Time-course and dose-effect of omalizumab in treating chronic idiopathic urticaria/chronic spontaneous urticaria.

PURPOSE: Several studies have shown that subcutaneous injections of omalizumab can treat chronic idiopathic/spontaneous urticaria (CIU/CSU) patients by only assessing the efficacy on specific endpoints. This study aimed to quantitatively analyze different doses of omalizumab in CIU/CSU and compare it with ligelizumab. METHODS: Literature searches were performed in PubMed, Embase, and Web of Science databases. A model-based meta-analysis (MBMA) was utilized to develop a model incorporating time since the initiation of treatment and dose for omalizumab, with the change from baseline in Urticaria Activity Score (CFB-UAS7) as the primary efficacy endpoint. The time-course and dose-effect relationship throughout the omalizumab treatment period was analyzed, and the findings were compared with those of the investigational ligelizumab. RESULTS: The model equation for the CFB-UAS7 was established as E = -Emax × time/(ET50 + time) × (b0 + b1 × dose). The estimated values of the model parameters E max , ET 50 , b 0 , and b 1 were -1.16, 1.26 weeks, -9.90, and -0.0361 mg-1, respectively. At week 12 after the first dose, the model-predicted CFB-UAS7 for 150 mg and 300 mg of omalizumab were -16.0 (95% CI, -17.2 to -14.8) and -21.7 (95% CI, -22.9 to -20.5), respectively. In the PEARL-1 trial, the CFB-UAS7 for 72 mg and 120 mg of ligelizumab were -19.4 (95% CI, -20.7 to -18.1) and -19.3 (95% CI, -20.6 to -18.0), respectively. In the PEARL-2 trial, these values were -19.2 (95% CI, -20.5 to -17.9) and -20.3 (95% CI, -21.6 to -19.0), respectively. CONCLUSION: Omalizumab showed a significant dose-dependent effect in the treatment of CSU. Both 72 mg and 120 mg ligelizumab might have the potential to outperform 150 mg (but not 300 mg) omalizumab.

Viral hepatitis in China during 2002-2021: epidemiology and influence factors through a country-level modeling study.

BACKGROUND: Viral hepatitis imposes a heavy disease burden worldwide and is also one of the most serious public health problems in China. We aimed to describe the epidemiological characteristics of hepatitis in China and to investigate the influencing factors. METHODS: We first used the JoinPoint model to analyze the percentage change (APC) and average annual percentage change (AAPC) of hepatitis in Chinese provinces from 2002 to 2021. We then explored the influencing factors by using the time-series global principal component analysis (GPCA) and the panel fixed-effects model. RESULTS: The disease burden varied across different provinces from 2002 to 2021. The AAPC of the total HAV incidence decreased by 10.39% (95% CI: [-12.70%, -8.02%]) from 2002 to 2021. Yet the AAPC of HBV, HCV, and HEV increased by 1.50% (95% CI: [0.23%, 2.79%]), 13.99% (95% CI: [11.28%, 16.77%]), and 7.10% (95% CI: [0.90%, 13.69%]), respectively. The hotspots of HAV, HBV, HCV, and HEV moved from the west to the center, from the northwest to the southeast, from the northeast to the whole country, and from the northeast to the southeast, respectively. Different types of viral hepatitis infections were associated with hygiene, pollutant, and meteorological factors. Their roles in spatial-temporal incidence were expressed by panel regression functions. CONCLUSIONS: Viral hepatitis infection in China showed spatiotemporal heterogeneity. Interventions should be tailored to its epidemiological characteristics and determinants of viral hepatitis.

Integrated transcriptomic and proteomic analyses of two sugarcane (Saccharum officinarum Linn.) varieties differing in their lodging tolerance.

BACKGROUND: Lodging seriously affects sugarcane stem growth and sugar accumulation, reduces sugarcane yield and sucrose content, and impedes mechanization. However, the molecular mechanisms underlying sugarcane lodging tolerance remain unclear. In this study, comprehensive transcriptomic and proteomic analyses were performed to explore the differential genetic regulatory mechanisms between upright (GT42) and lodged (GF98-296) sugarcane varieties. RESULTS: The stain test showed that GT42 had more lignin and vascular bundles in the stem than GF98-296. The gene expression analysis revealed that the genes that were differentially expressed between the two varieties were mainly involved in the phenylpropanoid pathway at the growth stage. The protein expression analysis indicated that the proteins that were differentially expressed between the two varieties were related to the synthesis of secondary metabolites, the process of endocytosis, and the formation of aminoacyl-tRNA. Time-series analysis revealed variations in differential gene expression patterns between the two varieties, whereas significant protein expression trends in the two varieties were largely consistent, except for one profile. The expression of CYP84A, 4CL, and CAD from the key phenylpropanoid biosynthetic pathway was enhanced in GT42 at stage 2 but suppressed in GF98-296 at the growth stage. Furthermore, the expression of SDT1 in the nicotinate and nicotinamide metabolism was enhanced in GT42 cells but suppressed in GF98-296 cells at the growth stage. CONCLUSION: Our findings provide reference data for mining lodging tolerance-related genes that are expected to facilitate the selective breeding of sugarcane varieties with excellent lodging tolerance.

Adaptive behaviors and vaccination on curbing COVID-19 transmission: Modeling simulations in eight countries.

Current persistent outbreak of COVID-19 is triggering a series of collective responses to avoid infection. To further clarify the impact mechanism of adaptive protection behavior and vaccination, we developed a new transmission model via a delay differential system, which parameterized the roles of adaptive behaviors and vaccination, and allowed to simulate the dynamic infection process among people. By validating the model with surveillance data during March 2020 and October 2021 in America, India, South Africa, Philippines, Brazil, UK, Spain and Germany, we quantified the protection effect of adaptive behaviors by different forms of activity function. The modeling results indicated that (1) the adaptive activity function can be used as a good indicator for fitting the intervention outcome, which exhibited short-term awareness in these countries, and it could reduce the total human infections by 3.68, 26.16, 15.23, 4.23, 7.26, 1.65, 5.51 and 7.07 times, compared with the reporting; (2) for complete prevention, the average proportions of people with immunity should be larger than 90%, 92%, 86%, 71%, 92%, 84%, 82% and 76% with adaptive protection behaviors, or 91%, 97%, 94%, 77%, 92%, 88%, 85% and 90% without protection behaviors; and (3) the required proportion of humans being vaccinated is a sub-linear decreasing function of vaccine efficiency, with small heterogeneity in different countries. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Transmission trends of the global COVID-19 pandemic with combined effects of adaptive behaviours and vaccination.

We developed a mechanism model which allows for simulating the novel coronavirus (COVID-19) transmission dynamics with the combined effects of human adaptive behaviours and vaccination, aiming at predicting the end time of COVID-19 infection in global scale. Based on the surveillance information (reported cases and vaccination data) between 22 January 2020 and 18 July 2022, we validated the model by Markov Chain Monte Carlo (MCMC) fitting method. We found that (1) if without adaptive behaviours, the epidemic could sweep the world in 2022 and 2023, causing 3.098 billion of human infections, which is 5.39 times of current number; (2) 645 million people could be avoided from infection due to vaccination; and (3) in current scenarios of protective behaviours and vaccination, infection cases would increase slowly, levelling off around 2023, and it would end completely in June 2025, causing 1.024 billion infections, with 12.5 million death. Our findings suggest that vaccination and the collective protection behaviour remain the key determinants against the global process of COVID-19 transmission.

Effects of temperature, relative humidity, and illumination on the entomological parameters of Aedes albopictus: an experimental study.

Aedes albopictus (Diptera: Culicidae) is a mosquito from Asia that can transmit a variety of diseases. This paper aimed to explore the effects of temperature, relative humidity, and illumination on the entomological parameters related to the population growth of Aedes albopictus, and provide specific parameters for developing dynamic models of mosquito-borne infectious disease. We used artificial simulation lab experiments, and set 27 different meteorological conditions to observe and record mosquito's hatching time, emergence time, longevity of adult females, and oviposition amount. We then applied generalized additive model (GAM) and polynomial regression to formulate the effects of temperature, relative humidity, and illumination on the biological characteristics of Aedes albopictus. Our results showed that hatchability closely related to temperature and illumination. The immature stage and the survival time of adult female mosquitoes were associated with temperature and relative humidity. The oviposition rate related to temperature, relative humidity, and illumination. Under the control of relative humidity and illumination, ecological characteristics of mosquitoes such as hatching rate, transition rate, longevity, and oviposition rate had an inverted J shape with temperature, and the thresholds were 31.2 °C, 32.1 °C, 17.7 °C, and 25.7 °C, respectively. The parameter expressions of Aedes albopictus using meteorological factors as predictors under different stages were established. Meteorological factors especially temperature significantly influence the development of Aedes albopictus under different physiological stages. The established formulas of ecological parameters can provide important information for modeling mosquito-borne infectious diseases.

Model-Based Projection of Zika Infection Risk with Temperature Effect: A Case Study in Southeast Asia.

Zika virus (ZIKV) recently reemerged in the Americas and rapidly expanded in global range. It is posing significant concerns of public health due to its link to birth defects and its complicated transmission routes. Southeast Asia is badly hit by ZIKV, but limited information was found on the transmission potential of ZIKV in the region. In this paper, we develop a new dynamic process-based mathematical model, which incorporates the interactions among humans (sexual transmissibility), and between human and mosquitoes (biting transmissibility), as well as the essential impacts of temperature. The model is first validated by fitting the 2016 ZIKV outbreak in Singapore via Markov chain Monte Carlo method. Based on that, we demonstrate the effects of temperature on mosquito ecology and ZIKV transmission, and further clarify the potential risk of ZIKV outbreak in Southeast Asian countries. The results show that (i) the estimated infection reproduction number [Formula: see text] in Singapore fell from 6.93 (in which the contribution of sexual transmission was 0.89) to 0.24 after the deployment of control strategies; (ii) the optimal temperature for the reproduction of ZIKV infections and adult mosquitoes are estimated to be [Formula: see text]C and [Formula: see text]C, respectively; and (iii) the [Formula: see text] in Southeast Asia could be between 3 and 7, with an inverted-U shape around the year. The large values of [Formula: see text] and the simulative patterns of ZIKV transmission in each country highlights the high risk of ZIKV attack in Southeast Asia.

The spatiotemporal transmission dynamics of COVID-19 among multiple regions: a modeling study in Chinese provinces.

Current explosive outbreak of COVID-19 around the world is a complex spatiotemporal process with hidden interactions between viruses and humans. This study aims at clarifying the transmission patterns and the driving mechanism that contributed to the COVID-19 prevalence across the provinces of China. Thus, a new dynamical transmission model is established by an ordinary differential system. The model takes into account the hidden circulation of COVID-19 virus among/within humans, which incorporates the spatial diffusion of infection by parameterizing human mobility. Theoretical analysis indicates that the basic reproduction number is a unique epidemic threshold, which can unite infectivity in each region by human mobility and can totally determine whether COVID-19 proceeds among multiple regions. By validating the model with real epidemic data in China, it is found that (1) if without any intervention, COVID-19 would overrun China within three months, resulting in more than 1.1 billion clinical infections and 0.2 billion subclinical infections; (2) high frequency of human mobility can trigger COVID-19 diffusion across each province in China, no matter where the initial infection locates; (3) travel restrictions and other non-pharmaceutical interventions must be implemented simultaneously for disease control; and (4) infection sites in central and east (rather than west and northeast) of China would easily stimulate quick diffusion of COVID-19 in the whole country. Supplementary Information: The online version supplementary material available at 10.1007/s11071-021-07001-1.

Different intervention strategies toward live poultry markets against avian influenza A (H7N9) virus: Model-based assessment.

BACKGROUND: Different interventions targeting live poultry markets (LPMs) are applied in China for controlling avian influenza A (H7N9), including LPM closure and "1110" policy (i.e., daily cleaning, weekly disinfection, monthly rest day, zero poultry stock overnight). However, the interventions' effectiveness has not been comprehensively assessed. METHODS: Based on the available data (including reported cases, domestic poultry volume, and climate) collected in Guangdong Province between October 2013 and June 2017, we developed a new compartmental model that enabled us to infer H7N9 transmission dynamics. The model incorporated the intrinsic interplay among humans and poultry as well as the impacts of absolute humidity and LPM intervention, in which intervention strategies were parameterized and estimated by Markov chain Monte Carlo method. RESULTS: There were 258 confirmed human H7N9 cases in Guangdong during the study period. If without interventions, the number would reach 646 (95%CI, 575-718) cases. Temporal, seasonal and permanent closures of LPMs can substantially reduce transmission risk, which might respectively reduce human infections by 67.2% (95%CI, 64.3%-70.1%), 75.6% (95%CI, 73.8%-77.5%), 86.6% (95%CI, 85.7-87.6%) in total four epidemic seasons, and 81.9% (95%CI, 78.7%-85.2%), 91.5% (95%CI, 89.9%-93.1%), 99.0% (95%CI, 98.7%-99.3%) in the last two epidemic seasons. Moreover, implementing the "1110" policy from 2014 to 2017 would reduce the cases by 34.1% (95%CI, 20.1%-48.0%), suggesting its limited role in preventing H7N9 transmission. CONCLUSIONS: Our study quantified the effects of different interventions and execution time toward LPMs for controlling H7N9 transmission. The results highlighted the importance of closing LPMs during epidemic period, and supported permanent closure as a long-term plan.

Population Movement, City Closure in Wuhan, and Geographical Expansion of the COVID-19 Infection in China in January 2020.

BACKGROUND: The unprecedented outbreak of corona virus disease 2019 (COVID-19) infection in Wuhan City has caused global concern; the outflow of the population from Wuhan was believed to be a main reason for the rapid and large-scale spread of the disease, so the government implemented a city-closure measure to prevent its transmission considering the large amount of travel before the Chinese New Year. METHODS: Based on the daily reported new cases and the population-movement data between 1 and 31 January, we examined the effects of population outflow from Wuhan on the geographical expansion of the infection in other provinces and cities of China, as well as the impacts of the city closure in Wuhan using different closing-date scenarios. RESULTS: We observed a significantly positive association between population movement and the number of the COVID-19 cases. The spatial distribution of cases per unit of outflow population indicated that the infection in some areas with a large outflow of population might have been underestimated, such as Henan and Hunan provinces. Further analysis revealed that if the city-closure policy had been implemented 2 days earlier, 1420 (95% confidence interval, 1059-1833) cases could have been prevented, and if 2 days later, 1462 (1090-1886) more cases would have been possible. CONCLUSIONS: Our findings suggest that population movement might be one important trigger for the transmission of COVID-19 infection in China, and the policy of city closure is effective in controlling the epidemic.

Spatiotemporal analysis of the dengue outbreak in Guangdong Province, China.

BACKGROUND: Dengue is becoming a major public health concern in Guangdong (GD) Province of China. The problem was highlighted in 2014 by an unprecedented explosive outbreak, where the number of cases was larger than the total cases in previous 30 years. The present study aimed to clarify the spatial and temporal patterns of this dengue outbreak. METHODS: Based on the district/county-level epidemiological, demographic and geographic data, we first used Moran's I statistics and Spatial scan method to uncover spatial autocorrelation and clustering of dengue incidence, and then estimated the spatial distributions of mosquito ovitrap index (MOI) by using inverse distance weighting. We finally employed a multivariate time series model to quantitatively decompose dengue cases into endemic, autoregressive and spatiotemporal components. RESULTS: The results indicated that dengue incidence was highly spatial-autocorrelated with the inclination of clustering and nonuniformity. About 12 dengue clusters were discovered around Guangzhou and Foshan with significant differences by district/county, where the most likely cluster with the largest relative risk located in central Guangzhou in October. Three significant high-MOI areas were observed around Shaoguan, Qingyuan, Shanwei and Guangzhou. It was further found the districts in Guagnzhou and Foshan were prone to local autoregressive transmission, and most region in southern and central GD exhibited higher endemic components. Moreover, nearly all of districts/counties (especially the urban area) have cases that were infected in adjacent regions. CONCLUSIONS: The study can help to clarify the heterogeneity and the associations of dengue transmission in space and time, and thus provide useful information for public health authorities to plan dengue control strategies.

Application of the analytic hierarchy approach to the risk assessment of Zika virus disease transmission in Guangdong Province, China.

BACKGROUND: An international spread of Zika virus (ZIKV) infection has attracted global attention in 2015. The infection also affected Guangdong province, which is located in southern China. Multiple factors, including frequent communication with South America and Southeast Asia, suitable climate (sub-tropical) for the habitat of Aedes species, may increase the risk of ZIKV disease transmission in this region. METHODS: An analytic hierarchy process (AHP) method was used to develop a semi-quantitative ZIKV risk assessment model. After selecting indicators, we invited experts in related professions to identify the index weight and based on that a hierarchical structure was generated. Then a series of pairwise comparisons were used to determine the relative importance of the criteria. Finally, the optimal model was established to estimate the spatial and seasonal transmission risk of ZIKV. RESULTS: A total of 15 factors that potentially influenced the risk of ZIKV transmission were identified. The factor that received the largest weight was epidemic of ZIKV in Guangdong province (combined weight [CW] =0.37), followed by the mosquito density (CW = 0.18) and the epidemic of DENV in Guangdong province (CW = 0.14). The distribution of 123 districts/counties' RIs of ZIKV in Guangdong through different seasons were presented, respectively. CONCLUSIONS: Higher risk was observed within Pearl River Delta including Guangzhou, Shenzhen and Jiangmen, and the risk is greater in summer and autumn compared to spring and winter.

Epidemic spreading on adaptively weighted scale-free networks.

We introduce three modified SIS models on scale-free networks that take into account variable population size, nonlinear infectivity, adaptive weights, behavior inertia and time delay, so as to better characterize the actual spread of epidemics. We develop new mathematical methods and techniques to study the dynamics of the models, including the basic reproduction number, and the global asymptotic stability of the disease-free and endemic equilibria. We show the disease-free equilibrium cannot undergo a Hopf bifurcation. We further analyze the effects of local information of diseases and various immunization schemes on epidemic dynamics. We also perform some stochastic network simulations which yield quantitative agreement with the deterministic mean-field approach.

Early rigorous control interventions can largely reduce dengue outbreak magnitude: experience from Chaozhou, China.

BACKGROUND: Dengue fever is a severe public heath challenge in south China. A dengue outbreak was reported in Chaozhou city, China in 2015. Intensified interventions were implemented by the government to control the epidemic. However, it is still unknown the degree to which intensified control measures reduced the size of the epidemics, and when should such measures be initiated to reduce the risk of large dengue outbreaks developing? METHODS: We selected Xiangqiao district as study setting because the majority of the indigenous cases (90.6%) in Chaozhou city were from this district. The numbers of daily indigenous dengue cases in 2015 were collected through the national infectious diseases and vectors surveillance system, and daily Breteau Index (BI) data were reported by local public health department. We used a compartmental dynamic SEIR (Susceptible, Exposed, Infected and Removed) model to assess the effectiveness of control interventions, and evaluate the control effect of intervention timing on dengue epidemic. RESULTS: A total of 1250 indigenous dengue cases was reported from Xiangqiao district. The results of SEIR modeling using BI as an indicator of actual control interventions showed a total of 1255 dengue cases, which is close to the reported number (n = 1250). The size and duration of the outbreak were highly sensitive to the intensity and timing of interventions. The more rigorous and earlier the control interventions implemented, the more effective it yielded. Even if the interventions were initiated several weeks after the onset of the dengue outbreak, the interventions were shown to greatly impact the prevalence and duration of dengue outbreak. CONCLUSIONS: This study suggests that early implementation of rigorous dengue interventions can effectively reduce the epidemic size and shorten the epidemic duration.

Estimating the epidemic threshold on networks by deterministic connections.

For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.

Transmission dynamics of Zika virus with multiple infection routes and a case study in Brazil.

The Zika virus (ZIKV) is a serious global public health crisis. A major control challenge is its multiple transmission modes. This paper aims to simulate the transmission patterns of ZIKV using a dynamic process-based epidemiological model written in ordinary differential equations, which incorporates the human-to-mosquito infection by bites and sewage, mosquito-to-human infection by bites, and human-to-human infection by sex. Mathematical analyses are carried out to calculate the basic reproduction number and backward bifurcation, and prove the existence and stability of the equilibria. The model is validated with infection data by applying it to the 2015-2016 ZIKV epidemic in Brazil. The results indicate that the reproduction number is estimated to be 2.13, in which the contributions by mosquito bite, sex and sewage account for 85.7%, 3.5% and 10.8%, respectively. This number and the morbidity rate are most sensitive to parameters related to mosquito ecology, rather than asymptomatic or human-to-human transmission. Multiple transmission routes and suitable temperature exacerbate ZIKV infection in Brazil, and the vast majority of human infection cases were prevented by the intervention implemented. These findings may provide new insights to improve the risk assessment of ZIKV infection.

Dictyophora indusiata and Bacillus aryabhattai improve sugarcane yield by endogenously associating with the root and regulating flavonoid metabolism.

Introduction: Endophytes play a significant role in regulating plant root development and facilitating nutrient solubilization and transportation. This association could improve plant growth. The present study has uncovered a distinct phenotype, which we refer to as "white root", arising from the intricate interactions between endophytic fungi and bacteria with the roots in a sugarcane and bamboo fungus (Dictyophora indusiata) intercropping system. Methods: We investigated the mechanisms underlying the formation of this "white root" phenotype and its impact on sugarcane yield and metabolism by metabarcoding and metabolome analysis. Results and Discussion: Initial analysis revealed that intercropping with D. indusiata increased sugarcane yield by enhancing the number of viable tillers compared with bagasse and no input control. Metabarcoding based on second-generation and third-generation sequencing indicated that D. indusiate and Bacillus aryabhattai dominates the fungal and bacterial composition in the "white root" phenotype of sugarcane root. The coexistence of D. indusiata and B. aryabhattai as endophytes induced plant growth-promoting metabolites in the sugarcane root system, such as lysoPC 18:1 and dihydrobenzofuran, probably contributing to increased sugarcane yield. Furthermore, the association also enhanced the metabolism of compounds, such as naringenin-7-O-glucoside (Prunin), naringenin-7-O-neohesperidoside (Naringin)*, hesperetin-7-O-neohesperidoside (Neohesperidin), epicatechin, and aromadendrin (Dihydrokaempferol), involved in flavonoid metabolism during the formation of the endophytic phenotype in the sugarcane root system. These observations suggest that the "white root" phenotype promotes sugarcane growth by activating flavonoid metabolism. This study reports an interesting phenomenon where D. indusiata, coordinate with the specific bacteria invade, forms a "white root" phenotype with sugarcane root. The study also provides new insights into using D. indusiata as a soil inoculant for promoting sugarcane growth and proposes a new approach for improve sugarcane cultivation.

Epidemic spreading on contact networks with adaptive weights.

The heterogeneous patterns of interactions within a population are often described by contact networks, but the variety and adaptivity of contact strengths are usually ignored. This paper proposes a modified epidemic SIS model with a birth-death process and nonlinear infectivity on an adaptive and weighted contact network. The links' weights, named as 'adaptive weights', which indicate the intimacy or familiarity between two connected individuals, will reduce as the disease develops. Through mathematical and numerical analyses, conditions are established for population extermination, disease extinction and infection persistence. Particularly, it is found that the fixed weights setting can trigger the epidemic incidence, and that the adaptivity of weights cannot change the epidemic threshold but it can accelerate the disease decay and lower the endemic level. Finally, some corresponding control measures are suggested.

Genomic epidemiology of dengue in Shantou, China, 2019.

Objectives: Dengue has been endemic in Southeast Asian countries for decades. There are few reports tracing the dynamics of dengue in real time. In this study, we generated hundreds of pathogen genomes to understand the genomic epidemiology of an outbreak in a hyper-endemic area of dengue. Methods: We leveraged whole-genome short-read sequencing (PE150) to generate genomes of the dengue virus and investigated the genomic epidemiology of a dengue virus transmission in a mesoscale outbreak in Shantou, China, in 2019. Results: The outbreak was sustained from July to December 2019. The total accumulated number of laboratory-confirmed cases was 944. No gender bias or fatalities were recorded. Cambodia and Singapore were the main sources of imported dengue cases (74.07%, n = 20). A total of 284 dengue virus strains were isolated, including 259 DENV-1, 24 DENV-2, and 1 DENV-3 isolates. We generated the entire genome of 252 DENV isolates (229 DENV-1, 22 DENV-2, and 1 DENV-3), which represented 26.7% of the total cases. Combined epidemiological and phylogenetic analyses indicated multiple independent introductions. The internal transmission evaluations and transmission network reconstruction supported the inference of phylodynamic analysis, with high Bayes factor support in BSSVS analysis. Two expansion founders and transmission chains were detected in CCH and LG of Shantou. Conclusions: We observed the instant effects of genomic epidemiology in monitoring the dynamics of DENV and highlighted its prospects for real-time tracing of outbreaks of other novel agents in the future.