Background Mathematical modelling of infectious diseases is a powerful tool for the design of management policies and a fundamental part of the arsenal currently deployed to deal with the COVID-19 pandemic. Methods We present a compartmental model for the disease where symptomatic and asymptomatic individuals move separately. We introduced healthcare burden parameters allowing to infer possible containment and suppression strategies. In addition, the model was scaled up to describe different interconnected areas, giving the possibility to trigger regionalized measures. It was specially adjusted to Mendoza-Argentina’s parameters, but is easily adaptable for elsewhere. Results Overall, the simulations we carried out were notably more effective when mitigation measures were not relaxed in between the suppressive actions. Since asymptomatics or very mildly affected patients are the vast majority, we studied the impact of detecting and isolating them. The removal of asymptomatics from the infectious pool remarkably lowered the effective reproduction number, healthcare burden and overall fatality. Furthermore, different suppression triggers regarding ICU occupancy were attempted. The best scenario was found to be the combination of ICU occupancy triggers (on: 50%, off: 30%) with the detection and isolation of asymptomatic individuals. In the ideal assumption that 45% of the asymptomatics could be detected and isolated, there would be no need for complete lockdown, and Mendoza’s healthcare system would not collapse. Conclusions Our model and its analysis inform that the detection and isolation of all infected individuals, without leaving aside the asymptomatic group is the key to surpass this pandemic.

Mathematical modeling of infectious diseases is a powerful tool for the design of management policies and a fundamental part of the arsenal currently deployed to deal with the COVID-19 pandemic. Here we present a compartmental model for the disease where symptomatic and asymptomatic individuals move separately. We introduced healthcare burden parameters allowing to infer possible containment and suppression strategies. In addition, the model was scaled up to describe different interconnected areas, giving the possibility to trigger regionalized measures. It was specially adjusted to Mendoza-Argentina's parameters, but is easily adaptable for elsewhere. Overall, the simulations we carried out were notably more effective when mitigation measures were not relaxed in between the suppressive actions.Since asymptomatics or very mildly affected patients are the vast majority, we studied the impact of detecting and isolating them. The removal of asymptomatics from the infectious pool remarkably lowered the effective reproduction number, healthcare burden and overall fatality. Furthermore, different suppression triggers regarding ICU occupancy were attempted. The best scenario was found to be the combination of ICU occupancy triggers (on: 50%, off: 30%) with the detection and isolation of asymptomatic individuals. In the ideal assumption that 45% of the asymptomatics could be detected and isolated, there would be no need for quarantine, and Mendoza's healthcare system would not collapse. Our model and its analysis inform that the detection and isolation of all infected individuals, without leaving aside the asymptomatic group is the key to surpass this pandemic.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a global pandemic. This disease has been shown to affect various organ systems, including the cerebrovascular system with sequelae still not completely uncovered. We present an unusual case of extensive brainstem intraparenchymal hemorrhage in a patient with COVID-19 to caution readers of this possible complication in patients positive for COVID-19. In this report, we outline the clinical presentation of a 40-year-old male who developed severe coughing and sneezing before presenting to the emergency department with confusion, somnolence, and respiratory distress. CT head without contrast revealed extensive pontine and midbrain hemorrhage with intraventricular extension and early hydrocephalus. Neurological examination revealed pinpoint, minimally reactive pupils, withdrawal to painful stimuli in the right hemibody, left hemibody paresis, and intact left corneal, cough, and gag reflexes. MRI and MRA brain revealed no evidence of an underlying vascular lesion. Over the next two days, the patient had worsening multiorgan failure and hypoxemia without intracranial hypertension. He remained too unstable to undergo cerebral angiogram. On hospital day four, his neurological examination deteriorated to quadriparesis and only cough and gag reflexes remaining intact after which his family opted for comfort measures only. In summary, a potential increased risk of intracerebral hemorrhage adds to the complexity of management of patients with COVID-19. This is especially true in those who have violent sneezing or coughing, or those who are on anticoagulation or antiplatelet therapy.

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Background: With the lack of an effective SARS-CoV-2 vaccine, mathematical modeling has stepped up in the COVID-19 management to guide non-pharmaceutical intervention (NPI) policies. Complete lockdown has been characterized as the most powerful strategy for the epidemic; anyhow, it is associated with undeniable negative consequences. Not aware that global panic could make countries adopt premature and lengthy lockdowns, previous studies only warned about the inefficacy of late quarantine sets. Therefore, we proposed ourselves to find the optimal timing and lasting for COVID-19 suppressive measures. Methods: We used our previously elaborated compartmental SEIR (Susceptible-Exposed-Infected-Recovered) model to scan different timings for lockdown set and various lockdown lengths under different reproduction number (R0) scenarios. We explored healthcare parameters focusing on ICU occupation and deaths since they condition the sanitary system and reflect the severity of the epidemic. Results: The timing for the lockdown trigger varies according to the original R0 and has great impact on ICU usage and fatalities. The less the R0 the later the lockdown should be for it to be effective. The lockdown length is also something to consider. Too short lockdowns (~15 days) have minimal effect on healthcare parameters, but too long quarantines (>45 days) do not benefit healthcare parameters proportionally when compared to more reasonable 30 to 45-day lockdowns. We explored the outcome of the combination of a 45-day lockdown followed by strict mitigation measures sustained in time, and interestingly, it outperformed the lengthy quarantine. Additionally, we show that if strict mitigation actions were to be installed from the very beginning of the epidemic, lockdown would not benefit substantially regarding healthcare parameters. Conclusion: Lockdown set timing and lasting are non-trivial variables to COVID-19 management.