Pneumonia Coinfection Research Articles

Robustness and exploration between the interplay of the nonlinear co-dynamics HIV/AIDS and pneumonia model via fractional differential operators and a probabilistic approach

In this article, we considered a nonlinear compartmental mathematical model that assesses the effect of treatment on the dynamics of HIV/AIDS and pneumonia (H/A-P) co-infection in a human population at different infection stages. Understanding the complexities of co-dynamics is now critically necessary as a consequence. The aim of this research is to construct a co-infection model of H/A-P in the context of fractional calculus operators, white noise and probability density functions, employing a rigorous biological investigation. By exhibiting that the system possesses non-negative and bounded global outcomes, it is shown that the approach is both mathematically and biologically practicable. The required conditions are derived, guaranteeing the eradication of the infection. Furthermore, adequate prerequisites are established, and the configuration is tested for the existence of an ergodic stationary distribution. For discovering the system’s long-term behavior, a deterministic-probabilistic technique for modeling is designed and operated in MATLAB. By employing an extensive review, we hope that the previously mentioned approach improves and leads to mitigating the two diseases and their co-infections by examining a variety of behavioral trends, such as transitions to unpredictable procedures. In addition, the piecewise differential strategies are being outlined as having promising potential for scholars in a range of contexts because they empower them to include particular characteristics across multiple time frame phases. Such formulas can be strengthened via classical techniques, power law, exponential decay, generalized Mittag-Leffler kernels, probability density functions and random procedures. Furthermore, we get an accurate description of the probability density function encircling a quasi-equilibrium point if the effect of H/A-P minimizes the propagation of the co-dynamics. Consequently, scholars can obtain better outcomes when analyzing facts using random perturbations by implementing these strategies for challenging issues. Random perturbations in H/A-P co-infection are crucial in controlling the spread of an epidemic whenever the suggested circulation is steady and the amount of infection eliminated is closely correlated with the random perturbation level.

Mycoplasma pneumoniae and Viral Pneumonia Coinfection: Something NOT to be Overlooked.

Mycoplasma pneumoniae and Viral Pneumonia Coinfection: Something NOT to be Overlooked.

Pneumonia and COVID-19 co-infection modeling with optimal control analysis

In this study, we present a nonlinear deterministic mathematical model for co-infection of pneumonia and COVID-19 transmission dynamics. To understand the dynamics of the co-infection of COVID-19 and pneumonia sickness, we developed and examined a compartmental based ordinary differential equation type mathematical model. Firstly, we showed the limited region and non-negativity of the solution, which demonstrate that the model is biologically relevant and mathematically well-posed. Secondly, the Jacobian matrix and the Lyapunov function are used to illustrate the local and global stability of the equilibrium locations. If the related reproduction numbers R0c, R0p, and R0 are smaller than unity, then pneumonia, COVID-19, and their co-infection have disease-free equilibrium points that are both locally and globally asymptotically stable otherwise the endemic equilibrium points are stable. Sensitivity analysis is used to determine how each parameter affects the spread or control of the illnesses. Moreover, we applied the optimal control theory to describe the optimal control model that incorporates four controls, namely, prevention of pneumonia, prevention of COVID-19, treatment of infected pneumonia and treatment of infected COVID-19. Then the Pontryagin's maximum principle is introduced to obtain the necessary condition for the optimal control problem. Finally, the numerical simulation of optimality system reveals that the combination of treatment and prevention is the most optimal to minimize the diseases.

Optimal control strategies on HIV/AIDS and pneumonia co-infection with mathematical modelling approach

In this paper, a compartmental model on the co-infection of pneumonia and HIV/AIDS with optimal control strategies was formulated using the system of ordinary differential equations. Using qualitative methods, we have analysed the mono-infection and HIV/AIDS and pneumonia co-infection models. We have computed effective reproduction numbers by applying the next-generation matrix method, applying Castillo Chavez criteria the models disease-free equilibrium points global stabilities were shown, while we have used the Centre manifold criteria to determine that the pneumonia infection and pneumonia and HIV/AIDS co-infection exhibit the phenomenon of backward bifurcation whenever the corresponding effective reproduction number is less than unity. We carried out the numerical simulations to investigate the behaviour of the co-infection model solutions. Furthermore, we have investigated various optimal control strategies to predict the best control strategy to minimize and possibly to eradicate the HIV/AIDS and pneumonia co-infection from the community.

Differences in RDW Values of COVID-19 Patients with Pneumonia and Without Pneumonia at RSUM and RSUDP NTB

Pneumonia coinfection in COVID-19 patients can be an important risk factor for patient mortality. Red blood cell distribution width (RDW) is a predictor that can determine clinical outcomes in patients with respiratory tract infections and serious illnesses, so researchers want to conduct research to determine the difference in RDW values in COVID-19 patients with and without pneumonia at RSUM and RSUDP NTB. The design of this research is cross sectional. The sampling technique used was consecutive sampling. There were 110 COVID-19 patient data used in this research. Data collection uses medical record notes. The statistical analysis used was the Mann-Whitney test. The average age of patients was 48 years ± 16 years. Most of the subjects were male (53.6%). The most common comorbidity was diabetes mellitus (21.8%). The average RDW values in COVID-19 patients with and without pneumonia were 13.9% and 13.1%. The difference in the mean RDW value in the two groups is 0.8%. This study found that clinically there were differences in the RDW values of COVID-19 patients with pneumonia and without pneumonia at RSUM and RSUDP NTB.

The Efficacy of High-Dose Pulse Therapy vs. Low-Dose Intravenous Methylprednisolone on Severe to Critical COVID-19 Clinical Outcomes: A Randomized Clinical Trial.

It remains unclear which formulation of the corticosteroid regimen has the optimum efficacies on COVID-19 pneumonia. The aim of this study was to compare the clinical outcomes of 2 different regimens in the treatment of acute respiratory distress syndrome (ARDS) caused by COVID-19: Methylprednisolone at a dose of 1 mg/kg every 12 hours (low-dose group) and 1000 mg/day pulse therapy for 3 days following 1 mg/kg methylprednisolone every 12 hours (high-dose group). In this randomized clinical trial, patients with mild to moderate ARDS due to COVID-19 were randomly assigned to receive either low-dose (n = 47) or high-dose (n = 48) intravenous methylprednisolone regimens. Two groups were matched for age, gender, body mass index (BMI), comorbidities, leukocytes, lymphocytes, neutrophil/lymphocyte, platelet, hemoglobin, and inflammatory markers (erythrocyte sedimentation rate [ESR], C-reactive protein [CRP], and ferritin). Both regimens were initiated upon admission and continued for 10 days. The clinical outcome and secondary complications were evaluated. Evaluating in-hospital outcomes, no difference was revealed in the duration of intensive care unit (ICU) stays (5.4 ± 4.6 vs. 4.5 ± 4.9; P = 0.35), total hospital stays (8 ± 3.1 vs. 6.9 ± 3.4; P = 0.1), requirement rate for invasive ventilation (29.2% vs. 36.2%; P = 0.4) or non-invasive ventilation (16.6% vs 23.4%; P = 0.4), and hemoperfusion (16.6% vs 11.3%; P = 0.3) between the low- and high-dose groups. There was no significant difference in fatality due to ARDS (29.2% vs. 38.3%; P = 0.3) and septic shock (4.2% vs. 6.4%; P = 0.3) between the low- and high-dose groups. Patients in the high-dose group had significantly higher bacterial pneumonia co-infection events compared with those in the low-dose group (18.7% vs 10.6%; P = 0.01). The use of adjuvant pulse therapy with intravenous methylprednisolone did not result in improved in-hospital clinical outcomes among patients with mild to moderate ARDS due to COVID-19. A higher risk of bacterial pneumonia should be considered in such cases as receiving a higher dose of steroids.

Procalcitonin and C-reactive protein to rule out early bacterial coinfection in COVID-19 critically ill patients

PurposeAlthough the prevalence of community-acquired respiratory bacterial coinfection upon hospital admission in patients with coronavirus disease 2019 (COVID-19) has been reported to be < 5%, almost three-quarters of patients received antibiotics. We aim to investigate whether procalcitonin (PCT) or C-reactive protein (CRP) upon admission could be helpful biomarkers to identify bacterial coinfection among patients with COVID-19 pneumonia.MethodsWe carried out a multicentre, observational cohort study including consecutive COVID-19 patients admitted to 55 Spanish intensive care units (ICUs). The primary outcome was to explore whether PCT or CRP serum levels upon hospital admission could predict bacterial coinfection among patients with COVID-19 pneumonia. The secondary outcome was the evaluation of their association with mortality. We also conducted subgroups analyses in higher risk profile populations.ResultsBetween 5 February 2020 and 21 December 2021, 4076 patients were included, 133 (3%) of whom presented bacterial coinfection. PCT and CRP had low area under curve (AUC) scores at the receiver operating characteristic (ROC) curve analysis [0.57 (95% confidence interval (CI) 0.51–0.61) and 0.6 (95% CI, 0.55–0.64), respectively], but high negative predictive values (NPV) [97.5% (95% CI 96.5–98.5) and 98.2% (95% CI 97.5–98.9) for PCT and CRP, respectively]. CRP alone was associated with bacterial coinfection (OR 2, 95% CI 1.25–3.19; p = 0.004). The overall 15, 30 and 90 days mortality had a higher trend in the bacterial coinfection group, but without significant difference. PCT ≥ 0.12 ng/mL was associated with higher 90 days mortality.ConclusionOur study suggests that measurements of PCT and CRP, alone and at a single time point, are not useful for ruling in or out bacterial coinfection in viral pneumonia by COVID-19.

Biomarkers of viral and bacterial infection in rhinovirus pneumonia.

Rhinovirus (RV) is often detected in children hospitalized with pneumonia, but the role of RV in causing pneumonia is still unclear. White blood cell count, C-reactive protein, procalcitonin, and myxovirus resistance protein A (MxA) levels were determined from blood samples in children (n = 24) hospitalized with radiologically verified pneumonia. Respiratory viruses were identified from nasal swabs by using reverse transcription polymerase chain reaction assays. Among RV-positive children, the cycle threshold value, RV subtyping by sequence analysis, and the clearance of RV by weekly nasal swabs were determined. RV-positive children with pneumonia were compared to other virus-positive children with pneumonia, and to children (n = 13) with RV-positive upper respiratory tract infection from a separate earlier study. RV was detected in 6 children and other viruses in 10 children with pneumonia (viral co-detections excluded). All RV-positive children with pneumonia had high white blood cell counts, plasma C-reactive protein or procalcitonin levels, or alveolar changes in chest radiograph strongly indicating bacterial infection. The median cycle threshold value for RV was low (23.2) indicating a high RV load, and a rapid clearance of RV was observed in all. Blood level of viral biomarker MxA was lower among RV-positive children with pneumonia (median 100 μg/L) than among other virus-positive children with pneumonia (median 495 μg/L, p = 0.034) or children with RV-positive upper respiratory tract infection (median 620 μg/L, p = 0.011). Our observations suggest a true viral-bacterial coinfection in RV-positive pneumonia. Low MxA levels in RV-associated pneumonia need further studies.

Modeling and analysis of tuberculosis and pneumonia co-infection dynamics with cost-effective strategies

Tuberculosis and Pneumonia are among the major airborne diseases that shares common clinical traits with high human morbidity and mortality impacts. Thus, the co-infection of the two diseases becomes unavoidable in a community of comorbid populations. Due to scare resources, the huge disease burden co-imposed by these endemics requires an effective intervention to cushion the effect. To achieve this goal, cost–benefit analysis for the optimal controls is deemed necessary. In this study, an SEIR model for the co-dynamics of tuberculosis and pneumonia is formulated. The model was shown to have a globally stable disease-free (endemic) equilibrium where the reproduction number is less (greater) than unity. Sensitivity analysis by partial rank correlation coefficients shows that increasing infection recovery is only one among the three most influential parameters that reduces the magnitude of the diseases. Through Pontryagin′s maximum principle, the number of infected individuals and cost of controls (public health campaign, chemoprophylaxis, oral fluid intake and treatment) was minimized. In implementing the cost–benefit analysis, we employ three techniques: the Infection Averted Ratio (IAR), the Average Cost-effectiveness Ratio (ACER) and the Incremental Cost-effectiveness Ratio (ICER). On comparing the strategies considering cases (A–E), the ICER results showed that, strategy with treating tuberculosis alone is the most effective and cost-saving strategy. But in terms of infections averted, strategy with all the control measures is the best; however, unaffordable since it is highly expensive. We hope that, the findings of this study should help policy-makers when dealing with the co-existence of tuberculosis and pneumonia.

305 - Tsukamurella and mycobacterium tuberculosis pneumonia co-infection

305 - Tsukamurella and mycobacterium tuberculosis pneumonia co-infection

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.

Co-infection by Mycobacterium Tuberculosis And Klebsiella Pneumoniae in an Elderly Male With Multiple Co-morbidities: A Rare Entity With High Mortality

Klebsiella pneumoniae and Mycobacterium tuberculosis coinfection is one of the most lethal combinations with high mortality specially if there is delay in diagnosis and proper management. Patients with uncontrolled diabetes mellitus are prone to develop this type of serious infection.There is a considerable overlap in the clinical presentation of these critical pulmonary infections hence there is need for a high index of clinical suspicion, appropriate judicious investigations, and promt management to improve survivality. Here, we have presented Mycobacterium tuberculosis and Klebsiella pneumonia co-infection presenting as cough, chest pain, and shortness of breath in an elderly male with multiple co-morbidities, like uncontrolled diabetes mellitus, hypertension, prosthetic aortic valve in situ (for aortic stenosis)&amp; previous history of ishchaemic stroke. This combination is rare and to the best of our knowledge not reported in the literature from Bangladesh. Bangladesh J Medicine 2022; 33: 52-57

A model for COVID-19 and bacterial pneumonia coinfection with community- and hospital-acquired infections

We propose a new epidemic model to study the coinfection dynamics of COVID-19 and bacterial pneumonia, which is the first model in the literature used to describe mathematically the interaction of these two diseases while considering two infection ways for pneumonia: community-acquired and hospital-acquired transmission. We show that the existence and local stability of equilibria depend on three different parameters, which are interpreted as the basic reproduction numbers of COVID-19, bacterial pneumonia, and bacterial population in the hospital. Numerical simulations are performed to complement our theoretical analysis, and we show that both diseases can persist if the basic reproduction number of COVID-19 is greater than one.

Appraisal and Simulation on Codynamics of Pneumonia and Meningitis with Vaccination Intervention: From a Mathematical Model Perspective.

The membranes that encompass the brain and spinal cord become inflamed by the potentially fatal infectious disease called pneumococcal meningitis. Pneumonia and meningitis "coinfection" refers to the presence of both conditions in a single host. In this work, we accounted for the dynamics of pneumonia and meningitis coinfection in communities by erroneously using a compartment model to analyze and suggest management techniques to stakeholders. We have used the next generation matrix approach and derived the effective reproduction numbers. When the reproduction number is less than one, the constructed model yields a locally asymptotically stable disease-free equilibrium point. Additionally, we conducted a sensitivity analysis to determine how different factors affected the incidence and transmission rate, which revealed that both the pneumonia and meningitis transmission rates are extremely sensitive. The performance of our numerical simulation demonstrates that the endemic equilibrium point of the pneumonia and meningitis coinfection model is locally asymptotically stable when max{ ℛ 1, ℛ 2} > 1. Finally, as preventative and control measures for the coinfection of pneumonia and meningitis illness, the stakeholders must concentrate on reducing the transmission rates, reducing vaccination wane rates, and boosting the portion of vaccination rates for both pneumonia and meningitis.

Clinical Profile, Risk Factors, and Therapeutic Outcome of Cavitating Fungal Pneumonia Coinfection in COVID-19 Patients: A Retrospective Analysis.

An end to the novel coronavirus disease 2019 (COVID-19) pandemic appears to be a distant dream. To make matters worse, there has been an alarming upsurge in the incidence of cavitating invasive fungal pneumonia associated with COVID-19, reported from various parts of the world including India. Therefore, it remains important to identify the clinical profile, risk factors, and outcome of this group of patients. Out of 50 moderate to severe COVID-19 inpatients with thoracic computed tomographic (CT) evidence of lung cavitation, we retrospectively collected demographic and clinical data of those diagnosed with fungal pneumonia for further investigation. We determined the association between risk factors related to 30-day and 60-day mortality. Of the 50 COVID-19 patients with cavitating lung lesions, 22 (44 %) were identified to have fungal pneumonia. Most of these patients (n = 16, 72.7 %) were male, with a median (range) age of 56 (38-64) years. On chest CT imaging, the most frequent findings were multiple cavities (n = 13, 59.1 %) and consolidation (n = 14, 63.6 %). Mucormycosis (n = 10, 45.5 %) followed by Aspergillus fumigatus (n = 9, 40.9 %) were the common fungi identified. 30-day and 60-day mortalities were seen in 12 (54.5 %) and 16 (72.7 %) patients, respectively. On subgroup analysis, high cumulative prednisolone dose was an independent risk factor associated with 30-day mortality (p = 0.024). High cumulative prednisolone dose, baseline neutropenia, hypoalbuminemia, multiple cavities on CT chest, leukopenia, lymphopenia and raised inflammatory markers were associated with poor prognosis in severe COVID-19 patients with cavitating fungal pneumonia.

Bloodstream and respiratory coinfections in patients with COVID-19 on ECMO.

BackgroundAlthough several studies have characterized the risk of coinfection in COVID pneumonia, the risk of the bloodstream and respiratory coinfection in patients with COVID‐19 pneumonia on extracorporeal membrane oxygenation (ECMO) supports severe acute respiratory distress syndrome (ARDS) is poorly understood.MethodsThis is a retrospective analysis of patients with COVID‐19 ARDS on ECMO at a single center between January 2020 and December 2021. Patient characteristics and clinical outcomes were compared.ResultsOf 44 patients placed on ECMO support for COVID‐19 ARDS, 30 (68.2%) patients developed a coinfection, and 14 (31.8%) patients did not. Most patients underwent venovenous ECMO (98%; 43/44) cannulation in the right internal jugular vein (98%; 43/44). Patients with coinfection had a longer duration of ECMO (34 [interquartile range, IQR: 19.5, 65] vs. 15.5 [IQR 11, 27.3] days; p = .02), intensive care unit (ICU; 44 [IQR: 27,75.5] vs 31 [IQR 20–39.5] days; p = .03), and hospital (56.5 [IQR 27,75.5] vs 37.5 [IQR: 20.5–43.3]; p = .02) length of stay. When stratified by the presence of a coinfection, there was no difference in hospital mortality (37% vs. 29%; p = .46) or Kaplan–Meier survival (logrank p = .82). Time from ECMO to first positive blood and respiratory culture were 12 [IQR: 3, 28] and 10 [IQR: 1, 15] days, respectively. Freedom from any coinfection was 50 (95% confidence interval: 37.2–67.2)% at 15 days from ECMO initiation.ConclusionsThere is a high rate of co‐infections in patients placed on ECMO for COVID‐19 ARDS. Although patients with coinfections had a longer duration of extracorporeal life support, and longer length of stays in the ICU and hospital, survival was not inferior.

Mathematical Model of Pertussis and Pneumonia Co-Infection in Infants with Maternally Derived Immunity

The transmission dynamics of a pertussis-pneumonia co-infection model is analyzed. The model takes into account temporary immunity of infected infants and includes a maternally derived immunity compartment. The basic reproduction number of the co-infected model is obtained using the next generation matrix, and stability analysis is carried out. The model exhibits four equilibria, namely, the pertussis-free equilibrium, the pneumonia-free equilibrium, the co-infection-free equilibrium and co-infection endemic equilibrium. Subsequently, the local stability of the co-infection-free equilibrium is analyzed and is shown to be locally asymptotically stable. Similarly, by constructing a suitable Lyapunov function, the co-infection endemic equilibrium is shown to be globally asymptotically stable. Numerical simulations are carried out to illustrate the validity of these results.

Evaluation of Procalcitonin's Utility to Predict Concomitant Bacterial Pneumonia in Critically Ill COVID-19 Patients.

Background: Historically, procalcitonin(PCT) has been used as a predictor of bacterial infection and to guide antibiotic therapy in hospitalized patients. The purpose of this study was to determine PCT's diagnostic utility in predicting secondary bacterial pneumonia in critically ill patients with severe COVID-19 pneumonia. Methods: A retrospective cohort study was conducted in COVID-19 adults admitted to the ICU between March 2020, and March 2021. All included patients had a PCT level within 72 h of presentation and serum creatinine of <1.5mg/dL. A PCT threshold of 0.5ng/mL was used to compare patients with high( ≥ 0.5ng/mL) versus low(< 0.5ng/mL) PCT. Bacterial pneumonia was defined by positive respiratory culture. A receiver operating characteristics (ROC) curve was utilized to evaluate PCT as a diagnostic test for bacterial pneumonia, with an area under the curve(AUC) threshold of 0.7 to signify an accurate diagnostic test. A multivariable model was constructed to identify variables associated with in-hospital mortality. Results: There were 165 patients included: 127 low PCT versus 38 high PCT. There was no significant difference in baseline characteristics, vital signs, severity of disease, or outcomes among low versus high PCT groups (all p > 0.05). While there was no difference in bacterial pneumonia in low versus high groups (34(26.8%) versus 12(31.6%), p = 0.562), more patients in the high PCT group had bacteremia (19(15%) versus 11(28.9%), p = 0.050). Sensitivity was 26.1% and specificity was 78.2% for PCT to predict bacterial pneumonia coinfection in ICU patients with COVID-19 pneumonia. ROC yielded an AUC 0.54 (p = 0.415). After adjusting for LDH>350U/L and creatinine in multivariable regression, PCT did not enhance performance of the regression model. Conclusions: PCT offers little to no predictive utility in diagnosing concomitant bacterial pneumonia in critically ill patients with COVID-19 nor in predicting increased severity of disease or worse outcomes including mortality.

Association between Virulence Factors and Antimicrobial Resistance of Klebsiella pneumoniae Clinical Isolates from North Kerala

Klebsiella pneumoniae is a common bacterial pathogen causes wide range of infections all over the world. The antimicrobial resistance of K. pneumoniae is a global concern and expresses several virulence factors contributing to the pathogenesis. The incidences of bacterial co-infection in viral pneumonia are common. Increased risk of K. pneumoniae co-infection in viral respiratory tract infection should be alerted in COVID-19 pandemic period. The study aims to detect the association between antimicrobial resistance and factors causing pathogenicity of K. pneumoniae. For the current study, 108 K. pneumoniae clinical isolates were included. Antimicrobial susceptibility test was done by Kirby-Bauer disc diffusion method according to CLSI guidelines. Virulence factors such as biofilm formation, haemagglutination, haemolysins, hypermucoviscocity, siderophore, amylase, and gelatinase production were determined by phenotypic method. In this study K. pneumoniae showed high level of antimicrobial resistance towards ampicillin (92.59%) followed by amoxicillin-clavulanic acid (67.59%) and cotrimoxazole (47,22%). An important association between biofilm formation and antimicrobial resistance was found to be statistically significant for cotrimoxazole (P-value 0.036) and amoxicillin-clavulanic acid (P-value 0.037). Other virulence factors like hypermucoviscocity, haemagglutination, amylase, and siderophore production were also showed a statistically significant relation (P-value &lt;0.05) with antimicrobial resistance. Further molecular studies are necessary for the identification of virulence and antimicrobial resistance genes, for the effective control of drug-resistant bacteria.

Co-Infection of COVID-19 and Pneumocystosis Following Rituximab Infusion—A Case Report

Immunocompromised patients with respiratory viral infections are at increased risk of fungal superinfections, including Pneumocystosis. Within the scope of the COVID-19 pandemic, Pneumocystis jirovecii co-infections are being increasingly reported. Differential diagnosis often creates a dilemma, due to multiple overlapping clinical and radiographic features. Awareness of fungal co-infections in the context of the COVID-19 pandemic is crucial to initiate prophylactic measures, especially in high-risk individuals. We report the second case of Pneumocystis jirovecii pneumonia and COVID-19 co-infection in a renal transplant recipient in Poland.