Hypothesis Generation During Foodborne-Illness Outbreak Investigations
© Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US..
Hypothesis generation is a critical, but challenging, step in a foodborne outbreak investigation. The pathogens that contaminate food have many diverse reservoirs, resulting in seemingly limitless potential vehicles. Identifying a vehicle is particularly challenging for clusters detected through national pathogen-specific surveillance, because cases can be geographically dispersed and lack an obvious epidemiologic link. Moreover, state and local health departments could have limited resources to dedicate to cluster and outbreak investigations. These challenges underscore the importance of hypothesis generation during an outbreak investigation. In this review, we present a framework for hypothesis generation focusing on 3 primary sources of information, typically used in combination: 1) known sources of the pathogen causing illness; 2) person, place, and time characteristics of cases associated with the outbreak (descriptive data); and 3) case exposure assessment. Hypothesis generation can narrow the list of potential food vehicles and focus subsequent epidemiologic, laboratory, environmental, and traceback efforts, ensuring that time and resources are used more efficiently and increasing the likelihood of rapidly and conclusively implicating the contaminated food vehicle.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:190 |
|---|---|
| Enthalten in: |
American journal of epidemiology - 190(2021), 10 vom: 01. Okt., Seite 2188-2197 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
White, Alice E [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Education |
|---|
| Anmerkungen: |
Date Completed 18.10.2021 Date Revised 18.10.2021 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.1093/aje/kwab118 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM324325738 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM324325738 | ||
| 003 | DE-627 | ||
| 005 | 20231225190101.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1093/aje/kwab118 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1081.xml |
| 035 | |a (DE-627)NLM324325738 | ||
| 035 | |a (NLM)33878169 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a White, Alice E |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Hypothesis Generation During Foodborne-Illness Outbreak Investigations |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 18.10.2021 | ||
| 500 | |a Date Revised 18.10.2021 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2021. This work is written by (a) US Government employee(s) and is in the public domain in the US. | ||
| 520 | |a Hypothesis generation is a critical, but challenging, step in a foodborne outbreak investigation. The pathogens that contaminate food have many diverse reservoirs, resulting in seemingly limitless potential vehicles. Identifying a vehicle is particularly challenging for clusters detected through national pathogen-specific surveillance, because cases can be geographically dispersed and lack an obvious epidemiologic link. Moreover, state and local health departments could have limited resources to dedicate to cluster and outbreak investigations. These challenges underscore the importance of hypothesis generation during an outbreak investigation. In this review, we present a framework for hypothesis generation focusing on 3 primary sources of information, typically used in combination: 1) known sources of the pathogen causing illness; 2) person, place, and time characteristics of cases associated with the outbreak (descriptive data); and 3) case exposure assessment. Hypothesis generation can narrow the list of potential food vehicles and focus subsequent epidemiologic, laboratory, environmental, and traceback efforts, ensuring that time and resources are used more efficiently and increasing the likelihood of rapidly and conclusively implicating the contaminated food vehicle | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, U.S. Gov't, P.H.S. | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a education | |
| 650 | 4 | |a foodborne illnesses | |
| 650 | 4 | |a infectious disease outbreaks | |
| 650 | 4 | |a interviews | |
| 650 | 4 | |a public health practice | |
| 650 | 4 | |a public health professional | |
| 650 | 4 | |a telephone | |
| 700 | 1 | |a Smith, Kirk E |e verfasserin |4 aut | |
| 700 | 1 | |a Booth, Hillary |e verfasserin |4 aut | |
| 700 | 1 | |a Medus, Carlota |e verfasserin |4 aut | |
| 700 | 1 | |a Tauxe, Robert V |e verfasserin |4 aut | |
| 700 | 1 | |a Gieraltowski, Laura |e verfasserin |4 aut | |
| 700 | 1 | |a Scallan Walter, Elaine |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t American journal of epidemiology |d 1965 |g 190(2021), 10 vom: 01. Okt., Seite 2188-2197 |w (DE-627)NLM000012327 |x 1476-6256 |7 nnns |
| 773 | 1 | 8 | |g volume:190 |g year:2021 |g number:10 |g day:01 |g month:10 |g pages:2188-2197 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1093/aje/kwab118 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 190 |j 2021 |e 10 |b 01 |c 10 |h 2188-2197 | ||