Evidence map›Paper›PMID 38623497›Full record

ArticleOne health (Amsterdam, Netherlands)2024

Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China.

Bo Wen, Zurong Yang, Shaolong Ren, Ting Fu, Rui Li, Mengwei Lu, Xiaoang Qin, Ang Li, Zhifu Kou, Zhongjun Shao and 1 more

Abstract read
In one paragraph

Article in One health (Amsterdam, Netherlands), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

11 authors.

Bo WenDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Zurong YangDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Shaolong RenDepartment of Epidemiology, School of Public Health, Fudan University, Shanghai, People's Republic of China.
Ting FuDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Rui LiDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Mengwei LuDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Xiaoang QinDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Ang LiDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Zhifu KouDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Zhongjun ShaoDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.
Kun LiuDepartment of Epidemiology, School of Public Health, Air Force Medical University, Xi'an, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: China is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. Methods: Newly diagnosed cases of HFRS from January 2004 to December 2019 were acquired from the China Public Health Science Data repository. We used Age-period-cohort and Bayesian Spacetime Hierarchy models to identify high-risk populations and regions in mainland China. Additionally, the Geographical Detector model was employed to quantify the determinant powers of significant driver factors to the disease. Results: A total of 199,799 cases of HFRS were reported in mainland China during 2004-2019. The incidence of HFRS declined from 1.93 per 100,000 in 2004 to 0.69 per 100,000 in 2019. The incidence demonstrated an inverted U-shaped trend with advancing age, peaking in the 50-54 age group, with higher incidences observed among individuals aged 20-74 years. Hyperendemic areas were mainly concentrated in the northeastern regions of China, while some western provinces exhibited a potential upward trend. Geographical detector model identified that the spatial variations of HFRS were significantly associated with the relative humidity (Q = 0.36), forest cover (Q = 0.26), rainfall (Q = 0.18), temperature (Q = 0.16), and the surface water resources (Q = 0.14). Conclusions: This study offered comprehensive examinations of epidemic patterns, identified high-risk areas quantitatively, and analyzed factors influencing HFRS transmission in China. The findings may contribute to the necessary implementations for the effective prevention and control of HFRS.

Indexed as

ChinaHemorrhagic fever with renal syndromeRisk factorsSpatial-temporal patterns

Identifiers

PMID38623497
PMCPMC11017347

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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.