Outpatient therapies for COVID-19: How do we choose?

Background: Several outpatient COVID-19 therapies have reduced hospitalization in randomized controlled trials. The choice of therapy may depend on drug efficacy, toxicity, pricing, availability, and access to administration infrastructure. To facilitate comparative decision making, we evaluated the efficacy of each treatment in clinical trials and then estimated the associated cost per hospitalization prevented. Methods: Wherever possible, we obtained relative risk for hospitalization from published randomized controlled trials. Otherwise, we extracted data from press releases, conference abstracts, government submissions, or preprints. If more than one study was published, the results were meta-analyzed. Using relative risk, we estimated the number needed to treat (NNT), assuming a baseline hospitalization risk of 5%. Drug pricing was based on Canadian formularies, government purchases, or manufacturer estimates. Administrative and societal costs were not included. Results will be updated online as new studies emerge or final publication numbers become available. Results: At a 5% risk of hospitalization the estimated NNTs were: 87 for colchicine, 80 for fluvoxamine, 72 for inhaled corticosteroids, 24 for nirmatrelvir/ritonavir, 25 for sotrovimab, 24 for remdesivir, 29 for casirivimab/imdevimab, 29 for bamlanivimab/etesevimab and 52 for molnupiravir. Colchicine, fluvoxamine, inhaled corticosteroids, and nirmatrelvir/ritonavir had cost per hospitalization prevented point estimates below the CIHI estimated cost of hospitalization ($23000). Interpretation: Canada is fortunate to have access to several effective outpatient therapies to prevent COVID-19 hospitalization. Given differences in efficacy, toxicity, cost and administration complexities, this assessment serves as one tool to help guide policy makers and clinicians in their treatment selection.

Using Machine Learning to Improve Public Reporting on U.S. Government Contracts

The U.S. government procures more than $500 billion annually in goods and services on public contracts, which it classifies using a hierarchical product and service taxonomy. Classification serves several purposes, including transparency in the use of taxpayer funding; reporting, tracing, and segmenting government expenditures; budgeting; and forecasting. Government acquisition personnel have historically performed these classifications manually, resulting in a process that is time-consuming and error-prone and offers limited visibility into government purchases. The problem faced is not unique to the public sector and is common across retail, manufacturing, and healthcare, among other settings. Using almost 4 million historical data records on governmental purchases, we fit a series of classifiers and demonstrate (a) superior performance when explicitly modeling the hierarchical structure of information domains through the use of top-down strategies and (b) the effectiveness of character-level convolutional neural networks when textual inputs are terse and contain irregularities such as abnormal character combinations and misspellings, which are common in government contracts. Our machine learning models are embedded in multiple software applications, including a web application that we developed, used by federal government personnel and other contracting professionals.

Estimating the True Size of Public Procurement to Assess Sustainability Impact

Public procurement, the government’s purchase of goods and services, is an important tool to advance sustainability objectives. Since government is the largest consumer in the economy, it can have a sizable impact on the market by purchasing sustainably. However, its sustainability impact (both environmental and social) is undermined because the public procurement’s size is underestimated. Previous estimates of public procurement only consider contract-based purchases or non-defense purchases. In other instances, data are too limited to estimate government purchases appropriately. These factors lead to underestimations of the extent to which government purchasing can be leveraged to advance sustainability objectives. To understand the true impact of government purchases, we estimated the size of public procurement by considering all aspects of public procurement. We used this estimation to assess whether current measurement processes misrepresent the size of public procurement and identify key elements that may be missing from the current public procurement measures. We applied our estimate to four OECD countries, the U.S., the U.K., Italy, and the Netherlands for two years (2017 and 2018). Our results showed that that across all levels of government, public procurement as a percentage of GDP in the U.S., the U.K., Italy, and the Netherlands ranged between 19–24%, 13–56%, 3–10%, and 12–38%, respectively. Our findings revealed that governments have substantially greater market power than previously estimated, which can be leveraged to pursue sustainability goals. Our findings also illustrate systemic data challenges to how public procurement data are collected and analyzed.

Effect of Eco Friendly Practices in Hospitality Industry

Recently, one of the biggest problem in world is greenhouse gas, because of still having problems, covering the global temperature change, and making the after the exhaustion of the gas, pollution, the prince of the powers of the partly strong, and for the promotion of funds to subsidize the consumption of the amount of waste. Hotels, such as the commercial trade, have a major impact on the environment. However, the hotel has the same proportion of mourning graduated development partner, ask whether to recommend a speech disability matters is very necessary to help Hoteliers green. The study measures the outlook in consumer activity. The case herein is has a fresh take on art with respect to the use of the construction of the exercises in Indian. The product is a quantitative method used, and a result in a structured manner to a secondary analysis expediency sampling was used. The study was conduct among cities of Delhi NCR. Fertilization will live only language to the behaviors and attitudes of consumers. Buyers of construction services that take advantage of specific environmental practices terribly chosen for their property. the operations of the types of study, uninitiated in the hotel, however, the quality of service they tend to belong to the cell which is offered to us. It was found that buyers were unwilling to pay more for the adoption of inexperienced practices. The construction trade will be necessary to create investment from an inexperienced trainees must be thought of as environmentally friendly. government purchases be an advantage to know the hotel recommends acting as a tax deduction. The study of the behavior on the client is to be measured, and, with a little experience, accessibility applications. Construction sector business model that immediately follows the consistent long-term objective of developing the proper hotels. It may be awkward, and urged for its operating practices are the most popular model.

Sources of Borrowing and Fiscal Multipliers

This paper finds that debt-financed fiscal multipliers vary depending on the location of the debt buyer. In a sample of 33 countries fiscal multipliers are larger when government purchases are financed by issuing debt to foreign investors (non-residents), compared to when they are financed by issuing debt to home investors (residents). In a theoretical model, the location of the government creditor produces these differential responses through the extent that private investment is crowded out. International capital mobility of the resident private sector decreases the difference between the two types of financing both in the model and in the data.

Multicriteria Anomaly Detection in Government Purchases

Government purchases are the usual instrument for public acquisition of goods and services. Despite extensive legislation and several control and auditing mechanisms, frauds are still diverse and commonplace at all levels of public administration. This work proposes a methodology for detecting anomalies in government purchases. The methodology promotes several levels of filtering with respect to entities involved and purchases considered as fraudulent considering diverse criteria. The applicability and effectiveness of the methodology is demonstrated through a case study using real data where we were able to identify a long term provider collusion.