assessing the burden of disease and risk assessment</categorytree>
<categorytree mode="all">Statistical Concepts</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Public Health Portal'''
<categorytree mode="all">Introduction to Public Health and basic concepts</categorytree>
<categorytree mode="all">General Communication</categorytree>
</div>
<div style="display: inline-block; width: 30%; vertical-align: top; border: 1px solid #000; padding: 10px; margin: 5px;">
'''Infection Control'''
<categorytree mode="all">Infection control and hospital hygiene</categorytree>
</div>

=References=
<References/>

=FEMWiki Needs You!=
YES, you should contribute!
If you are a Field Epidemiologist who loves to manage and share knowledge, then you are the one FEMWiki needs. Request an account here, and we will be delighted to include more Field Epidemiologists in the FEM-editor crew!

User:LucretiaMacFarla

2023-12-28T20:50:04Z

Bosmana fem: Replaced content with "SPAM"

SPAM

User:RowenaV6018925

2023-12-28T20:48:15Z

Bosmana fem: Replaced content with "SPAM"

SPAM

Category:Public Health Interventions

2023-07-11T04:41:25Z

Bosmana fem:

Interventions in communicable disease control are by preference, guided by evidence, coming from existing scientific knowledge, and newly generated by [[Assessing the burden of disease and risk assessment|assessment methods for the burden of disease]] and [[Field Epidemiology|field epidemiology]].

Interventions are aimed at preventing or interrupting the transmission of an infectious agent to [[Host|hosts]] and may be proactive (prevention measures) or reactive (control response measures). Each of those measures can be targeted at 'critical control points' in the chain of transmission of infectious agents (see figure).
[[File:transmissionmodelBosman.png|600px|frame|none]]

For example, measures targeting [[Reservoir for infectious agents|reservoirs]] may include rodent control/extermination in case of leptospirosis or culling of poultry flocks in case of avian influenza. A large portion of control measures includes measures targeted at specific [[Source of infection|sources]], for example, removing botulism-contaminated olives from the market or searching for an infectious tuberculosis patient to treat the infection.

Examples of measures targeted at [[transmission routes]] include [[Vector Borne|vector]] control, behavioural education (e.g., safe sex, safe cooking, hand hygiene promotion), and drinking water treatment. Interventions targeting barriers around the [[host]] could include providing personal protective equipment, treatment, and covering skin lesions. Immunizations (vaccinations and prophylaxis through immunoglobulins) are well-known intervention measures to enhance specific immunity against microorganisms.

Finally, treatment and/or quarantine of infectious patients or carriers ensures that the risk of person-to-person transmission is reduced in certain diseases.

=Question:=
What is the difference between preventive, response control, and intervention measures?

=Reflection:=
In various textbooks and articles, these terms are used in different ways. In the FEMWiki, we prefer the following distinction:

Preventive interventions in communicable disease control:
# Primary prevention: Intervention in the population, targeting healthy population (i.e., not infected) at risk to avoid infection (e.g., immunisations)
# Secondary prevention: intervention in the population infected in order to mitigate symptomatic disease or avoid complications (e.g., screening)
# Tertiary prevention: intervention targeting the population with disease symptoms aimed at limiting the impaired functions in daily life or society due to the disease (e.g., rehabilitation regimes for paralytic polio patients)

In addition to these 3 levels of preventive interventions, a more generic level is often used: primordial prevention, which includes generic measures such as improvements in civil engineering (clean drinking water, sewage systems, etc.).

Communicable disease control response measures that do not include primary, secondary or tertiary prevention are treatment or quarantine of carriers, culling infected poultry flocks, or removing certain food items from the market.
However, it is important to be aware that these classifications of prevention are under debate in public health since they do not offer a complete framework for disease prevention and control, and several alternatives have been suggested.

==References==
Barbara Starfield. Public Health and Primary Care: A Framework for Proposed Linkages. Am J Public Health, 1996 Oct.;86(10):1365–1369.
B Starfield, J Hyde, J Gérvas, I Heath. The concept of prevention: a good idea gone astray? J Epidemiol Community Health 2008;62:580–583. doi:10.1136/jech.2007.071027

; FEM Editor 2007
: Arnold Bosman

;FEM Contributors
: Vladimir Prikazsky
: Arnold Bosman

[[Category:Introduction to Public Health and basic concepts]]