Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic 1 , caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations  . Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth 5,6 , to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported 7 .The COVID-19 pandemic is forcing societies worldwide to make consequential policy decisions with limited information. After containment of the initial outbreak failed, attention turned to implementing non-pharmaceutical interventions that are designed to slow the contagion of the virus. In general, these policies aim to decrease virus transmission by reducing contact among individuals within or between populations, such as by closing restaurants or restricting travel, thereby slowing the spread of COVID-19 to a manageable rate. These large-scale anti-contagion policies are informed by epidemiological simulations 2,4,8,9 and a small number of natural experiments during past epidemics 10 . However, the actual effects of these policies on infection rates in the ongoing pandemic are unknown. Because the modern world has never confronted this pathogen, nor deployed anti-contagion policies of such scale and scope, it is crucial that direct measurements of the effects of policies are used together with numerical simulations in current decision-making.Societies around the world are considering whether the health benefits of anti-contagion policies are worth their social and economic costs. Many ...
1Governments around the world are responding to the novel coronavirus (COVID-2 19) pandemic 1 with unprecedented policies designed to slow the growth rate of 3 infections. Many actions, such as closing schools and restricting populations to 4 their homes, impose large and visible costs on society, but their benefits cannot 5 be directly observed and are currently understood only through process-based 6 simulations.  Here, we compile new data on 1,717 local, regional, and national 7 non-pharmaceutical interventions deployed in the ongoing pandemic across local-8 ities in China, South Korea, Italy, Iran, France, and the United States (US). We 9 then apply reduced-form econometric methods, commonly used to measure the ef-10 fect of policies on economic growth, 5, 6 to empirically evaluate the effect that these 11 anti-contagion policies have had on the growth rate of infections. In the absence of 12 policy actions, we estimate that early infections of COVID-19 exhibit exponential 13 growth rates of roughly 38% per day. We find that anti-contagion policies have 14 significantly and substantially slowed this growth. Some policies have different 15 impacts on different populations, but we obtain consistent evidence that the pol-16 icy packages now deployed are achieving large, beneficial, and measurable health 17 outcomes. We estimate that across these six countries, interventions prevented 18 or delayed on the order of 62 million confirmed cases, corresponding to averting : medRxiv preprint 23The COVID-19 pandemic is forcing societies worldwide to make consequential policy decisions 24 with limited information. After containment of the initial outbreak failed, attention turned to 25 implementing non-pharmaceutical interventions designed to slow contagion of the virus. In general, 26 these policies aim to decrease virus transmission by reducing contact among individuals within 27 or between populations, such as by closing restaurants or restricting travel, thereby slowing the 28 spread of COVID-19 to a manageable rate. These large-scale anti-contagion policies are informed 29 by epidemiological simulations 2, 4, 8, 9 and a small number of natural experiments in past epidemics. 10 30 However, the actual effects of these policies on infection rates in the ongoing pandemic are unknown. 31Because the modern world has never confronted this pathogen, nor deployed anti-contagion policies 32 of such scale and scope, it is crucial that direct measurements of policy impacts be used alongside 33 numerical simulations in current decision-making. 34Societies around the world are weighing whether the health benefits of anti-contagion policies 35 are worth their social and economic costs. Many of these costs are plainly seen; for example, 36 business restrictions increase unemployment and school closures impact educational outcomes. It is 37 therefore not surprising that some populations have hesitated before implementing such dramatic 38 policies, especially when their costs are visible while their health benefits -infec...
This article has an accompanying continuing medical education activity, also eligible for MOC credit, on page e19. Learning Objective: Upon completion of this CME activity, successful learners will be able to (1) explain the risk factors for and outcomes of acute-on-chronic liver failure (ACLF), (2) determine when supportive care for these patients may be futile, and (3) recognize factors associated with reduced patient survival after liver transplantation.
Introduction: More than 93,000 cases of coronavirus disease have been reported worldwide. We describe the epidemiology, clinical course, and virologic characteristics of the first 12 U.S. patients with COVID-19. Methods:We collected demographic, exposure, and clinical information from 12 patients confirmed by CDC during January 20-February 5, 2020 to have COVID-19. Respiratory, stool, serum, and urine specimens were submitted for SARS-CoV-2 rRT-PCR testing, virus culture, and whole genome sequencing. Results:Among the 12 patients, median age was 53 years (range: 21-68); 8 were male, 10 had traveled to China, and two were contacts of patients in this series. Commonly reported signs and symptoms at illness onset were fever (n=7) and cough (n=8). Seven patients were hospitalized with radiographic evidence of pneumonia and demonstrated clinical or laboratory signs of worsening during the second week of illness. Three were treated with the investigational antiviral remdesivir. All patients had SARS-CoV-2 RNA detected in respiratory specimens, typically for 2-3 weeks after illness onset, with lowest rRT-PCR Ct values often detected in the first week. SARS-CoV-2 RNA was detected after reported symptom resolution in seven patients. SARS-CoV-2 was cultured from respiratory specimens, and SARS-CoV-2 RNA was detected in stool from 7/10 patients. Conclusions:In 12 patients with mild to moderately severe illness, SARS-CoV-2 RNA and viable virus were detected early, and prolonged RNA detection suggests the window for diagnosis is long. Hospitalized patients showed signs of worsening in the second week after illness onset.for use under a CC0 license.
Bariatric surgery (BS) is effective in treating morbid obesity, but the impact of prior BS on candidacy for liver transplantation (LT) is unclear. We examined 78 patients with cirrhosis with prior BS compared with a concurrent cohort of 156 patients matched by age, Model for End‐Stage Liver Disease score, and underlying liver disease. We compared rates of transplant denial after evaluation, delisting on the waiting list, and survival after LT. The median time from BS to LT evaluation was 7 years. Roux‐en‐Y gastric bypass was the most common BS procedure performed (63% of cohort). Nonalcoholic fatty liver disease was the leading etiology for liver cirrhosis (47%). Delisting/death on the waiting list was higher among patients with BS (33.3% versus 10.1%; P = 0.002), and the transplantation rate was lower (48.9% versus 65.2%; P = 0.03). Intention‐to‐treat (ITT) survival from listing to 1 year after LT was lower in the BS cohort versus concurrent cohort (1‐year survival, 84% versus 90%; P = 0.05). On adjusted analysis, a history of BS was associated with an increased risk of death on the waiting list (hazard ratio [HR], 5.7; 95% confidence interval [CI], 2.2‐15.1), but this impact was attenuated (HR, 4.9; 95% CI, 1.8‐13.4) by the presence of malnutrition. When limited to matched controls by sex, mortality attributed to BS was no longer significant for females (P = 0.37) but was significant for males (P = 0.046). Sarcopenia, as captured by skeletal muscle index, was calculated in a subset of patients (n = 49). The total skeletal surface area was lower in the BS group (127 [105‐141] cm2 versus 153 [131‐191] cm2; P = 0.005). Rates of sarcopenia were higher among patients delisted after listing (71.4% versus 16.7%; P = 0.04). In conclusion, a history of BS was associated with higher rates of delisting on the waiting list as well as lower survival from the time of listing on ITT analysis. Presence of malnutrition and sarcopenia among patients with BS may contribute to worse outcomes.
The ability to make rapid diagnosis of infectious diseases broadly available in a portable, low-cost format would mark a great step forward in global health. Many molecular diagnostic assays are developed based on using thermal cyclers to carry out polymerase chain reaction (PCR) and reverse-transcription PCR for DNA and RNA amplification and detection, respectively. Unfortunately, most commercial thermal cyclers are expensive and need continuous electrical power supply, so they are not suitable for uses in low-resource settings. We have previously reported a low-cost and simple approach to amplify DNA using vacuum insulated stainless steel thermoses food cans, which we have named it thermos thermal cycler or TTC. Here, we describe the use of an improved set up to enable the detection of viral RNA targets by reverse-transcription PCR (RT-PCR), thus expanding the TTC’s ability to identify highly infectious, RNA virus-based diseases in low resource settings. The TTC was successful in demonstrating high-speed and sensitive detection of DNA or RNA targets of sexually transmitted diseases, HIV/AIDS, Ebola hemorrhagic fever, and dengue fever. Our innovative TTC costs less than $200 to build and has a capacity of at least eight tubes. In terms of speed, the TTC’s performance exceeded that of commercial thermal cyclers tested. When coupled with low-cost endpoint detection technologies such as nucleic acid lateral-flow assay or a cell-phone-based fluorescence detector, the TTC will increase the availability of on-site molecular diagnostics in low-resource settings.
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