Reproduction Number Research Articles

Reproductive Coercion: Prevalence and Risk Factors Related to Relationship Health Knowledge and Skills.

Reproductive coercion is any behavior that limits a person's reproductive decision-making and can lead to negative health and safety outcomes. Previous research has explored reproductive coercion prevalence rates in clinical samples, as well as demographic risk factors for experiencing reproductive coercion. The purpose of this study is to assess the prevalence rates of two specific forms of reproductive coercion, pregnancy coercion and condom manipulation, in an ethnically and racially diverse sample of young females. We also explore the association between relationship health knowledge and skills with reproductive coercion. We used a sample of 143 females with previous sexual activity. Participants were diverse in terms of race, ethnicity, sexual orientation, and family immigration status. Descriptive statistics and logistic regression analyses were used to determine prevalence rates of pregnancy coercion and condom manipulation and the likelihood of experiencing reproductive coercion based on participants' knowledge and skills related to relationship health. Results revealed that 16.1% of the sample had experienced reproductive coercion, with all participants in this group reporting lifetime experiences of pregnancy coercion. Lifetime experiences of condom manipulation were reported by 6.3% of the sample. The most common form of reproductive coercion experienced by participants was being told by a partner not to use any birth control. Furthermore, results indicate that higher relationship health knowledge may be a protective factor for pregnancy coercion and condom manipulation. Likewise, higher decision-making skills in relationships and higher confidence in relationships may also protect against condom manipulation. Results from this study suggest implications for sexual and relationship health programming that expands education around consent, choice, decision-making, and communication around the use of contraception.

A Between-Host Cholera Mathematical Model Incorporating Temperature Dependence

This paper establishes a between-host cholera model with temperature dependent parameter. This is done using system of ODEs to analyse the effect of temperature change on cholera disease. The model analysis reveals that when R0 < 1, the disease free equilibrium point is locally and globally asymptotically. It is also noticed that if R0 > 1, the endemic equilibrium point is locally and globally asymptotically stable. The sensitivity analysis of model parameters shows that R0 ​depends intensively on infection rate of pathogen α1​ normalized with temperature. An increase in infection rate of pathogen α1​ that is dependent on temperature by 10% would increase R0​ by 10% and decreasing it by 10% reduces R0 by 10%; hence, increasing the temperature of the environment where the pathogen lives would help reduce the rate of infection of the pathogen, thus reducing the reproduction number R0​. We conducted numerical simulation of the model in response to temperature changes, and the results indicate that Vibrio cholerae pathogens multiply faster at 23°C but between 23°C < T ≤ 43°C the pathogen multiplication is hindered, therefore, at 23°C, more pathogens are active to cause infection compared to high temperatures.

Ecological and epidemiological ramification of fear: Exploring deterministic and stochastic dynamics in a predator–prey system with predator switching and harvesting

In an ecosystem, harvesting infected prey can assist in managing and containing the spread of the illness within the prey species. On the other hand, the harvesting of predators can be beneficial as it regulates their numbers, preventing them from over-consuming prey and subsequently preserving existence of the prey population. This study introduces a predator–prey model that encompasses prey infection, predator–prey interactions influenced by fear, switching and harvesting. We derive an analytic expression for the basic reproduction number, a critical determinant of disease spread. We investigate the global stability of disease-free and endemic equilibria contingent on the basic reproduction number’s value, highlighting the potential for disease eradication by maintaining it below unity. In-depth analysis of the deterministic model is undertaken, with a focus on Hopf bifurcations that delineate thresholds for disease-free and endemic states. Furthermore, the deterministic model is extended to incorporate environmental stochasticity. We obtain the conditions under which population extinction occurs. Our findings elucidate how the intensity of environmental noise influences population dynamics, providing valuable insights into extinction risks under varying noise levels.

The optimal spatially-dependent control measures to effectively and economically eliminate emerging infectious diseases.

Non-pharmaceutical interventions (NPIs) are effective in mitigating infections during the early stages of an infectious disease outbreak. However, these measures incur significant economic and livelihood costs. To address this, we developed an optimal control framework aimed at identifying strategies that minimize such costs while ensuring full control of a cross-regional outbreak of emerging infectious diseases. Our approach uses a spatial SEIR model with interventions for the epidemic process, and incorporates population flow in a gravity model dependent on gross domestic product (GDP) and geographical distance. We applied this framework to identify an optimal control strategy for the COVID-19 outbreak caused by the Delta variant in Xi'an City, Shaanxi, China, between December 2021 and January 2022. The model was parameterized by fitting it to daily case data from each district of Xi'an City. Our findings indicate that an increase in the basic reproduction number, the latent period or the infectious period leads to a prolonged outbreak and a larger final size. This indicates that diseases with greater transmissibility are more challenging and costly to control, and so it is important for governments to quickly identify cases and implement control strategies. Indeed, the optimal control strategy we identified suggests that more costly control measures should be implemented as soon as they are deemed necessary. Our results demonstrate that optimal control regimes exhibit spatial, economic, and population heterogeneity. More populated and economically developed regions require a robust regular surveillance mechanism to ensure timely detection and control of imported infections. Regions with higher GDP tend to experience larger-scale epidemics and, consequently, require higher control costs. Notably, our proposed optimal strategy significantly reduced costs compared to the actual expenditures for the Xi'an outbreak.

Stability Analysis and Optimal Control for Spreading Typhoid Fever Model with Direct and Indirect Transmissions

This article discusses a model of spreading typhoid fever with direct and indirect transmissions. There are five compartments included in the model, namely susceptible individuals, infected individuals, chronic carrier individuals, recovered individuals, and salmonella typhi bacteria in the environment. As an effort to control and minimize the numbers of infected individuals and chronic carrier individuals, we introduce simultaneously campaign for the susceptible individuals and treatment for the infected individuals and for chronic carrier individuals. The resulting model is a system of non-linear differential equations and quite challenging to analysis globally. Existence of both disease-free equilibrium point and endemic equilibrium point are analysed analytically. Stability of the equilibrium point is analysed locally by determining the eigenvalues of the associated Jacobian matrix, Routh-Hurwitz stability criteria, and basic reproduction number () via next generation matrix. The minimum Pontryagin principle and Hamiltonian equation are referred to minimize the numbers of infected and chronic carrier individuals. Simulation is carried out using suitable values of parameters. We found that the eigenvalues for endemic equilibrium point are all negative real numbers and . Optimal paths for state and constate variables are plotted using fourth order forward-backward Runge-Kutta method. In case there are no campaign and treatments, we found and endemic occurs. When campaign and treatments are included together in the model, we found optimal paths for all compartments that minimize the number of infected and chronic carrier individuals. Giving campaign and treatments increase significantly the susceptible and recovered individuals. At the same time, it reduces significantly the infected, chronic carrier individuals, and salmonella typhi bacteria in the environment. Involving campaign and treatment in the model of spreading typhoid fever can be considered as an effective strategy to minimize the numbers of infected and chronic carrier individuals.

The role of some types of erythrocytes on the growth of Entamoeba histolytica trophozoite in vitro

The parasite E.histolytica was first isolated from a stool sample, and then cultivated and maintained in vitro using Locke-egg medium (LEM) and Liver infusion agar medium (LIAM) . Then, the effect of some types of erythrocytes (human and sheep), on the growth and activity of the parasite in the two culture media was investigated. The parasite was able to ingest and lysis erythrocytes of human and sheep that were supplemented to the culture media and such manipulation was able to augment the reproduction rate of the cultivated E. histolytica, however, such consequence was media- and concentration-dependent. The reproduction rate was significantly increased (66.0, 57.5 and 58.6%, respectively) in LEM medium containing human erythrocytes types B at 0.11 x 106 cells/ml and O at 0.13 x 106 and 0.15 x 106 cells/ml. The sheep erythrocytes showed a similar enhancement (56.1%) at a concentration of 0.13 x 106 cells/ml. In contrast, adding erythrocytes to LIAM medium did not enhance the reproduction rate of the parasite significantly.

Dynamics of Human Fertility, Environmental Pollution, and Socio-Economic Factors in Aral Sea Basin

One of the worst natural, economic, and social catastrophes caused by human activity is the Aral Sea crisis in Central Asia. The Aral Sea’s desiccation, which has an impact on the region’s overall sustainable development, human welfare, security, and survival, is what led to the problem. This study assesses the effects of economic expansion, population ageing, life expectancy, internet usage, and greenhouse gas emissions on the fertility rate in the countries that made up the Aral Sea basin between 1990 and 2021. Several econometric techniques were used in this study, including Pooled OLS (Ordinary Least Squares) with the Driscoll–Kraay estimating method, FMOLS (Fully Modified Ordinary Least Square), and DOLS (Dynamic Ordinary Least Square). Additionally, we used the Hurlin and Dumitrescu non-cause tests to verify the causal links between the variables. The empirical findings verify that a decrease in the fertility rate among women in the nations surrounding the Aral Sea occurs when the population of a certain age (women aged 15–64 as a percentage of the total population) grows and life expectancy rises. Greenhouse gas emissions (GHGs) also have an adverse effect on reproductive rates. Conversely, the region’s fertility rate may rise as a result of increased internet usage and economic growth. Furthermore, this study indicates that certain variables—aside from greenhouse gas emissions (GHGs)—have a causal relationship with the fertility rate.

Characterizing best practices for tonsil-oral-scrubbing (TOSc) collection for PRRSV RNA detection in sows

BackgroundA Tonsil-Oral-Scrubbing (TOSc) method was developed to sample the sow’s oropharyngeal and tonsillar area without snaring and has shown comparable porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection rates with tonsil scraping in infected sows. This study investigated the effect of specific TOSc collection factors on the PRRSV RT-rtPCR results (detection rates and Ct values). Those factors include whether the sow was snared or not snared at TOSc collection (“snared” vs. “not snared”); whether the sow was laying down or standing at collection (“laying down” vs. “standing”); and type of collectors used for TOSc collection (“TOSc prototype” vs. “Spiral-headed AI catheter (SHAC)”). Volume of fluid was compared between “snared” and “not snared” groups, and collection time was compared between “laying down” and “standing” groups as well.ResultsThe effect for each factor was assessed in three independent studies following the same design: TOSc was collected twice from each studied sow, once with the baseline level for a factor (“not snared”, or “standing”, or “TOSc prototype”), and another time followed by the other level of the paired factor (“snared”, “laying down”, or “SHAC”, correspondingly). Results showed that “not snared” TOSc had numerically higher PRRSV RNA detection rate (60.7% vs. 52.5%, p = 0.11), significantly lower median Ct values (31.9 vs. 32.3, p < 0.01), and significantly higher volume of fluid than “snared” samples (1.8 mL vs. 1.2 mL, p < 0.01); “laying down” TOSc samples did not differ statistically (60.7% vs. 60.7%) in the PRRSV RNA detection rate, obtained numerically lower median Ct values (30.9 vs. 31.3, p = 0.19), but took 40% less collection time compared to “standing” TOSc samples; samples collected using the “TOSc prototype” had numerically higher PRRSV RNA detection rate (91.7% vs. 88.3%, p = 0.27) and significantly lower median Ct values (32.8 vs. 34.5, p < 0.01) than that from “SHAC”.ConclusionsUnder the conditions of this study best practices for TOSc collection aiming higher detection rate of PRRSV RNA while minimizing time for collection were suggested to be sampling TOSc without snaring, when sows are laying down, and using a prototype TOSc collector.

Stability and computational analysis of Influenza-A epidemic model through double time delay

Delay factors demonstration has a significant role in controlling a strain of infectious disease instead of a pharmaceutical strategy. According to the World Health Organization (WHO), 3–5 million cases are reported annually and approximately 290,000 to 650,000 respiratory deaths annually. So, in the present study, we develop a delayed mathematical model based on delay differential equations (DDEs) for the influenza epidemic using a deterministic approach by introducing double delay parameters. The four distinct sub-populations are considered susceptible, exposed, infected, and recovered. For the rigorous analysis, the fundamental properties of the model like positivity, boundedness, existence, and uniqueness, were studied. The influenza-free equilibrium (IFE) and influenza-existing equilibrium (IEE), are the two nonnegative equilibrium points that the model demonstrates. Both locally and globally, the asymptotic stability of the equilibrium points of the model is established and shown under specific situations of reproduction number. Additionally, investigated the model's parameter sensitivity and determined the relative sensitivity of each parameter. Both standard and nonstandard methods—such as Euler, Runge-Kutta, and nonstandard finite difference with a delayed sense—are presented to make computational analysis support a dynamical analysis and the best visualization of results. The stability of the non-standard finite difference scheme is thoroughly analyzed around the steady states of the model. Additionally, the results show that the nonstandard finite difference approximation is an efficient, cost-effective method, independent of time step size, to solve such highly nonlinear and complex real-world problems.

Evaluating the effects of short-term low temperature on the growth and development of Trichopria drosophilae based on the age–stage two-sex life table

BackgroundThe effects of low temperatures on parasitic wasps are crucial for maintaining farmland biodiversity and enhancing biological control, especially given the implications of global warming and frequent extreme cold events.MethodsWe studied the effects of different low temperatures (−8 ± 1 °C, −4 ± 1 °C, 0 ± 1 °C, 4 ± 1 °C, and 8 ± 1 °C) on the mating frequency and duration of male adults of Trichopria drosophilae and the number of pupae beaten by female adults, and constructed the age–stage two-sex life table of T. drosophilae.ResultsThis study found that male T. drosophilae adults exposed to low temperatures for 12 h significantly altered their mating behavior, peaking between 15:00 and 17:00. As the temperature dropped during the exposure, both the mating frequency of T. drosophilae and the duration of pupal beating were affected. The survival rate of female adults dropped from 39.55% at 8 °C to just 21.17% at −8 °C. Low-temperature treatment shortened the development period and lifespan for T. drosophilae adults. They developed 4.71 days faster and had a total lifespan that was 10.66 days shorter than those in the control group after being exposed to −8 °C. Furthermore, the average number of eggs laid by females at −8 °C was 4.46 less than that at 8 °C and 6.16 less than that in the control group, which laid an average of 21.55 eggs. The net reproductive rate (R0) of T. drosophilae decreased with lower temperatures, reaching a low of 23.64 at −8 °C. Conversely, the intrinsic growth rate (rm) actually increased as temperatures dropped, with the lowest value being 0.21 at −8 °C.ConclusionsThe findings indicate that short-term exposure to low temperatures hampers the growth and population increase of T. drosophilae, thereby reducing their effectiveness as biological control agents.Graphical

Stability Analysis of the Transmission Model of TB-HIV Co-Dynamics with Vaccination and Treatment

This study aims to analyse and determine the stability of the equilibrium point of the spread model consists of TB infection, HIV infection, and TB-HIV co-infection disease. This model considers eight compartments, namely unvaccinated susceptible, vaccinated susceptible, exposed, infected with TB, infected with HIV, infected with TB and HIV, treatment, and recovered by considering vaccination and treatment in the compartments as the strategies to manage spread of the diseases. The stability of non-endemic equilibrium point is carried out by determining the basic reproduction number and eigenvalues. Simulation is conducted to investigate effect of vaccination and treatment. By giving appropriate values of parameters and varying values of vaccination rate we found that increasing value of vaccination rate will reduce and eliminate TB infection, HIV infection, and TB-HIV co-infection disease from the population. The curve solutions of the dynamics of each compartment are given to confirm the analytical results.

Sublethal effects of emamectin benzoate on biological characteristics and the expression of vitellogenin (SgVg) and its receptor in Sclerodermusguani

Emamectin benzoate (EMB) is a commonly used insecticide for controlling agricultural and forest pests. To facilitate its rational use in integrated pest management (IPM), the sublethal effects of EMB on the development and reproduction of Scleroderma guani were evaluated. Sublethal doses of EMB (LD10 and LD30) significantly reduced the longevity and fecundity of F0 females. In the F1 generation, sublethal doses significantly reduced larval development duration and male longevity but significantly extended female longevity. Additionally, the LD30 treatment significantly decreased the number of laid eggs in F1 females by 20.72% compared with the control group. The net reproductive rate (R0) was significantly declined by the LD30 treatment compared with the control group (CK). Furthermore, the mean generation time (T) was significantly extended in both LD10 and LD30 treatment groups. Compared to the control group, the expression of SgVg and SgVgR genes in the LD10 and LD30 groups was significantly lower, which may be a crucial factor for the reduced fecundity of the females. These results indicate that sublethal doses of EMB significantly reduced adult longevity and fecundity of S. guani. The findings are practical for developing IPM strategies for forestry pests using S. guani and EMB.

Dynamics and backward bifurcations of SEI tuberculosis models in homogeneous and heterogeneous populations

The main difference between tuberculosis (TB) and other infectious diseases is that the transmission of the bacterium should be considered not only as the development of a primary infection, but also as exogenous reinfection or endogenous reactivation. Moreover, individuals in the population may have heterogeneous contact rates, which can be described by complex networks. To this end, we present two differential equation-based TB models in homogeneous and heterogeneous populations. The first model assumes that the number of contacts per unit time is constant for the whole population, whereas the second model considers the heterogeneous number of contacts per unit time for each individual. We derive the basic reproduction number of each model using the next-generation matrix method, and analyze the dynamical properties of each model in detail. We find that the two models undergo backward bifurcations and have the same threshold condition for backward bifurcation. From this threshold condition, we see that the reduced rate of exogenous reinfection of individuals plays an important role in causing the backward bifurcation. Interestingly, the second model allows the threshold condition for backward bifurcation to be independent of network parameters. Thus, unlike other infectious disease models on complex networks, in controlling the spread of tuberculosis among populations with different numbers of contacts, we only need to focus on disease parameters during treatment. Finally, numerical simulations more intuitively demonstrate the impact of parameter changes on the prevalence of tuberculosis and reveal the model's richer and more interesting dynamical properties, such as bistability. Sensitivity analysis indicates that the basic reproduction number is highly correlated with both the relapse rate of latent individuals progressing to active infection and the probability of healthy individuals becoming infected after contact with the pathogen. Therefore, enhancing the detection and treatment of latent cases and reducing contact between infected and uninfected individuals are the most crucial public health interventions.

Insights into the community structure and environmental functions of water hyacinth rhizobiome in urban river ecosystem.

Water hyacinth (WH) is a widespread floating invasive aquatic plant with a prolific reproductive and dispersion rate. With the aid of its root-associated microbes, WH significantly modulates the ecosystem's functioning. Despite their irrevocable importance, the WH microbiome remains unexplored in detail. Here, we present a shotgun sequencing analysis of WH rhizobiome predominant in urban rivers and their surrounding water to unveil the diversity drivers and functional relationship. The core microbiome of the WH mainly consisted of the methane-metabolizing archaebacteria and sulfate-reducing bacteria, which are probably driving the methane and sulfur metabolic flux along the vegetative zone in the water. The beta diversity analysis revealed temporal variations (River WH_2020 vs. WH_2022) (R of 0.8 to 1 and R2 of 0.17 to 0.41), which probably could be attributed to the transient taxa as there was a higher sharing of core bacteria (48%). Also, the WH microbiome significantly differed (R = 0.46 to 1.0 and R2 of 0.18 to 0.52) from its surrounding water. Further, the functional analysis predicted 140 pollutant-degrading enzymes (PDEs) well-implicated in various xenobiotic pollutant degradation, including hydrocarbons, plastics, and aromatic dyes. These PDEs were mapped to bacterial genera such as Hydrogenophaga, Ideonella, Rubrivivax, Dechloromonas, and Thauera, which are well-reported for facilitating the metabolism of xenobiotic compounds. The higher prevalence of metal and biocide resistance genes further highlighted the persistence of resistant microbes assisting WH in bioremediation applications.

Evolution of COVID-19 dynamics in Guangdong Province, China: an endemic-epidemic modeling study

BackgroundFrom January 2020 to June 2022, strict interventions against COVID-19 were implemented in Guangdong Province, China. However, the evolution of COVID-19 dynamics remained unclear in this period.ObjectivesThis study aims to investigate the evolution of within- and between-city COVID-19 dynamics in Guangdong, specifically during the implementation of rigorous prevention and control measures. The intent is to glean valuable lessons that can be applied to refine and optimize targeted interventions for future crises.MethodsData of COVID-19 cases and synchronous interventions from January 2020 to June 2022 in Guangdong Province were collected. The epidemiological characteristics were described, and the effective reproduction number (Rt) was estimated using a sequential Bayesian method. Endemic-epidemic multivariate time-series model was employed to quantitatively analyze the spatiotemporal component values and variations, to identify the evolution of within- and between-city COVID-19 dynamics.ResultsThe incidence of COVID-19 in Guangdong Province was 12.6/100,000 population (15,989 cases) from January 2020 to June 2022. The Rt predominantly remained below 1 and increased to a peak of 1.39 in Stage 5. As for the evolution of variations during the study period, there were more spatiotemporal components in stage 1 and 5. All components were fewer from Stage 2 to Stage 4. Results from the endemic-epidemic multivariate time-series model revealed a strong follow-up impact from previous infections in Dongguan, Guangzhou and Zhanjiang, with autoregressive components of 0.48, 0.45 and 0.36, respectively. Local risk was relatively high in Yunfu, Shanwei and Shenzhen, with endemic components of 1.17, 1.04 and 0.71, respectively. The impact of the epidemic on the neighboring regions was significant in Zhanjiang, Shenzhen and Zhuhai, with epidemic components of 2.14, 1.92, and 1.89, respectively.ConclusionThe findings indicate the presence of spatiotemporal variation of COVID-19 in Guangdong Province, even with the implementation of strict interventions. It’s significant to prevent transmissions within cities with dense population. Preventing spatial transmissions between cities is necessary when the epidemic is severe. To better cope with future crises, interventions including vaccination, medical resource allocation and coordinated non-pharmaceutical interventions were suggested.

Complex dynamics of an SIHR epidemic model with variable hospitalization rate depending on unoccupied hospital beds

In this paper, we propose an susceptible-infectious-hospitalized-recovered (SIHR) epidemic model with a nonlinear hospitalization rate depending on the number of unoccupied hospital beds. Note that the number of all hospital beds is used as a measure of all available medical resources. The basic reproduction number is calculated using the next-generation matrix method. We analyze the existence of endemic equilibria and discuss the global stability of the disease-free equilibrium. Existence and stability of endemic equilibria indicate possible occurrences of bifurcations. We confirm the appearance of backward bifurcation, saddle–node bifurcation, Hopf bifurcation, and Bogdanov–Takens bifurcation using normal form theory and central manifold theory. Numerical simulations show that the dynamic behavior of the model undergoes a transition from forward bifurcation to backward bifurcation and saddle–node bifurcation when the number of total hospital beds is reduced. Our findings suggest that when the number of total hospital beds falls below a threshold, backward bifurcation will occur, meaning that the disease cannot be eliminated even if the basic reproduction number is below unity. Therefore, the number of hospital beds should be increased beyond the bed threshold during an outbreak of a disease, which has important implications for disease control.

A deterministic Analysis of an Age-Gender structured model for malaria transmission dynamics

Objectives: Children below five years and women especially pregnant women are at high risk of malaria infection and death due to their weak immunity and exposition to mosquitoes. Different studies have been undertaken considering only the age structured model and other factors but did not take into account the gender. The objective of this work is to develop and analyze the malaria transmission model including this structure, to contribute on the existing measures and mechanisms to eradicate malaria in Rwanda.Methods: The dynamic malaria transmission model considering age and gender structure was developed and analyzed. To study the dynamics of disease, the basic reproduction number was analytically computed and numerically estimated and the normalized forward sensitivity index was used to highlight its sensitive parameters.Results: The most positive sensitive parameters in the model are the force of infection and infection rate for vectors and Infection rate for female of 5 years and above. The most negative sensitive parameters are the per capita death rate for vectors and humans.Conclusion: To control the spread of malaria in Rwanda, the biting and infection rate should be decreased.Therefore, women must comply with government measures against malaria and educate children about it.

Optimal control analysis on the spread of COVID-19: Impact of contact transmission and environmental contamination

The study investigates the intricate dynamics of SARS-CoV-2 transmission, with a particular focus on both close-contact interactions and environmental factors. Using advanced mathematical modeling and epidemiological analysis, explored the effects of these transmission pathways on the spread of COVID-19. The equilibrium points for both the disease-free and endemic states calculated and evaluated their global stability. Additionally, the basic reproduction number (R0) is derived to quantify the transmission potential of the virus.To ensure model accuracy, numerical simulations are performed using MATLAB, utilizing daily COVID-19 case data from India. Parameter values are sourced from existing literature, with certain parameters estimated through fitting the model to observed data. Crucially, the model incorporates environmental transmission factors, such as surface contamination and airborne spread. The inclusion of these factors provides a more comprehensive understanding of the virus’s spread, demonstrating the importance of interventions like use of face masks, environmental sanitization, vaccine efficacy, availability of treatment resources underappreciated when focusing solely on direct human contact. A sensitivity analysis is conducted to assess the impact of different parameters on R0, with results visualized through heat maps to identify the most influential factors.Furthermore, Pontryagin’s maximum principle is employed to develop an optimal control model, enabling the formulation of effective intervention strategies. By analysing both interpersonal and environmental transmission mechanisms, this study offers a more holistic framework for understanding SARS-CoV-2 transmission. The insights gained are critical for informing public health strategies, emphasizing the necessity of addressing both direct contact and environmental sources of infection to more effectively manage current and future outbreaks.

Using the basic reproduction ratio to quantify transmission and identify data gaps for epizootic haemorrhagic disease virus.

Epizootic haemorrhagic disease virus (EHDV) is an arbovirus transmitted by Culicoides biting midges that has recently emerged in Europe. Here, the basic reproduction ratio (R 0) was used to quantify the transmission of EHDV and its dependence on temperature for cattle and deer. Using data from the published literature the parameters needed to calculate R 0 were estimated with Bayesian methods to incorporate uncertainty in the calculations. The Sobol method of sensitivity analysis was used to determine the parameters having the greatest influence on R 0 and, hence, to identify important data gaps. Depending on the strain, the maximum R 0 for EHDV varied from 0.7 to 2.5 in cattle and 1.3 to 4.3 in deer. The maximum R 0 occurred at temperatures between 22 and 25°C, while the lowest temperature at which R 0 exceeded one was between 16 and 20°C. The sensitivity analysis identified the threshold temperature for virus replication, the probability of transmission from host to vector and the vector- to- host ratio as the most important parameters influencing R 0. Furthermore, there are only limited data on EHDV in European deer species and on transmission in wildlife and at the livestock/wildlife interface. These data gaps should be the focus of future research.

Epidemiologic Quantities for Monkeypox Virus Clade I from Historical Data with Implications for Current Outbreaks, Democratic Republic of the Congo.

We used published data from outbreak investigations of monkeypox virus clade I in the Democratic Republic of the Congo to estimate the distributions of critical epidemiological parameters. We estimated a mean incubation period of 9.9 days (95% credible interval [CrI] 8.5-11.5 days) and a mean generation time of 17.2 days (95% CrI 14.1-20.9 days) or 11.3 days (95% CrI 9.4-14.0 days), depending on the considered dataset. Presymptomatic transmission was limited. Those estimates suggest generally slower transmission dynamics in clade I than in clade IIb. The time-varying reproduction number for clade I in the Democratic Republic of the Congo was estimated to be below the epidemic threshold in the first half of 2024. However, in the South Kivu Province, where the newly identified subclade Ib has been associated with sustained human-to-human transmission, we estimated an effective reproduction number above the epidemic threshold (95% CrI 0.96-1.27).