Invasive fungal infections (IFIs) can complicate the clinical course of COVID-19 and are associated with a significant increase in mortality, especially in critically ill patients admitted to an intensive care unit (ICU). This narrative review concerns 4099 cases of IFIs in 58,784 COVID-19 patients involved in 168 studies. COVID-19-associated invasive pulmonary aspergillosis (CAPA) is a diagnostic challenge because its non-specific clinical/imaging features and the fact that the proposed clinically diagnostic algorithms do not really apply to COVID-19 patients. Forty-seven observational studies and 41 case reports have described a total of 478 CAPA cases that were mainly diagnosed on the basis of cultured respiratory specimens and/or biomarkers/molecular biology, usually without histopathological confirmation. Candidemia is a widely described secondary infection in critically ill patients undergoing prolonged hospitalisation, and the case reports and observational studies of 401 cases indicate high crude mortality rates of 56.1% and 74.8%, respectively. COVID-19 patients are often characterised by the presence of known risk factors for candidemia such as in-dwelling vascular catheters, mechanical ventilation, and broad-spectrum antibiotics. We also describe 3185 cases of mucormycosis (including 1549 cases of rhino-orbital mucormycosis (48.6%)), for which the main risk factor is a history of poorly controlled diabetes mellitus (>76%). Its diagnosis involves a histopathological examination of tissue biopsies, and its treatment requires anti-fungal therapy combined with aggressive surgical resection/debridement, but crude mortality rates are again high: 50.8% in case reports and 16% in observational studies. The presence of other secondary IFIs usually diagnosed in severely immunocompromised patients show that SARS-CoV-2 is capable of stunning the host immune system: 20 cases of Pneumocystis jirovecii pneumonia, 5 cases of cryptococcosis, 4 cases of histoplasmosis, 1 case of coccidioides infection, 1 case of pulmonary infection due to Fusarium spp., and 1 case of pulmonary infection due to Scedosporium.

The emergence of carbapenem-resistant Klebsiella pneumoniae strains is threatening antimicrobial treatment. Sixty-eight carbapenemase-producing K. pneumoniae strains isolated at Luigi Sacco University Hospital-ASST Fatebenefratelli Sacco (Milan, Italy) between 2012 and 2014 were characterised microbiologically and molecularly. They were tested for drug susceptibility and carbapenemase phenotypes, investigated by means of repetitive extra-genic palindromic polymerase chain reaction (REP-PCR), and fully sequenced by means of next-generation sequencing for the in silico analysis of multi-locus sequence typing (MLST), their resistome, virulome and plasmid content, and their core single nucleotide polymorphism (SNP) genotypes. All of the samples were resistant to carbapenems, other β-lactams and ciprofloxacin; many were resistant to aminoglycosides and tigecycline; and seven were resistant to colistin. Resistome analysis revealed the presence of blaKPC genes and, less frequently blaSHV, blaTEM, blaCTX-M and blaOXA, which are related to resistance to carbapenem and other β-lactams. Other genes conferring resistance to aminoglycoside, fluoroquinolone, phenicol, sulphonamide, tetracycline, trimethoprim and macrolide-lincosamide-streptogramin were also detected. Genes related to AcrAB-TolC efflux pump-dependent and pump-independent tigecycline resistance mechanisms were investigated, but it was not possible to clearly correlate the genomic features with tigecycline resistance because of the presence of a common mutation in susceptible, intermediate and resistant strains. Concerning colistin resistance, the mgrB gene was disrupted by an IS5-like element, and the mobile mcr-1 and mcr-2 genes were not detected in two cases. The virulome profile revealed type-3 fimbriae and iron uptake system genes, which are important during the colonisation stage in the mammalian host environment. The in silico detected plasmid replicons were classified as IncFIB(pQil), IncFIB(K), ColRNAI, IncX1, IncX3, IncFII(K), IncN, IncL/M(pMU407) and IncFIA(HI1). REP-PCR showed five major clusters, and MLST revealed six different sequence types: 512, 258, 307, 1519, 745 and 101. Core SNP genotyping, which led to four clusters, correlated with the MLST data. Isolates of the same sequencing type often had common genetic traits, but the SNP analysis allowed greater strain tracking and discrimination than either the REP-PCR or MLST analysis. Our findings support the importance of implementing bacterial genomics in clinical medicine in order to complement traditional methods and overcome their limited resolution.

Human histoplasmosis is a mycosis caused by two distinct varieties of a dimorphic fungus: Histoplasma capsulatum var. capsulatum and H. capsulatum var. duboisii. In Europe, it is usually imported by migrants and travellers, although there have been some autochthonous cases, especially in Italy; however, most European physicians are unfamiliar with its clinical and pathological picture, particularly among immunocompromised patients without HIV infection. This systematic review of all the cases of histoplasmosis reported in Europe and Israel between 2005 and 2020 identified 728 cases diagnosed in 17 European countries and Israel described in 133 articles. The vast majority were imported (mainly from Central and South America), but there were also seven autochthonous cases (six in Europe and one in Israel). The patients were prevalently males (60.4%), and their ages ranged from 2 to 86 years. The time between leaving an endemic region and the diagnosis of histoplasmosis varied from a few weeks to more than 40 years. Progressive disseminated histoplasmosis was the most frequent clinical picture among people living with HIV infection (89.5%) or a different immunocompromising condition (57.1%), but it was also recorded in 6.2% of immunocompetent patients. Twenty-eight cases were caused by Histoplasma duboisii. Immunocompromised patients without HIV infection had the worst outcomes, with a mortality rate of 32%.

Objectives Healthcare workers (HCWs) are at high risk of developing SARS-CoV-2 infection. The aim of this single-centre prospective study was to evaluate the trend of SARS-CoV-2 seroprevalence in HCWs working at the primary referral centre for infectious diseases and bioemergencies (eg, COVID-19) in Northern Italy and investigate the factors associated with seroconversion. Methods Six hundred and seventy-nine HCW volunteers were tested for anti-SARS-CoV-2 antibodies three times between 4 March and 27 May 2020 and completed a questionnaire covering COVID-19 exposure, symptoms and personal protective equipment (PPE) training and confidence at each time. Results SARS-CoV-2 seroprevalence rose from 3/679 to 26/608 (adjusted prevalence: 0.5%, 95% CI 0.1 to 1.7% and 5.4%, 95% CI 3.6 to 7.9, respectively) between the first two time points and then stabilised, in line with the curve of the COVID-19 epidemic in Milan. From the first time point, 61.6% of the HCWs had received training in the use of PPE and 17 (61.5%) of those who proved to be seropositive reported symptoms compatible with SARS-CoV-2 infection. Contacts with ill relatives or friends and self-reported symptoms were independently associated with an increased likelihood of seroconversion (p<0.0001 for both), whereas there was no significant association with professional exposure. Conclusion The seroprevalence of SARS-CoV-2 among the HCWs at our COVID-19 referral hospital was low at the time of the peak of the epidemic. The seroconversions were mainly attributable to extrahospital contacts, probably because the hospital readily adopted effective infection control measures. The relatively high number of asymptomatic seropositive HCWs highlights the need to promptly identify and isolate potentially infectious HCWs.

We report the case of two patients in whom acute hepatitis A was associated with a marked and prolonged increase in human immunodeficiency virus type 1 (HIV-1) viral load. Although in one patient the rise in HIV-1 RNA might also have been related to the interruption of antiretroviral therapy, we also observed a similar pattern in the other patient who had a stable undetectable plasma viraemia prior to acute hepatitis and never received treatment with antiretrovirals. Our observation supports the hypothesis that immune activation that is induced by acute hepatitis A virus (HAV) infection may trigger HIV-1 replication. This highlights the importance of maintaining antiretroviral therapy throughout the acute phase of hepatitis A and of preventing HAV infection through active immunization.

Estimating the prevalence of accumulated HIV drug resistance in patients receiving antiretroviral therapy (ART) is difficult due to lack of resistance testing at all occasions of virological failure and in patients with undetectable viral load. A method to estimate this for 6498 EuroSIDA patients who were under follow-up on ART at 1 July 2008 was therefore developed by imputing data on patients with no prior resistance test results, based on the probability of detecting resistance in tested patients with similar profiles. Using all resistance test results available, predicted intermediate/high-level resistance to specific drug classes [nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs)] was derived using the Stanford algorithm v5.1.2. Logistic regression models were then employed to estimate predicted probability of resistance to each drug class for given values of current viral load, history of virological failure and previous virological suppression. Based on these predicted probabilities and patients’ covariate profiles, estimates of prevalence in 5355 patients with no prior test results were obtained. Overall prevalence of resistance was estimated by pooling these data with those observed in the remaining 1143 tested patients. Prevalence of NRTI, NNRTI and PI resistance was estimated as 43% (95% confidence interval: 39%–46%), 15% (13%–18%) and 25% (22%–28%), respectively. This method provides estimates for the proportion of treated patients in a cohort who harbour resistance on a given date, which are less likely to be affected by selection bias due to missing resistance data and will allow us to estimate prevalence of resistance to different drug classes at specific timepoints in HIV-infected populations on ART.