Changing Dynamics of COVID-19 in the U.S. with the Emergence of the Delta Variant: Projections of the COVID-19 Simulator

With the recent emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2 in the U.S., many states are seeing rising cases and hospitalizations after a period of steady decline. As We used the COVID-19 Simulator, an interactive online tool that utilizes a validated mathematical model, to simulate the trajectory of COVID-19 at the state level in the U.S. COVID-19 Simulators forecasts are updated weekly and included in the Centers for Disease Control and Prevention (CDC) ensemble model. We employed our model to analyze scenarios where the Delta variant becomes dominant in every state. The combination of high transmissibility of the Delta variant, low vaccination coverage in several regions, and more relaxed attitude towards social distancing is expected to result in as surge in COVID-19 deaths in at least 40 states. In several states - including Idaho, Maine, Montana, Nebraska, North Carolina, Oregon, Puerto Rico, Washington, and West Virginia - the projected daily deaths in 2021 could exceed the prior peak daily deaths under current social distancing behavior and vaccination rate. The number of COVID-19 deaths across the U.S. could exceed 1600 per day. Between August 1, 2021, and December 31, 2021, there could be additional 157,000 COVID-19 deaths across the U.S. Of note, our model projected approximately 20,700 COVID-19 deaths in Texas, 16,000 in California, 12,400 in Florida, 12,000 in North Carolina, and 9,300 in Georgia during this period. In contrast, the projected number of COVID-19 deaths would remain below 200 in New Jersey, Massachusetts, Connecticut, Vermont, and Rhode Island. We project COVID-19 deaths based on the current vaccination rates and social distancing behavior. Our hope is that the findings of this report serve a warning sign and people revert to wearing masks and maintain social distancing to reduce COVID-19 associated deaths in the U.S. Our projections are updated weekly by incorporating vaccination rates and social distancing measures in each state; the latest results can be found at the COVID-19 Simulator website.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. Significance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.

Invasive Pneumococcal Disease Associated with Fanconi-Like Syndrome.

Acquired causes of Fanconi syndrome in adults are usually due to drugs, toxins or paraproteinaemias. Infectious causes are rarely described. We report a case of invasive pneumococcal disease in a patient who developed a Fanconi-like syndrome during the course of her illness. This patient presented with multiple electrolyte derangements consisting predominantly of hypokalaemia, hypomagnesaemia and hypophosphataemia during hospitalization for invasive pneumococcal disease with possible Austrian syndrome. Further evaluation revealed significant urinary losses of these electrolytes, uric acid and ß2-microglobulin. Together with evidence of hypouricaemia, this is suggestive of proximal renal tubulopathy, and hence a Fanconi-like syndrome. The patient's clinical condition and biochemical anomalies improved following pneumococcus treatment. LEARNING POINTS: Suspect Fanconi syndrome when there are multiple electrolyte derangements consisting of hypokalaemia, hypomagnesaemia and hypophosphataemia.Recognise the common causes of Fanconi syndrome and appreciate that infections such as legionellosis, leptospirosis and pneumococcal disease can potentially result in Fanconi syndrome.The management of Fanconi syndrome is generally supportive and involves treating the underlying cause.

Quadruple valve infective endocarditis presenting with suspected Austrian syndrome: a case report and a case series of quadruple valve infective endocarditis.

OBJECTIVES: Austrian syndrome comprises the triad of pneumonia, meningitis, and endocarditis secondary to Streptococcus pneumonia. We present what we believe to be the first reported case of Austrian syndrome with quadruple heart valve involvement and review the literature detailing cases of quadruple valve infective endocarditis. CASE PRESENTATION AND RESULTS: A case is presented of a patient with radiographic evidence of a left lower lobe pneumonia. Sequential transthoracic followed by transesophageal echocardiogram done to evaluate the presence of a cardiac murmur revealed the presence of quadruple valve vegetations. Multiple blood cultures were persistently negative. The patient went on to develop seizures secondary to proven meningitis. Microbiological diagnosis was eventually established through positive Streptococcus pneumoniae antigen (Alere BinaxNOW®) from cerebrospinal fluid, establishing a presumptive clinical diagnosis of Austrian syndrome. A computerized PubMed search for reports of quadruple valve infective endocarditis and their references was collated. A total of 22 patients were found, including our patient. The median age of presentation was 47.5 years. Five patients had a history of intravenous drug abuse, another 5 had underlying congenital heart disease, and 1 had both. Two patients (9.1%) had 2 microorganisms isolated. Staphylococcus aureus and Streptococcus viridans (3 cases, 13.6% each) were the most commonly implicated microorganism. Heart failure was the commonest complication, afflicting 11 patients (50.0%). Ten patients (45.5%) underwent surgery. Overall case fatality rate was 50.0%. Cardiac surgery was of statistical significance in predicting survival (P = 0.009). CONCLUSION: Quadruple valve endocarditis is associated with a high mortality rate, and cardiac surgery may be protective.