Evidence map›Paper›PMID 40672920›Full record

ArticleFrontiers in public health2025

Spatial analysis and prediction of psittacosis in Zhejiang Province, China, 2019-2024.

Zheyuan Ding, Haocheng Wu, Chen Wu, Kui Liu, Qinbao Lu, Xinyi Wang, Tianying Fu, Junjie Li, Ke Yang, Queping Song and 1 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Zheyuan DingZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Haocheng WuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Chen WuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Kui LiuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Qinbao LuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Xinyi WangZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Tianying FuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Junjie LiZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Ke YangZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Queping SongHangzhou Medical College, Hangzhou, Zhejiang, China.
Junfen LinZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The emergence of advanced diagnostic techniques and improved disease surveillance have led to increased recognition of psittacosis cases in recent years. This study aimed to characterize the epidemiological patterns and spatiotemporal distribution of psittacosis in Zhejiang Province, China, and to identify high-risk clusters through predictive modeling. Methods: We conducted a comprehensive analysis of reported psittacosis cases in Zhejiang Province from January 2019 to June 2024. Demographic characteristics and seasonal trends were systematically analyzed. Spatial epidemiological methods, including spatiotemporal distribution mapping, spatial autocorrelation analysis, and Kriging interpolation, were employed to identify disease hotspots and predict risk areas. Results: During the study period, 315 psittacosis cases were reported, with an annual average incidence rate of 0.0914 per 100,000 population, showing a significant increasing trend. The geographic distribution of cases expanded over time. More cases were reported in winter. Cases demonstrated a male predominance (sex ratio 1.1:1) with a median age of 64 years. Occupational analysis revealed farmers as the most affected group (52.4%). Spatial analysis identified significant clustering ( Conclusions: Our findings demonstrate a concerning upward trend in psittacosis incidence with expanding geographic distribution in Zhejiang Province. The identification of high-risk clusters in western, central, and northern regions provides critical evidence for targeted public health interventions, including enhanced surveillance in agricultural communities and seasonal prevention campaigns during winter months.

Indexed as

PsittacosisSpatial AnalysisAdolescentAdultAgedChildChinaFemaleHumansIncidenceMaleMiddle AgedRisk FactorsSeasonsepidemiological characteristicsKriging interpolationprediction mappsittacosisspatial analysis

Identifiers

PMID40672920
PMCPMC12263594

What OpenQuestion holds

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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.