Modeling the onset of symptoms of COVID-19: Effects of SARS-CoV-2 variant.

Identifying order of symptom onset of infectious diseases might aid in differentiating symptomatic infections earlier in a population thereby enabling non-pharmaceutical interventions and reducing disease spread. Previously, we developed a mathematical model predicting the order of symptoms based on data from the initial outbreak of SARS-CoV-2 in China using symptom occurrence at diagnosis and found that the order of COVID-19 symptoms differed from that of other infectious diseases including influenza. Whether this order of COVID-19 symptoms holds in the USA under changing conditions is unclear. Here, we use modeling to predict the order of symptoms using data from both the initial outbreaks in China and in the USA. Whereas patients in China were more likely to have fever before cough and then nausea/vomiting before diarrhea, patients in the USA were more likely to have cough before fever and then diarrhea before nausea/vomiting. Given that the D614G SARS-CoV-2 variant that rapidly spread from Europe to predominate in the USA during the first wave of the outbreak was not present in the initial China outbreak, we hypothesized that this mutation might affect symptom order. Supporting this notion, we found that as SARS-CoV-2 in Japan shifted from the original Wuhan reference strain to the D614G variant, symptom order shifted to the USA pattern. Google Trends analyses supported these findings, while weather, age, and comorbidities did not affect our model's predictions of symptom order. These findings indicate that symptom order can change with mutation in viral disease and raise the possibility that D614G variant is more transmissible because infected people are more likely to cough in public before being incapacitated with fever.

The Ethics of Emergent Health Technologies: Implications of the 21st Century Cures Act for Nursing.

The 21st Century Cures Act, passed in December 2016 by the United States Congress, is a public law aimed at accelerating the time it takes to get pharmaceutical drugs and medical devices into the market, in addition to shifting connected review processes from randomized controlled trials to real-world efficacy tests. As of December 2019, efforts are underway to introduce a "Cures Act 2.0" bill, with particular attention to the implementation of digital health within health systems. Research on the development of emergent health technologies is nascent; research examining health technology implications of 21st Century Cures Act for the health care workforce is nonexistent. This article fills a crucial gap in public awareness, discussing ethical implications of the 21st Century Cures Act and centering nursing. Nursing is a profession frequently acknowledged as practicing on "the front lines of care" and frequently responsible for the trialing of products in clinical settings. The article summarizes and evaluates key components of the 21st Century Cures Act related to health technology development. Discrete health technologies addressed are (a) breakthrough devices, (b) digital health software, and (c) combination products. It then connects these provisions to ethical considerations for nursing practice, research, and policy. The article concludes by discussing the relevance of emerging digital health technologies to the crafting of a "Cures 2.0" bill, with particular attention to this moment in light of digital care precedents set during the COVID-19 pandemic.

Modeling the Onset of Symptoms of COVID-19.

COVID-19 is a pandemic viral disease with catastrophic global impact. This disease is more contagious than influenza such that cluster outbreaks occur frequently. If patients with symptoms quickly underwent testing and contact tracing, these outbreaks could be contained. Unfortunately, COVID-19 patients have symptoms similar to other common illnesses. Here, we hypothesize the order of symptom occurrence could help patients and medical professionals more quickly distinguish COVID-19 from other respiratory diseases, yet such essential information is largely unavailable. To this end, we apply a Markov Process to a graded partially ordered set based on clinical observations of COVID-19 cases to ascertain the most likely order of discernible symptoms (i.e., fever, cough, nausea/vomiting, and diarrhea) in COVID-19 patients. We then compared the progression of these symptoms in COVID-19 to other respiratory diseases, such as influenza, SARS, and MERS, to observe if the diseases present differently. Our model predicts that influenza initiates with cough, whereas COVID-19 like other coronavirus-related diseases initiates with fever. However, COVID-19 differs from SARS and MERS in the order of gastrointestinal symptoms. Our results support the notion that fever should be used to screen for entry into facilities as regions begin to reopen after the outbreak of Spring 2020. Additionally, our findings suggest that good clinical practice should involve recording the order of symptom occurrence in COVID-19 and other diseases. If such a systemic clinical practice had been standard since ancient diseases, perhaps the transition from local outbreak to pandemic could have been avoided.