Quantitative evaluation of China’s public health emergencies response policies: a PMC index model approach

The study demonstrates was generally good. However, significant variability was observed in the scores of individual indicators across different policies. These findings provide valuable insights into the strengths and weaknesses of PHERPs and offer a reference for optimizing policy design and implementation.

Authors

Institutions

Publication Details

Journal
BMC Public Health
Published
2025-01-22
DOI
https://doi.org/10.1186/s12889-024-21180-7
Citations
12
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
50.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative evaluation of China’s public health emergencies response policies: a PMC index model approach

Liu Yong-wen, Anning Ma, Yan Wang, Min Jiao
12 citations
BMC Public Health
Disaster Management and Resilience
50.42
article

Quantitative evaluation of China’s public health emergencies response policies: a PMC index model approach

Liu Yong-wen, Anning Ma, Yan Wang, Min Jiao
article en
12 citations

Abstract

The study demonstrates was generally good. However, significant variability was observed in the scores of individual indicators across different policies. These findings provide valuable insights into the strengths and weaknesses of PHERPs and offer a reference for optimizing policy design and implementation.

BMC Public HealthVol. 25(1)
Weifang Medical University (CN)
Openalex Percentile: Top 0%
Disaster Management and Resilience
50.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.