Evidence map›Paper›PMID 35332199›Full record

ArticleScientific reports2022

Spatial-temporal patterns and risk factors for human leptospirosis in Thailand, 2012-2018.

Sudarat Chadsuthi, Karine Chalvet-Monfray, Suchada Geawduanglek, Phrutsamon Wongnak, Julien Cappelle

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  9. The Role of Hydrometeorological Factors in Leptospirosis Transmission in Central Java, Indonesia.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2025
    Article
  10. Article
  11. Article
  12. Review
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  17. Analysing the outbreaks of leptospirosis after floods in Kerala, India.International journal of health geographics · 2024
    Article
  18. Article
  19. Article
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

5 authors.

Sudarat ChadsuthiDepartment of Physics, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand. sudaratc@nu.ac.th.
Karine Chalvet-MonfrayUniversité de Lyon, INRAE, VetAgro Sup, UMR EPIA, 69280, Marcy l'Etoile, France.
Suchada GeawduanglekMedical and Graduate Education Division, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
Phrutsamon WongnakUniversité de Lyon, INRAE, VetAgro Sup, UMR EPIA, 69280, Marcy l'Etoile, France.
Julien CappelleUniversité de Lyon, INRAE, VetAgro Sup, UMR EPIA, 69280, Marcy l'Etoile, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leptospirosis is a globally important zoonotic disease. The disease is particularly important in tropical and subtropical countries. Infections in humans can be caused by exposure to infected animals or contaminated soil or water, which are suitable for Leptospira. To explore the cluster area, the Global Moran's I index was calculated for incidences per 100,000 population at the province level during 2012-2018, using the monthly and annual data. The high-risk and low-risk provinces were identified using the local indicators of spatial association (LISA). The risk factors for leptospirosis were evaluated using a generalized linear mixed model (GLMM) with zero-inflation. We also added spatial and temporal correlation terms to take into account the spatial and temporal structures. The Global Moran's I index showed significant positive values. It did not demonstrate a random distribution throughout the period of study. The high-risk provinces were almost all in the lower north-east and south parts of Thailand. For yearly reported cases, the significant risk factors from the final best-fitted model were population density, elevation, and primary rice crop arable areas. Interestingly, our study showed that leptospirosis cases were associated with large areas of rice production but were less prevalent in areas of high rice productivity. For monthly reported cases, the model using temperature range was found to be a better fit than using percentage of flooded area. The significant risk factors from the model using temperature range were temporal correlation, average soil moisture, normalized difference vegetation index, and temperature range. Temperature range, which has strongly negative correlation to percentage of flooded area was a significant risk factor for monthly data. Flood exposure controls should be used to reduce the risk of leptospirosis infection. These results could be used to develop a leptospirosis warning system to support public health organizations in Thailand.

Indexed as

LeptospiraLeptospirosisAnimalsHumansIncidenceRisk FactorsSoilThailandSoil

Identifiers

PMID35332199
PMCPMC8948194

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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.