Evidence map›Paper›PMID 42192356›Full record

ArticleBMC public health2026

Evaluation on the efficiencies of centers for disease control and prevention in China: results from a 12-year national survey.

Yujie Yang, Mile Lin, Chongyi Wang, Zhuoyi Ji, Qing Zhu, Yueli Meng, Pei Dong, Kun Wang, Wuqi Qiu, Ayan Mao

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Yujie Yang *Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Mile Lin *Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Chongyi WangInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Zhuoyi JiInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Qing ZhuInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Yueli MengInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Pei DongInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Kun WangInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China.
Wuqi QiuInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China. qiu.wuqi@imicams.ac.cn.
Ayan MaoInstitute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100020, China. mao.ayan@imicams.ac.cn.

Funding

IMICAMS Youth Talent Development Fund 2024YT11
6 · The paper itself

Abstract

backgroundThe disease prevention and control system represents a fundamental component of public health services. Although the Chinese government has consistently prioritized and increased funding for Centers for Disease Control and Prevention (CDCs), whether these additional resources have been effectively translated into improved public health outcomes remains indeterminate. This study was designed to evaluate the operational efficiency of CDCs in China, objectively present the changes in efficiency values, and provide an evidence base for optimizing their service effectiveness.

methodsTaking the CDCs in 31 provincial-level administrative regions in mainland China as the research objects, a mixed research design was adopted, integrating longitudinal panel data (2011-2022) and provincial cross-sectional data (2022). Input indicators, output indicators, and environmental variables were all sourced from authoritative statistical yearbooks. The three-stage Data Envelopment Analysis (DEA) model was used to measure the static efficiency of different regions, and the Malmquist index model was applied to decompose the dynamic changes in Total Factor Productivity (TFP) of CDCs.

resultsAt the national level, the average annual growth rate of TFP in the CDCs was 1.3%, mainly driven by technological progress (+ 2.2% annually), but offset by a decline in technical efficiency (-0.9% annually; pure technical efficiency: -0.7%; scale efficiency: -0.2%). All 31 provinces achieved technological progress (Malmquist index > 1), while only 41.94% of provinces experienced an improvement in technical efficiency. In 2022, the average adjusted comprehensive efficiency across regions was 0.811, showing a significant regional gradient: eastern region (0.914) > central region (0.876) > western region (0.672). The average pure technical efficiency was 0.863, and the average scale efficiency was 0.927, with 61.29% of provinces exhibiting decreasing returns to scale. After excluding environmental factors, 22.58% of provinces maintained unchanged efficiency values, most provinces showed fluctuations (both increases and decreases), and the efficiency values of remote western regions slightly improved.

conclusionThe efficiency improvement of China's CDCs mainly relies on technological progress, while the continuous decline in technical efficiency reflects shortcomings in resource utilization and organizational management. Significant regional disparities in efficiency exist and are influenced by environmental factors. Future efficiency improvement should focus more on the coordination of internal management and technological application, implement differentiated scale optimization strategies, and emphasize regional quality-oriented collaboration (including technology and talent). These measures will promote the high-quality and sustainable development of the disease prevention and control system.

Indexed as

Centers for Disease Control and Prevention, U.S.Efficiency, OrganizationalChinaCross-Sectional StudiesHumansPublic Health InfrastructureSurveys and QuestionnairesUnited StatesChina centers for disease control and preventionEfficiency evaluationMalmquist indexNational surveyThree-stage DEA model

Identifiers

PMID42192356
PMCPMC13393803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.