Evidence map›Paper›PMID 23628771›Full record

ArticleJournal of medical Internet research2013

Examining the differences in format and characteristics of zoonotic virus surveillance data on state agency websites.

Matthew Scotch, Brittany Baarson, Rachel Beard, Robert Lauder, Aarthi Varman, Rolf U Halden

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Matthew ScotchCenter for Environmental Security, Biodesign Institute and Security and Defense Systems Initiative, Arizona State University, Tempe, AZ 85287-5904, United States. matthew.scotch@asu.edu
Brittany Baarson
Rachel Beard
Robert Lauder
Aarthi Varman
Rolf U Halden

Funding

Informatics for zoonotic disease surveillance: combining animal and human dataR00LM009825 · NLM · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI SCOTCH, MATTHEW · 2010 to 2012
$723k
NLM NIH HHS R00 LM009825NLM NIH HHS R00LM009825
6 · The paper itself

Abstract

backgroundZoonotic viruses are infectious organisms transmittable between animals and humans. Agencies of public health, agriculture, and wildlife conduct surveillance of zoonotic viruses and often report data on their websites. However, the format and characteristics of these data are not known.

objectiveTo describe and compare the format and characteristics of statistics of zoonotic viruses on state public health, agriculture, and wildlife agency websites.

methodsFor each state, we considered the websites of that state's public health, agriculture, and wildlife agency. For each website, we noted the presence of any statistics for zoonotic viruses from 2000-2012. We analyzed the data using numerous categories including type of statistic, temporal and geographic level of detail, and format. We prioritized our analysis within each category based on assumptions of individuals' preferences for extracting and analyzing data from websites. Thus, if two types of data (such as city and state-level) were present for a given virus in a given year, we counted the one with higher priority (city). External links from agency sites to other websites were not considered.

resultsFrom 2000-2012, state health departments had the most extensive virus data, followed by agriculture, and then wildlife. We focused on the seven viruses that were common across the three agencies. These included rabies, West Nile virus, eastern equine encephalitis, St. Louis encephalitis, western equine encephalitis, influenza, and dengue fever. Simple numerical totals were most often used to report the data (89% for public health, 81% for agriculture, and 82% for wildlife), and proportions were not different (chi-square P=.15). Public health data were most often presented yearly (66%), while agriculture and wildlife agencies often described cases as they occurred (Fisher's Exact test P<.001). Regarding format, public health agencies had more downloadable PDF files (68%), while agriculture (61%) and wildlife agencies (46%) presented data directly in the text of the HTML webpage (Fisher's Exact test P<.001). Demographics and other information including age, gender, and host were limited. Finally, a Fisher's Exact test showed no association between geography data and agency type (P=.08). However, it was noted that agriculture department data was often at the county level (63%), while public health was mixed between county (38%) and state (35%).

conclusionsThis study focused on the format and characteristics of statistics of zoonotic viruses on websites of state public health, wildlife, and agriculture agencies in the context of population health surveillance. Data on zoonotic viruses varied across agencies presenting challenges for researchers needing to integrate animal and human data from different websites.

Indexed as

InternetAgricultureAnimalsAnimals, WildData CollectionGovernment AgenciesHumansPublic Health SurveillanceTelemedicineUnited StatesVirus DiseasesZoonosesdata analysisepidemiologypublic healthWorld Wide Webzoonoses

Identifiers

PMID23628771
PMCPMC3650930

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.