Using the network scale-up method to characterise kidney trafficking in Kalai Upazila, Bangladesh.

This study aimed to estimate the prevalence of illegal kidney sales in Kalai Upazila, Bangladesh, using the Network Scale-Up Method (NSUM), an ego-centric network survey-based technique used to estimate the size of hidden populations. The study estimated the size of the kidney seller population, analysed the profiles of kidney sellers and kidney brokers and investigated the characteristics of villagers who are more likely to be connected to kidney sellers to identify possible biases of the NSUM estimate. The study found that the prevalence of kidney trafficking in Kalai Upazila was between 1.98% and 2.84%, which is consistent with the estimates provided by a local leader and reporters, but with much narrower bounds. The study also found that a large proportion of kidney sellers and brokers were men (over 70% and 90%, respectively) and relatively young (mean age of 33 and 39, respectively). Specific reasons for kidney sales included poverty (83%), loan payment (4%), drug addiction (2%) and gambling (2%). While most reported male sellers were farmers (56%) and female sellers were housewives (78%) in need of money, most reported brokers were characterised as rich, well-known individuals.

Identifying kidney trade networks using web scraping data.

Kidney trade has been on the rise despite the domestic and international law enforcement aiming to protect the vulnerable population from potential exploitation. Regional hubs are emerging in several parts of the world including South Asia, Central America, the Middle East and East Asia. Kidney trade networks reported in these hot spots are often complex systems involving several players such as buyers, sellers and surgery countries operating across international borders so that they can bypass domestic laws in sellers and buyers' countries. The exact patterns of the country networks are, however, largely unknown due to the lack of a systematic approach to collect the data. Most of the kidney trade information is currently available in the form of case studies, court materials and news articles or reports, and no comprehensive database exists at this time. The present study thus explored online newspaper scraping to systematically collect 10 419 news articles from 24 major English newspapers in South Asia (January 2016 to May 2019) and build transnational kidney trade networks at the country level. Additionally, this study applied text mining techniques to extract words from each news article and developed machine learning algorithms to identify kidney trade and non-kidney trade news articles. Our findings suggest that online newspaper scraping coupled with the machine learning method is a promising approach to compile such data, especially in the dire shortage of empirical data.

Explainable AI: A Neurally-Inspired Decision Stack Framework.

European law now requires AI to be explainable in the context of adverse decisions affecting the European Union (EU) citizens. At the same time, we expect increasing instances of AI failure as it operates on imperfect data. This paper puts forward a neurally inspired theoretical framework called "decision stacks" that can provide a way forward in research to develop Explainable Artificial Intelligence (X-AI). By leveraging findings from the finest memory systems in biological brains, the decision stack framework operationalizes the definition of explainability. It then proposes a test that can potentially reveal how a given AI decision was made.

Cost-effectiveness of Babesia microti antibody and nucleic acid blood donation screening using results from prospective investigational studies.

BACKGROUND: Babesia microti causes transfusion-transmitted babesiosis (TTB); currently, blood donor screening assays are unlicensed but used investigationally. STUDY DESIGN AND METHODS: We developed a decision tree model assessing the comparative- and cost-effectiveness of B. microti blood donation screening strategies in endemic areas compared to the status quo (question regarding a history of babesiosis), including testing by: (1) universal antibody (Ab), (2) universal polymerase chain reaction (PCR), (3) universal Ab/PCR, and (4) recipient risk-targeted Ab/PCR. The model predicted the number of TTB cases, complicated TTB cases, cases averted, and quality-adjusted life years (QALYs). Economic outcomes included each strategy's per-donation cost, waste (number of infection-free units incorrectly discarded), and waste index (number wasted units/number true positives). Sensitivity analyses examined uncertainty in transmission probabilities, prevalence rates, and other key model inputs. RESULTS: Universal PCR in four endemic states would prevent 24 to 31 TTB cases/100,000 units transfused (pht) at an incremental cost-effectiveness ratio (ICER) of $26,000 to $44,000/QALY (transmission probability dependent) and waste index of zero. Universal Ab/PCR would prevent 33 to 42 TTB cases pht at an ICER of $54,000 to $83,000/QALY and waste index of 0.05. The questionnaire is most wasteful (99.62 units wasted pht; 208.62 waste index), followed by the risk-targeted strategy (76.27 units wasted pht; 0.68 waste index). The model predicted zero cases of TTB or complicated TTB with universal Ab/PCR (versus [33, 42] and [13, 18] pht, respectively [no screening]). Results are highly sensitive to transmission probabilities. CONCLUSIONS: Universal PCR in endemic states is an effective blood donation screening strategy at a threshold of $50,000/QALY. Using a higher cost-effectiveness ratio, universal Ab/PCR is the most effective strategy.

A socio-technical, probabilistic risk assessment model for surgical site infections in ambulatory surgery centers.

BACKGROUND: To understand how structural and process elements may affect the risk for surgical site infections (SSIs) in the ambulatory surgery center (ASC) environment, the researchers employed a tool known as socio-technical probabilistic risk assessment (ST-PRA). ST-PRA is particularly helpful for estimating risks in outcomes that are very rare, such as the risk of SSI in ASCs. OBJECTIVE: Study objectives were to (1) identify the risk factors associated with SSIs resulting from procedures performed at ASCs and (2) design an intervention to mitigate the likelihood of SSIs for the most common risk factors that were identified by the ST-PRA for a particular surgical procedure. METHODS: ST-PRA was used to study the SSI risk in the ASC setting. Both quantitative and qualitative data sources were utilized, and sensitivity analysis was performed to ensure the robustness of the results. RESULTS: The event entitled "fail to protect the patient effectively" accounted for 51.9% of SSIs in the ambulatory care setting. Critical components of this event included several failure risk points related to skin preparation, antibiotic administration, staff training, proper response to glove punctures during surgery, and adherence to surgical preparation rules related to the wearing of jewelry, watches, and artificial nails. Assuming a 75% reduction in noncompliance on any combination of 2 of these 5 components, the risk for an SSI decreased from 0.0044 to between 0.0027 and 0.0035. CONCLUSION: An intervention that targeted the 5 major components of the major risk point was proposed, and its implications were discussed.