中国疾病预防控制中心周报最新文献

Introduction: We analyzed the spatial distribution of years lived with disability (YLDs) among patients with Kashin-Beck disease (KBD) at the county level across the country, identified hotspot regions and the primary areas of disease burden. This provides a foundation for the prevention and control of KBD and the rational allocation of healthcare resources to regions with high disease burden.

Methods: The data were obtained from the National KBD Surveillance System. Spatial autocorrelation analysis was conducted to assess spatial clustering and to identify hotspots of YLDs in patients with KBD. Geographically weighted regression (GWR) models were used to identify counties with limited economic and healthcare resources and a high burden of health losses.

Results: Spatial aggregation of YLDs among patients with KBD was observed nationwide, with hotspots concentrated in diseased counties in western China, including Shaanxi, Gansu, and Sichuan, and in the northern regions of Heilongjiang and Inner Mongolia. Among the variables, the number of health technicians was negatively correlated with the YLD rate of patients with KBD across 2 years (P<0.05). Significant geographical differences were found in the spatial distribution of YLDs, with key disease burden areas in 85 northern counties, including Heilongjiang, Jilin, and Inner Mongolia, and 145 western counties, including Shaanxi, Shanxi, and other provincial-level administrative divisions.

Conclusions: YLDs among patients with KBD at the county level in China demonstrated spatial clustering, with hotspots primarily in the western regions. Strengthening the recruitment and training of health professionals in high-burden, underserved areas may help improve the quality of life of patients.

What is already known about this topic?: A total of 117 H9N2 cases of human infection of Chinese origin had been reported to the World Health Organization (WHO) by May 9, 2025, with 22 of them originating in Hunan Province.

What is added by this report?: This article reported on the investigation of three new H9N2 avian influenza virus (AIV) infections detected in Changsha, Hunan Province, in April 2025. No epidemiological link was found among them. Exposure to live poultry was identified as the primary risk factor for infection. Sequence analysis of the three H9N2 AIVs showed a similarity of 99.71%-99.82% between hemagglutinin (HA), and the homology of the neuraminidase (NA) genes was 98.41%-99.83%. Although the tests showed that the HA had enhanced binding ability to upper respiratory tract cells' receptors, no evidence of sustained human-to-human transmission has been found so far.

What are the implications for public health practice?: This study indicated that H9N2 AIV remains a public health issue in China. We need to strengthen publicity and education efforts to inform people of the potential risk of avian influenza virus, especially to keep children away from poultry and poultry-related facilities, to effectively prevent the occurrence of avian influenza A(H9N2) infection.

What is already known about this topic?: School-aged children represent a particularly vulnerable population for influenza transmission due to their dense social interactions and limited awareness of protective measures. Since 2019, Shenzhen has provided free influenza immunizations to this demographic, with vaccination campaigns typically initiated during the autumn months.

What is added by this report?: This study utilized influenza surveillance data from Shenzhen to develop an age-stratified compartmental model for epidemiological simulations, evaluating the disease burden prevented by influenza vaccinations among school-aged children during the 2023-2024 season. Additionally, an optimization framework was developed to design strategic vaccination schedules while considering the importance of maintaining stable public health policies over time.

What are the implications for public health practice?: The findings suggest concentrating vaccination efforts during November and December; however, optimal strategies may vary depending on specific influenza transmission patterns. A more robust approach involves implementing a generalized strategy optimized using historical seasonal data with comparable transmission characteristics.

What is already known about this topic?: The H3N8 avian influenza virus (AIV) demonstrates considerable capacity for interspecies transmission and has been documented in multiple mammalian hosts, including equine and canine species. During 2022-2023, three laboratory-confirmed human infections with H3N8 were reported in China, heightening public health concerns about the zoonotic spillover potential of H3 subtype AIVs.

What is added by this report?: This study reports the isolation of a genetically reassorted, low-pathogenicity H3N8 avian influenza virus (AIV) from an islet in Niukouyu Wetland Park, Beijing Municipality - the first detection of this viral strain in a wild environment within the city. Throat swabs collected from park staff tested negative for influenza viruses. Phylogenetic analysis demonstrated that the viral hemagglutinin gene originated from the Eurasian lineage, while the neuraminidase gene was derived from the North American lineage. Although no direct evidence of human infection has been documented, multiple mutations identified in the virus's internal genes are associated with enhanced replication capacity, increased virulence, and improved adaptation to mammalian hosts. These molecular features indicate a potential risk for cross-species transmission to humans.

What are the implications for public health practice?: Given the potential threat that H3N8 AIVs pose to mammalian species, including humans, this study emphasizes the critical need to strengthen influenza surveillance networks and broaden monitoring efforts specifically targeting H3 subtype AIVs.

Introduction: Public health surveillance is crucial for decision-making. Given the significant threat of influenza to public health, developing predictive models using multichannel surveillance systems is imperative.

Methods: Data were collected from multichannel surveillance systems, including hospitals, search engines, and climatological and air pollutant surveillance systems, in a southern Chinese city from January 2023 to January 2025. Spearman's correlation analysis assessed the relationships between variables and reported influenza cases. Several machine learning models were used to predict trends in reported cases.

Results: Correlation analysis showed that all four surveillance systems were related to influenza, with 27 variables correlated with daily reported cases. The Long Short-Term Memory model, established based on variables with the highest lagged correlations (5-day to 7-day lag) through combined surveillance systems, outperformed other models for 5-day forecasts (R²=0.92; mean absolute error=156.92; mean absolute percentage error=79.95%; root Mean Squared Error=292.33).

Conclusions: Data from various surveillance systems effectively track influenza epidemics. The model shows potential for infectious disease surveillance and epidemic preparedness.

Influenza pandemics arise when novel influenza virus subtypes emerge in populations with little or no pre-existing immunity. The recent expansion of H5N1 virus circulation in mammals - including documented spread in cattle and sporadic human infections - coupled with the emergence of mutations associated with enhanced pandemic potential, underscores the persistent threat of novel influenza strains. Pandemic preparedness critically depends on developing effective vaccines capable of providing broad protection across diverse viral strains. While vaccination remains the most effective strategy for preventing influenza and its complications, pandemic vaccine development faces substantial challenges. These include the rapid mutation rates characteristic of influenza viruses, driven by error-prone RNA replication, broad host range, environmental selection pressures, and frequent genetic recombination. Such factors complicate predictions of which strain will trigger the next pandemic and hinder efforts to create universal vaccines. Recent advances in vaccine production platforms, bioinformatics, and artificial intelligence have accelerated pandemic vaccine development capabilities. Continued research is essential to enhance vaccine technology, expedite production timelines, and broaden vaccine efficacy against the full spectrum of influenza virus strains.

Introduction: Rabies remains a significant zoonotic disease in China. Following comprehensive control measures implemented since 2006, annual human cases declined steadily from 2008 through 2023. However, 2024 witnessed a 36.9% increase in cases compared with 2023, indicating possible changes in transmission dynamics or control effectiveness. This study analyzes the epidemiological characteristics and spatiotemporal patterns of rabies from 2005 to 2024 to inform targeted prevention strategies.

Methods: We employed descriptive epidemiological methods to analyze the spatiotemporal distribution and demographic characteristics of rabies cases in China. Spatial clustering was assessed using global and local Moran's I statistics (P<0.05). Retrospective space-time scan analysis (2005-2024) was performed using SaTScan software to identify significant disease clusters. We conducted spatial frequency analysis by calculating the number of years each county reported at least one case during the study period; counties reporting cases in ≥10 years were classified as high-frequency areas.

Results: Following a peak of 3,300 cases in 2007, rabies incidence declined continuously for 16 years before resurging in 2024 (167 cases, representing a 36.9% increase compared with 2023). Cases remained geographically concentrated, with 76.0% occurring in six central and southern provincial-level administrative divisions. The majority of affected counties (74%) reported only a single case. Males (70.0%), farmers (68.6%), and individuals aged 41-70 years (53.8%) comprised the highest-risk populations. Spatial analysis revealed that High-High clusters decreased in number over time. These clusters also shifted geographically: from widespread distribution across southwestern provincial-level administrative divisions (PLADs) during 2005-2014 to concentration in central agricultural zones during 2020-2024, particularly along the border regions of Henan, Hunan, Hubei, and Anhui PLADs. We identified 352 high-frequency counties. Spatiotemporal scan statistics detected seven significant clusters during 2005-2024, all located in central and southwestern regions. Outbreaks within these clusters peaked during summer and autumn months (July-November) from 2006 to 2013, with no new clusters emerging after 2014.

Conclusions: Our findings demonstrate that China's rabies control efforts have successfully transitioned the epidemic from widespread endemic transmission to sporadic occurrence with localized clustering. The 2024 resurgence occurred predominantly in historically endemic hotspots identified through spatial analysis. Sustaining these control achievements will require implementing precision prevention strategies specifically targeted at these persistent high-risk counties.

What is already known about this topic?: Dengue fever is primarily transmitted by Aedes mosquitoes. While most cases are asymptomatic or mild, some may progress to severe complications. Laboratory diagnosis relies on detection of nucleic acid, antigen, or antibodies in blood specimens.

What is added by this report?: A patient who developed dengue fever 1 day before delivery had dengue virus RNA, NS1 antigen, and IgM detected in breast milk within 10 days of symptom onset. Nucleic acid and NS1 turned negative by day 15, while IgM antibodies remained positive and turned negative by day 22, suggesting potential transmission risk via early breastfeeding.

What are the implications for public health practice?: Breastfeeding should be avoided until 22 days post-onset, after confirming clearance of viral RNA and IgM from breast milk and excluding infection in the infant. Household members of pregnant women exhibiting suspected dengue symptoms should seek immediate medical attention for dengue NS1 antigen testing during dengue season.