Evidence map›Paper›PMID 38179332›Full record

ArticleFrontiers in veterinary science2023

Geo-temporal patterns to design cost-effective interventions for zoonotic diseases -the case of brucellosis in the country of Georgia.

Ariel L Rivas, Stephen D Smith, V Basiladze, Tengiz Chaligava, Lile Malania, Irma Burjanadze, Tamar Chichinadze, Nikoloz Suknidze, Nana Bolashvili, Almira L Hoogesteijn and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in veterinary science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 20% of its field
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

3 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 3 countries.

Ariel L Rivas *Center for Global Health, Internal Medicine, School of Medicine, University of New Mexico, Albuquerque, NM, United States.
Stephen D Smith *Geospatial Research Services, Ithaca, NY, United States.
V BasiladzeNational Food Agency, Ministry of Environmental Protection and Agriculture of Georgia, Tbilisi, Georgia.
Tengiz ChaligavaNational Food Agency, Ministry of Environmental Protection and Agriculture of Georgia, Tbilisi, Georgia.
Lile MalaniaNational Center for Disease Control and Public Health, Tbilisi, Georgia.
Irma BurjanadzeNational Center for Disease Control and Public Health, Tbilisi, Georgia.
Tamar ChichinadzeVakhushti Bagrationi Institute of Geography, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia.
Nikoloz SuknidzeVakhushti Bagrationi Institute of Geography, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia.
Nana BolashviliVakhushti Bagrationi Institute of Geography, Ivane Javakhishvili Tbilisi State University, Tbilisi, Georgia.
Almira L HoogesteijnDepartment of Human Ecology, CINVESTAV, Merida, Yucatan, Mexico.
Kendra GilbertsonGraduate Degree Program in Ecology, Department of Biology, Colorado State University, Fort Collins, CO, United States.
Jonathan H BertramGraduate Degree Program in Ecology, Department of Biology, Colorado State University, Fort Collins, CO, United States.
Jeanne Marie FairGenomics and Bioanalytics, Los Alamos National Laboratory, Los Alamos, NM, United States.
Colleen T WebbGraduate Degree Program in Ecology, Department of Biology, Colorado State University, Fort Collins, CO, United States.
Paata ImnadzeNational Center for Disease Control and Public Health, Tbilisi, Georgia.
Michael KosoyKB One Health LLC, Fort Collins, CO, United States.
Colorado State University · USNational Center for Disease Control and Public Health · GETbilisi State University · GECenter for Global Health · USCenter for Research and Advanced Studies of the National Polytechnic Institute · MXLos Alamos National Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Control of zoonosis can benefit from geo-referenced procedures. Focusing on brucellosis, here the ability of two methods to distinguish disease dissemination patterns and promote cost-effective interventions was compared. Method: Geographical data on bovine, ovine and human brucellosis reported in the country of Georgia between 2014 and 2019 were investigated with (i) the Hot Spot (HS) analysis and (ii) a bio-geographical (BG) alternative. Results: More than one fourth of all sites reported cases affecting two or more species. While ruminant cases displayed different patterns over time, most human cases described similar geo-temporal features, which were associated with the route used by migrant shepherds. Other human cases showed heterogeneous patterns. The BG approach identified small areas with a case density twice as high as the HS method. The BG method also identified, in 2018, a 2.6-2.99 higher case density in zoonotic (human and non-human) sites than in non-zoonotic sites (which only reported cases affecting a single species) -a finding that, if corroborated, could support cost-effective policy-making. Discussion: Three dissemination hypotheses were supported by the data: (i) human cases induced by sheep-related contacts; (ii) human cases probably mediated by contaminated milk or meat; and (iii) cattle and sheep that infected one another. This proof-of-concept provided a preliminary validation for a method that may support cost-effective interventions oriented to control zoonoses. To expand these findings, additional studies on zoonosis-related decision-making are recommended.

Indexed as

brucellosiscost-benefit analysisGeorgia (country)geo-temporal analysiszoonosis

Identifiers

PMID38179332
PMCPMC10765567
OpenAlexW4390010750

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Registered trials

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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.