ArticlePLoS neglected tropical diseases2025
Association between hydrometeorological conditions and hemorrhagic fever with renal syndrome in Shandong Province, China, from 2005 to 2019.
Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Non-negligible impacts of urbanization on spatiotemporal variations of infectious disease: a case study of hemorrhagic fever with renal syndrome epidemics in China.Infectious diseases of poverty · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundHemorrhagic fever with renal syndrome (HFRS) is a rodent-borne zoonotic disease with a case fatality rate ranging from 1% to 15%. Long-term evidence regarding its association with local hydrometeorological conditions remain limited. This study aimed to assess the non-linear and lagged effects of extreme hydrometeorological conditions on HFRS risk and examine the modifying effects of regional characteristics in Shandong Province, China.
methodsData from January 1, 2005 to December 31, 2019 across 136 counties in Shandong Province were collected. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated from temperature, precipitation and evaporation, was used to represent local hydrometeorological conditions (dry and wet). A spatiotemporal Bayesian hierarchical model combined with distributed lag non-linear model was applied to explore the association between climate indicators and HFRS risk over a 6-month lag. Modification effects were quantified using linear interaction terms.
resultsOver the 15-year period, annual HFRS incidence declined from 2.62/100,000 to 0.72/100,000, with two minor peaks observed. The cumulative association between SPEI and HFRS over 6-month lag appeared U-shaped. The relative risk (RR) of HFRS under extreme wet conditions increased at 4-6 months lag, peaking at the 6-month lag (RR = 1.49, 95% confidence interval (CI): 1.37-1.63). Extreme dry conditions had a persistent impact, also peaking at the 6-month lag (RR = 1.05, 95% CI: 1.01-1.09). Areas with low per capita Gross Domestic Product, Normalized difference vegetation index, Total power of agricultural machinery and annual temperature, as well as high elevation, exhibited higher risks of HFRS under extreme wet conditions. The modification effects under extreme dry conditions were similar but weaker.
conclusionsBoth extreme wet and dry conditions increase the risk of HFRS, with county characteristics further modifying these associations. These findings provide a scientific foundation for policymakers to develop targeted and effective HFRS prevention and control strategies, particularly in high-risk regions, while considering hydrometeorological conditions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.