On Infant Mortality in the Soviet Union: A Comment

The global fallout from atmospheric nuclear weapons testing in the 1950s and 1960s caused by far the greatest exposure of mankind to ionizing radiation. Surprisingly few epidemiological studies of the possible health effects of atmospheric testing have been conducted. Here, long-term trends in infant mortality rates in the United States (U.S.) and five major European countries (EU5) were examined: The United Kingdom, Germany, France, Italy, and Spain. Bell-shaped deviations from a uniformly decreasing secular trend were found beginning in 1950, with maxima around 1965 in the U.S. and 1970 in EU5. From the difference between observed and predicted infant mortality rates, in the period 1950-2000, the overall increase in infant mortality rates was estimated to be 20.6 (90% CI: 18.6 to 22.9) percent in the U.S. and 14.2 (90% CI: 11.7 to 18.3) percent in EU5 which translates to 568,624 (90% CI: 522,359 to 619,705) excess infant deaths in the U.S. and 559,370 (90% CI: 469,308 to 694,589) in the combined five European countries. The results should be interpreted with caution because they rely on the assumption of a uniformly decreasing secular trend if there had been no nuclear tests, but this cannot be verified. It is concluded that atmospheric nuclear weapons testing may be responsible for the deaths of several million babies in the Northern Hemisphere.

Between the 1950s and 2000, Venezuela showed one of the most substantial improvements in infant mortality rates in Latin America. However, the recent economic crisis alongside an increase in infectious and parasitic diseases might be reversing previous patterns. Because no official updated mortality statistics have been published since 2013, the effect of these recent events has been difficult to assess accurately. We therefore aimed to estimate infant mortality rate trends and report the effect of the crisis. We estimated infant mortality rates using direct methods (ie, death counts from Venezuelan Ministry of Health via yearbooks and notifiable diseases bulletins, and birth records published by the UN Economic Commission for Latin America and the Caribbean and the Venezuelan National Institute of Statistics) and indirect methods (using census data and a Living Conditions Survey ENCOVI 2016). We shaped yearly estimations using a semiparametric regression model, specifically a P-Spline model with a cubic thin plate base. The primary objective was to estimate infant mortality rate trends from 1985 to 2016. Around 2009, the long-term decline in infant mortality rate stopped, and a new pattern of increase was observed. The infant mortality rate reached 21·1 deaths per 1000 livebirths (90% CI -17·8 to 24·3) in 2016, almost 1·4 times the rate of 2008 (15·0, -14·0 to 16·1). This increase represents a huge setback on previous achievements in reducing infant mortality. Our conservative estimation indicates that Venezuela is in the throes of a humanitarian crisis. The increase in infant mortality rate in 2016 compared with 2008 takes the country back to the level observed at the end of the 1990s, wiping out 18 years of expected progress, and leaves the Venezuelan Government far from achieving the target of nine deaths per 1000 livebirths stated in the UN Millennium Development Goals. None.

The human interaction with machines has come a long way from the ancient times to the Artificial Intelligence (AI) tools today, threatening individuals and organisations in various professions. ChatGPT (CGPT) has entered on the scenes to replace researchers and research assistants, creating a hysertia and hype at every level that CGPT will replace science. Although it is dubbed as a substitute of scholars, CGPT, its true implications can be judged by the error of omission versus commission to answer whether CGPT plays an effective role in the efficiency and effectiveness of supporting research and practice. Based on the framework of errors of commission and omission, this article tests the function of CGPT as a research assistant, which answers theoretical question why biases occur (if any) and how they occur, and a practical question how to prevent them. This article is based on an experiment with CGPT to test whether it can produce (a) summaries based on citations, (b) citations based on summaries it produced, and (c) citations based on the published abstract of the research article in the literature. For consistency, this study uses 1 author (who was able and willing to participate), 34 publications in referred journals, multiple experiments. The result shows three patterns. First, CGPT produced summaries of all citations correctly, and the proximity between the abstract and summary ranged from 5 to 10 with average about 7 on 10-scale. Second, the summary to citation was 100% inaccurate and biased. Third, the link from the abstract to citation was 100% biased. In the theory of errors of omission and errors of commission, this study explains where, how and why those errors occur in the contextualised world.

We assess the surface gravity data requirements for a 5-mm quasi-geoid model for the Netherlands mainland and continental shelf in terms of omission and commission errors. The omission error critically depends on the roughness of the topography and bathymetry. For the Netherlands continental shelf, Central and Northern Netherlands, the omission error is well described by the model 0.32d mm, where d is the data spacing in km. For the more hilly Southern Netherlands, the omission error model is 0.92d mm. The commission error depends on the kernel modification, the data spacing, and the data accuracy. When using the spheroidal Stokes kernel, it is well described by 0.277 d σΔg mm, where σΔg is the noise standard deviation of surface gravity data in mGal. An upper bound of the commission error of the state-of-the-art satellite-only gravity model GOCO05S over the Netherlands is e0.03676L–11.419 mm, where L is the maximum degree up to which this model is used. Only if this model is truncated at a sufficiently low degree, e.g., at degree 100, its contribution to the total commission error can be neglected. We determine the total error as the sum of commission and omission errors. Hence, to realize a 5-mm quasi-geoid model for the Netherlands mainland and continental shelf, a data spacing of 3.5 km is needed when assuming a noise standard deviation of 1.5 mGal for surface gravity data. The currently available land-based gravity data fulfill this requirement. This does not apply to the situation at sea, where the density of the shipboard gravity data and the accuracy of the radar altimeter-derived data do not allow the realization of a 5-mm quasi-geoid model.

BackgroundRecently, the demand for care has risen, while in contrast, healthcare resources remain limited. These resources include health expenditure, the number of physicians, nurses, and hospital beds. Many studies have revealed that healthcare resources are one of the most critical factors contributing to a population’s health status. The healthcare system plays a key role in transforming these resources into health outcomes, which are widely used as indicators to measure population health and the performance of healthcare systems. Previous work has primarily investigated the relationship between health expenditure or the number of doctors and population health. However, the association between healthcare resources as a whole has yet to be widely examined.MethodsThis study utilized multilevel regression analysis to explore the association between healthcare resources, healthcare systems, and population health outcomes across 25 European countries. The healthcare systems in these countries are primarily categorized into two types: Beveridge-type and Bismarck-type. In addition to regression analysis, descriptive statistics were used to analyze the allocation patterns of healthcare resources. Welch’s t-test was employed to compare the performance metrics of the Beveridge-type and Bismarck-type healthcare systems, providing a statistical basis for understanding differences in their effectiveness.ResultsThe regression analysis revealed positive correlations between health expenditure per capita, the number of physicians, and nurses, and life expectancy at birth, while the number of hospital beds showed a negative correlation. Conversely, infant mortality was negatively correlated with health expenditure per capita and the number of physicians and nurses, and positively correlated with the number of hospital beds. The models did not find statistical significance in the effects of healthcare system type (Beveridge-type or Bismarck-type) on life expectancy at birth or infant mortality rates. Additionally, Welch’s t-test indicated that the Beveridge-type healthcare system generally showed better performance outcomes compared to the Bismarck-type system.ConclusionsThe findings indicate that higher allocations of certain healthcare resources, such as hospital beds, are associated with poorer health outcomes, which suggests potential inefficiencies in resource utilization. Observations also show that countries using the same healthcare systems tend to have similar patterns of resource allocation, which may influence the performance of these systems. Policymakers should consider these associations when planning resource allocation and when selecting or modifying healthcare system models in their countries.

In this paper, the optimal threshold for fire detection is derived based on the probability density functions of the fire and background pixels. The threshold values and the commission and omission errors are computed according to several detection criteria: maximum likelihood, null-hypothesis testing, and minimum cost. This statistical approach enables the determination of optimal threshold value according to the specific requirements of the detection tasks I. INTRODUCTION Active fire detection using satellite thermal sensors usually involves thresholding the detected brightness temperature in several bands. The frequently used features for fire detection are the brightness temperature in the 4-µm wavelength band (T4) and the brightness temperature difference between the 4- µm and 11- µm bands (∆T=T4-T11) (1), (2), (3). Due to the statistical nature of the fire and background temperature distribution, no matter how the thresholds are chosen, there are bound to be commission errors (i.e. false alarms) and omission errors (false negatives) in the detection outcomes. In the commonly used fire detection algorithms, the thresholds are often arbitrarily defined, and hence may not be optimal for a given fire detection task. The optimal threshold values are expected to be site dependent. They are different in different regions and for different fire conditions (such as smoldering and flaming fires). Hence, a global set of threshold values may not work optimally for a specific site. The task of active fire hot spot detection can be modeled as a stochastic target detection procedure (4). In this model, each pixel of the image occupies a point (T4, ∆T) in the two- dimensional feature space, and each pixel belongs to either the fire class or the non-fire background class. This approach considers the probability density functions of the fire and background pixels and optimal thresholds are derived depending on the specific objectives of the detection tasks. In a previous work (4), we implemented a method for deriving the optimal detection threshold by minimizing a cost function which is a weighted sum of the omission and commission errors. Alternatively, the threshold can also be derived based on other criteria. In this paper, we derive the optimal thresholds for detecting active fires in MODIS scenes using various detection criteria: maximum likelihood, constant false alarm rate, and null-hypothesis testing. The test data set consists of several MODIS scenes over Sumatra and Borneo islands and coincidental high resolution SPOT scenes (5). The SPOT data serves as ground truth for validation of MODIS hotspots detected by the new algorithms based on stochastic models. The probability density functions (pdf's) of the fire and background pixels are derived from this dataset and these pdf's are used to derive the optimal thresholds for active fire detection.

AimPresence‐only data represent a significant source of information for quantifying biodiversity distributions and provide opportunities for use in conservation planning. The large databases of presence‐only records that are available and the lower cost of acquisition could help overcome the traditional problem of lack of data for conservation. However, there are risks associated with the use of presence‐only data inherent with the lack of true absences that might cause omission errors (species are erroneously thought to be absent) and loss of efficiency (more areas are thought to be necessary than needed). These errors could constrain the economic viability of conservation plans and thus the success of conservation practice. We therefore evaluated the opportunities and risks of using presence‐only data for conservation planning.LocationNorthern Australia.MethodsThe effects of using two different types (presence‐only and presence–absence) and different quantities of data were simulated by building predictive models on different subsets of data with increasing numbers of presence–absence or presence‐only records or a combination of both, for 80 freshwater fish species. We then compared the performance of conservation planning outcomes with the best information attainable (a true model built on the complete set of presence–absence data). We measured omission and commission errors in conservation planning outcomes, and the efficiency of and return on the investment in data acquisition.ResultsIncluding presence‐only data helped reduce commission and omission errors in conservation planning outcomes, but only when used in combination with at least some presence–absence data. The use of just a large quantity of presence‐only data resulted in significant reductions in the efficiency of conservation planning outcomes, as more areas than actually needed were required to achieve conservation targets. This reduction in efficiency was mainly related to inflated omission errors.Main conclusionsWe recommend using presence‐only data cautiously if this is the only source of data available; whenever possible, presence‐only data should be complemented with presence–absence data.

Association between DRD4 Gene and Performance of Children with ADHD in a Test of Sustained Attention

Background: The health sector is one of the most important service sectors and one of the indicators of development and social welfare. The aim of this study is to evaluate the efficiency of Iranchr('39')s health system compared to developed countries.Methods: This study used data envelopment analysis to evaluate efficiency. All members of the Organization for Economic Co-operation and Development (OECD), along with Iran, were considered as the decision units in the analysis. Outputs are life expectancy at birth and infant mortality rate; and inputs are health expenditure, number of physicians, and number of hospital beds. DEA Solver software was used for the analysis.Results: The most efficient countries in terms of the health system are Canada, Chile, Estonia, Iceland, Ireland, Israel, Japan, South Korea, Latvia, Luxembourg, Mexico, Slovenia, Spain, Switzerland, Turkey, and Iran. Their inefficiency was calculated using the axial output model. The most inefficient countries were Portugal, Germany, the United States, Poland, the Czech Republic, Slovakia and Hungary.Conclusion: Iranchr('39')s health system was found efficient, which showed that in terms of life expectancy and infant mortality rate (2 important markers of the health system), Iran performed efficiently comparing to its inputs, health expenditures, physicians, and the hospital bed. However, the Iranian health system was more efficient in this method due to the fewer inputs (physician and hospital bed) with similar outputs to other countries (life expectancy and infant mortality rate). On the other hand, the outbreak of the coronavirus showed that the health systems of the countries should be prepared for such pandemics and be able to increase the number of hospital beds, physicians, and other health system inputs.

This article develops and tests a model of how organizational structure influences organizational performance. Organizational structure, conceptualized as the decision‐making structure among a group of individuals, is shown to affect the number of initiatives pursued by organizations and the omission and commission errors (Type I and II errors, respectively) made by organizations. The empirical setting is more than 150,000 stock‐picking decisions made by 609 mutual funds. Mutual funds offer an ideal and rare setting to test the theory, since there are detailed records on the projects they face, the decisions they make, and the outcomes of these decisions. The study's independent variable, organizational structure, is coded based on fund management descriptions made by Morningstar, and estimates of the omission and commission errors are computed by a novel technique that uses bootstrapping to create measures that are comparable across funds. The findings suggest that organizational structure has relevant and predictable effects on a wide range of organizations. In particular, the article shows empirically that increasing the consensus threshold required by a committee in charge of selecting projects leads to more omission errors, fewer commission errors, and fewer approved projects. Applications include designing organizations that achieve a given mix of exploration and exploitation, as well as predicting the consequences of centralization and decentralization. This work constitutes the first large‐sample empirical test of the model by Sah and Stiglitz (). Copyright © 2012 John Wiley & Sons, Ltd.

Prescribing errors are one of the leading causes of diminished therapeutic outcomes even resulting in treatment failures. The Present study is a comparative evaluation of prescribing errors in non-steroidal antiinflammatory drugs containing prescriptions in four different health care facilities of District Khairpur, Sindh, Pakistan, since these drugs are among the widely-misused drugs. A total of 479 prescriptions, which were written in the primary health care facilities, public hospitals, university hospital and private hospitals were collected, compared and analyzed for common omission and commission prescribing errors as per prescription writing guidelines/parameters established by the World Health Organization, The drug information book and the British national formulary. Only 21 (4.4%) prescriptions consisting of 9 prescriptions of the university hospital and 12 prescriptions of the private hospitals were found error free and the rest 458 (95.6 %) prescriptions from different health care facilities contained different types of omission and commission errors. In omission errors, patient diagnosis, registration number of the prescriber and duration of therapy was missing in 84, 88.9 and 82.8 % prescriptions, respectively. Among commission errors, 85.2% of prescriptions were ambiguously written. A significant percentage of these errors were found in routine practice. As compared to all health care facilities, it was alarmingly found that, more number of prescribing errors were found in prescriptions of primary healthcare facilities followed by public hospitals followed by the university hospital and least number of prescribing errors were found in prescriptions of private hospitals. Computerized physician order entry and continuous educational training programs for prescribers to be executed in order to decrease these vital prescribing errors, besides that evaluation of prescriptions by pharmacists for prescribing errors can diminish the magnitude of these grave and life threatening errors.

Bu çalışmanın amacı, beklenen yaşam süresini etkileyen faktörlerin farklı gelir grubu ülkeler arasında değişiklik gösterip göstermediğinin belirlenmesidir. Bu amaçla üç farklı gelir grubundan seçilen toplam 15 ülkenin 2000-2017 yılları arasındaki veriler panel eşbütünleşme ve nedensellik analizleri ile incelenmiştir. Çalışmada kamu harcamaları içerisinde kamu sağlık harcamalarının oranı, bebek ölüm oranı, işsizlik oranı, CO2 emisyonu ve Gini katsayısı değişkenlerinin beklenen yaşam süresine etkileri araştırılmıştır. Elde edilen toplu panel sonuçlarına göre bebek ölüm oranı ve Gini katsayısındaki %1’lik artış beklenen yaşam süresini sırasıyla %0.142 ve %0.034 azaltırken, işsizlik oranı ve kamu sağlık harcamalarındaki %1’lik artış ise beklenen yaşam süresini sırasıyla %0.016 ve %0.030 arttırmaktadır. Önceki çalışmalardan farklı olarak analiz kapsamında ele alınan ülkeler için özellikle işsizlik oranı ve Gini katsayısının incelenmesinin literatüre katkı sağlayacağı umulmaktadır.

Errors directly causing serious harm are rare during pediatric trauma resuscitation, limiting the use of adverse outcome analysis for performance improvement in this setting. Errors not causing harm because of mitigation or chance may have similar causation and are more frequent than those causing adverse outcomes. Analyzing these error types is an alternative to adverse outcome analysis. The purpose of this study was to identify errors of any type during pediatric trauma resuscitation and evaluate team responses to their occurrence. Errors identified using video analysis were classified as errors of omission or commission and selection errors using input from trauma experts. The responses to error types and error frequency based on patient and event features were compared. Thirty-nine resuscitations were reviewed, identifying 337 errors (range, 2-26 per resuscitation). The most common errors were related to cervical spine stabilization (n = 93, 27.6%). Errors of omission (n = 135) and commission (n = 106) were more common than errors of selection (n = 96). Although 35.9% of all errors were acknowledged and compensation occurred after 43.6%, no response (acknowledgement or compensation) was observed after 51.3% of errors. Errors of omission and commission were more often acknowledged (40.7% and 39.6% vs. 25.0%, p = 0.03 and p = 0.04, respectively) and compensated for (50.4% and 47.2% vs. 29.2%, p = 0.004 and p = 0.01, respectively) than selection errors. Response differences between errors of omission and commission were not observed. The number of errors and the number of high-risk errors that occurred did not differ based on patient or event features. Errors are common during pediatric trauma resuscitation. Teams did not respond to most errors, although differences in team response were observed between error types. Determining causation of errors may be an approach for identifying latent safety threats contributing to adverse outcomes during pediatric trauma resuscitation. Therapeutic study, level III.

Mortality in chronic schizophrenia during decreasing number of psychiatric beds in Finland

To determine IMR trends and regional variations among 47 prefectures in Japan and to identify associated population-based factors. We conducted an ecological study of infant mortality rate (IMR) by analyzing publicly available data from the Ministry of Health, Labour and Welfare of Japan. Outcome measure for trend is the IMR for each of 47 prefectures from 1999 to 2007; for variation, IMRs for 2006 and 2007 in each prefecture were averaged. We considered as covariates prefecture-level variables related to public health, socio-economic status, clinical services and health care facilities. We conducted multivariate statistical analyses to determine covariates most strongly associated with both 1999-2007 IMR trends and 2006-2007 IMR. The mean IMR decreased from 3.42 deaths per 1000 live births (range 2.1 to 5.1) in 1999 to 2.54 (range 1.5 to 4.4) in 2007; reductions were greater in prefectures with higher concentrations of public health nurses (PHNs) and nurses. In 2006-2007, nine prefectures had IMRs ≤ 2.25; eight had IMRs ≥ 3.0. When low-, moderate- and high-IMR prefectures were compared, per capita PHNs, maternal education, centralized water supply and household income were identified as significant covariates. Both national and prefecture-level IMR in Japan decreased from 1999 to 2007; however, the degree of reduction varied by prefecture. Given that more nurses and PHNs per capita were associated with greater IMR reductions from 1999 to 2007 and more PHNs with lower 2006-2007 IMRs, distribution of preventive health services may play a major role in reducing regional disparities in IMR.