Reproduction Number Research Articles

A Novel Nonlinear SAZIQHR Epidemic Transmission Model: Mathematical Modeling, Simulation, and Optimal Control

Abstract This study presents a seven-compartmental nonlinear epidemic model to explore the dynamics and control of the epidemic. The model extends the traditional susceptible-infected-recovered (SIR) framework by including additional compartments for aware, infodemic, hospitalized, and quarantined populations. It also incorporates three Holling type II saturated nonlinear incidence rates to better represent the disease transmission process. The "infodemic population" refers to those spreading misinformation about the disease, its spread, control, and treatment. The study examines disease dynamics in the absence of a vaccine and identifies two key equilibria: the disease-free equilibrium (DFE) and the endemic equilibrium (EE). It is found that the DFE is locally asymptotically stable when the basic reproduction number (R_0) is below one and becomes unstable when R_0 exceeds one. The model's behavior at R_0=1 is analyzed using center manifold theory, revealing a forward bifurcation. Additionally, the existence of a positive endemic equilibrium is confirmed for R_0>1, with no backward bifurcation observed when R_0≤1. The EE is also shown to be locally asymptotically stable when R_0 is greater than one. Furthermore, the study formulates and mathematically analyzes an optimal control problem. Finally, numerical simulations are presented to support the analytical results.

Stability and Optimality Criteria for an SVIR Epidemic Model with Numerical Simulation

The mathematical modeling of infectious diseases plays a vital role in understanding and predicting disease transmission, as underscored by recent global outbreaks; to delve deep into the dynamic of infectious disease considering latent period presciently is inevitable as it bridges the gap between realistic nature and mathematical modeling. This study extended the classical Susceptible–Infected–Recovered (SIR) model by incorporating vaccination strategies during incubation. We introduced multiple time delays to an account incubation period to capture realistic disease dynamics better. The model is formulated as a system of delay differential equations that describe the transmission dynamics of diseases such as polio or COVID-19, or diseases for which vaccination exists. Critical aspects of the study include proving the positivity of the model’s solutions, calculating the basic reproduction number (R0) using next-generation matrix theory, and identifying disease-free and endemic equilibrium points. The local stability of these equilibria is then analyzed using the Routh–Hurwitz criterion. Due to the complexity introduced by the delay components, we examine the stability by studying the roots of a fourth-degree exponential polynomial. The effects of educational campaigns and vaccination efficacy are also investigated as control measures. Furthermore, an optimization problem is formulated, based on Pontryagin’s maximum principle, to minimize the number of infections and associated intervention costs. Numerical simulations of the delay differential equations are conducted, and a modified Runge–Kutta method with delays is used to solve the optimal control problem. Finally, we present a few simulation results to illustrate the analytical findings.

Mathematical modeling of containing the spread of heroin addiction via awareness program

As many countries are hit by the social economic impact of heroin addiction, there is an urgent need to have an effective awareness program that focuses on educating the population on the danger of heroin addiction and helping the heroin‐users quit. This paper aims to study the effect of the awareness program on the spread of heroin dependence using a mathematical model with distributed delay. First, we show the existence threshold parameter , which we call the basic reproduction number of the spread of heroin use. We prove, via the Lyapunov direct method, that the drug‐free equilibrium is globally asymptotically stable if . If , the drug dependence persists, and the drug equilibrium is globally asymptotically stable. We give three possible scenarios to find the optimal awareness program strategy that puts the heroin epidemic under control. These scenarios take into consideration the reachability of the population, the immunity against heroin addiction, and the effectiveness of the program to contain the use of heroin in the population and bring below one.

In Vivo Dynamics of HIV-1 Infection With Impaired Antibody Immunity and Three General Infection Mechanisms

In this paper we investigate two generalized human immunodeficiency virus type-1 (HIV-1) dynamics models with impaired antibody immunity. The models include both latently and actively infected cells. Three infection mechanisms are incorporated into the models, viral infection mechanism (VIM), latent cellular infection mechanism (CIM) and active CIM. The three infection rates are provided by generic nonlinear functions. The second model includes three types of distributed time delays. We find that our models are biologically feasible. The global stability analysis of equilibria are performed and found the basic reproduction ratio (R0) as a threshold parameter. Using Lyapunov method we show that, the virus-free equilibrium is globally asymptotically stable when R0≤1 and the virus-persistence equilibrium is globally asymptotically stable when R0>1. Sensitivity analysis on R0 is studied. To support our theoretical results we provide some numerical simulations. We have demonstrated that R0 is influenced by all three of the infection types, and that if one of them were ignored, R0 would be underestimated. This might lead to inadequate medication effectiveness that aims to remove HIV-1 from the body. The effects of time delay and impaired antibody immunity on HIV-1 progression are examined. According to our research, lowered immunity is a significant factor in the infection's growth. Furthermore, time delays might drastically reduce R0, which would prevent HIV-1 from replicating. The information provided by our research in this work can improve our comprehension of HIV-1 dynamics within-host and provide guidance for the creation of novel pharmacological treatments.

Computational analysis of the Covid-19 model using the continuous Galerkin–Petrov scheme

Abstract Epidemiological models feature reliable and valuable insights into the prevention and transmission of life-threatening illnesses. In this study, a novel SIR mathematical model for COVID-19 is formulated and examined. The newly developed model has been thoroughly explored through theoretical analysis and computational methods, specifically the continuous Galerkin–Petrov (cGP) scheme. The next-generation matrix approach was used to calculate the reproduction number ( R 0 ) ({R}_{0}) . Both disease-free equilibrium (DFE) ( E 0 ) ({E}^{0}) and the endemic equilibrium ( E ⁎ ) ({E}^{\ast }) points are derived for the proposed model. The stability analysis of the equilibrium points reveals that ( E 0 ) ({E}^{0}) is locally asymptotically stable when R 0 < 1 {R}_{0}\lt 1 , while E ⁎ {E}^{\ast } is globally asymptotically stable when R 0 > 1 {R}_{0}\gt 1 . We have examined the model’s local stability (LS) and global stability (GS) for endemic equilibrium \text{ } and DFE based on the number ( R 0 ) ({R}_{0}) . To ascertain the dominance of the parameters, we examined the sensitivity of the number ( R 0 ) ({R}_{0}) to parameters and computed sensitivity indices. Additionally, using the fourth-order Runge–Kutta (RK4) and Runge–Kutta–Fehlberg (RK45) techniques implemented in MATLAB, we determined the numerical solutions. Furthermore, the model was solved using the continuous cGP time discretization technique. We implemented a variety of schemes like cGP(2), RK4, and RK45 for the COVID-19 model and presented the numerical and graphical solutions of the model. Furthermore, we compared the results obtained using the above-mentioned schemes and observed that all results overlap with each other. The significant properties of several physical parameters under consideration were discussed. In the end, the computational analysis shows a clear image of the rise and fall in the spread of this disease over time in a specific location.

A new approach to determine occupational accident dynamics by using ordinary differential equations based on SIR model

The motivation of this study is to develop and establish an occupational accident dynamical model (OA model) based on Susceptible-Infected-Recovered framework. In order to investigate the dynamics of the OA model, monthly occupational accident data from Turkey between 2013 and 2020 has been selected as dataset. The OA model is defined by a coupled first-order ordinary nonlinear differential equation with four variables. In addition, the relationships between these variables are described with ten parameters. The OA model’s characterization of the equilibrium points is analyzed by investigating the behaviors of these points according to the eigenvalues derived from the Jacobian matrix. Also, the stability of these points is obtained according to the eigenvalues. These results show the behavior of the system near equilibrium points. After that, the reproduction number is computed by using the next-generation matrix method. The calculated reproduction number for given parameters reveals that the OA model is unstable. The OA model is numerically solved in 96 steps, with a time interval of 1 month, using the ODE45 Matlab routine based on the explicit Runge–Kutta algorithm. In addition, a modified OA model is developed by adding the Occupational Health and Safety (OHS) re-training parameter to the OA model to observe a reducing effect on occupational accident numbers. The main results of this study provide a new approach about the future estimation of the number of occupational accidents. Furthermore, through the comparison of numerical results from both models, the study demonstrates that national safety policies, particularly those enhancing the efficacy of OHS training, can effectively mitigate accidents.

Compartmental Model for Unemployment Dynamics in Ghana using Caputo Fractional Derivative

The study develops a compartmental model for unemployment dynamics in Ghana. The compartmental model is first developed through the method of compartmental designs under certain assumptions such as, all entrants into the labor force qualify for any job, some of the employed become unemployed with time, some of the unemployed go through skill training, among others. The compartmental model is further represented in terms of integral form, and the value of the kernel is thereafter substituted as a power law correlation function to achieve a Caputo fractional derivative model. The Caputo model is analyzed to ascertain its invariant and boundedness, its fixed points and its stability. The unemployment basic reproduction number \(\Re_0\) which determines the threshold of recruitment is analyzed using the Next Generation Method Approach, and the global stability for the unemployment-free equilibrium is also analyzed through the approach of Lyapunov function. The results from the analysis show that, there is attraction of all the solution of the model in \(\mathbb{R}_+^4\) since the region is positively invariant. Again, the results indicates that, the model has two fixed point. Thus, unemployment-free equilibrium and risky-unemployment equilibrium. Notwithstanding, the analysis of both the local and global stability of the model show that, the unemployment free equilibrium is local asymptotically stable (LAS) for \(\Re_0\) <1, and global asymptotically stable (GAS). The results indicate that, the model can examine the unemployment dynamics decision making.

Smoking and alcoholism dual addiction dissemination model analysis with optimal control theory and cost-effectiveness.

A mathematical model of the dual addiction dissemination dynamics of alcoholism and smoking was created and examined in this work, along with cost-effectiveness and optimal control techniques. The primary goal of the research is to determine which cost-efficient management techniques are most helpful in lowering the problem of dual addiction dispersion in the community. The smoking addiction sub-model, the alcohol addiction sub-model, and the dual addiction model between alcohol and smoking were all calculated, and their stability was examined in this study. The effective reproduction numbers of the models are computed using the next-generation operator technique. When the model's effective reproduction number is smaller than one, the backward bifurcation phenomenon is seen. Six time-dependent control measures are taken into consideration when formulating and analyzing the optimum control issue. Utilizing and applying the parameter values and using MATLAB ode45 solver we performed numerical simulations for both the dual addiction model and its optimal control problem. Furthermore, using the incremental cost-effectiveness ratio (ICER), we carried out the cost-effectiveness analyses. The cost-effectiveness analysis shows that implementing all the protection (education) control measures simultaneously (i.e., implementing Strategy A) is the most cost-effective strategy. Finally, we recommend that the public health stakeholders must put great effort into the implementation of Strategy A to reduce the smoking and alcoholism dual addiction dissemination problem in the community.

Analisis Kestabilan Model Penyebaran Penyakit Antraks pada Populasi Ternak dengan Transmisi Tak Langsung dan Penggunaan Desinfektan

Anthrax is an infectious disease caused by the bacterium Bacillus anthracis. This disease causes a fairly high mortality rate in livestock populations that can threaten food security in a region. Therefore, it is necessary to prevent and control its spread. This study aims to examine the model of the spread of anthrax disease in a livestock population by considering indirect transmission and the use of disinfectants. The constructed model is expressed as a system of ordinary differential equations. Dynamical analysis is carried out to identify the stability properties of the disease-free equilibrium point. The results of the dynamical analysis show that the disease-free equilibrium point is conditionally stable, namely when the basic reproduction number is less than one. In addition, the results of numerical experiments show that the use of disinfectants has a significant effect on the dynamics of the spread of anthrax disease, namely the higher the rate of bacterial death due to disinfectants, the fewer cases of anthrax. This study shows that the use of disinfectants can be an effective strategy to control the spread of anthrax disease in livestock populations.

Fungal Parasite Transmission in a Planktonic Ecosystem Under Light and Nutrient Constraints.

The two main components of the planktonic ecosystem are phytoplankton and zooplankton. Fungal parasites can infect zooplankton and spread between them. In this paper, we construct a dynamic model to describe the spread of fungal parasites among zooplankton. Basic reproduction number for fungal parasite transmission among zooplankton are rigorously derived. The dynamics of this system are analyzed including dissipativity and equilibria. We further explore the effects of ecological factors on population dynamics and the relationship between fungal parasite transmission and phytoplankton blooms. Interestingly, our theoretical and numerical results indicate that a low-light or oligotrophic aquatic environment is helpful in mitigating the transmission of fungal parasites. We also show that fungal parasites on zooplankton can increase phytoplankton biomass and induce blooms.

Effect of EV71 Vaccination on Transmission Dynamics of Hand, Foot, and Mouth Disease and Its Epidemic Prevention Threshold

Objective: To investigate the effect of Enterovirus A71 (EV71) vaccination on the transmissibility of different enterovirus serotypes of hand, foot, and mouth disease (HFMD) in Zhejiang, China. Methods: Daily surveillance data of HFMD and EV71 vaccination from August 2016 to December 2019 were collected. Epidemic periods for each HFMD type were defined, and the time-varying effective reproduction number (Rt) was estimated, which could provide more direct evidence of disease epidemics than case number. General additive models (GAMs) were employed to analyze associations between EV71 vaccination quantity and rate and HFMD transmissibility. The epidemic prevention threshold, represented by required vaccination numbers and rates, was also estimated. Results: Vaccinating every 100,000 children ≤ 5 years could lead to a decrease in the Rt of EV71-associated HFMD by 14.44% (95%CI: 6.76%, 21.42%). Additionally, a positive correlation was observed between vaccinations among children ≤ 5 years old (per 100,000) and the increased transmissibility of other HFMD types (caused by enteroviruses other than EV71 and CA16) at 1.82% (95%CI: 0.80%, 2.84%). It was estimated that an additional 362,381 vaccinations, corresponding to increased vaccine coverage to 54.51% among children ≤ 5 years could effectively prevent EV71 epidemics in Zhejiang. Conclusions: Our findings highlight the importance of enhancing EV71 vaccine coverage for controlling the epidemic of EV71-HFMD and assisting government officials in developing strategies to prevent HFMD.

SACR EPIDEMIC MODEL FOR THE SPREAD OF HEPATITIS B DISEASE BY CONSIDERING VERTICAL TRANSMISSION

Hepatitis B is an infectious disease that causes inflammation of the liver due to infection with the Hepatitis B virus. Hepatitis B is divided into two phases: the acute phase and the chronic phase. Hepatitis B virus (HBV) can be prevented through vaccination and treatment of susceptible and infected individuals. The spread of the virus can be modeled using mathematical modeling of epidemics. In this study, the model used consists of four classes, namely vulnerable individuals (S), acute individuals (A), chronic individuals (C), and recovered individuals (R). The purpose of this study is to explain the formation of the Hepatitis B disease epidemic model, analyze the stability of the model, perform simulations, and conduct parameter sensitivity analysis on the basic reproductive number. The result of this study is the construction of an epidemic model of the spread of hepatitis B disease in the form of a SACR model. This model takes into account the transmission that occurs not only through interactions between susceptible individuals and chronic individuals but also through the birth process, which occurs in chronic subpopulations because babies born can be chronically infected (vertical transmission from mother to baby). The model produces two equilibrium points, the disease-free equilibrium and the endemic equilibrium. Both points were analyzed for stability using the linearization method and were found to be asymptotically stable. Furthermore, the model simulation was carried out using the fourth-order Runge-Kutta method and sensitivity analysis of the basic reproduction number. From the results obtained, it can be concluded that the spread of hepatitis B disease can be minimized by reducing contact between susceptible and chronic individuals, increasing treatment of chronic individuals, and increasing the number of vaccinated individuals in susceptible populations.

Modeling Ebola Dynamics with a Φ-Piecewise Hybrid Fractional Derivative Approach

Ebola virus disease (EVD) is a severe and often fatal illness posing significant public health challenges. This study investigates EVD transmission dynamics using a novel fractional mathematical model with five distinct compartments: individuals with low susceptibility (S1), individuals with high susceptibility (S2), infected individuals (I), exposed individuals (E), and recovered individuals (R). To capture the complex dynamics of EVD, we employ a Φ-piecewise hybrid fractional derivative approach. We investigate the crossover effect and its impact on disease dynamics by dividing the study interval into two subintervals and utilize the Φ-Caputo derivative in the first interval and the Φ-ABC derivative in the second interval. The study determines the basic reproduction number R0, analyzes the stability of the disease-free equilibrium and investigates the sensitivity of the parameters to understand how variations affect the system’s behavior and outcomes. Numerical simulations support the model and demonstrate consistent results with the theoretical analysis, highlighting the importance of fractional calculus in modeling infectious diseases. This research provides valuable information for developing effective control strategies to combat EVD.

Generalized contact matrices allow integrating socioeconomic variables into epidemic models.

Variables related to socioeconomic status (SES), including income, ethnicity, and education, shape contact structures and affect the spread of infectious diseases. However, these factors are often overlooked in epidemic models, which typically stratify social contacts by age and interaction contexts. Here, we introduce and study generalized contact matrices that stratify contacts across multiple dimensions. We demonstrate a lower-bound theorem proving that disregarding additional dimensions, besides age and context, might lead to an underestimation of the basic reproductive number. By using SES variables in both synthetic and empirical data, we illustrate how generalized contact matrices enhance epidemic models, capturing variations in behaviors such as heterogeneous levels of adherence to nonpharmaceutical interventions among demographic groups. Moreover, we highlight the importance of integrating SES traits into epidemic models, as neglecting them might lead to substantial misrepresentation of epidemic outcomes and dynamics. Our research contributes to the efforts aiming at incorporating socioeconomic and other dimensions into epidemic modeling.

TRANSMISSION AND CONTROL DYNAMICS OF ROTAVIRUS DIARRHEA MODEL WITH DOUBLE DOSE VACCINATION

This study introduces a six-compartmental mathematical model (S, , , E, I, R) to examine the impact of administering a double dose vaccine on the dynamic spread of diarrhea within a community. The mathematical analysis shows the existence of equilibrium points for both disease-free and endemic states in the model. The basic reproduction number was determined using the Next Generation Matrix. Analysis has shown that the basic reproduction number which indicates the disease-free equilibrium point is locally asymptotically stable. Also, using a suitable Lyapunov functional for the model system expressed in state variables and parameters defining the dynamic characteristics of spread and control strategies of the rotavirus diarrhea to obtain the global stability of disease-free equilibrium point over time. A numerical simulation was carried out by Wolfram Mathematica to show the effect of a second-dose vaccine. The inclusion of a double-dose vaccine has been found to have a significant effect on completely eliminating the outbreak of diarrhea. This is evidenced by the local and global stability results, which indicate that effective measures have been taken to prevent the reintroduction or transmission of the disease, and if there may be a risk of outbreaks or reemergence of the disease, very little continuous monitoring and intervention strategies are required to maintain control as this should be taken seriously by medical practitioners or policy health makers.

Stability and Bifurcation Analysis of a Symmetric Fractional-Order Epidemic Mathematical Model with Time Delay and Non-Monotonic Incidence Rates for Two Viral Strains

This study investigates a symmetric fractional-order epidemic model with time delays and non-monotonic incidence rates, considering two viral strains. By confirming the existence, uniqueness, and boundedness of the system’s solutions, the research ensures the model’s well-posedness, guaranteeing its mathematical soundness and practical relevance. The study calculates and evaluates the equilibrium points and the basic reproduction numbers R01 and R02 to understand the dynamic behavior of the model under different parameter settings. Through the application of the Lyapunov method, the research examines the asymptotic global stability of the system, determining whether it will converge to a particular equilibrium state over time. Furthermore, Hopf bifurcation theory is employed to investigate potential periodic solutions and bifurcation scenarios, highlighting how the system might shift from stability to periodic oscillations under certain conditions. By utilizing the Adams-Bashforth-Moulton numerical simulation method, the theoretical results are validated, reinforcing the conclusions and demonstrating the model’s applicability in real-world contexts. It emphasizes the importance of fractional-order models in addressing epidemiological issues related to time delays (τ), individual heterogeneity (m, k), and memory effects (θ), offering greater accuracy compared with traditional integer-order models. In summary, this research provides a theoretical foundation and practical insights, enhancing the understanding and management of epidemic dynamics through fractional-order epidemic models.

The role of asymptomatic cattle for leptospirosis dynamics in a herd with imperfect vaccination

Leptospirosis is an emerging zoonotic disease with high health and economic damage. In this study, we developed a deterministic mathematical model that describes the dynamics of leptospirosis transmission within a cattle herd, incorporating asymptomatic infected and vaccinated compartments. The study examined the transmission role of asymptomatic cattle that contaminate herds without farmers’ knowledge. We proved the well-posedness of the proposed model and found the basic reproduction number using the next-generation matrix. Analytically, we demonstrated that the disease-free equilibrium point is locally and globally asymptotically stable when R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathscr {R}}_0$$\\end{document} is less than unity and is otherwise unstable. Graphically, we further established the local asymptotic stability of disease-free and endemic equilibria. Sensitivity analysis showed that the contact rate with asymptomatic infected cattle, βA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta _A$$\\end{document}, is the most sensitive parameter in the stated model, followed by the recovery rate of asymptomatic infected cattle, σ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sigma $$\\end{document}, and the vaccination rate of susceptible cattle, τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au $$\\end{document}. Numerical simulations revealed that a reduction in contact rate with asymptomatic infected cattle significantly reduced pathogen Leptospira transmission in the herd. In addition, fostering the recovery rate of asymptomatic infected cattle can significantly reduce new infections in the herd. Furthermore, augmenting the vaccination rate among susceptible cattle resulted in a notable decrease in disease prevalence within the herd. Findings of this study underscore the remarkable importance of targeted interventions, such as reducing contact rates with asymptomatic infected cattle, increasing recovery rates using proper treatments, and enhancing vaccination efforts to manage leptospirosis transmission in cattle herds.

Power and sample size calculations for testing the ratio of reproductive values in phylogenetic samples.

The quality of the inferences we make from pathogen sequence data is determined by the number and composition of pathogen sequences that make up the sample used to drive that inference. However, there remains limited guidance on how to best structure and power studies when the end goal is phylogenetic inference. One question that we can attempt to answer with molecular data is whether some people are more likely to transmit a pathogen than others. Here we present an estimator to quantify differential transmission, as measured by the ratio of reproductive numbers between people with different characteristics, using transmission pairs linked by molecular data, along with a sample size calculation for this estimator. We also provide extensions to our method to correct for imperfect identification of transmission linked pairs, overdispersion in the transmission process, and group imbalance. We validate this method via simulation and provide tools to implement it in an R package, phylosamp.

Host plant suitability for the biological performance of Tetranychus urticae Koch and its predator, Phytoseiulus persimilis Athias-Henriot

The life table parameters provide the most extensive information on the biological features of pests and natural enemies, facilitating the potential employment of biological agents in pest management programs. This study investigated how cucumber, strawberry, eggplant, and tomato plants influence the reproduction and life-table parameters of Tetranychus urticae Koch and its predator, Phytoseiulus persimilis Athias-Henriot under laboratory conditions. It also explored the relationship between these parameters and leaf trichome density and the levels of polyphenol compounds. The mites’ biological properties varied based on the morphological and chemical differences in host plant leaves. Both T. urticae and P. persimilis exhibited higher development and reproduction rates on strawberry and cucumber leaves compared to eggplant and tomato plants. Eggplant leaves had the highest polyphenol content (3826.99 mg/kg), followed by tomato leaves (2406.86 mg/kg). The lowest total amount of polyphenol compounds was (704.34 mg/kg) and (273.743 mg/kg) in strawberry and cucumber leaves, respectively. The life table parameters of P. persimilis significantly differed when it fed on T. urticae that had been reared on strawberry, cucumber, eggplant, and tomato leaves. Overall, the results showed that the net (R0) and gross (GRR) reproductive rates were reduced when the predator preyed T. urticae that had been reared on eggplant and tomato leaves. Consequently, the intrinsic (rm) and finite (λ) rates of increase were affected. As a result, the performance of P. persimilis was negatively affected on these plants. The availability of information on the biological performance of P. persimilis is necessary for promoting biological control implementation.

Prenatal phthalate exposure and pubertal development in 16-year-old daughters: reproductive hormones and number of ovarian follicles.

Is there a possible association between prenatal phthalate exposure and late effects in teenage daughters with respect to reproductive hormone levels, uterine volume, and number of ovarian follicles? Our study showed subtle associations between phthalate metabolite concentrations in maternal serum from pregnancy or cord blood and LH and insulin-like growth factor 1 (IGF-1) levels as well as uterine volume in their daughters 16 years later. Endocrine-disrupting environmental chemicals may adversely affect human reproductive health, and many societies have experienced a trend toward earlier puberty and an increasing prevalence of infertility in young couples. The scientific evidence of adverse effects of foetal exposure to a large range of chemicals, including phthalates, on male reproductive health is growing, but very few studies have explored effects on female reproduction. This follow-up study included 317 teenage daughters who were part of the Copenhagen Mother-Child Cohort, a population-based longitudinal birth cohort of 1210 females born between 1997 and 2002. A total of 317 female participants (median age 16 years) were examined for weight, height, and menstrual pattern. A serum sample was analysed for concentrations of reproductive hormones, and trans-abdominal 3D ultrasonography was performed to obtain the number of ovarian follicles, ovarian and uterine size. Prenatal maternal serum samples were available for 115 females, and cord blood samples were available for 118 females. These were analysed for concentrations of 32 phthalate metabolites. Weighted quantile sum regression was used for modelling associations of combined prenatal phthalate exposure with the reproductive outcomes in post-menarcheal females. In bivariate correlation analyses, negative significant associations were found between several prenatal phthalate metabolite concentrations and serum hormone concentrations (testosterone, 17-OH-progesterone, and IGF-1) as well as number of ovarian follicles in puberty. Positive significant correlations were found between prenatal phthalate exposure and FSH and sex hormone-binding globulin concentrations. Combined analyses of phthalate exposure (weighted quantile sums) showed significant negative associations with IGF-1 concentration and uterine volume as well as a significant positive association with LH concentration. Phthalate metabolites were measured in serum from single prenatal maternal blood samples and cord blood samples. Potential concomitant exposure to other endocrine-disrupting environmental chemicals before or after birth was not controlled for. The study population size was limited. Our results support the need for further research into possible adverse effects of environmental chemicals during foetal development of the female reproductive system. The work was supported by The Center on Endocrine Disruptors (CeHoS) under The Danish Environmental Protection Agency and The Ministry of Environment and Food (grant number: MST-621-00 065). No conflicts of interest are declared. N/A.