Explore the vast range of titles available.

Background Good quality cause of death (COD) information is fundamental for formulating and evaluating public health policy; yet most deaths in developing countries, including the Solomon Islands, occur at home without medical certification of cause of death (MCCOD). As a result, COD data in such contexts are often of limited use for policy and planning. Verbal autopsies (VAs) are a cost-effective way of generating reliable COD information in populations lacking comprehensive MCCOD coverage, but this method has not previously been applied in the Solomon Islands. This study describes the establishment of a VA system to estimate the cause specific mortality fractions (CSMFs) for community deaths that are not medically certified in the Solomon Islands. Methods Automated VA methods (SmartVA) were introduced into the Solomon Islands in 2016. Trained data collectors (nurses) conducted VAs on eligible deaths to December 2020 using electronic tablet devices and VA responses were analysed using the Tariff 2.0 automated diagnostic algorithm. CSMFs were generated for both non-inpatient deaths in hospitals (i.e. ‘dead on/by arrival’) and community deaths. Results VA was applied to 914 adolescent-and-adult deaths with a median (IQR) age of 62 (45–75) years, 61% of whom were males. A specific COD could be diagnosed for more than 85% of deaths. The leading causes of death for both sexes combined were: ischemic heart disease (16.3%), stroke (13.5%), diabetes (8.1%), pneumonia (5.7%) and chronic-respiratory disease (4.8%). Stroke was the top-ranked cause for females, and ischaemic heart disease the leading cause for males. The CSMFs from the VAs were similar to Global Burden of Disease (GBD) estimates. Overall, non-communicable diseases (NCDs) accounted for 73% of adult deaths; communicable, maternal and nutritional conditions 15%, and injuries 12%. Six of the ten leading causes reported for facility deaths in the Solomon Islands were also identified as leading causes of community deaths based on the VA diagnoses. Conclusions NCDs are the leading cause of adult deaths in the Solomon Islands. Automated VA methods are an effective means of generating reliable COD information for community deaths in the Solomon Islands and should be routinely incorporated into the national mortality surveillance system.

Background A verbal autopsy (VA) is a post-hoc written interview report of the symptoms preceding a person’s death in cases where no official cause of death (CoD) was determined by a physician. Current leading automated VA coding methods primarily use structured data from VAs to assign a CoD category. We present a method to automatically determine CoD categories from VA free-text narratives alone. Methods After preprocessing and spelling correction, our method extracts word frequency counts from the narratives and uses them as input to four different machine learning classifiers: naïve Bayes, random forest, support vector machines, and a neural network. Results For individual CoD classification, our best classifier achieves a sensitivity of.770 for adult deaths for 15 CoD categories (as compared to the current best reported sensitivity of.57), and.662 with 48 WHO categories. When predicting the CoD distribution at the population level, our best classifier achieves.962 cause-specific mortality fraction accuracy for 15 categories and.908 for 48 categories, which is on par with leading CoD distribution estimation methods. Conclusions Our narrative-based machine learning classifier performs as well as classifiers based on structured data at the individual level. Moreover, our method demonstrates that VA narratives provide important information that can be used by a machine learning system for automated CoD classification. Unlike the structured questionnaire-based methods, this method can be applied to any verbal autopsy dataset, regardless of the collection process or country of origin.

Background Physician-coded verbal autopsy (PCVA) is the most widely used method to determine causes of death (CODs) in countries where medical certification of death is uncommon. Computer-coded verbal autopsy (CCVA) methods have been proposed as a faster and cheaper alternative to PCVA, though they have not been widely compared to PCVA or to each other. Methods We compared the performance of open-source random forest, open-source tariff method, InterVA-4, and the King-Lu method to PCVA on five datasets comprising over 24,000 verbal autopsies from low- and middle-income countries. Metrics to assess performance were positive predictive value and partial chance-corrected concordance at the individual level, and cause-specific mortality fraction accuracy and cause-specific mortality fraction error at the population level. Results The positive predictive value for the most probable COD predicted by the four CCVA methods averaged about 43% to 44% across the datasets. The average positive predictive value improved for the top three most probable CODs, with greater improvements for open-source random forest (69%) and open-source tariff method (68%) than for InterVA-4 (62%). The average partial chance-corrected concordance for the most probable COD predicted by the open-source random forest, open-source tariff method and InterVA-4 were 41%, 40% and 41%, respectively, with better results for the top three most probable CODs. Performance generally improved with larger datasets. At the population level, the King-Lu method had the highest average cause-specific mortality fraction accuracy across all five datasets (91%), followed by InterVA-4 (72% across three datasets), open-source random forest (71%) and open-source tariff method (54%). Conclusions On an individual level, no single method was able to replicate the physician assignment of COD more than about half the time. At the population level, the King-Lu method was the best method to estimate cause-specific mortality fractions, though it does not assign individual CODs. Future testing should focus on combining different computer-coded verbal autopsy tools, paired with PCVA strengths. This includes using open-source tools applied to larger and varied datasets (especially those including a random sample of deaths drawn from the population), so as to establish the performance for age- and sex-specific CODs.

Background Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data. Methods Tariff calculates a score, or \"tariff,\" for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data. Results Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates. Conclusions Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science.

As tariffs on imports of manufactures have been reduced as a result of multi-lateral trade negotiations, interest in the extent to which existing nontariff barriers may distort and restrict international trade is growing. Accurate and reliable measures are needed in order to address the issues involving the use and impacts of nontariff barriers. This study assesses currently available methods for quantifying such barriers and makes recommendations as to those methods that can be most effectively employed. The authors focus both on the conceptual issues arising in the measurement of the different types of nontariff barriers and on the applied research that has been carried out in studies prepared by country members of the OECD Pilot Group and others seeking to quantify the barriers. Nontariff barriers include quotas, variable levies, voluntary export restraints, government procurement regulations, domestic subsidies, and antidumping and countervailing duty measures. The authors discuss the many different methods available for measuring the effects of these and other nontariff barriers. Illustrative results are presented for industrial OECD countries, including Australia, Canada, Germany, Norway, the European Union, the United Kingdom, and the United States. Finally, the authors offer guideline principles and recommend procedures for measuring different types of nontariff barriers. Economists, political scientists, government officials, and lawyers involved in international trade will find this an invaluable resource for understanding and measuring NTBs. Alan V. Deardorff and Robert M. Stern are Professors of Economics and Public Policy, University of Michigan.

The conducted researches have shown that the features of the housing and communal sector do not allow talking about the possibility of calculating the “optimal” tariff rate. The development of an effective method of tariff formation for rural areas is particularly acute. The use of traditional method to calculate the amount of tariffs for housing and communal services provided to the population and enterprises (called “cost plus” approach) consists in a simple summation of the cost price of a service with a premium that was set directly by a particular housing and communal enterprise within the maximum and minimum values. The authors found that none of the current pricing and tariffs’ setting methods fulfills the requirements for an effective and economically founded tariff policy in the housing and communal services sector. In this regard, the development of a new methodology that will ensure the receipt of compromise tariffs for housing and communal services is required. Compromise analysis, the main purpose of which is to obtain optimal prices, can be used as a basis of such methodology.

This study contains the attempt of the comprehensive approach to issues of the correlation of concepts, provisions and obligations of States and their associations with respect to technical barriers to trade (in particular, technical regulations, standardization, certification, and accreditation, conformity assessment procedures and market surveillance systems) enshrined in international world treaties (in particular, the Agreement on Technical Barriers to Trade (TBT), which is binding for Member-States in the system of the WTO treaties) and regional multilateral and bilateral treaties (for example, the Association Agreement between Ukraine, from one part, and the European Union, European Atomic Energy Community, and their Member-States, from the other part, dd. June 27, 2014). The particular attention is paid to the national, including unified (or that being in the process of unification/adaptation), institutional and legal provision in this area, most notably in Ukraine and the European Union (first of all, the Regulation of the European Parliament and of the Council No. 765/2008/EC and Decision of the European Parliament and of the Council No. 768/2008/EC of 9 July 2008). The performance by Ukraine at the domestic/national level of its international obligations in accordance with the Association Agreement 2014 has been separately considered in terms of technical regulations and standardization, accreditation, conformity assessment procedures and market surveillance systems and their implementation (adaptation, entrenchment) in relevant regulatory legal, and organizational and institutional forms.

This publication identifies export products from Maldives that are affected by sanitary and phytosanitary measures and technical barriers to trade. The trade patterns of Maldives within South Asia, particularly with regard to Bangladesh, Bhutan, India, Nepal, and Sri Lanka, were examined and a gap analysis was conducted on relevant legal structures, institutional frameworks, and infrastructure. Specific trade-hindering nontariff measures applied to the potential export products are identified and prioritized recommendations to address them are also proposed.

Oil transportation via trunk pipelines is an important part of the oil industry's activity. The main instrument of tariff regulation is the method of tariffs formation. Three methods of tariffs formation such as the method of economically justified costs (the Cost plus method), the method of economically justified return on investment capital (the RAB method), and the method of tariffs indexation were considered.

Evaluates methods for measuring nontariff barriers and recommends the most effective procedures.