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.

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.

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.

Soil chemistry, metabarcoding, and metabolome analyses reveal that a sugarcane-Dictyophora indusiata intercropping system can enhance soil health by reducing soil nitrogen loss.

Introduction: Greater amounts of fertilizer are applied every year to meet the growing demand for food. Sugarcane is one of the important food sources for human beings. Methods: Here, we evaluated the effects of a sugarcane-Dictyophora indusiata (DI) intercropping system on soil health by conducting an experiment with three different treatments: (1) bagasse application (BAS process), (2) bagasse + DI (DIS process), and (3) the control (CK). We then analyzed soil chemistry, the diversity of soil bacteria and fungi, and the composition of metabolites to clarify the mechanism underlying the effects of this intercropping system on soil properties. Results and discussion: Soil chemistry analyses revealed that the content of several soil nutrients such as nitrogen (N) and phosphorus (P) was higher in the BAS process than in the CK. In the DIS process, a large amount of soil P was consumed by DI. At the same time, the urease activity was inhibited, thus slowing down the loss of soil in the DI process, while the activity of other enzymes such as ß-glucosidase and laccase was increased. It was also noticed that the content of lanthanum and calcium was higher in the BAS process than in the other treatments, and DI did not significantly alter the concentrations of these soil metal ions. Bacterial diversity was higher in the BAS process than in the other treatments, and fungal diversity was lower in the DIS process than in the other treatments. The soil metabolome analysis revealed that the abundance of carbohydrate metabolites was significantly lower in the BAS process than in the CK and the DIS process. The abundance of D(+)-talose was correlated with the content of soil nutrients. Path analysis revealed that the content of soil nutrients in the DIS process was mainly affected by fungi, bacteria, the soil metabolome, and soil enzyme activity. Our findings indicate that the sugarcane-DIS intercropping system can enhance soil health.

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.

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.

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".

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.

Assessing different interventions against Avian Influenza A (H7N9) infection by an epidemiological model.

This paper aims at evaluating the effectiveness of different intervention measures against the infection of avian influenza A (H7N9) by using an epidemiological model. The model formulates the intrinsic interactions of domestic poultry (DP), H7N9 virus and humans by ordinary differential equations and couples the essential roles of various interventions (including culling, vaccinating, screening, disinfecting, and reducing contact rate, etc). Qualitative analysis indicates that when the recruiting poultry is virus-free, there is a transmission threshold denoted by basic reproduction number which can determine the invasion of H7N9; and there is always a stable H7N9 endemic in case of persistent import of virus-carrying poultry, under which only complete vaccination or cutting off poultry-to-poultry/human contacts can stop H7N9 transmission. By performing numerical analysis of the model with biological background parameters, the intervention outcomes against H7N9 infection are further quantified. It is found that (1) reducing poultry-human/poultry interaction and per-contact infection probability, as well as culling DP, are highly effective in diminishing the infections of humans and DP; (2) the disease is prevented when larger than (1 - 0.1λ p ) proportion of DP is vaccinated, where λ p is the DP-to-DP transmission rate; (3) cleaning and disinfecting environment play limited role in reducing the risk of infection; and (4) screening imported poultry is quite important for stopping disease diffusion, but it works little when local epidemic is prevailing. Combing these measures with real situations would be necessary for controlling H7N9 epidemics and reaching one health purpose.

Modeling coupling dynamics between the transmission, intervention of COVID-19 and economic development.

Current explosive outbreak of the novel coronavirus (COVID-19) pandemic is posing serious threats to public health and economics around the world. To clarify the coupling mechanism between this disease and economic development, a new dynamical system is established by ordinary differential equations (ODEs). It is theoretically proved that the basic reproduction number is a nonlinear combination of parameters regarding disease transmission, intervention and economy effect, which totally determines the stability of the disease-free and endemic equilibria. Further analyses indicate the existence of interaction and mutual restraint among transmissibility, quarantine and economics, in which (1) COVID-19 would cause a long-term impact on halting economic progress; (2) strong coupling of COVID-19 and economics would easily trigger disease outbreak, cause more human infections and alleviate the intervention effects of quarantine; and (3) there exists optimal strategy of time-varying quarantine for disease control and economic development. It is highlighted that adaptive isolation (rather than constant isolation) of at-risk population (rather than random individuals) is highly effective in reducing morbidity at the cost of least economic loss.

Capturing noroviruses circulating in the population: sewage surveillance in Guangdong, China (2013-2018).

Noroviruses (NoVs) are the leading cause of acute gastroenteritis (AGE) outbreaks. Since 2014, novel genetic variants of NoV have been continuously identified and have caused a sharp increase in the number of AGE outbreaks. The specific geographical distribution and expanding genetic diversity of NoV has posed a challenge to conventional surveillance. Here, we describe the long-term dynamic correlation between NoV distribution in sewage and in the local population through the molecular surveillance of NoV in Guangdong, 2013-2018. The relative viral loads of the GI and GII genotypes in sewage were calculated through RT-PCR. A high-throughput sequencing method and operational taxonomic unit (OTU) clustering pipeline were developed to illustrate the abundances of different genotypes and genetic variants in sewage. Our results showed that the NoV viral loads and the emergence of new variants in sewage were closely associated with NoV outbreak risks in the population. Compared with the outbreaks surveillance, the dominance of the newly emerged variants, GII.P17-GII.17 and GII.P16-GII.2, could be detected one or two months ahead in sewage of a hub city. In addition, the dynamics of pre-epidemic variants, which were rarely detected in clinics, could be captured through sewage surveillance, thus improving our understanding of the origin and evolution of these novel epidemic variants. Our data highlight that sewage surveillance could provide nearly real-time and high-throughput data on NoV circulation in the community. With the advances in sequencing techniques, the sewage surveillance system could also be extended to other related infectious diseases.

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.

Spatiotemporal heterogeneity of social contact patterns related to infectious diseases in the Guangdong Province, China.

The social contact patterns associated with the infectious disease transmitted by airborne droplets or close contact follow specific rules. Understanding these processes can improve the accuracy of disease transmission models, permitting their integration into model simulations. In this study, we performed a large-scale population-based survey to collect social contact patterns in three cities on the Pearl River Delta of China in winter and summer. A total of 5,818 participants were face-to-face interviewed and 35,542 contacts were recorded. The average number of contacts per person each day was 16.7 considering supplementary professional contacts (SPCs). Contacts that occurred on a daily basis, lasted more than 4 hours, and took place in households were more likely to involve physical contact. The seasonal characteristics of social contact were heterogeneous, such that contact in the winter was more likely to involve physical contact compared to summer months. The spatial characteristics of the contacts were similar. Social mixing patterns differed according to age, but all ages maintained regular contact with their peers. Taken together, these findings describe the spatiotemporal distribution of social contact patterns relevant to infections in the Guangdong Province of China. This information provides important parameters for mathematical models of infectious diseases.

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.

Assessment of control strategies against Clonorchis sinensis infection based on a multi-group dynamic transmission model.

Clonorchiasis is one of the most important food-borne trematodiases affecting millions of people. Strategies were recommended by different organizations and control programmes were implemented but mostly in short-time periods. It's important to assess the long-term benefits and sustainability of possible control strategies on morbidity control of the disease. We developed a multi-group transmission model to describe the dynamics of C. sinensis transmission among different groups of people with different raw-fish-consumption behaviors, based on which, a full model with interventions was proposed and three common control measures (i.e., preventive chemotherapy, information, education, and communication (IEC) and environmental modification) and their possible combinations were considered. Under a typical setting of C. sinensis transmission, we simulated interventions according to different strategies and with a series of values of intervention parameters. We found that combinations of measures were much beneficial than those singly applied; higher coverages of measures had better effects; and strategies targeted on whole population performed better than that on at-risk population with raw-fish-consumption behaviors. The strategy recommended by the government of Guangdong Province, China shows good and sustainable effects, under which, the infection control (with human prevalence <5%) could be achieved within 7.84 years (95% CI: 5.78-12.16 years) in our study setting (with original observed prevalence 33.67%). Several sustainable strategies were provided, which could lead to infection control within 10 years. This study makes the effort to quantitatively assess the long-term effects of possible control strategies against C. sinensis infection under a typical transmission setting, with application of a multi-group dynamic transmission model. The proposed model is easily facilitated with other transmission settings and the simulation outputs provide useful information to support the decision-making of control strategies on clonorchiasis.