Evidence map›Paper›PMID 39198489›Full record

ArticleScientific reports2024

A thirty-year time series analyses identifies coherence between oscillations in Anthrax outbreaks and El Niño in Karnataka, India.

Mohammed Mudassar Chanda, Lindsay Campbell, Henry Walke, Johanna S Salzer, Divakar Hemadri, Sharanagouda S Patil, Bethan V Purse, Sathish Bhadravati Shivachandra

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Mohammed Mudassar ChandaICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Ramagondanahalli, Yelahanka, Post Box-6450, Bengaluru, Karnataka, 560064, India. chandamudassar@gmail.com.
Lindsay CampbellFlorida Medical Entomology Laboratory, Department of Entomology and Nematology, IFAS, University of Florida, 200 9th St SE, Vero Beach, FL, 32962, USA.
Henry WalkeBacterial Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention (CDC), National Center for Emerging and Zoonotic Infectious Diseases, 1600 Clifton Rd. NE MS A-30, Atlanta, GA, 30333, USA.
Johanna S SalzerBacterial Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention (CDC), National Center for Emerging and Zoonotic Infectious Diseases, 1600 Clifton Rd. NE MS A-30, Atlanta, GA, 30333, USA.
Divakar HemadriICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Ramagondanahalli, Yelahanka, Post Box-6450, Bengaluru, Karnataka, 560064, India.
Sharanagouda S PatilICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Ramagondanahalli, Yelahanka, Post Box-6450, Bengaluru, Karnataka, 560064, India.
Bethan V PurseUK Centre for Ecology and Hydrology, Benson Lane, Crowmarsh Gifford, Oxfordshire, OX10 8BB, UK.
Sathish Bhadravati ShivachandraICAR-National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Ramagondanahalli, Yelahanka, Post Box-6450, Bengaluru, Karnataka, 560064, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anthrax is an economically important zoonotic disease affecting both livestock and humans. The disease is caused by a spore forming bacterium, Bacillus anthracis, and is considered endemic to the state of Karnataka, India. It is critical to quantify the role of climatic factors in determining the temporal pattern of anthrax outbreaks, so that reliable forecasting models can be developed. These models will aid in establishing public health surveillance and guide strategic vaccination programs, which will reduce the economic loss to farmers, and prevent the spill-over of anthrax from livestock to humans. In this study, correlation and coherence between time series of anthrax outbreaks in livestock (1987-2016) and meteorological variables and Sea Surface Temperature anomalies (SST) were identified using a combination of cross-correlation analyses, spectral analyses (wavelets and empirical mode decomposition) and further quantified using a Bayesian time series regression model accounting for temporal autocorrelation. Monthly numbers of anthrax outbreaks were positively associated with a lagged effect of rainfall and wet day frequency. Long-term periodicity in anthrax outbreaks (approximately 6-8 years) was coherent with the periodicity in SST anomalies and outbreak numbers increased with decrease in SST anomalies. These findings will be useful in planning long-term anthrax prevention and control strategies in Karnataka state of India.

Indexed as

AnthraxDisease OutbreaksEl Nino-Southern OscillationAnimalsBacillus anthracisBayes TheoremHumansIndiaLivestock

Identifiers

PMID39198489
PMCPMC11358154

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.