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Background <p>The 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.</p> Methods <p>Taking 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.</p> Results <p>At 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 &gt; 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) &gt; central region (0.876) &gt; 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.</p> Conclusion <p>The 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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月27日

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

摘要

Background

The 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.

Methods

Taking 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.

Results

At 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.

Conclusion

The 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.