Biosafety and Health最新文献

Beyond antibiotics: Multidimensional interventions and coordinated governance against ESKAPE resistance 抗生素之外：针对ESKAPE耐药性的多维干预和协调治理

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-03-19 DOI: 10.1016/j.bsheal.2026.03.004

Guzhen Cui , Xinxin Wang , Wei Hong , Zhenghong Chen , Yingqian Kang

{"title":"Beyond antibiotics: Multidimensional interventions and coordinated governance against ESKAPE resistance","authors":"Guzhen Cui , Xinxin Wang , Wei Hong , Zhenghong Chen , Yingqian Kang","doi":"10.1016/j.bsheal.2026.03.004","DOIUrl":"10.1016/j.bsheal.2026.03.004","url":null,"abstract":"<div><div>ESKAPE, including <em>Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa</em>, and <em>Enterobacter spp</em>. pose a significant global health threat due to their extensive drug resistance and rapid evolutionary capacity. This article advocates a paradigm shift from conventional antibiotic warfare to “ecological co-management”, integrating four innovative strategies plus an overarching framework: (1) microbiome-based interventions using probiotics, phages, and niche modulation; (2) a One Health 2.0 framework that incorporates wastewater surveillance and artificial intelligence (AI)-driven stewardship; (3) evolutionary constraint methods including anti-virulence agents and clustered regularly interspaced short palindromic repeats (CRISPR)-based targeting; (4) metabolic pathway intervention and antimetabolite therapy such as biotin biosynthesis inhibition; and (5) the establishment of a clinical translation and risk management system for innovative antimicrobial strategies. These multidimensional efforts aim to disrupt resistance transmission, restore antibiotic susceptibility, and promote sustainable pathogen control through ecological and systems-level integration.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 81-85"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147753965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of monoclonal antibody-based methods for detecting mpox virus 基于单克隆抗体的痘病毒检测方法的建立

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.bsheal.2026.01.004

Zuoyuan Du , Xingqi Wu , Li Guo , Qiao Zhang , He Huang , Lili Ren , Jianwei Wang

引用次数: 0

An improved and high-throughput mpox virus microneutralization assay 一种改进的高通量m痘病毒微量中和试验

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-01-30 DOI: 10.1016/j.bsheal.2026.01.003

Danyang Li , Zuoyuan Du , Qiao Zhang , Rui Song , Lan Chen , He Huang , Jianwei Wang , Li Guo , Lili Ren

{"title":"An improved and high-throughput mpox virus microneutralization assay","authors":"Danyang Li , Zuoyuan Du , Qiao Zhang , Rui Song , Lan Chen , He Huang , Jianwei Wang , Li Guo , Lili Ren","doi":"10.1016/j.bsheal.2026.01.003","DOIUrl":"10.1016/j.bsheal.2026.01.003","url":null,"abstract":"<div><div>Since the 2022 global mpox outbreak, the lack of specific antibodies for mpox virus (MPXV) detection has hindered precise immunoassays due to cross-reactivity among <em>Orthopoxviruses</em> (OPXVs). This study developed and characterized two monoclonal antibodies (mAbs), CML01 and CML02, targeting the MPXV A35 protein, a conserved surface antigen of extracellular virions. Cross-reactivity assessments via enzyme-linked immunosorbent assay (ELISA), western blot, and indirect immunofluorescence assays (IFA) confirmed that both mAbs bound exclusively to MPXV A35, showing no reactivity with homologous proteins from cowpox (A34), vaccinia (A33), or variola viruses (A36) despite 92.3 %–96.1 % sequence homology. IFA showed recognition of MPXV-infected cells with half-maximal effective concentrations (EC<sub>50</sub>) of 0.15 and 0.17 μg/mL, respectively. Notably, an IFA-based microneutralization assay using the mAb CML02 exhibited strong correlation (<em>r</em> = 0.93, <em>P</em> < 0.0001) with the traditional plaque reduction neutralization test (PRNT) while enabling higher throughput. Plasma from convalescent mpox patients validated the assay’s utility in testing neutralizing antibody titers. These mAbs address critical gaps in MPXV-specific immunological testing by virtue of their high specificity, which prevents cross-reactivity with other OPXVs and eliminates interference from immunity induced by smallpox vaccination. This work underscores A35 as a key epitope for MPXV-specific immunity and provides essential tools for combating the ongoing mpox threat.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 96-103"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147753967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A rapid and sensitive yellow fever virus detection method based on CRISPR/Cas13a and reverse transcription recombinase-aided amplification with special lateral-flow test strips 基于CRISPR/Cas13a和逆转录重组酶辅助特异侧流试纸扩增的快速灵敏黄热病病毒检测方法

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-03-07 DOI: 10.1016/j.bsheal.2026.03.001

Yujie Yan , Tong Wei , Xue Dong , Mengwei Niu, Yao Han, Yansong Sun , Hao Li

{"title":"A rapid and sensitive yellow fever virus detection method based on CRISPR/Cas13a and reverse transcription recombinase-aided amplification with special lateral-flow test strips","authors":"Yujie Yan , Tong Wei , Xue Dong , Mengwei Niu, Yao Han, Yansong Sun , Hao Li","doi":"10.1016/j.bsheal.2026.03.001","DOIUrl":"10.1016/j.bsheal.2026.03.001","url":null,"abstract":"<div><div>Yellow fever (YF) is an epidemic disease caused by the yellow fever virus (YFV). Historically, it has caused several epidemics and continues to result in fatalities in South Sudan and other regions today. Due to its limited therapeutic options, high mortality rate, and high transmissibility, YFV is classified as a biosafety level-3 (BSL-3) pathogen. The development of a rapid and sensitive YFV detection method is therefore important for epidemic prevention and response. Herein, we combined the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas) 13a system, reverse transcription recombinase-aided amplification (RT-RAA), and the easy-readout, sensitive enhanced lateral flow strip (ERASE LFS) to establish a new detection method for YFV. YFV ribonucleic acid and infectious YFV 17D particles were effectively detected using this approach. The RT-RAA-CRISPR-ERASE LFS (RCE) assay for YFV RNA demonstrated a detection sensitivity of 10<sup>0</sup> copies/μL with no cross-reactivity observed with five other common flaviviruses. The lyophilized RCE kit successfully detected YFV 17D in spiked human serum samples at a titer of 10<sup>2</sup> plaque-forming units (PFU)/mL. Furthermore, the optimized RCE reaction required only 35 min with a portable heat block. The RCE assay we established enabled rapid and sensitive on-site detection of YFV, holding substantial biosecurity significance for resource-limited regions with inadequate healthcare infrastructure.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 135-142"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147754249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MTB-ImmunogenKG: An LLM-assisted knowledge graph for antigen selection in tuberculosis vaccine research MTB-ImmunogenKG：一个llm辅助的结核病疫苗研究抗原选择知识图谱

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-02-04 DOI: 10.1016/j.bsheal.2026.02.001

Jielong Peng , Xinhao Zhuang , Yingying Chen , Haitong Xu , Yunjie Du , Bingdong Zhu , Guoping Zhao , Ying Wang , Yunchao Ling , Guoqing Zhang

{"title":"MTB-ImmunogenKG: An LLM-assisted knowledge graph for antigen selection in tuberculosis vaccine research","authors":"Jielong Peng , Xinhao Zhuang , Yingying Chen , Haitong Xu , Yunjie Du , Bingdong Zhu , Guoping Zhao , Ying Wang , Yunchao Ling , Guoqing Zhang","doi":"10.1016/j.bsheal.2026.02.001","DOIUrl":"10.1016/j.bsheal.2026.02.001","url":null,"abstract":"<div><div>Tuberculosis (TB) vaccine design relies on the selection of optimal antigens. However, evidence on candidate antigens is scattered across the literature and rarely linked to critical vaccine parameters, such as immune responses, antigen combinations, and adjuvants. Here, we introduce <em>Mycobacterium tuberculosis</em> (MTB)-ImmunogenKG, a provenance-linked, antigen-centric knowledge graph for MTB, that is constructed <em>via</em> an optimized information-extraction pipeline and integrated with a large language model (LLM) system to enable knowledge-augmented reasoning. From over 77,000 publications indexed in PubMed (as of July 2024), this graph consolidates 1.48 million sentence-level statements spanning 14 entity types. In practical applications, MTB-ImmunogenKG enables contradiction-aware antigen profiling for 3,154 proteins (representing about 77% of the total annotated proteins) and improves protective-efficacy prediction with a Matthews correlation coefficient (MCC) gain of 0.19 over sequence-based tools and 0.45 over an LLM-only baseline. By delivering a traceable synthesis of fragmented findings, MTB-ImmunogenKG facilitates the construction of antigen panels and the pairing of adjuvants, thereby streamlining the experimental design cycle for next-generation TB vaccines.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 143-149"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147753964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient reporting delay calibration in spatial metapopulation models for reconstructing cross-regional epidemic dynamics 用于重建跨区域流行病动态的空间元人口模型的有效报告延迟校准

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-01-22 DOI: 10.1016/j.bsheal.2026.01.002

Huichun Li, Yue Teng, Zhenghu Zu, Jingning Chen

{"title":"Efficient reporting delay calibration in spatial metapopulation models for reconstructing cross-regional epidemic dynamics","authors":"Huichun Li, Yue Teng, Zhenghu Zu, Jingning Chen","doi":"10.1016/j.bsheal.2026.01.002","DOIUrl":"10.1016/j.bsheal.2026.01.002","url":null,"abstract":"<div><div>Reconstructing the early spatiotemporal dynamics of emerging infectious diseases (EIDs) is essential for effective public health response but remains difficult due to reporting delays, heterogeneous surveillance systems, and cryptic transmission chains. This study proposes a systems-oriented computational framework that tackles these challenges through three key innovations. First, we develop a stochastic infectious disease model tailored to limited early-stage case counts, grounded in a simplified metapopulation structure that enables accurate reconstruction of initial outbreak conditions while maintaining computational efficiency comparable to existing methods. Second, we introduce a matrix-based algorithm for calibrating reporting delays in spatial metapopulation models. By leveraging matrix operations to synchronize case-report updates across multiple regions, the method eliminates the need for traditional iterative traversal, thereby achieving substantial gains in computational efficiency and improving its practical utility in engineering applications. Third, leveraging complex network theory, we develop a parameter estimation framework using open-source algorithm libraries from the Medical Research Council Centre for Global Infectious Disease Analysis (MRC GIDA), achieving more than a tenfold increase in estimation efficiency for individual cities with populations exceeding one million. Validation using both simulated networks and empirical Chinese urban mobility networks covering early coronavirus disease 2019 (COVID-19) transmission scenarios demonstrates that the proposed approach substantially improves parameter estimation efficiency while ensuring robustness and accuracy. This framework provides a powerful tool for rapid, high-fidelity reconstruction of epidemic dynamics, enabling more informed responses to future public health emergencies.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 112-123"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147753969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A landscape of epidemiology and strain distribution of Nocardia in China 中国诺卡菌流行病学及菌株分布概况

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-03-18 DOI: 10.1016/j.bsheal.2026.03.003

Ziyu Song , Bingqian Du , Deming Tang , Jiang Yao , Jirao Shen , Zhiguo Liu , Min Yuan , Wanchun Guan , Zhenjun Li

{"title":"A landscape of epidemiology and strain distribution of Nocardia in China","authors":"Ziyu Song , Bingqian Du , Deming Tang , Jiang Yao , Jirao Shen , Zhiguo Liu , Min Yuan , Wanchun Guan , Zhenjun Li","doi":"10.1016/j.bsheal.2026.03.003","DOIUrl":"10.1016/j.bsheal.2026.03.003","url":null,"abstract":"<div><div>Nocardiosis is an uncommon infection that can cause severe damage or be life-threatening. However, the epidemiology and strain distribution of nocardiosis in China remain poorly characterized. In this study, a comprehensive literature search was conducted using the keyword “(‘<em>Nocardia</em>’ OR ‘Nocardiosis’) AND (‘China’ OR ‘Chinese’)” in PubMed and Web of Science, and “(Nuokajun) OR (Nukajun)” in the China National Knowledge Infrastructure (CNKI) database. All published cases of nocardiosis between April 1, 1990, and September 13, 2024, were included. Geographic analysis identified a concentration of cases in eastern coastal China. The mean patient age was 52.6 ± 17.4 years, with a male predominance (61.0%) and the highest burden in the 50–59 age group (24.4%). The primary infection sites were the lungs (69.9%), skin (30.3%), and brain/central nervous system (CNS) (19.3%). Disseminated infections accounted for 29.0% of all cases and were associated with a markedly higher mortality rate (16.1%) compared with the overall rate (9.0%), underscoring the importance of early diagnosis and treatment. The predominant species were <em>Nocardia farcinica</em>, <em>Nocardia cyriacigeorgica,</em> and <em>Nocardia brasiliensis.</em> Most isolates remained highly susceptible to trimethoprim-sulfamethoxazole, amikacin, and linezolid. This study has established a national epidemiological pattern of <em>Nocardia</em> infections and strain distribution in China. The elevated risk and mortality associated with disseminated infections warrant vigilance. This underscores the need for heightened clinical awareness of <em>Nocardia</em> infections and ensure timely screening and treatment.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 124-134"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147754248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Shifting seasonal patterns of influenza before, during, and after the COVID-19 pandemic in Shanghai, China: A population-based surveillance study, 2015–2023 2015-2023年中国上海2019冠状病毒病大流行之前、期间和之后流感季节性模式的变化：基于人群的监测研究

IF 3

Biosafety and Health Pub Date : 2026-04-01 Epub Date: 2026-03-17 DOI: 10.1016/j.bsheal.2026.03.002

Yaxu Zheng , Yinzi Chen , Shenghua Mao , Genming Zhao , Qi Qiu , Shiying Yuan , Huilin Shi , Ruobing Han , Chenyan Jiang , Jian Chen , Huanyu Wu

{"title":"Shifting seasonal patterns of influenza before, during, and after the COVID-19 pandemic in Shanghai, China: A population-based surveillance study, 2015–2023","authors":"Yaxu Zheng , Yinzi Chen , Shenghua Mao , Genming Zhao , Qi Qiu , Shiying Yuan , Huilin Shi , Ruobing Han , Chenyan Jiang , Jian Chen , Huanyu Wu","doi":"10.1016/j.bsheal.2026.03.002","DOIUrl":"10.1016/j.bsheal.2026.03.002","url":null,"abstract":"<div><div>Seasonal influenza activity was disrupted due to the emergence of coronavirus disease 2019 (COVID-19) and the implementation of non-pharmaceutical interventions. In this study, we analyzed weekly influenza-like illness (ILI) cases and influenza positivity rate by subtype and age group from the Shanghai influenza surveillance system from 2015 to 2023. A wavelet analysis was conducted to explore the seasonal pattern of influenza. The average weekly ILI consultation rate was 20.28 ILI cases per 1,000 consultations, with 40,778 of 173,155 specimens (22.63 %) testing positive for influenza. During the COVID-19 pandemic, nearly no influenza viruses were detected until January 2021. Only B/Victoria was circulated for about eight months and peaked in January 2022, with a positivity rate of 47.48 %, which was lower than the peaks in each year before the COVID-19 pandemic. In 2023, the first epidemic, dominated by A(H1N1), began in week 8 (one month later than the 8-year average) and peaked at 76.89 %. The second epidemic, which was unusually not summer-based and driven by A(H3N2), started in week 38 and peaked in week 48 at 75.31 %, advancing the winter-spring epidemic by approximately one month. The age preference of influenza A changed during the era of normalized COVID-19 transmission. The seasonal patterns of influenza varied significantly across different stages of the COVID-19 pandemic, including differences in epidemic onset, peak timing, duration, periodicity, and dominant strains. Stability of seasonal changes in influenza requires longer-term surveillance, as well as further virologic and epidemiologic studies.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 2","pages":"Pages 104-111"},"PeriodicalIF":3.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147753968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The urban infection susceptibility index and its application in cities of China 中国城市感染易感指数及其在城市中的应用。

IF 3

Biosafety and Health Pub Date : 2026-02-01 Epub Date: 2025-11-08 DOI: 10.1016/j.bsheal.2025.11.002

Wei Yan , Jianping Huang , Xinbo Lian , Han Li , Shuoyuan Gao , Shujuan Hu

{"title":"The urban infection susceptibility index and its application in cities of China","authors":"Wei Yan , Jianping Huang , Xinbo Lian , Han Li , Shuoyuan Gao , Shujuan Hu","doi":"10.1016/j.bsheal.2025.11.002","DOIUrl":"10.1016/j.bsheal.2025.11.002","url":null,"abstract":"<div><div>Infectious diseases pose a serious threat to human health and social safety. In order to better respond to large-scale outbreaks of infectious diseases in the context of climate change, it is essential to identify potential high-risk areas in cities. However, there is currently a lack of a standardized metric or indicator for quantifying the potential risk of urban infectious diseases. The main objective of this study is to construct an urban infection susceptibility index (UISI) to identify and quantify susceptibility risk, thereby providing insights for constraining and prevent future epidemics. The UISI considers both human activities (population density, closeness index, betweenness index, life service, functional synthesis indicator, hospital accessibility) and climate-related factors (temperature, particulate matter 2.5, wind speed, humidity), and is specifically designed to analyze potential high-risk areas of urban epidemics across cities worldwide. The index integrates a wide range of factors based on the criteria importance obtained through the intercriteria correlation method, producing fine-scale susceptibility maps at the urban grid level. We apply the UISI to the coronavirus disease 2019 risk assessment in Lanzhou and Shanghai, which has been well verified. This UISI is both easy and effective to calculate across various cities, providing a scientific basis for rapid policy-making and implementation to prevent the spread of infectious diseases. Furthermore, we predict the UISI trends across different shared socioeconomic pathways (SSP), specifically SSP5-8.5 and SSP2-4.5, which demonstrate an increasing trend from 2025 to 2100.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 1","pages":"Pages 55-62"},"PeriodicalIF":3.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A semi-mechanistic modeling strategy for infectious diseases forecasting: Error correction and probabilistic prediction 传染病预测的半机械建模策略：误差修正与概率预测。

IF 3

Biosafety and Health Pub Date : 2026-02-01 Epub Date: 2025-12-18 DOI: 10.1016/j.bsheal.2025.12.002

Zihan Hao , Jiaxuan Hu , Shujuan Hu , Zhen Zhang , Donghuai Jia , Jianping Huang

{"title":"A semi-mechanistic modeling strategy for infectious diseases forecasting: Error correction and probabilistic prediction","authors":"Zihan Hao , Jiaxuan Hu , Shujuan Hu , Zhen Zhang , Donghuai Jia , Jianping Huang","doi":"10.1016/j.bsheal.2025.12.002","DOIUrl":"10.1016/j.bsheal.2025.12.002","url":null,"abstract":"<div><div>Global climate change and technological advancements have intensified the threats of pandemics, while complex transmission dynamics challenge infectious disease forecasting. Traditional compartmental models struggle to fully capture both the dynamic transmission processes and their associated uncertainties. Here, we develop a novel hybrid methodology that integrates dynamic modeling with statistical approaches, establishing a semi-mechanistic model for error correction and probabilistic prediction. Our error analysis of the dynamic model reveals that frequent population mobility compromises the accuracy of dynamic predictions and that meteorological conditions further modulate forecast performance by regulating human movement patterns. To capture these effects, we implement a quantile regression long short-term memory (QRLSTM) network to estimate prediction errors of the epidemic dynamic model based on mobility and environmental data. This hybrid approach corrects dynamic prediction errors and generates probabilistic forecasts. Validation using multi-state the United States (U.S.) coronavirus disease 2019 (COVID-19) outbreak data shows that our framework reduces dynamic prediction errors by over 50 %. Compared with pure deep learning approaches, the semi-mechanistic model significantly enhances long-term prediction performance and interpretability. By integrating mechanistic modeling with data-driven learning, the proposed approach improves the predictive accuracy and reliability of models in real-world outbreaks, thereby delivering more effective decision support for public health interventions.</div></div>","PeriodicalId":36178,"journal":{"name":"Biosafety and Health","volume":"8 1","pages":"Pages 63-70"},"PeriodicalIF":3.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147310740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0