Co-infection Model Research Articles

Deterministic and Fractional-Order Co-Infection Model of Omicron and Delta Variants of Asymptomatic SARS-CoV-2 Carriers

The Delta and Omicron variants’ system was used in this research study to replicate the complex process of the SARS-CoV-2 outbreak. The generalised fractional system was designed and rigorously analysed in order to gain a comprehensive understanding of the transmission dynamics of both variants. The proposed dynamical system has heredity and memory effects, which greatly improved our ability to perceive the disease propagation dynamics. The non-singular Atangana–Baleanu fractional operator was used to forecast the current pandemic in order to meet this challenge. The Picard recursions approach can be used to ensure that the designed fractional system has at least one solution occupying the growth condition and memory function regardless of the initial conditions. The Hyers–Ulam–Rassias stability criteria were used to carry out the stability analysis of the fractional governing system of equations, and the fixed-point theory ensured the uniqueness of the solution. Additionally, the model exhibited global asymptotically stable behaviour in some conditions. The approximate behaviour of the fatal virus was investigated using an efficient and reliable fractional numerical Adams–Bashforth approach. The outcome demonstrated that there will be a significant decline in the population of those infected with the Omicron and Delta SARS-CoV-2 variants if the vaccination rate is increased (in both the symptomatic and symptomatic stages).

The Synergy of Chicken Anemia Virus and Gyrovirus Homsa 1 in Chickens.

Chicken anemia virus (CAV) and Gyrovirus homsa 1 (GyH1) are members of the Gyrovirus genus. The two viruses cause similar clinical manifestations in chickens, aplastic anemia and immunosuppression. Our previous investigation displays that CAV and GyH1 often co-infect chickens. However, whether they have synergistic pathogenicity in chickens remains elusive. Here, we established a co-infection model of CAV and GyH1 in specific pathogen-free (SPF) chickens to explore the synergy between CAV and GyH1. We discovered that CAV and GyH1 significantly inhibited weight gain, increased mortality, and hindered erythropoiesis in co-infected chickens. Co-infected chickens exhibited severe immune organ atrophy and lymphocyte exhaustion. The proventriculus and gizzard had severe hemorrhagic necrosis and inflammation. We also discovered that the viral loads and shedding levels were higher and lasted longer in CAV and GyH1 co-infected chickens than in mono-infected chickens. Our results demonstrate that CAV and GyH1 synergistically promote immunosuppression, pathogenicity, and viral replication in co-infected chicken, highlighting the interaction between CAV and GyH1 in the disease process and increasing potential health risk in the poultry breeding industry, and needs further attention.

Stochastic dynamical analysis of the co-infection of the fractional pneumonia and typhoid fever disease model with cost-effective techniques and crossover effects

In this paper, we suggest and assess a stochastic model for pneumonia-typhoid co-infection to investigate their distinctive correlation under the impact of preventative techniques considering environmental noise and piecewise fractional derivative operators. Initially, we conducted a descriptive investigation of the model, and the basic reproductive number is defined in terms of the existence and stability of dynamic equilibrium. Then, we obtain the sufficient requirements for the existence of an ergodic stationary distribution by utilizing a novel methodology for constructing stochastic Lyapunov candidates. Besides that, the basic stochastic reproductive R0s as a threshold that will examine the extinction and persistence of the disease. Through a rigorous analysis, this study presents the concept of piecewise derivative with the goal of modelling the co-dynamics of pneumonia and typhoid fever with varying kernels. We viewed various possibilities and described numerical strategies for addressing difficulties. Visual observations, such as chaotic and dynamical behaviour patterns, are provided to demonstrate the efficacy of the proposed notion. Thus, the innovative considerations of fractional calculus include more versatile configurations, allowing us to more effectively acclimate to the dynamic system behaviours of real-world manifestations. Finally, we discovered that treating pneumonia with typhoid fever preventative measures is the least expensive. As a result, for advantageous and cost-effective regulation of both pathogens, legislators must prioritize preventative measures while not overlooking treatment of affected patients.

Modeling Syphilis and HIV Coinfection: A Case Study in the USA.

Syphilis and HIV infections form a dangerous combination. In this paper, we propose an epidemic model of HIV-syphilis coinfection. The model always has a unique disease-free equilibrium, which is stable when both reproduction numbers of syphilis and HIV are less than 1. If the reproduction number of syphilis (HIV) is greater than 1, there exists a unique boundary equilibrium of syphilis (HIV), which is locally stable if the invasion number of HIV (syphilis) is less than 1. Coexistence equilibrium exists and is stable when all reproduction numbers and invasion numbers are greater than 1. Using data of syphilis cases and HIV cases from the US, we estimated that both reproduction numbers for syphilis and HIV are slightly greater than 1, and the boundary equilibrium of syphilis is stable. In addition, we observed competition between the two diseases. Treatment for primary syphilis is more important in mitigating the transmission of syphilis. However, it might lead to increase of HIV cases. The results derived here could be adapted to other multi-disease scenarios in other regions.

COVID-19 and syphilis co-dynamic analysis using mathematical modeling approach

In this study, we have proposed and analyzed a new COVID-19 and syphilis co-infection mathematical model with 10 distinct classes of the human population (COVID-19 protected, syphilis protected, susceptible, COVID-19 infected, COVID-19 isolated with treatment, syphilis asymptomatic infected, syphilis symptomatic infected, syphilis treated, COVID-19 and syphilis co-infected, and COVID-19 and syphilis treated) that describes COVID-19 and syphilis co-dynamics. We have calculated all the disease-free and endemic equilibrium points of single infection and co-infection models. The basic reproduction numbers of COVID-19, syphilis, and COVID-19 and syphilis co-infection models were determined. The results of the model analyses show that the COVID-19 and syphilis co-infection spread is under control whenever its basic reproduction number is less than unity. Moreover, whenever the co-infection basic reproduction number is greater than unity, COVID-19 and syphilis co-infection propagates throughout the community. The numerical simulations performed by MATLAB code using the ode45 solver justified the qualitative results of the proposed model. Moreover, both the qualitative and numerical analysis findings of the study have shown that protections and treatments have fundamental effects on COVID-19 and syphilis co-dynamic disease transmission prevention and control in the community.

Dynamic Behaviors of a COVID-19 and Influenza Co-Infection Model with Time Delays and Humoral Immunity

Co-infections with respiratory viruses were reported in hospitalized patients in several cases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A virus (IAV) are two respiratory viruses and are similar in terms of their seasonal occurrence, clinical manifestations, transmission routes, and related immune responses. SARS-CoV-2 is the cause of coronavirus disease 2019 (COVID-19). In this paper, we study the dynamic behaviors of an influenza and COVID-19 co-infection model in vivo. The role of humoral (antibody) immunity in controlling the co-infection is modeled. The model considers the interactions among uninfected epithelial cells (ECs), SARS-CoV-2-infected ECs, IAV-infected ECs, SARS-CoV-2 particles, IAV particles, SARS-CoV-2 antibodies, and IAV antibodies. The model is given by a system of delayed ordinary differential equations (DODEs), which include four time delays: (i) a delay in the SARS-CoV-2 infection of ECs, (ii) a delay in the IAV infection of ECs, (iii) a maturation delay of newly released SARS-CoV-2 virions, and (iv) a maturation delay of newly released IAV virions. We establish the non-negativity and boundedness of the solutions. We examine the existence and stability of all equilibria. The Lyapunov method is used to prove the global stability of all equilibria. The theoretical results are supported by performing numerical simulations. We discuss the effects of antiviral drugs and time delays on the dynamics of influenza and COVID-19 co-infection. It is noted that increasing the delay length has a similar influence to that of antiviral therapies in eradicating co-infection from the body.

Global Dynamics of an HTLV-I and SARS-CoV-2 Co-Infection Model with Diffusion

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel respiratory virus that causes coronavirus disease 2019 (COVID-19). Symptoms of COVID-19 range from mild to severe illness. It was observed that disease progression in COVID-19 patients depends on their immune response, especially in elderly patients whose immune system suppression may put them at increased risk of infection. Human T-cell lymphotropic virus type-I (HTLV-I) attacks the CD4+ T cells (T cells) of the immune system and leads to immune dysfunction. Co-infection with HTLV-I and SARS-CoV-2 has been reported in recent studies. Modeling HTLV-I and SARS-CoV-2 co-infection can be a helpful tool to understand the in-host co-dynamics of these viruses. The aim of this study was to construct a model that characterizes the in-host dynamics of HTLV-I and SARS-CoV-2 co-infection. By considering the mobility of the viruses and cells, the model is represented by a system of partial differential equations (PDEs). The system contains two independent variables, time t and position x, and seven dependent variables for representing the densities of healthy epithelial cells (ECs), latent SARS-CoV-2-infected ECs, active SARS-CoV-2-infected ECs, SARS-CoV-2, healthy T cells, latent HTLV-I-infected T cells and active HTLV-I-infected T cells. We first studied the fundamental properties of the solutions of the system, then deduced all steady states and proved their global properties. We examined the global stability of the steady states by constructing appropriate Lyapunov functions. The analytical results were illustrated by performing numerical simulations. We discussed the effect of HTLV-I infection on COVID-19 progression. The results suggest that patients with HTLV-I have a weakened immune response; consequently, their risk of COVID-19 infection may be increased.

Hepatitis D virus interferes with hepatitis B virus RNA production via interferon-dependent and -independent mechanisms

Chronic coinfection with HBV and HDV leads to the most aggressive form of chronic viral hepatitis. Herein, we aimed to elucidate the molecular mechanisms underlying the widely reported observation that HDV interferes with HBV in most coinfected patients. Patient liver tissues, primary human hepatocytes, HepaRG cells and human liver chimeric mice were used to analyze the effect of HDV on HBV using virological and RNA-sequencing analyses, as well as RNA synthesis, stability and association assays. Transcriptomic analyses in cell culture and mouse models of coinfection enabled us to define an HDV-induced signature, mainly composed of interferon (IFN)-stimulated genes (ISGs). We also provide evidence that ISGs are upregulated in chronically HDV/HBV-coinfected patients but not in cells that only express HDV antigen (HDAg). Inhibition of the hepatocyte IFN response partially rescued the levels of HBV parameters. We observed less HBV RNA synthesis upon HDV infection or HDV protein expression. Additionally, HDV infection or expression of HDAg alone specifically accelerated the decay of HBV RNA, and HDAg was associated with HBV RNAs. On the contrary, HDAg expression did not affect other viruses such as HCV or SARS-CoV-2. Our data indicate that HDV interferes with HBV through both IFN-dependent and IFN-independent mechanisms. Specifically, we uncover a new viral interference mechanism in which proteins of a satellite virus affect the RNA production of its helper virus. Exploiting these findings could pave the way to the development of new therapeutic strategies against HBV. Although the molecular mechanisms remained unexplored, it has long been known that despite its dependency, HDV decreases HBV viremia in patients. Herein, using invitro and invivo models, we showed that HDV interferes with HBV through both IFN-dependent and IFN-independent mechanisms affecting HBV RNA metabolism, and we defined the HDV-induced modulation signature. The mechanisms we uncovered could pave the way for the development of new therapeutic strategies against HBV by mimicking and/or increasing the effect of HDAg on HBV RNA. Additionally, the HDV-induced modulation signature could potentially be correlated with responsiveness to IFN-α treatment, thereby helping to guide management of HBV/HDV-coinfected patients.

Effect of Macrophages and Latent Reservoirs on the Dynamics of HTLV-I and HIV-1 Coinfection

Human immunodeficiency virus type 1 (HIV-1) and human T-lymphotropic virus type I (HTLV-I) are two retroviruses that have a similar fashion of transmission via sharp objects contaminated by viruses, transplant surgery, transfusion, and sexual relations. Simultaneous infections with HTLV-I and HIV-1 usually occur in areas where both viruses have become endemic. CD4+T cells are the main targets of HTLV-I, while HIV-1 can infect CD4+T cells and macrophages. It is the aim of this study to develop a model of HTLV-I and HIV-1 coinfection that describes the interactions of nine compartments: susceptible cells of both CD4+T cells and macrophages, HIV-1-infected cells that are latent/active in both CD4+T cells and macrophages, HTLV-I-infected CD4+T cells that are latent/active, and free HIV-1 particles. The well-posedness, existence of equilibria, and global stability analysis of our model are investigated. The Lyapunov function and LaSalle’s invariance principle were used to study the global asymptotic stability of all equilibria. The theoretically predicted outcomes were verified by utilizing numerical simulations. The effect of including the macrophages and latent reservoirs in the HTLV-I and HIV-1 coinfection model is discussed. We show that the presence of macrophages makes a coinfection model more realistic when the case of the coexistence of HIV-1 and HTLV-I is established. Moreover, we have shown that neglecting the latent reservoirs in HTLV-I and HIV-1 coinfection modeling will lead to the design of an overflow of anti-HIV-1 drugs.

Pathogenicity of duck circovirus and fowl adenovirus serotype 4 co-infection in Cherry Valley ducks

Duck circovirus (DuCV) is one of the most prevalent infectious viruses in the duck industry in China. Although the clinical symptoms vary, it often causes immunosuppression in the host and leads to secondary infection with other pathogens. Fowl adenovirus serotype 4 (FAdV-4) mainly infects chickens and causes hydropericardium hepatitis syndrome. However, the incidence of infection in ducks has increased in recent years, and the phenomenon of mixed infection with DuCV is very common, resulting in more severe clinical morbidity. However, there is no systematic study evaluating the presence of mixed infection. To explore the synergistic pathogenicity of DuCV and FAdV-4 co-infection in Cherry Valley ducks, a comparative experiment was established between DuCV and FAdV-4 co-infection and single infection animal models. It was found that DuCV and FAdV-4 co-infected ducks showed more pronounced clinical signs of pericardial effusion, hepatitis and immunosuppression; more severe tissue damage in target organs; and more significant levels of viral load, biochemical indicators and immune indicators in various organs compared with Cherry Valley ducks infected with just one virus. The results showed that co-infection with DuCV and FAdV-4 may promote greater viral replication, causing more severe tissue damage and immunosuppression than infection with just one virus. Therefore, the monitoring and prevention of the two viruses should be strengthened clinically, with a particular focus on the potential harm of DuCV as it carries the highest infection rate.

Rhinovirus increases Moraxella catarrhalis adhesion to the respiratory epithelium.

Rhinovirus causes many types of respiratory illnesses, ranging from minor colds to exacerbations of asthma. Moraxella catarrhalis is an opportunistic pathogen that is increased in abundance during rhinovirus illnesses and asthma exacerbations and is associated with increased severity of illness through mechanisms that are ill-defined. We used a co-infection model of human airway epithelium differentiated at the air-liquid interface to test the hypothesis that rhinovirus infection promotes M. catarrhalis adhesion and survival on the respiratory epithelium. Initial experiments showed that infection with M. catarrhalis alone did not damage the epithelium or induce cytokine production, but increased trans-epithelial electrical resistance, indicative of increased barrier function. In a co-infection model, infection with the more virulent rhinovirus-A and rhinovirus-C, but not the less virulent rhinovirus-B types, increased cell-associated M. catarrhalis. Immunofluorescent staining demonstrated that M. catarrhalis adhered to rhinovirus-infected ciliated epithelial cells and infected cells being extruded from the epithelium. Rhinovirus induced pronounced changes in gene expression and secretion of inflammatory cytokines. In contrast, M. catarrhalis caused minimal effects and did not enhance RV-induced responses. Our results indicate that rhinovirus-A or C infection increases M. catarrhalis survival and cell association while M. catarrhalis infection alone does not cause cytopathology or epithelial inflammation. Our findings suggest that rhinovirus and M. catarrhalis co-infection could promote epithelial damage and more severe illness by amplifying leukocyte inflammatory responses at the epithelial surface.

Mathematical Model for Coinfection of HIV/AIDS and Kaposi’s Sarcoma with Treatment

HIV destroys T-cells in order to target the body's defence mechanism. Without treatment HIV infection advances in stages causing destruction and reduction in T-cells thus, rendering the body incapable of fighting other infections such as respiratory infections, sexually transmitted diseases and some cancers. Kaposi’s sarcoma is the cancer that allows a tumour to grow in an HIV patient and its presence in a patient is an indication that HIV has fully developed into AIDS in the patient. Research has indicated that AIDS-associated Kaposi Sarcoma was on the rise in sub-Saharan Africa until the introduction of Antiretroviral Therapy (ART). The Kenyan community has struggled in the past decade to combat the spread of HIV/AIDS and successes have been recorded in many areas. However, Kaposi Sarcoma, an opportunistic infection, has continued to rise steadily through the years. In this study, a simple model for the coinfection of HIV/AIDS and KS is developed and studied. The model solution is explored for positivity and boundedness while the DFE point is determined for stability where it was verified that the infection-free equilibrium <I>E</I>₀ is locally asymptotically stable when <img width="40" height="10" src="http://article.sciencepublishinggroup.com/journal/247/2471233/image001.png" />. The NGM is used to derive the basic reproduction number of the model. By providing treatment to the HIV and the co-infected population immune system is strengthened and thus progression rate to AIDS is reduced.

The Staphylococcus aureus protein IsdA increases SARS CoV-2 replication by modulating JAK-STAT signaling

The Severe Acute Respiratory Syndrome Coronavirus 2 (CoV-2) pandemic has affected millions globally. A significant complication of CoV-2 infection is secondary bacterial co-infection, as seen in approximately 25% of severe cases. The most common organism isolated during co-infection is Staphylococcus aureus. Here, we describe the development of an invitro co-infection model where both viral and bacterial replication kinetics may be examined. We demonstrate CoV-2 infection does not alter bacterial interactions with host epithelial cells. In contrast, S.aureus enhances CoV-2 replication by 10- to 15-fold. We identify this pro-viral activity is due to the S.aureus iron-regulated surface determinant A (IsdA) protein and demonstrate IsdA modifies host transcription. We find that IsdA alters Janus Kinase- Signal Transducer and Activator of Transcription (JAK-STAT) signaling, by affecting JAK2-STAT3 levels, ultimately leading to increased viral replication. These findings provide key insight into the molecular interactions between host cells, CoV-2 and S.aureus during co-infection.

Niche theory for within‐host parasite dynamics: Analogies to food web modules via feedback loops

Why do parasites exhibit a wide dynamical range within their hosts? For instance, why does infecting dose either lead to infection or immune clearance? Why do some parasites exhibit boom-bust, oscillatory dynamics? What maintains parasite diversity, that is coinfection v single infection due to exclusion or priority effects? For insights on parasite dose, dynamics and diversity governing within-host infection, we turn to niche models. An omnivory food web model (IGP) blueprints one parasite competing with immune cells for host energy (PIE). Similarly, a competition model (keystone predation, KP) mirrors a new coinfection model (2PIE). We then drew analogies between models using feedback loops. The following three points arise: first, like in IGP, parasites oscillate when longer loops through parasites, immune cells and resource regulate parasite growth. Shorter, self-limitation loops (involving resources and enemies) stabilise those oscillations. Second, IGP can produce priority effects that resemble immune clearance. But, despite comparable loop structure, PIE cannot due to constraints imposed by production of immune cells. Third, despite somewhat different loop structure, KP and 2PIE share apparent and resource competition mechanisms that produce coexistence (coinfection) or priority effects of prey or parasites. Together, this mechanistic niche framework for within-host dynamics offers new perspective to improve individual health.

Decoding the double trouble: A mathematical modelling of co-infection dynamics of SARS-CoV-2 and influenza-like illness

After the detection of coronavirus disease 2019 (Covid-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, Hubei Province, China in late December, the cases of Covid-19 have spiralled out around the globe. Due to the clinical similarity of Covid-19 with other flulike syndromes, patients are assayed for other pathogens of influenza like illness. There have been reported cases of co-infection amongst patients with Covid-19. Bacteria for example Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, Mycoplasma pneumoniae, Chlamydia pneumonia, Legionella pneumophila etc and viruses such as influenza, coronavirus, rhinovirus/enterovirus, parainfluenza, metapneumovirus, influenza B virus etc are identified as co-pathogens.In our current effort, we develop and analysed a compartmental based Ordinary Differential Equation (ODE) type mathematical model to understand the co-infection dynamics of Covid-19 and other influenza type illness. In this work we have incorporated the saturated treatment rate to take account of the impact of limited treatment resources to control the possible Covid-19 cases.As results, we formulate the basic reproduction number of the model system. Finally, we have performed numerical simulations of the co-infection model to examine the solutions in different zones of parameter space.

Investigating the Effects of Intervention Strategies on Pneumonia and HIV/AIDS Coinfection Model

HIV/AIDS and pneumonia coinfection have imposed a major socioeconomic and health burden throughout the world, especially in the developing countries. In this study, we propose a compartmental epidemic model on the spreading dynamics of HIV/AIDS and pneumonia coinfection to investigate the impacts of protection and treatment intervention mechanisms on the coinfection spreading in the community. In the qualitative analysis of the model, we have performed the positivity and boundedness of the coinfection model solutions; the effective reproduction numbers using the next‐generation operator approach; and both the disease‐free and endemic equilibrium points’ local and global stabilities using the Routh‐Hurwiz and Castillo–Chavez stability criteria, respectively. We performed the sensitivity analysis of the model parameters using both the forward normalized sensitivity index criteria and numerical methods (simulation). Moreover, we carried out the numerical simulation for different scenarios to investigate the effect of model parameters on the associated reproduction number, the effect of model parameters on the model state variables, and the solution behavior and convergence to the equilibrium point(s) of the models. Finally, from the qualitative analysis and numerical simulation results, we observed that the disease‐spreading rates, protection rates, and treatment rates are the most sensitive parameters, and we recommend for stakeholders to concentrate and exert their maximum effort to minimize the spreading rates by maximizing the protection and treatment rates.

Beta lactamase-producing Neisseria gonorrhoeae alleviates Amoxicillin-induced chlamydial persistence in a novel in vitro co-infection model

Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) cause most bacterial sexually transmitted infections (STIs) worldwide. Epidemiological studies have shown high percentages of co-infections with CT/NG and indicate that NG co-infection can reactivate CT shedding during persistent chlamydial infection. These data also suggest that biological interaction between the two bacteria may increase susceptibility or transmissibility. CT is an obligate intracellular bacterium with a developmental cycle that alternates between two forms: infectious elementary bodies (EBs) which invade the epithelium and non-infectious reticulate bodies (RBs) which divide and replicate inside the inclusion. Adverse environmental conditions can interrupt chlamydial development, with a consequent temporary halt in RB division, reduction in infectious EB production and formation of enlarged chlamydiae (aberrant bodies, ABs) – characterizing chlamydial persistence. When the stressor is removed, the chlamydial developmental cycle is restored, together with production of infectious EBs. The beta-lactam amoxicillin (AMX) induces chlamydial persistence, both in vitro and in mice. We investigated the impact of penicillinase-producing NG strain (PPNG) on AMX-persistent chlamydial infection utilizing our recently developed, contact-independent in vitro model of co-infection. We hypothesized that co-infection with PPNG could prevent and/or reverse AMX-induced chlamydial persistence. Our results showed that PPNG can ameliorate AMX-persistence in two chlamydial species, CT and C. muridarum (CM), providing novel evidence for a range of Chlamydia/NG interactions.

Analysis of HBV and COVID-19 Coinfection Model with Intervention Strategies.

Coinfection of hepatitis B virus (HBV) and COVID-19 is a common public health problem throughout some nations in the world. In this study, a mathematical model for hepatitis B virus (HBV) and COVID-19 coinfection is constructed to investigate the effect of protection and treatment mechanisms on its spread in the community. Necessary conditions of the proposed model nonnegativity and boundedness of solutions are analyzed. We calculated the model reproduction numbers and carried out the local stabilities of disease-free equilibrium points whenever the associated reproduction number is less than unity. Using the well-known Castillo-Chavez criteria, the disease-free equilibrium points are shown to be globally asymptotically stable whenever the associated reproduction number is less than unity. Sensitivity analysis proved that the most influential parameters are transmission rates. Moreover, we carried out numerical simulation and shown results: some parameters have high spreading effect on the disease transmission, single infections have great impact on the coinfection transmission, and using protections and treatments simultaneously is the most effective strategy to minimize and also to eradicate the HBV and COVID-19 coinfection spreading in the community. It is concluded that to control the transmission of both diseases in a population, efforts must be geared towards preventing incident infection with either or both diseases.

Dynamics of herpes and chlamydia co-infection in a population

A mathematical model was formulated to investigate Chlamydia trachomatis (C. trachomatis) and herpes simplex virus (HSV) co-infection in a population; taking into account that HSV can induce a viable but non-cultivable state of C. trachomatis in a host. A complete description of the global dynamics is given for the sub-systems where only one of the diseases is present. For the co-infection model, we show that the extinction or persistence of HSV is determined solely by the basic reproduction number of HSV, regardless of C. trachomatis prevalence. On the contrary, C. trachomatis can not always invade a HSV-endemic population even when it could invade a susceptible one, and this is determined by a newly introduced threshold parameter. By a limiting system approach, the existence of a co-infection steady state is shown when all reproduction numbers are greater than one. Applying the theory of asymptotically autonomous systems, we prove global stability results for the disease free and the boundary equilibria. Finally, we calibrate the model to estimate the prevalence of both diseases in the population, and compare it with epidemiological observations.

Optimal control for co-infection with COVID-19-Associated Pulmonary Aspergillosis in ICU patients with environmental contamination.

In this paper, we propose a mathematical model for COVID-19-Associated Pulmonary Aspergillosis (CAPA) co-infection, that enables the study of relationship between prevention and treatment. The next generation matrix is employed to find the reproduction number. We enhanced the co-infection model by incorporating time-dependent controls as interventions based on Pontryagin's maximum principle in obtaining the necessary conditions for optimal control. Finally, we perform numerical experiments with different control groups to assess the elimination of infection. In numerical results, transmission prevention control, treatment controls, and environmental disinfection control provide the best chance of preventing the spread of diseases more rapidly than any other combination of controls.