Journal of Biosafety and Biosecurity最新文献

In the spread of infectious diseases, intervention levels play a crucial role in shaping interactions between healthy and infected individuals, leading to a nonlinear transmission process. Additionally, the availability of medical resources limits the recovery rate of infected patients, adding further nonlinear dynamics to the healing process. Our research introduces novelty by combining nonlinear incidence and recovery rates alongside waning immunity in an epidemic model. We present a modified SIRW-type model, examining the epidemic problem with these factors. Through analysis, we explore conditions for non-endemic and co-existing cases based on the basic reproduction ratio. The local stability of equilibria is verified using the Routh-Hurwitz criteria, while global stability is assessed using Lyapunov functions for each equilibrium. Furthermore, we investigate bifurcations around both non-endemic and co-existing equilibria. Numerically, we give some simulations to support our analytical findings.

Background

Candida species are the fourth most common etiological agents of late-onset infection in the neonatal intensive care unit (NICU) and are responsible for considerable morbidity and mortality.

Objectives

From November 2023 to February 2024, we investigated the association of mycotic pneumonia with septicemia in 60 neonates, and their roles of mycotic pneumonia in the morbidity and mortality of neonates in two NICUs in the Al-Ramadi Teaching Hospital for Maternity and Children.

Methods

All infants in this study had been diagnosed with septicemia and treated with empirical antimicrobial therapy. An early morning nasogastric tube (NG-tube) was used to collect swallowed sputum by suction for culture and sensitivity testing.

Results

The average white blood count for the neonates was 8547 ± 5884.5 cells/mm². The mean C-reactive protein was 39.3 ± 26 mg/l, the mean serum albumin was 2.9 ± 0.2 g/dl and the positive bacterial blood culture was 28 (46.7 %). 9 (15 %) neonates died during the study period. The NG-tube culture identified fungal growth in all samples. Of these, 49 (81.6 %) were identified as Candida albicans, 6 (10 %) as Candida tropicalis, and 5 (8.3 %) as Cryptococcus laurentii. The bacterial culture results from the NG-tube samples identified 13 (21.6 %) patients with gram-positive bacteria and 47 (78.3 %) with gram-negative bacteria.

Conclusion

We found a prevalence of Candida spp. among neonates in addition to microbial oxygen tube contamination, indicating a biosafety breach in the neonatal unit. Mycotic infection requires global attention as a probable cause of respiratory failure in neonatal septicemia.

Outbreaks of Monkeypox (mpox) in over 100 non-endemic countries in 2022 represented a serious global health concern. Once a neglected disease, mpox has become a global public health issue. A42R profilin-like protein from mpox (PDB ID: 4QWO) represents a potential new lead for drug development and may interact with various synthetic and natural compounds. In this report, the interaction of A42R profilin-like protein with six phytochemicals found in the medicinal plant Ficus religiosa (abundant in India) was examined. Based on the predicted and compared protein–ligand binding energies, biological properties, IC₅₀ values and toxicity, two compounds, kaempferol (C-1) and piperine (C-4), were selected. ADMET characteristics and quantitative structure–activity relationship (QSAR) of these two compounds were determined, and molecular dynamics (MD) simulations were performed. In silico examination of the kaempferol (C-1) and piperine (C-4) interactions with A42R profilin-like protein gave best-pose ligand-binding energies of –6.98 and –5.57 kcal/mol, respectively. The predicted IC₅₀ of C-1 was 7.63 μM and 82 μM for C-4. Toxicity data indicated that kaempferol and piperine are non-mutagenic, and the QSAR data revealed that piperlongumine (5.92) and piperine (5.25) had higher log P values than the other compounds examined. MD simulations of A42R profilin-like protein in complex with C-1 and C-4 were performed to examine the stability of the ligand–protein interactions. As/C and C-4 showed the highest affinity and activities, they may be suitable lead candidates for developing mpox therapeutic drugs. This study should facilitate discovering and synthesizing innovative therapeutics to address other infectious diseases.

The co-infection of HIV and COVID-19 is a pressing health concern, carrying substantial potential consequences. This study focuses on the vital task of comprehending the dynamics of HIV-COVID-19 co-infection, a fundamental step in formulating efficacious control strategies and optimizing healthcare approaches. Here, we introduce an innovative mathematical model grounded in Caputo fractional order differential equations, specifically designed to encapsulate the intricate dynamics of co-infection. This model encompasses multiple critical facets: the transmission dynamics of both HIV and COVID-19, the host’s immune responses, and the influence of treatment interventions. Our approach embraces the complexity of these factors to offer an exhaustive portrayal of co-infection dynamics. To tackle the fractional order model, we employ the Laplace-Adomian decomposition method, a potent mathematical tool for approximating solutions in fractional order differential equations. Utilizing this technique, we simulate the intricate interactions between these variables, yielding profound insights into the propagation of co-infection. Notably, we identify pivotal contributors to its advancement. In addition, we conduct a meticulous analysis of the convergence properties inherent in the series solutions acquired through the Laplace-Adomian decomposition method. This examination assures the reliability and accuracy of our mathematical methodology in approximating solutions. Our findings hold significant implications for the formulation of effective control strategies. Policymakers, healthcare professionals, and public health authorities will benefit from this research as they endeavor to curtail the proliferation and impact of HIV-COVID-19 co-infection.

Background

This study represents the first Spanish investigation to rigorously evaluate compliance with the use of safety goggles and face masks as essential personal protective equipment (PPE) in companies with workplaces involving exposure to biological agents.

Objectives

This study aimed to examine the degree of use of face masks and safety goggles as personal protective equipment (PPE), the factors that influence their use, and the profile of workers exposed to occupational biological agents in Spanish companies in the health sector, farming sector, meat industry, waste treatment plants, food industry, and veterinary centers.

Methods

We conducted a cross-sectional descriptive study involving 590 Spanish workers from 51 companies. We developed a 34-item questionnaire to assess workers’ perception of risk related to exposure to biological agents in their workplaces. Among the questions, three were designed to measure the degree of use of key protective equipment in sectors with biological agent exposure: protective gloves, safety goggles or face masks. We only analyzed safety goggles and face masks. We performed various statistical analyses, including Cronbach’s alpha, frequency of endorsement, content validity ratio using Lawshe’s method, varimax rotation, the Kaiser-Meyer-Olkin test, and Bartlett’s sphericity test, to assess the internal consistency and reliability of the questionnaire. Additionally, we employed a chi-square automatic interaction detection (CHAID) segmentation analysis, using workers’ responses regarding their attitudes toward safety goggles and face mask usage as PPE for protection against biological risks, with demographic variables as independent factors.

Results

In the current study, CHAID analysis revealed that workers exposed to group 2 biological agents used more safety goggles and face shields compared with workers exposed to other groups of biological agents. Moreover, workers in laboratories and the food industry used face masks more than workers of other sectors.

Conclusion

The CHAID analysis in the current study indicated that workers exposed to biological agents from both group 2 and group 3 demonstrated satisfactory levels of compliance and utilization of protective masks, surpassing their counterparts in terms of usage. Workers in the food and laboratory industries had subpar compliance with preventive measures, and employees from companies with internal health and safety departments exhibited significant adherence to workplace mask usage, safeguarding themselves against biological risks.

In this paper, we study the dynamics of the CoVid-19 outbreak in Semarang, Indonesia, using a fractional CoVid-19 model. We first determine the effects of the isolation rate $∊$ and infection rate $\beta$ on the reproduction number $R_0$ and infected number V. We find that $R_0$ is directly proportional to $\beta$ and inversely proportional to $∊$. For V, the effect of physical distancing is not as significant as changing $∊$. As $∊$ increases, V decreases, the number of susceptible individuals increases, the number of quarantined individuals decreases sharply, and the number of recovered individuals decreases. Moreover, the effect of vaccination is also considered. The combination of physical distancing, isolation, and vaccination has a significant impact on reducing the number of infected individuals. Analysis of dynamical systems allows us to understand the characteristics of our model, such as its boundedness and non-negativity, the existence of equilibrium points, the existence and uniqueness of solutions, and the local and global stability. To validate our fractional CoVid-19 model, we introduce the fractional extended Kalman filter (FracEKF) as a prediction method and compare the results against reported CoVid-19 data. FracEKF is a modified version of the basic extended Kalman filter with a time-fractional memory effect. The prediction results illustrate the accuracy of this model in terms of the root mean square error (RMSE), normalized root mean square error (NRMSE), and mean absolute percentage error (MAPE) for each fractional-order. Varying $∊$ reproduces the trends observed in the reported data for the number of infected individuals, i.e., when $∊$ increases, the infected number decreases. Moreover, a higher fractional-order results in higher model accuracy. Furthermore, higher values of the process noise $Q_f$ give smaller errors, whereas higher values of the observation noise $R_f$ produce higher errors. $Q_f$ and the fractional-order $\alpha$ are inversely proportional to