Interactions among zoonotic pathogens play a critical role in shaping disease transmission, severity, and public health responses. However, the mechanisms and population-level consequences of these interactions remain underexplored in current modelling frameworks. This review aims to synthesize emerging evidence and address key scientific challenges in understanding how pathogen interactions influence transmission dynamics and mathematical modelling, with a focus on zoonotic and other cocirculating pathogens. In this review, we synthesize current evidence on synergistic, antagonistic, and neutral interactions between zoonotic and other cocirculating pathogens. We explore the underlying mechanisms of these interactions, such as transmission enhancement, immune modulation, and resource competition, at both the individual and population levels. We further review mathematical models to illustrate how these interaction features, such as transmission pathways, coinfection histories, cross-immunity, and superspreading potential, could be incorporated into epidemiological frameworks to increase our understanding of the community transmission of infections. Particular attention is given to the challenges of parameter estimation, incomplete surveillance data, and the difficulty of modelling interactions across scales and pathogen types. Understanding and modelling these interactions is essential for predicting outbreak trajectories, designing effective vaccination strategies, and improving early-warning systems. We conclude by calling for enhanced integration of empirical data and mechanistic modelling, especially in the context of emerging zoonoses and postpandemic preparedness. This review provides a structured perspective to support future interdisciplinary efforts aimed at managing cocirculating pathogens and mitigating their public health impact.

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

International movement plays an important role in spatial spread of infectious diseases. Here, we share two successful COVID-19 interventions based on real-time digital information collected from international passengers, which have been performed in Greece and China respectively. Both of the interventions demonstrated good performance and showed the potential of real-time digital data in containing the spread. However, several key points should not be ignored when we promote similar strategies.

Although recognized as a curable disease, the persistence of hepatitis C virus (HCV) in chronically infected patients remains a great burden for public health. T cell immune responses serve a key role in anti-HCV infection; however, the features of T cell immunity in patients after a long-term infection are not well explored. We recruited a special cohort of patients with similar genetic background and natural developing progression of disease who were infected with HCV through blood donation 35 y ago. We found that self-resolved individuals had higher levels of cytokine-secreting T cells than individuals with chronic infections, indicating HCV-specific T cell immunity could be sustained for >35 y. Meanwhile, virus-specific CD8+ T cells in chronic patients were characterized by programmed cell death-1high, TIM-3high expression, which was related to liver injury characterized by aspartate transaminase/alanine aminotransferase levels and morphopathological changes. Unexpectedly, the expression of Lymphocyte-activation gene 3 on CD8+ T cells was lower in chronic patients and negatively correlated with alanine aminotransferase/aspartate transaminase. Our findings provided new insights into HCV-specific T cell responses and may shed light on a way to figure out novel effector targets and explore a way to reverse chronic infections.

Background The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America. Methods We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports). Findings We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2.28 million cases in 2020 vs 4.08 million cases in 2019; a 44.1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0.01-0.17, p<0.01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0.72 million (95% CI 0.12-1.47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption. Interpretation In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.

[This corrects the article DOI: 10.1038/s43856-022-00073-z.].

Background: Responding to the COVID-19 pandemic, China implemented strict border restrictions to prevent disease importation. Yunnan, a province of China that shares borders with dengue-endemic countries in Southeast Asia, experienced unprecedented reduction in dengue from 6840 cases in 2019 to 260 cases in 2020. Methods: By using a unique epidemiological and genomic dataset from 2013 to 2020 collected in Yunnan, we reconstruct the dynamics of DENV transboundary transmission and investigate the impact of border restriction on dengue expansion. Findings: Dengue transmission in Yunnan was strongly correlated with historical cases in border countries with a 2-3 months lag ( r = 0.58, P <0.01 with Laos; r = 0.55, P <0.01 with Thailand; r = 0.34, P <0.01 with Viet Nam), while the pattern vanished since the beginning of border restriction in 2020. Our analyses revealed multiple independent DENV transboundary introductions from endemic countries to Yunnan all year round, that likely triggered seasonal outbreaks of dengue in the summer when environmental conditions were suitable for mosquito vectors. This work suggests that Yunnan is a sink of DENV transmission and that border restrictions may have substantially reduced dengue burden in 2020, potentially averting hundreds or thousands of cases. Interpretation: The study reveals that surveillance and management of human movement, particularly of travelers returning from high-risk areas could be an effective method to prevent dengue spread, provided other negative impacts of movement restrictions can be minimized.Funding Statement: Funding for this study was provided by Beijing Science and Technology Planning Project (Z201100005420010); Beijing Natural Science Foundation (JQ18025); Beijing Advanced Innovation Program for Land Surface Science; National Natural Science Foundation of China (82073616); Young Elite Scientist Sponsorship Program by CAST (YESS) (2018QNRC001); H.T. and M.U.G.K. acknowledge support from the Oxford Martin School.Declaration of Interests: The authors declare no competing interests.

High rate of cardiovascular disease (CVD) has been reported among patients with coronavirus disease 2019 (COVID-19). Importantly, CVD, as one of the comorbidities, could also increase the risks of the severity of COVID-19. Here we identified phospholipase A2 group VII (PLA2G7), a well-studied CVD biomarker, as a hub gene in COVID-19 though an integrated hypothesis-free genomic analysis on nasal swabs (n=486) from patients with COVID-19. PLA2G7 was further found to be predominantly expressed by proinflammatory macrophages in lungs emerging with progression of COVID-19. In the validation stage, RNA level of PLA2G7 was identified in nasal swabs from both COVID-19 and pneumonia patients, other than health individuals. The positive rate of PLA2G7 were correlated with not only viral loads but also severity of pneumonia in non-COVID-19 patients. Serum protein levels of PLA2G7 were found to be elevated and beyond the normal limit in COVID-19 patients, especially among those re-positive patients. We identified and validated PLA2G7, a biomarker for CVD, was abnormally enhanced in COVID-19 at both nucleotide and protein aspects. These findings provided indications into the prevalence of cardiovascular involvements seen in patients with COVID-19. PLA2G7 could be a potential prognostic and therapeutic target in COVID-19.

Background: In response to the COVID-19 pandemic, China implemented strict restrictions on cross-border travel to prevent disease importation. Yunnan, a Chinese province that borders dengue-endemic countries in Southeast Asia, experienced unprecedented reduction in dengue, from 6840 recorded cases in 2019 to 260 in 2020.Methods: Using a combination of epidemiological and virus genomic data, collected from 2013 to 2020 in Yunnan and neighbouring countries, we conduct a series of analyses to characterise the role of virus importation in driving dengue dynamics in Yunnan and assess the association between recent international travel restrictions and the decline in dengue reported in Yunnan in 2020.Findings: We find strong evidence that dengue incidence between 2013-2019 in Yunnan was closely linked with international importation of cases. A 0-2 month lag in incidence not explained by seasonal differences, absence of local transmission in the winter, effective reproductive numbers < 1 (as estimated independently using genetic data) and diverse cosmopolitan dengue virus phylogenies all suggest dengue is non-endemic in Yunnan. Using a multivariate statistical model we show that the substantial decline in dengue incidence observed in Yunnan in 2020 but not in neighbouring countries is closely associated with the timing of international travel restrictions, even after accounting for other environmental drivers of dengue incidence.Interpretation: We conclude that Yunnan is a regional sink for DENV lineage movement and that border restrictions may have substantially reduced dengue burden in 2020, potentially averting thousands of cases. Targeted testing and surveillance of travelers returning from high-risk areas could help to inform public health strategies to minimise or even eliminate dengue outbreaks in non-endemic settings like southern China.Funding: Funding for this study was provided by National Key Research and Development Program of China, Beijing Science and Technology Planning Project (Z201100005420010); Beijing Natural Science Foundation (JQ18025); Beijing Advanced Innovation Program for Land Surface Science; National Natural Science Foundation of China (82073616); Young Elite Scientist Sponsorship Program by CAST (YESS) (2018QNRC001); H.T., O.P.G. and M.U.G.K. acknowledge support from the Oxford Martin School. O.J.B was supported by a Wellcome Trust Sir Henry Wellcome Fellowship (206471/Z/17/Z).Chinese translation of the abstract (Appendix 2)

Backgroud Hantaan virus (HTNV) , as one of the pathogenic hantaviruses of HFRS, has raised serious concerns in Eurasia. China and its neighbors, especially Russia and South Korea, are seriously suffered HTNV infections. Recent studies reported genetic diversity and phylogenetic features of HTNV in different parts of China, but the analyses from the holistic perspective are rare. Methodology and Principal Findings To better understand HTNV genetic diversity and dynamics, we analyzed all available complete sequences derived from the S and M segments with bio-informatic tools. Our study revealed 11 phylogroups and sequences showed obvious geographic clustering. We found 42 significant amino acid variants sites and 18 of them located in immune epitopes. Nine recombination events and seven reassortment isolates were deteced in our study. Sequences from Guizhou were highly genetic divergent, characterized by the emergence of multiple lineages, recombination and reassortment events. We found that HTNV probably emerged in Zhejiang about 1,000 years ago and the population size expanded from 1980s to 1990s. Bayesian stochastic search variable selection analysis revealed that Heilongjiang, Shaanxi and Guizhou played important roles in HTNV evolution and migration. Conclusions/Significance These findings reveal the original and evolution features of HTNV which might assist in understanding Hantavirus epidemics and would be useful for disease prevention and control. Author summary Hemorrhagic Fever with Renal Syndrome (HFRS) and Hantavirus Pulmonary Syndrome (HPS) are endemic zoonotic infectious diseases caused by hantaviruses that belong to the Family Bunyaviridae. Hantaviruses have gained worldwide attention as etiological agents of emerging zoonotic diseases, with fatality rates ranging from <10% up to 60%. However, our knowledge about the emergence and evolution of HTNV is limited. To get more information about HTNV genetic diversity and phylogenetic features in holistic perspective, we investigated the genetic diversity and spatial distribution of HTNV using all available whole genomic sequences of S and M segments. We also gain insights into the genetic diversity and spatial-temporal dynamics of HTNV. These data can augment traditional approach to infectious disease surveillance and control.

为了建立牛轭湖病毒(Bayou virus,BAYV)、纽约病毒(New York virus,NYV)、厄尼诺洛峡谷病毒(El Moro Canyon virus,ELMCV)以及岛景病毒(Isla Vista virus,ISLAV)四种病毒快速筛查、诊断的核酸检测技术,本研究选用上述四种病毒的N蛋白基因作为靶标区域设计四组特异性引物探针,建立四重实时荧光定量RT-PCR检测方法.用四种病毒体外转录RNA进行灵敏度和重复性验证,并使用其他病毒细胞培养物及体外转录RNA进行特异性验证.结果 显示,四重实时荧光定量PCR扩增效率均可达到95％以上,四种病毒体外转录RNA灵敏度介于1～10拷贝/μL,与单重检测方法无明显差异,且与其他病毒无交叉反应.稳定性评价结果显示,批内、批间变异系数均在3％以内.本研究所建立的检测方法具有良好的敏感性、特异性和重复性,可用于相关样本的诊断与筛查.

Host response biomarkers offer a promising alternative diagnostic solution for identifying acute respiratory infection (ARI) cases involving influenza infection. However, most of the published panels involve multiple genes, which is problematic in clinical settings because polymerase chain reaction (PCR)-based technology is the most widely used genomic technology in these settings, and it can only be used to measure a small number of targets. This study aimed to identify a single-gene biomarker with a high diagnostic accuracy by using integrated bioinformatics analysis with XGBoost. The gene expression profiles in dataset GSE68310 were used to construct a co-expression network using weighted correlation network analysis (WGCNA). Fourteen hub genes related to influenza infection (blue module) that were common to both the co-expression network and the protein-protein interaction network were identified. Thereafter, a single hub gene was selected using XGBoost, with feature selection conducted using recursive feature elimination with cross-validation (RFECV). The identified biomarker was oligoadenylate synthetases-like (OASL). The robustness of this biomarker was further examined using three external datasets. OASL expression profiling triggered by various infections was different enough to discriminate between influenza and non-influenza ARI infections. Thus, this study presented a workflow to identify a single-gene classifier across multiple datasets. Moreover, OASL was revealed as a biomarker that could identify influenza patients from among those with flu-like ARI. OASL has great potential for improving influenza diagnosis accuracy in ARI patients in the clinical setting.

2015年以来,寨卡病毒(Zika virus,ZIKV)感染被报告和小头症之间存有关联,已有多个国家和地区报告ZIKV感染证据,我国持续面对ZIKV输入风险.为发展适用于现场的快速高效的ZIKV核酸检测方法,选取ZIKVNS1片段保守区设计特异性引物探针,经优化建立了多种功能蛋白介导的ZIKV RNA恒温快速扩增检测方法.利用所制备的ZIKV NS1片段体外转录RNA作为参考品,并与实时荧光定量RT-PCR检测结果进行比较.同时利用ZIKV细胞培养物中加入健康人血清制备的模拟临床标本进行初步验证.结果 显示,建立的RNA恒温快速扩增检测方法可100％检出100拷贝/μL体外转录RNA,可在15 min以内判读,大大低于PCR的常规检测时间;用该方法检测其他相关病毒,无交叉反应.病毒滴度在(104～107 PFU/mL)之间的模拟临床病人标本可达到100％检出.本研究建立的ZIKV RNA恒温扩增快速检测方法快速、灵敏、特异,适用于ZIKV现场应急检测,为ZIKV的防控提供了重要的技术支撑.

Objective:To develop a rapid nucleic acid detection method for Zika virus (ZIKV), Dengue virus (DENV), Yellow fever virus (YFV), Chikungunya virus (CHIKV) based on microfluidic fluorescence quantitative RT-PCR technologies, in order to achieve rapid diagnosis of these four viral infections.Methods:Four sets of specific primers and probes were designed targeting the NS1 gene of ZIKV, the NS5 gene of DENV, and YFV, the E1 gene of CHIKV, respectively. The sensitivity was evaluated using in vitro transcribed RNA of ZIKV, DENV, YFV and CHIKV, and the specificity were evaluated using other viral nucleic acid. ZIKV, YFV and CHIKV detection method were verified using simulated positive samples, and DENV detection method was verified using clinical patient samples, the result of which were also compared with the quantitative RT-PCR detection method . Results:The limit of detection (LOD) of ZIKV, DENV, YFV, and CHIKV microfluidic qRT-PCR method were 14.57 copies/μl, 94.27 copies/μl, 8.25 copies/μl, and 223.19 copies/μl, respectively, and the four detection method showed no cross-reactivity with other viral nucleic acids. The prepared ZIKV, YFV and CHIKV simulated positive samples were 100% detected, and the variation coefficient of Ct value measured at each concentration were all around 2%; the 20 clinical patient specimens of DENV infection were 100% detected, which is consistent with the result of fluorescent quantitative RT-PCR detection.Conclusions:The ZIKV, DENV, YFV, and CHIKV microfluidic quantitative RT-PCR detection method showed good sensitivity, specificity, and stability. The detection could be completed within 25 minutes, which could be used for laboratory detection and early diagnosis.

Objective To obtain the optimum of lentiviral library packaging based on CRISPR/cas9 (Clustered regularly interspaced short palindromic repeat sequences/CRISPR-associated protein 9).Methods Reverse transcription polymerase chain reaction (RT-PCR),immunofluorescence antibody (IFA) and enzyme linked immunosorbent assay (ELISA) were used to detect the lentivirus titers in condition of different ratio of packaging plasmids,different addition of lipofectamine 3000 reagent and different time points post-transfection.Then,high-throughput sequencing was performed to evaluate the representation and distribution of single guide (sg) RNAs in the library.Results The lentivirus titer was the highest when the molar ratio of psPAX2 ∶pMD2.0G ∶Lentivirus library was 2 ∶ 1 ∶ 1,and the optimum addition of Lipofectamine 3000 reagent was 10 μl,while the result of ELISA were correspondent to that of RT-PCR.The IFA result showed that the lentivirus titer was the highest at 60 h post-transfecion.The coverage of sgRNAs in the lentivirus library packaged with the optimum we obtained was 99.3％,and the read counts of sgRNAs was observed in a normal distribution.Conclusions The optimal lentivirus library packaging was obtained,and this can provide basis for CRISPR/cas9-based screening.

Objective To explore the method of enhancing the ability to detect HCV infection and to provide the advice for practical work.Methods A total of 487 samples from a village in Hebei Province were selected by cluster sampling.Serum samples were detected by anti-HCV and HCV-RNA assays.The results were compared between the two tests.The correlation of HCV-RNA quantification and its anti-HCV s/n value was analyzed.Results The positive values of anti-HCV and HCV-RNA were 22.1% and 14.2%, respectively, which were lower than that of the parallel test (x2=4.0000, P=0.0455, x2=42.0000, P <0.0001).The HCV-RNA quantification of the samples was positively correlated with the anti-HCV s/n value, which means anti-HCV s/n value increased with HCV-RNA quantification.Conclusion The parallel test of anti-HCV and HCV-RNA can enhance the ability to detect HCV infection.