A stochastically perturbed co-infection epidemic model for COVID-19 and hepatitis B virus.

A new co-infection model for the transmission dynamics of two virus hepatitis B (HBV) and coronavirus (COVID-19) is formulated to study the effect of white noise intensities. First, we present the model equilibria and basic reproduction number. The local stability of the equilibria points is proved. Moreover, the proposed stochastic model has been investigated for a non-negative solution and positively invariant region. With the help of Lyapunov function, analysis was performed and conditions for extinction and persistence of the disease based on the stochastic co-infection model were derived. Particularly, we discuss the dynamics of the stochastic model around the disease-free state. Similarly, we obtain the conditions that fluctuate at the disease endemic state holds if min ( R H s , R C s , R HC s ) > 1 . Based on extinction as well as persistence some conditions are established in form of expression containing white noise intensities as well as model parameters. The numerical results have also been used to illustrate our analytical results.

The impact of behavioral interventions on co-infection dynamics: An exploration of the effects of home isolation.

Behavioral epidemiology, the field aiming to determine the impact of individual behavior on the spread of an epidemic, has gained increased recognition during the last few decades. Behavioral changes due to the development of symptoms have been studied in mono-infections. However, in reality, multiple infections are circulating within the same time period and behavioral changes resulting from contraction of one of the diseases affect the dynamics of the other. The present study aims at assessing the effect of home isolation on the joint dynamics of two infectious diseases, including co-infection, assuming that the two diseases do not confer cross-immunity. We use an age- and time- structured co-infection model based on partial differential equations. Social contact matrices, describing different mixing patterns of symptomatic and asymptomatic individuals are incorporated into the calculation of the age- and time-specific marginal forces of infection. Two scenarios are simulated, assuming that one of the diseases has more severe symptoms than the other. In the first scenario, people stay only at home when having symptoms of the most severe disease. In the second scenario, twice as many people stay at home when having symptoms of the most severe disease than when having symptoms of the other disease. The results show that the impact of home isolation on the joint dynamics of two infectious diseases depends on the epidemiological parameters and properties of the diseases (e.g., basic reproduction number, symptom severity). In case both diseases have a low to moderate basic reproduction number, and there is no home isolation for the less severe disease, the final size of the less severe disease increases with the proportion of symptomatic cases of the most severe disease staying at home, after an initial decrease. This counterintuitive result could be explained by a shift in the peak time of infection of the disease with the most severe symptoms, resulting in a smaller number of people with less contacts at the peak time of the other infection. When twice as many people stay at home when having symptoms of the most severe disease than when having symptoms of the other disease, increasing the proportion staying at home always reduces the final size of both diseases, and the number of co-infections. In conclusion, when providing advise if people should stay at home in the context of two or more co-circulating diseases, one has to take into account epidemiological parameters and symptom severity.

Assessment of Mycoplasma gallisepticum vaccine efficacy in a co-infection challenge model with QX-like infectious bronchitis virus.

Mycoplasma gallisepticum (MG) is the primary cause of chronic respiratory disease in poultry. We investigated the protective efficacy of the live-attenuated ts-11 and 6/85 MG vaccines against a local MG strain and, in order to enhance signs and mimic a typical field situation, we co-infected birds with a virulent strain of QX-like infectious bronchitis virus (IBV). Both vaccines showed similar ability to protect infected chickens from clinical signs, although ts-11 performed slightly better. Despite the lower protection against clinical disease, 6/85-vaccinated birds had significantly (P ≤ 0.05) lower tracheal lesion scores and mucosal thickness at day 28 post-vaccination (7 days post-challenge [dpc] with MG, 2 dpc IBV) and day 31 post-vaccination (10 dpc MG challenge, 5 dpc IBV) compared to ts-11 vaccinated birds, but these difference was not significant at day 33 (12 dpc MG, 7 dpc IBV). Pathogen infection and replication was assessed by qPCR, and the 6/85 vaccine produced a more significant (P ≤ 0.05) reduction in MG replication in the lungs, kidneys and livers but enhanced late replication in bursae and caecal tonsils. In contrast, the ts-11 vaccine had a more pronounced reductive effect on replication in tracheas, air sacs, bursae and heart at days 28 and 31, yet increased replication in lungs. Interestingly, both vaccines provided non-specific protection against IBV challenge. The co-challenge model provided useful data on vaccine efficacy, especially on days 31 and 33, and tracheas, lungs, air sacs, kidneys, liver and caecal tonsils were the best organs to assess.

Wavelet Collocation Method for HIV-1/HTLV-I Co-Infection Model Using Hermite Polynomial.

In this study, the dynamic behavior of fractional order co-infection model with human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) is analyzed using operational matrix of Hermite wavelet collocation method. Also, the uniqueness and existence of solutions are calculated based on the fixed point hypothesis. For the fractional order co-infection model, its positivity and boundedness are demonstrated. Furthermore, different types of Ulam-Hyres stability are also discussed. The numerical solution of the model are obtained by using the operational matrix of the Hermite wavelet approach. This scheme is used to solve the system of nonlinear equations that are very fruitful and easy to implement. Additionally, the stability analysis of the numerical scheme is explained. The mathematical model taken in this work incorporates the biological characteristics of both HIV-1 and HTLV-I. After that all the equilibrium points of the fractional order co-infection model are found and their existence conditions are explored with the help of the Caputo derivative. The global stability of all equilibrium points of this model are determined with the help of Lyapunov functions and the LaSalle invariance principle. Convergence analysis is also discussed. Hermite wavelet operational matrix methods are more accurate and convergent than other numerical methods. Lastly, variations in model dynamics are found when examining different fractional order values. These findings will be valuable to biologists in the treatment of HIV-1/HTLV-I.

Comments on "Optimal control analysis of a COVID-19 and tuberculosis co-dynamics model".

Study of dynamics of COVID-19 and its co-infection with other diseases through mathematical models is the major focus of recent advancement in mathematical modeling of infectious diseases. There are numerous mathematical models on COVID-19 which describe its dynamics for different geographic regions. However, there are very few research papers dealing with co-infection of COVID-19 and TB. As both TB and COVID-19 are infectious diseases of same nature it becomes very difficult to predict the co-dynamics of these two diseases. The formulation of a correct mathematical model is very important in any kind of modeling and if the mathematical model is not proper then any prediction based on this may not be valid. This letter highlights the important limitations in the proposed mathematical model of co-dynamics of COVID-19 and TB by [1].

Experimental infection of high health pigs with porcine circovirus type 2 (PCV2) and Lawsonia intracellularis.

Background: Porcine circovirus type 2 (PCV2) and Lawsonia intracellularis infections can cause enteritis in pigs. A Danish study showed a significantly higher probability of detecting PCV2 without concurrent L. intracellularis infection, indicating that one of these pathogens has an impact on the dynamics of the other. Therefore, a delayed co-infection model was set up, initially aiming at investigating the interaction between PCV2 and L. intracellularis in pigs challenged with PCV2 and 2 weeks later with L. intracellularis. But due to PCV2 contamination of the L. intracellularis inoculum the aim was revisited to describing the infection dynamics and pathogenesis of pigs infected with PCV2 followed by delayed simultaneous exposure to PCV2 and L. intracellularis. Twenty-four high-health piglets were divided into three groups of eight pigs (A, B, C) and inoculated at experimental day (EXD) 0 with mock (groups A and B) or PCV2 (group C), and at EXD 14 with mock (group A) or L. intracellularis/PCV2 (groups B and C). The pigs underwent daily clinical examination, and were necropsied at EXD 51-52. Furthermore, histology, immunohistochemistry, serology and PCR for PCV2 and L. intracellularis, and measurement of C-reactive protein were carried out. Results: Group A remained negative for PCV2 and L. intracellularis. Following inoculation with L. intracellularis/PCV2, no significant differences were observed between group B and C, however pigs already infected with PCV2 (group C) showed milder clinical signs and exhibited milder intestinal lesions, less shedding of L. intracellularis and developed higher L. intracellularis antibody titers than the pigs in group B that only received the combined infection. Though the differences between group B and C were non-significant, all results pointed in the same direction, indicating that the pigs in group B were more affected by the L. intracellularis infection compared to the pigs in group C. Conclusions: Previous exposure to PCV2 had limited impact on the subsequent exposure to a combined L. intracellularis/PCV2 inoculation. However, there was a tendency that the infection dynamics of PCV2 and development of antibodies to PCV2 and L. intracellularis were altered in pigs previously exposed to PCV2. These differences should be confirmed in further experimental trials.

COVID-19 co-infection mathematical model as guided through signaling structural framework.

SARS-CoV-2 and Influenza co-infection turned out to be a huge threat in recent times. The clinical presentation and disease severity is common in both the infection condition. The present paper deals with studying co-infection model system through systems biology approaches. Understanding signaling regulation in COVID-19 and co-infection model systems aid in the development of network-based models thereby suggesting intervention points for therapeutics. This paper highlights the aim of revealing such perturbations to decipher opportune mediating cross talks characterizing the deadly viral disease. The comparative analysis of both the models reveals major signaling protein NFκB and STAT1 playing a crucial role in establishing co-infection. By targeting these proteins at cellular level, it might help modulating the release of potent pro-inflammatory cytokines thereby taming the severity of the disease symptoms. Mathematical models developed here are precisely tailored and serves as a first step towards co-infection model offering flexibility and pitching towards therapeutic investigation.