To date, there have been no detailed reports of patients developing persistent psychotic symptoms following Coronavirus disease 2019 (COVID-19) infection. There have been reports of patients developing transient delirium (with and without hypoxia) after COVID-19 infection as well as other neurological manifestations. We report on a female patient who, post-COVID-19 infection, developed an initial delirium followed by persistent and florid psychotic symptoms consisting of persecutory delusion, complex visual and auditory hallucinations and Capgras phenomenon in the absence of hypoxia but elevated tumour necrosis factor (TNF)-α. The psychotic symptoms persisted for about 40 days. Her magnetic resonance imaging brain scan, electroencephalogram, cerebrospinal fluid examination and extensive autoimmune panel did not show any abnormalities. The cause of the psychotic symptoms in this patient were not ascertained but we propose either an inflammatory state, characterised by the patient's elevated TNF-alpha levels as a possible contributing mechanism for her psychosis in line with the proinflammatory changes observed in some cases of psychosis. Or, an alternative, but unproven, hypothesis is one of an antibody-mediated encephalitic event induced by viral infection.

Reducing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infections among healthcare workers is critical. We ran Monte Carlo simulations modeling the spread of SARS-CoV-2 in non–COVID-19 wards, and we found that longer nursing shifts and scheduling designs in which teams of nurses and doctors co-rotate no more frequently than every 3 days can lead to fewer infections.

In São Paulo, Brazil, the first case of coronavirus disease 2019 (CoViD-19) was confirmed on 26 February, the first death due to CoViD-19 was registered on 16 March, and on 24 March, São Paulo implemented the isolation of persons in non-essential activities. A mathematical model was formulated based on non-linear ordinary differential equations considering young (60 years old or less) and elder (60 years old or more) subpopulations, aiming to describe the introduction and dissemination of the new coronavirus in São Paulo. This deterministic model used the data collected from São Paulo to estimate the model parameters, obtaining R0 = 6.8 for the basic reproduction number. The model also allowed to estimate that 50% of the population of São Paulo was in isolation, which permitted to describe the current epidemiological status. The goal of isolation implemented in São Paulo to control the rapid increase of the new coronavirus epidemic was partially succeeded, concluding that if isolation of at least 80% of the population had been implemented, the collapse in the health care system could be avoided. Nevertheless, the isolated persons must be released one day. Based on this model, we studied the potential epidemiological scenarios of release by varying the proportions of the release of young and elder persons. We also evaluated three different strategies of release: All isolated persons are released simultaneously, two and three releases divided in equal proportions. The better scenarios occurred when young persons are released, but maintaining elder persons isolated for a while. When compared with the epidemic without isolation, all strategies of release did not attain the goal of reducing substantially the number of hospitalisations due to severe CoViD-19. Hence, we concluded that the best decision must be postponing the beginning of the release.

Understanding the clinical risk factors for COVID-19 disease severity and outcomes requires a combination of data from electronic health records and patient reports. To facilitate the collection of patient-reported data, as well as accelerate and standardize the collection of data about host factors, we have constructed a COVID-19 survey. This survey is freely available to the scientific community to send electronically for patients to complete online. This patient survey is designed to be comprehensive, yet not overly burdensome, to gather data useful for a range of clinical investigations, and to accommodate a wide variety of implementation settings including at a COVID-19 testing site, at home during infection or after recovery, and/or for individuals while they are hospitalized. A widely adopted standardized survey that can be implemented online with minimal resources can serve as a critical tool for combining and comparing data across studies to improve our understanding of COVID-19 disease.