Accurate short-term influenza forecasting is important for early warning and public health preparedness, but routine sentinel surveillance may be delayed and may not fully capture behavioural and environmental signals related to influenza activity. This study aimed to develop and evaluate multi-source machine-learning models for short-term influenza forecasting in Hunan Province, China. Weekly influenza-like illness plus (ILI+) data from 54 sentinel hospitals across 14 prefecture-level cities in Hunan Province were used to characterise influenza activity from 2015 to 2024. For forecasting during 2020–2024, ILI+ data were integrated with Baidu Search Index indicators, meteorological variables and air quality index data. ILI + was calculated as the product of the weekly ILI proportion and weekly influenza virus test positivity rate. Five models, including LSTM, GRU, stacked autoencoder, random forest and LightGBM, were compared for 1–3-week-ahead forecasting under four feature settings. Performance was evaluated using RMSE, MAE, MAPE, SMAPE and R², with SeasonalNaive52 as the baseline comparator. Influenza activity showed pronounced winter–spring seasonality with substantial interannual and city-level heterogeneity. At the provincial level, the all-features RF model achieved the lowest absolute errors among the machine-learning models (RMSE = 0.00882, MAE = 0.00389) and an out-of-sample R² of 0.723. Compared with the SeasonalNaive52 baseline, the machine-learning models showed lower RMSE, MAE and SMAPE and higher out-of-sample R². In city-level analyses, RF ranked highest in 11 of 14 cities based on the descriptive summary score, whereas GRU ranked highest in Yueyang, Zhangjiajie and Hengyang, indicating that model suitability may vary across local epidemic settings. We developed a city-level multi-source framework for short-term influenza forecasting in Hunan Province by integrating surveillance, Baidu Search Index, meteorological and air-quality data. Multi-source predictors improved forecasting beyond a seasonal naive baseline, with RF providing a robust option for reducing absolute weekly errors. City-level performance differences highlight the need for local validation before operational deployment. With prospective validation, this framework could support 1–2-week-ahead early warning and targeted influenza preparedness.

[This corrects the article DOI: 10.3389/fpubh.2025.1614339.].

Pertussis remains a global threat for infants, and recent increases in notifications have renewed interest in optimising vaccination strategies and improving vaccines. At the biological level, the rationale for maternal pertussis immunization extends beyond passive antibody transfer alone and may also involve broader maternal-infant immune interactions; however, at the population level these mechanisms are operationalized through policy adoption, timing recommendations, and coverage. We compared incidence constructs from WHO routine notifications and Global Burden of Disease (GBD) modelled estimates and assessed how associations with vaccination policy indicators change across outcome definitions. Trends were characterised with Joinpoint regression; policy associations were estimated using Bayesian hierarchical models fitted separately to each dataset with Universal Health Coverage stratified random intercepts. Incidence levels and trends differed markedly between WHO and GBD. Unadjusted analyses showed heterogeneous, sometimes opposing, associations for maternal immunization and schedule timing. After adjustment, most schedule parameters were small and imprecise, whereas DTP3 coverage remained strongly inversely associated with incidence in GBD but not in WHO. Surveillance and modelled estimates should not be interpreted interchangeably; harmonized constructs and routine implementation and ascertainment metadata are needed for robust cross-country inference.

Urban wastewater systems connect hospitals, residential communities, transport hubs, and wastewater treatment plants, creating opportunities for the dissemination of microorganisms and antibiotic resistance genes (ARGs). Here, we conduct a three-month, citywide metagenomic survey of wastewater in Xiamen, China, comprising 252 samples from seven hospital sites (n = 16), 27 residential sites (n = 55), 16 wastewater treatment plant sites (n = 159), and individual international flights (n = 22). Genome-resolved analyses reveal source-specific microbial community structures, resistome profiles, lineage-sharing patterns, and associations between ARGs and mobile genetic elements across wastewater sources. Hospital wastewater harbors the most diverse resistome, while international flight wastewater introduces microbial taxa and ARGs absent from local wastewater networks. Wastewater treatment plants accumulate ARGs from multiple upstream sources, exhibiting frequent lineage sharing and signals of potential horizontal gene transfer. Compared with within-environment sharing, cross-environment lineage sharing is associated with lower nucleotide diversity, consistent with possible genetic bottlenecks. Among potential correlates, pH shows strong non-linear associations with microbial diversity and resistome composition. These findings indicate that urban wastewater systems function as interconnected networks for microbial and ARG dissemination and identify potential hotspots for targeted antimicrobial resistance surveillance.

Abstract In 2026, a Bundibugyo ebolavirus (BDBV) outbreak emerged in the Democratic Republic of the Congo (DRC), with 4,566 confirmed cases and 2,128 deaths reported as of 11 August, potentially becoming the largest Ebola outbreak on record globally. We developed a susceptible-exposed-infectious-deceased-recovered (SEIDR) model incorporating incorporating three categories of interventions—public self-protection, safe burial, and treatment and convalescence—to assess early transmission dynamics, the current epidemic trajectory, and cross-border spillover risk, and to inform the formulation of control strategies. Based on cumulative confirmed case data up to 31 July, sensitivity analyses across multiple candidate start dates identified 28 March as the optimal start date of sustained transmission, with 31 March to 3 April as the most likely onset window. As of 31 July, the basic reproduction number (ℛ 0 ) was 1.83 (95% CI: 1.81–1.84). When 58.12% of the susceptible population adopted protective behaviours, the transmission chain could be effectively interrupted. By integrating the non-dominated sorting genetic algorithm II (NSGA-II) with Pontryagin’s minimum principle (PMP), we derived a time-varying optimal control strategy, with adjustments every two weeks, that could shorten the epidemic duration by approximately 7 months. Using International Migrant Stock data and Facebook IP-based mobility data with the Prophet forecasting model, we assessed spillover risk. Four countries were identified as very high risk at the end of July. Compared with the status quo scenario, the optimised control strategy could substantially reduce global importation risk. Enhanced entry screening and preparedness are warranted in neighbouring countries of the DRC in Africa, France in Europe, and Canada in North America.

As natural hosts of avian influenza viruses, wild birds pose an increasing threat to public health. Here, using surveillance data from wild bird infections across the United States (2022-2025), we show that HPAI-H5 transmission exhibits strong interspecific variation, seasonality, and spatial heterogeneity linked to migratory flyways. Phylogeographic analysis reveals that viral genotypes evolve from early, limited transmission along single migratory routes to a nationwide dispersal pattern spanning multiple migratory flyways. Anseriformes exhibits the highest number of infections but the lowest transmission risk, whereas Strigiformes demonstrates the greatest transmission risk. The HPAI-H5 transmission in wild birds along migratory flyways exhibits significant spatial heterogeneity and is associated with bird migration. Meteorological conditions are correlated with outbreak timing and may inform early warning efforts; however, these relationships are nonlinear. These findings provide a foundation for risk assessment, early warning systems, and integrated management of avian influenza in wild bird populations.

Between 2022 and 2025, nearly 130,000 confirmed monkeypox (mpox) cases, including over 280 deaths, were reported to the World Health Organization (WHO) from 130 countries and territories, prompting the WHO to declare it a public health emergency of international concern on two occasions. Hence, to enable a scientific approach to prevention and control, transmission dynamics through mathematical modeling must be elucidated. Through a comprehensive literature review on the modeling of mpox transmission dynamics, this study indicates that existing research primarily extends the susceptible-infectious-recovered (SIR) modeling framework and largely focuses on the 2022 global outbreak. The analysis revealed significant variations in mpox virulence, particularly dependent on the subtypes, and variations according to the descending order of clades: Ib>Ia>IIa>IIb. Interpersonal transmission capacity was notably higher for clade II than for clade I, highlighting geographical disparities, with the highest transmission capacity in the Americas, moderate in Europe and Oceania, and the lowest in Asia. In contrast, Africa maintained consistently low but non-declining transmission levels. Furthermore, the study confirmed significant co-infection patterns between mpox and sexually transmitted diseases, such as Human Immunodeficiency Virus (HIV) and syphilis, along with evidence of synergistic transmission interactions among multiple pathogens. This study provides crucial modeling evidence for mpox regulation. By quantifying high-risk populations, evaluating intervention effectiveness, and identifying the risks associated with subtypes and geographic areas, this study offers a comprehensive reference for understanding the interface between model complexity and practical application. These advancements have enhanced the strategic focus and precision of public health responses during outbreaks.

Abstract Against the backdrop of global climate change and accelerating population mobility in 2025, chikungunya fever (CHIKF) exhibited a trend of worldwide spread, significantly increasing the difficulty of controlling tropical mosquito-borne diseases. To enhance the precision of intervention strategies, this study developed an age- and sex-structured human–mosquito interaction dynamic model based on data from the largest CHIKF outbreak ever recorded in China, and conducted a targeted analysis of prevention and control strategies. By decomposing the basic reproduction number and examining population heterogeneity, asymptomatic males aged 15–59 years were identified as the core transmission group. Optimal control analysis revealed that the synergistic implementation of three measures— reducing the effective human-to-mosquito transmission rate, reducing the effective mosquito-to-human transmission rate, and suppressing mosquito population density—could reduce the overall infection rate by 95.7586%. Among these, mosquito population suppression should be prioritized as a universal core strategy; however, its protective effect on females aged 60 years and above was relatively weak, warranting particular attention. The study further demonstrated that asymmetric intensity combinations targeting these three intervention pathways—such as intensity profiles of “10%, 90%, 90%” or “60%, 80%, 90%”—could achieve effective outbreak control. This research elucidates population-specific transmission patterns and key pathways for intervention intensity, providing a theoretical and strategic foundation for the precise control of mosquito-borne diseases. It also provides actionable operational insights to support rapid response and strategy optimization for future emerging outbreaks. Author summary CHIKF is a mosquito-borne viral disease that is gradually spreading from tropical regions to other areas. To achieve more precise control of this disease, we developed an age- and sex-structured analytical model based on the largest CHIKF outbreak in China, aiming to provide a scientific basis for responding to potential future outbreaks with inherent uncertainties. The study found that asymptomatic males aged 15–59 years were the primary drivers of transmission and should be prioritized as a key population for reducing viral spread in prevention efforts. When evaluating the effectiveness of different intervention strategies, females aged 60 years and above were the least affected by the implemented measures, indicating that this group should strengthen personal protection to lower their infection risk. Among all control measures, mosquito suppression was the most effective, suggesting that vector control strategies should be prioritized in future outbreak responses.

Background The largest documented chikungunya fever (CF) outbreak in China occurred in Foshan, yet evidence on outbreak-wide epidemiological characteristics and intervention-associated effects has remained limited. Methods We conducted a longitudinal analysis from 16 June to 10 August 2025, integrating case and vector epidemiology, and generalised estimating equation (GEE) models. Results A total of 8,964 cases were reported, with no deaths. Females had a higher incidence than males (1,027.12 vs 919.71 per 100,000), and males had lower infection odds (OR 0.89, 95% CI = 0.86–0.93). Adults older than 60 years showed the highest incidence (2371.62 vs. <1402.00 per 100,000) and infection risk (OR < 1 in other age groups). Cases were concentrated in Shunde District (82.42%). The onset-to-diagnosis interval shortened after interventions. 2.60% were asymptomatic; fever, rash and arthralgia were the predominant symptoms. The effective reproduction number (\(\:{R}_{t}\)) rose rapidly (3.12, 95% CI = 0.08–11.51) and declined below 1 by 1 August (0.87, 95% CI = 0.80–0.94). Breteau index (BI) and adult mosquito density Index (ADI) were decreased and high in the border areas between districts. For non-lagged GEE, one-unit changes in ADI and BI were associated with 9.28% (95% CI= -13.40–37.92; P = 0.45) and 0.60% (95% CI =-1.48–2.73; p = 0.57) changes in case numbers. One-unit changes in ADI were associated with a 10.73% change in \(\:{R}_{t}\) (95% CI = 3.23–18.78; p = 0.004), and 7.50% in BI (95% CI =-5.15–21.84; p = 0.26). For lagged GEE, lagged ADI remained associated with \(\:{R}_{t}\) (8.74%, 95% CI = 1.14–16.91; p = 0.023), while lagged tOD showed no significant association with case numbers (2.68%, 95% =CI -8.21 to 14.86; p = 0.64) and \(\:{R}_{t}\) (2.17%, 95% CI= -1.70 to 6.20; p = 0.28). Conclusions This outbreak showed high transmissibility, concentration in Shunde, and elevated risk in females and older adults. The key area for vector control was the border of different districts. Prioritising routine and targeted adult-mosquito surveillance and control, while maintaining larval source management and accelerating case detection, not only for this outbreak but also for other non-endemic urban settings facing comparable arboviral threats.

To investigate the transmission dynamics of respiratory multi-pathogen co-infection, this study developed a dual-pathogen co-infection transmission dynamics model comprising 10 compartments, incorporating an exponentially decaying time-varying effective transmission rate. The model was systematically calibrated and validated using epidemiological surveillance data from a major Chinese metropolis—Wuhan—covering approximately 2.72 million cases between January 1, 2023 and January 1, 2025. The analysis focused on the 13 most common pathogen combinations, which accounted for the top 1% of infection cases. Results revealed three distinct winter-centered epidemic peaks in Wuhan over the two-year period. Co-infection cases were most frequently observed as virus–bacteria and virus–other pathogen combinations. Analysis of the major co-infection combinations showed that the mean basic reproduction number of the system ranged between 1.19 and 1.88, while the median ranged from 1.08 to 1.35. Transmission peaks in each combination were primarily driven by the most transmissible pathogen within the pair. Transmission route analysis further indicated that when individuals were infected with multiple pathogens, sequential secondary infection was the dominant pattern, whereas direct simultaneous co-infection occurred at a relatively low proportion. This study suggests that respiratory pathogens continue to exhibit sustained transmission potential. The findings provide an important evidence based reference for designing risk oriented, precision prevention and control strategies in the future.

What is already known about this topic?:Given the proportion of undiagnosed human immunodeficiency virus (HIV) cases and regional disparities in Fujian Province, achieving the 2030 targets to end acquired immunodeficiency syndrome (AIDS) remains uncertain. What is added by this report?:HIV transmission in Fujian has stabilized through treatment and viral suppression, achieving the "95-95-95" targets; however, a diagnostic gap persists (86.30%). Transmissibility recently increased (R eff =1.03), with males and adults aged 20-70 years as the primary high-risk populations, threatening elimination goals. What are the implications for public health practice?:Improving diagnostic coverage is essential for epidemic elimination. Targeted screening and self-testing must be intensified among key populations, particularly middle-aged and older adults, while maintaining treatment achievements to prevent resurgence.

Background:Recently, surges in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfections in China have raised public concern. We investigated the epidemiological features and risk factors for SARS-CoV-2 reinfection in China. Methods:A retrospective cohort study was conducted in Xiamen, China (2021-2023) with two subcohorts: Delta-Omicron (cohort 1) and Omicron-Omicron (cohort 2). Descriptive analysis and ensemble modeling were employed to evaluate reinfections. Results:A total of 327 cases without fatalities were included. Reinfections accounted for 14.68% of cases, with 22.51% in cohort 1 and 3.68% in cohort 2. Compared with primary infections (PIs) (99.69% symptomatic, 56.54% hospitalized), reinfections were less severe, with fewer symptomatic instances (47.92%) and hospitalizations (4.65%). The majority of reinfections (83.33%) occurred following the relaxation of strict public health and social measures. The median time interval between PI and reinfection was longer for cohort 1 (462 days) than for cohort 2 (280 days). Reinfection risks were noted among lesser developed regions, those without persistent PI, those with primary Delta variant infection, government and hospital workers, and unvaccinated individuals. Conclusions:SARS-CoV-2 reinfections are generally less severe and are influenced by the relaxation of control measures, viral evolution, and changing patterns of population immunity and contact; this underscores the need for ongoing surveillance and targeted public health strategies to manage future infection waves.

OBJECTIVES:The mpox outbreak in Beijing's Chaoyang District after late May 2023, this study aims to evaluate the epidemiological characteristics and environmental contamination of this outbreak. METHODS:A field investigation was conducted to evaluate the epidemiological characteristics of mpox cases and their living environments in Chaoyang District, Beijing, between May 2023 and May 2024. Laboratory testing, epidemiological description, and statistical analysis were conducted subsequently. RESULTS:The outbreak resulted in 43 non-fatal cases, 97.67 % were Men who have Sex with Men (MSM) and symptomatic, tracking a peak in August 2023 and declining thereafter. Travel history was reported in 27.91 % (12 of 43), and coinfections with both HIV and syphilis were among 16.28 % of mpox cases. MPXV-positive rates were 97.67 % for rash swabs, 55.81 % for throat swabs, and 59.38 % for environmental samples. Median cycle threshold (Ct) values were 20.45 (IQR: 4.57) for rash swabs, 31.59 (IQR: 5.64) for throat swabs, and 33.33 (IQR: 4.37) for environmental samples. Contact tracing revealed a 9.09 % prevalence among close contacts and a secondary attack rate of 10.26 %. High environmental contamination was found in bedrooms and items such as electronics and cups. CONCLUSIONS:The mpox outbreak in Beijing's Chaoyang District predominantly affected MSM, that transmitted through diverse transmission routes. Environmental contamination in long-lived rooms or used items highlights the importance of targeted hygiene measures.

Objective:China faces significant challenges in ending tuberculosis (TB). Active case finding (ACF) and TB preventive therapy (TPT) have proven to be critical measures in reducing TB incidence. This study uses a transmission dynamics model to identify the optimal intervention strategies for achieving WHO's TB elimination targets in Shangrao City. The findings guide targeted TB control efforts in similar settings. Methods:To account for COVID-19 pandemic disruptions, we first used a seasonal autoregressive integrated moving average (SARIMA) model to predict and substitute the reported TB incidence during 2020-2023. Subsequently, we developed an age-stratified dynamic transmission model using surveillance data from Shangrao City's Infectious Diseases Reporting System (IDRS) between 2008 and 2023 to evaluate tuberculosis transmission patterns across age groups. The model assessed the effectiveness of key interventions including active case finding (ACF), latent tuberculosis infection (LTBI) screening, and tuberculosis preventive treatment (TPT). Results:The model fit well with the reported data (R2 = 0.53, p < 0.001). Preventive treatment measures can fully achieve the goal of reducing incidence. All five TPT regimens showed potential to meet the TB elimination targets, with the 3HP regimen (weekly rifapentine + isoniazid for 3 months) performing the best. With the proportion of post-detection consent to TPT of 0.6 and rate of LTBI screening of 0.5, the 3HP regimen met the 2030 and 2035 incidence targets, with projected rates of 15.27/100,000 and 7.98/100,000, respectively. Conclusion:The current TB control efforts face significant challenges, with a considerable gap remaining in achieving TB elimination targets. Combining ACF with TPT presents a promising strategy to reach these goals. Older tuberculosis (TB) patients constitute a high-risk population, and effective prevention and treatment in this group are critical to achieving future TB elimination goals. To reduce the risk of recurrence and reinfection, enhanced follow-up monitoring of older patients should be prioritised alongside targeted health education interventions tailored to high-risk groups.

Objectives: Mycoplasma pneumoniae (MP) is a key cause of community-acquired pneumonia, and coinfections lead to varied patient outcomes. A comprehensive understanding of the outcome characteristics and associated etiologies of coinfections in MP patients is lacking. Methods and results: We analyzed 121,357 MP cases from 522,292,680 visits in Wuhan, China, in 2023 (the final year of the COVID-19 pandemic). Children aged 1–10 years had the highest incidence, whereas those over 60 years had elevated hospitalization, severe infection, and fatality rates. Coinfection patterns differed by age, with bacterial-viral-Chlamydia pneumoniae (C. pneumoniae) / other pathogens prevalent in infants, bacterial-viral pathogens prevalent in preschoolers, and viral-viral pathogens prevalent in school-aged children. Bacterial coinfections were most common in MP-infected patients, especially those who were hospitalized. Coinfection, especially with C. pneumoniae, Pseudomonas aeruginosa (P. aeruginosa), Haemophilus influenzae (H. influenzae), and Streptococcus pneumoniae (S. pneumoniae), increased hospitalization rates. The most severe outcomes and deaths occurred in patients coinfected with C. pneumoniae-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A-parainfluenza virus (PIV) or adenovirus-PIV. Logistic regression analysis demonstrated that male sex and adult age (particularly ≥40 years) were significantly associated with adverse outcomes in MP monoinfection. For coinfections, significantly higher hospitalization rates were reported among very young children (0–5 years) and adults aged ≥40 years, whereas adults presented an increased risk of severe disease. Coinfection outcomes were significantly associated with seasons of the year (winter, spring, and summer), specific age groups (3–5 years, 18–39 years, 40–50 years, and 60 years and over), gender (male), and longer onset-to-diagnosis periods. Middle-aged and elderly patients, coinfection, spring and summer, gender (male), and longer onset-to-diagnosis periods were significantly associated with increased hospitalization and serious illness risk. Coinfection, winter, older (adult) age, and gender (male) were significantly associated with an increased risk of death. Conclusions: Compared with adults, children with MP have a greater morbidity risk, whereas middle-aged and older adults face greater risks of hospitalization, serious illness, and death. Coinfection with other pathogens heightens hospitalization and death risks. These insights are crucial for etiological screening, diagnosing multiple pathogens, and preventing and treating infections.

Recently, the epidemiological profile of avian influenza has changed dramatically worldwide. Avian influenza sampling and surveillance of wholesale and retail markets in Nanchang, the largest city in the southwestern region of Poyang Lake, have been conducted since 2017. The transmission pattern of avian influenza in this region was comprehensively evaluated in multiple dimensions including time, subtype changes, seasonality and meteorological factors. Samples were tested for avian influenza A virus nucleic acids using real-time reverse transcription polymerase chain reaction, and positive results were typed. Wavelet coherence analysis was used to reveal the time-frequency variation in meteorological factors associated with avian influenza. The random forest algorithm was used to perform a multifactorial analysis of meteorological factors. Results revealed that the highest avian influenza positivity rate of 42.29 % (95 % CI: 41.18-43.41) occurred in summer. Meteorological factors were found to be significantly associated with the avian influenza positivity rate on a periodic basis. Random forest analysis revealed significant heterogeneity between meteorological factors and changes in the positivity rates of different avian influenza subtypes. Pollution concentration significantly affected the positivity rate of different avian influenza subtypes. The effect of temperature on the positivity rate of the H5 and H9 subtypes followed the opposite pattern to that of the non-H5/H7/H9 positivity rate. In winter, positivity rates of the H5 and H9 subtypes were lower and those of the non-H5/H7/H9 samples were higher; the opposite was true in spring. There is a correlation between pollutant concentration and avian influenza positivity rate. Authorities should consider climatic conditions and the level of contaminants in the prevention and control of avian influenza and adopt different preventive and control measures according to the characteristics of the different subtypes. We recommend continued surveillance of avian influenza in the region and the adoption of a 'one-health' approach for integrated prevention and control.

Despite the high coverage of childhood vaccination, pertussis remains a significant global health challenge, with increasing adult cases attributed to waning immunity and enhanced diagnostic capability. This study quantified the global burden of pertussis in adults from 1990 to 2021 and evaluated the impact of the COVID-19 pandemic on disease trends. Using data from the Global Burden of Disease Study 2021, we assessed pertussis incidence and disability-adjusted life years (DALYs) in adults, stratified by age, sex, sociodemographic factors, and geographic regions. Temporal trends were analysed using joinpoint regression to detect significant changes and calculate the average annual percentage change (AAPC). An exponential smoothing state-space model with hierarchical forecast reconciliation was used to estimate the impact of the COVID-19 pandemic on pertussis burden. Globally, the incidence rate of adult pertussis declined from 17.44 per 100,000 population in 1990 to 9.00 per 100,000 in 2019, and fell sharply to 2.70 per 100,000 by 2021. DALYs rates followed a similar trend. The burden was consistently highest in low Socio-demographic Index (SDI) countries, where the 2019 incidence rate was over four times that of high SDI countries (18.59 vs. 3.96 per 100,000). Between 1990 and 2019, incidence numbers increased in low SDI countries [AAPC: 0.63%; 95% confidence interval: 0.36%, 0.91%] and in older adults (AAPC > 0), despite falling incidence rates. From 2009 to 2019, incidence rates increased in 84 countries. During the COVID-19 pandemic, estimates based on the model indicated a 58.41% reduction in incidence and a 50.34% decrease in DALYs. Although the global incidence of adult pertussis has declined over the past three decades, a resurgence from 2009 to 2019, particularly in low-income regions and specific age groups, underscores the persistent challenges. The sharp decline during the COVID-19 pandemic highlights the importance of public health and social measures. These findings emphasise the need for targeted vaccination strategies and sustained surveillance to address regional disparities and prevent the resurgence of the disease.

The overused quinolone antibiotics in animal husbandry and clinical medicine pose a growing threat for global health as they enter ecosystem via agricultural discharge and medical wastewater. Consequently, risk assessment for environmental and human exposure is highly demanded, which calls for an accurate, reliable and rapid qualitative and quantitative analysis of trace antibiotics in different matrices. Surface-enhanced Raman spectroscopy (SERS), providing fingerprint chemical information with near-single-molecule sensitivity, has received considerable attention. Herein, considering the common physicochemical properties of various quinolone antibiotics, we first developed sample pretreatment strategy consisting of solid-phase extraction (SPE), liquid-liquid extraction (LLE), salting-out assisted liquid-liquid extraction (SALLE), and NPs purification (NPs (p)). The modular SPE-LLE-SALLE-NPs (p) coupling with spectral separate network (SSNet) (a deep-learning based spectral unmixing algorithm) enabled a rapid (<8 min per sample), sensitive (μg L-1), on-site, and intelligent SERS analysis of 19 quinolone antibiotics in food, biological, and environmental matrices. Besides, the identification of each QN in a five-target mixture sample enabled SPE-LLE-SALLE-NPs (p)-SSNet-SERS to be a highly promising rapid detection strategy in blind sample screening qualitatively and quantitatively. The integrated SPE-LLE-SALLE-NPs (p)-SSNet-SERS offers a cross-media, full-process, and big data-enhanced rapid monitoring solution for antibiotic pollution within the "source-pathway-sink" framework.

[This corrects the article DOI: 10.1016/j.heliyon.2024.e32164.].

Following the onset of an index chikungunya case on July 8, 2025, a significant outbreak occurred in Foshan, Guangdong Province, China. This study aimed to quantify the outbreak's transmissibility between June 16 and July 21, 2025. Data were obtained from local Government, Statistics Bureau, Centers for Disease Control and Prevention, and the relevant literature. We employed a transmission dynamic model that integrated human host-vector transmission to estimate the basic reproduction number ( R_0 ). The key parameters of the model were calibrated using early-phase limited surveillance data on the cumulative number of cases. We calculated the correlation coefficient to evaluate the accuracy of this calibration. Sensitivity analyses were conducted to quantify the uncertainties in the parameter inputs. Between June 16 and July 31, 2025, cumulative cases reached 2658, with 92.96 R_0 of this outbreak was 7.2807 [interquntile range (IQR): 7.2809‒7.2811], suggesting sustained transmission. Human-to-mosquito transmission (Median: 22.79, IQR: 5.44‒40.14) had a higher median R_0 than mosquito-to-human transmission (Median: 2.33, IQR:0.58‒4.07) (Mann–Whitney U P < 0.001). Symptomatic infections (Median: 19.60, IQR: 4.68‒34.52) had a higher median R_0 than asymptomatic infections (Median: 3.19, IQR: 0.76‒5.62) (Mann–Whitney U P < 0.001). The model simulated cumulative cases were sensitive to parameters a , b , ω_m , and ω_p . The overall R_0 and mosquito-to-human R_0 were sensitive to parameters a and b . The human-to-mosquito and symptomatic human-to-mosquito R_0 were sensitive to parameter γ , while asymptomatic human-to-mosquito R_0 was sensitive to parameter ω_p'. The transmissibility of CHIKV is high. Human-to-mosquito transmission, especially symptomatic infections to mosquito transmission, was the main driver of chikungunya virus transmission. These findings underscore the critical need for enhanced screening of travellers from endemic regions, timely case isolation, and targeted vector control to mitigate autochthonous transmission.