The performance evaluation of the Centers for Disease Control and Prevention (CDC) is crucial for enhancing the quality of public health services. With the ongoing reform of the CDC system in China, the existing performance evaluation system faces challenges. This study used the Delphi method to develop a new performance evaluation system for China\'s provincial, city, and county-level CDC.
Following the \"Structure-Process-Outcome\" model, assessment indicators were systematically collected. Indicators were modified and screened through two Delphi rounds based on CDC responsibilities, health development, and national policies. Twenty-four experts provided ratings and recommendations, and the research team evaluated questionnaire reliability, expert positivity, expert authority, and opinion consistency.
The preliminary index system identified through the literature review and pre-survey included 11 primary, 30 secondary, and 64 tertiary indicators. After the first round of consultation, two secondary indicators and 11 tertiary indicators were removed and 22 tertiary indicators were added. After the second round of consultation, three secondary indicators and 11 tertiary indicators were removed and three tertiary indicators were added, at which point the p-value of the test for Kendall\'s coefficient of concordance W was < 0.001 and the coefficient of variation was within acceptable limits (< 0.25), so the consultation was concluded. The final index system included 11 primary, 25 secondary, and 67 tertiary indicators.
This study responded to the CDC system reform by developing a comprehensive performance evaluation index system for provincial, city, and county-level CDC in China. The index system is both scientifically grounded and practical, serving as an effective tool for promoting the high-quality work of CDC organizations.

This cross-sectional study assesses changes in levels of public trust in US government health agencies providing cancer information.

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The impacts of climate change on human health are a critical public health concern, with previous studies highlighting its clear effects on well-being. Understanding how state and territorial health agencies (STHAs) are addressing these emerging risks is important. This study conducted 26 in-depth interviews across the U.S. to explore the perceptions and communication strategies of STHA officials regarding climate change\'s impact on human health. Additionally, the study sought to identify the primary challenges faced by these officials to effectively communicate the impacts. Thematic analysis of the data revealed three major themes: community building and coalitions, climate denialism on social media, and misinformation about climate change and its effects on human health. These findings offer valuable insights for climate change and public health communication. The importance of the STHAs\' development of technical and informational capacity to effectively communicate climate-related risks and threats is emphasized.

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Without data, knowing how to respond to the COVID-19 pandemic would have been impossible. Data were crucial to understanding how the disease spread and which efforts successfully protected people. Yet, national agencies often did not publish their data in an optimal way, which made responding to the pandemic challenging. Therefore, learning from what went well and what did not for the future is crucial. Drawing on our first-hand experience of republishing COVID-19 data, we identify seven best practices for how to publish data in an optimal way: collect the data that are relevant; make them comparable; clearly document the data; share them frequently and promptly; publish data at a stable location; choose a reusable format; and license others to reuse the data. These best practices are straightforward, inexpensive, and achievable, with some countries already having implemented most of them during the COVID-19 pandemic. More government agencies following these best practices will enable others to access their data and address the world\'s public health challenges-including the next pandemic.

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The development of digital technology and the sharing economy has extended corporations\' innovative activities beyond the corporation\'s boundaries, so it has become more urgent to govern the lack of social responsibility and alienation of platform corporations from the perspective of social agents. First, the platform\'s CSR classification and social responsibility governance\'s main content are analyzed in this research. Then, this study uses government agencies, platform corporations, users, and the public as governance subjects and compares governance decisions with and without public and user oversight. Finally, the optimal balance strategy for each governing subject, the optimal trajectory of governance volume, and the trajectory of total revenue are obtained. The study found that: 1) Public and user supervision can improve the governance volume while encourage the governance motivation of government agencies and platform corporations. 2) The level of user supervision effort has a greater impact on the total governance revenue than public supervision. 3) The revenue of the system and the governance volume are greater in a centralized decision-making process, indicating that those involved should co-operate in governance based on the principle of mutual benefit. 4) The platform corporation has an incompatible but unified relationship between its social duty and financial success.

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In 2022, the Pentagon Force Protection Agency found threat agnostic detection of novel bioaerosol threats to be \"not feasible for daily operations\" due to the cost of reagents used for metagenomics, cost of sequencing instruments, and cost of labor for subject matter experts to analyze bioinformatics. Similar operational difficulties might extend to many of the 280,000 buildings (totaling 2.3 billion square feet) at 5,000 secure US Department of Defense military sites, 250 Navy ships, as well as many civilian buildings. These economic barriers can still be addressed in a threat agnostic manner by dynamically pooling samples from dry filter units, called spike-triggered virtualization, whereby pooling and sequencing depth are automatically modulated based on novel biothreats in the sequencing output. By running at a high average pooling factor, the daily and annual cost per dry filter unit can be reduced by 10 to 100 times depending on the chosen trigger thresholds. Artificial intelligence can further enhance the sensitivity of spike-triggered virtualization. The risk of infection during the 12- to 24-hour window between a bioaerosol incident and its detection remains, but in some cases it can be reduced by 80% or more with high-speed indoor air cleaning exceeding 12 air changes per hour, which is similar to the rate of air cleaning in passenger airplanes in flight. That level of air changes per hour or higher is likely to be cost-prohibitive using central heating ventilation and air conditioning systems, but it can be achieved economically by using portable air filtration in rooms with typical ceiling heights (less than 10 feet) for a cost of approximately $0.50 to $1 per square foot for do-it-yourself units and $2 to $5 per square foot for high-efficiency particulate air filters.