Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015 : a novel analysis from the Global Burden of Disease Study 2015

Background National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. Methods We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r= 0.88), an index of 11 universal health coverage interventions (r= 0.83), and human resources for health per 1000 (r= 0.77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. Findings Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28.6 to 94.6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40.7 (95% uncertainty interval, 39.0-42.8) in 1990 to 53.7 (52.2-55.4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21.2 in 1990 to 20.1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73.8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. Interpretation This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-systemcharacteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Knowledge of Neonatal Danger Signs and Its Associated Factors among Mothers Attending Child Vaccination Centers at Sheko District in Southwest Ethiopia

Background. Even though a great improvement in the last twenty years, the problem of newborn deaths is still remaining. In 2017 alone, an estimated 2.5 million neonatal deaths occurred worldwide, around 39 percent of all deaths in sub-Saharan Africa. Early detection of neonatal illness is an important step towards improving newborn survival. If mothers know the appropriate manifestations of the causes of death in newborns (neonatal danger signs), it is possible to avert related mortality, because of the health-seeking behavior of mothers highly relies on their knowledge of neonatal danger signs. Objective. To assess knowledge of neonatal danger signs and its associated factors among mothers attending child vaccination centers at Sheko District in Southwest Ethiopia. Methods. A facility-based cross-sectional study was conducted among 351 mothers who attended health centers for child vaccination in Sheko District from March 17 to April 30, 2018. A consecutive sampling method was used to select study participants. Data were collected by using structured questionnaires through face-to-face interviews. Data were entered using EPI-DATA version 3.1 and analysed using SPSS version 21. Results. Of the 351 mothers interviewed, 39% (137) had good knowledge of neonatal danger signs. The study also found that mothers aged 29-40 years (AOR=2.37, 95% CI [1.35-4.17], P=0.003), educational status of primary and above (AOR=2.68, 95% CI [1.48-4.88], P=0.001), attending ≥ 4 antenatal care visits during pregnancy (AOR=3.57, 95% CI [2.10-6.06], P<0.001), and history of postnatal attendance after birth (AOR=2.33, 95% CI [1.16-4.65], P=0.017) were significantly associated with good knowledge of neonatal danger signs. Conclusion. The proportion of mothers with good knowledge of neonatal danger signs was remarkably low. Since the problem is a public health importance in developing countries, particularly in Ethiopia, which determines future generations. Great efforts are needed to create awareness for mothers on the importance of the early identifying neonatal danger signs plus to avert the high magnitude of neonatal mortality

DataSheet_1_Deep-learning models for image-based gynecological cancer diagnosis: a systematic review and meta- analysis.zip

IntroductionGynecological cancers pose a significant threat to women worldwide, especially those in resource-limited settings. Human analysis of images remains the primary method of diagnosis, but it can be inconsistent and inaccurate. Deep learning (DL) can potentially enhance image-based diagnosis by providing objective and accurate results. This systematic review and meta-analysis aimed to summarize the recent advances of deep learning (DL) techniques for gynecological cancer diagnosis using various images and explore their future implications.MethodsThe study followed the PRISMA-2 guidelines, and the protocol was registered in PROSPERO. Five databases were searched for articles published from January 2018 to December 2022. Articles that focused on five types of gynecological cancer and used DL for diagnosis were selected. Two reviewers assessed the articles for eligibility and quality using the QUADAS-2 tool. Data was extracted from each study, and the performance of DL techniques for gynecological cancer classification was estimated by pooling and transforming sensitivity and specificity values using a random-effects model.ResultsThe review included 48 studies, and the meta-analysis included 24 studies. The studies used different images and models to diagnose different gynecological cancers. The most popular models were ResNet, VGGNet, and UNet. DL algorithms showed more sensitivity but less specificity compared to machine learning (ML) methods. The AUC of the summary receiver operating characteristic plot was higher for DL algorithms than for ML methods. Of the 48 studies included, 41 were at low risk of bias.ConclusionThis review highlights the potential of DL in improving the screening and diagnosis of gynecological cancer, particularly in resource-limited settings. However, the high heterogeneity and quality of the studies could affect the validity of the results. Further research is necessary to validate the findings of this study and to explore the potential of DL in improving gynecological cancer diagnosis.</p

Antigen-Specific Cytokine and Chemokine Gene Expression for Diagnosing Latent and Active Tuberculosis

Tuberculosis infection exhibits different forms, namely, pulmonary, extrapulmonary, and latent. Here, diagnostic markers based on the gene expression of cytokines and chemokines for differentiating between tuberculosis infection state(s) were identified. Gene expression of seven cytokines (Interferon gamma (IFN-&gamma;), Interferon gamma-induced protein 10 (IP-10), Interleukin-2 receptor (IL-2R), C-X-C Motif Chemokine Ligand 9 (CXCL-9), Interleukin 10 (IL-10), Interleukin 4 (IL-4), and Tumor Necrosis Factor alpha (TNF-&alpha;)) in response to tuberculosis antigen was analyzed using real-time polymerase reaction. The sensitivity and specificity of relative quantification (2^-&Delta;&Delta;Ct) of mRNA expression were analyzed by constructing receiver operating characteristic curves and measuring the area under the curve (AUC) values. Combinations of cytokines were analyzed using the R statistical software package. IFN-&gamma;, IP-10, IL2R, and CXCL-9 showed high expression in latent and active tuberculosis patients (p = 0.001), with a decrease in IL10 expression, and no statistical difference in IL-4 levels among all the groups (p = 0.999). IL-10 differentiated pulmonary tuberculosis patients from latent cases with an AUC of 0.731. IL10 combined with CXCL-9 distinguished pulmonary tuberculosis patients from extrapulmonary cases with a sensitivity, specificity, and accuracy of 85.7%, 73.9%, and 81.0%, respectively. IL-10 together with IP-10 and IL-4 differentiated pulmonary tuberculosis from latent cases with a sensitivity and specificity of 77.1% and 88.1%, respectively. Decision tree analysis demonstrated that IFN-&gamma; IL-2R, and IL-4 can diagnose tuberculosis infection with a sensitivity, specificity, and accuracy of 89.7%, 96.1%, and 92.7%, respectively. A combination of gene expression of cytokines and chemokines might serve as an effective marker to differentiate tuberculosis infection state(s)

Knowledge and attitude of the communities towards COVID-19 and associated factors among Gondar City residents, northwest Ethiopia: A community based cross-sectional study.

BackgroundCOVID-19 is the novel coronavirus responsible for the ongoing global outbreak of acute respiratory disease and viral pneumonia. In order to tackle the devastating condition of the virus, countries need to attack the virus with aggressive and targeted tactics. Thus, to strengthen the COVID-19 mitigation measures and to give rapid response, there is an urgent need to understand the public's knowledge and attitude about of the pandemic at this critical moment.ObjectiveThis study was aimed to assess the knowledge and attitude of communities about COVID-19 and associated factors among Gondar City residents.MethodsA community based cross-sectional study was done among 623 respondents in Gondar city from April 20-27/2020. Data were collected using a structured questionnaire adapted from different literatures. The data were entered using Epi data version 3.1 and then exported into STATA version 14 for analysis. Bi-variable and multivariable binary logistic regression were performed. Adjusted odds ratio with 95% CI was used to declare statistically significant variables on the basis of p value less than 0.05 in the multivariable binary logistic regression model.ResultsThe overall knowledge and attitude of the community towards COVID19 was 51.85% [95% CI (47.91%-55.78%)] and 53.13% [95% CI (49.20, 57.06%)], respectively. In this study, being married [AOR = 0.60 at 95% CI: (0.42, 0.86)], educational level; primary [AOR = 3.14 at 95% CI: (1.78,5.54)], secondary [AOR = 2.81 at 95% CI: (1.70,4.63)], college and above [AOR = 4.49 at 95% CI: 7.92, 13.98)], and family size [AOR = 1.80, at 95% CI: (1.05, 3.08)] were emerged as statistically significant factors impacting the knowledge of the community about COVID-19. Besides, educational level; primary [AOR = 1.76 at 95% CI: (1.03, 3.01)], secondary [AOR = 1.69 at 95% CI: (1.07, 2.68)], and college & above [AOR = 2.38 at 95% CI: (1.50, 3.79)], and family size; four to six members [AOR = 1.84 at 95% CI (1.27, 2.67)], above seven members [AOR = 1.79 at 95% CI (1.08, 2.96)] were factors identified as significantly attribute for positive attitude of the communities towards COVID-19.ConclusionMore than half of the respondents had better knowledge and attitude regarding COVID-19. Higher educational level and larger family size were significant factors predominantly affecting the knowledge and attitude of the communities towards COVID-19

Community's perceived high risk of coronavirus infections during early phase of epidemics are significantly influenced by socio-demographic background, in Gondar City, Northwest Ethiopia: A cross-sectional -study.

BackgroundEpidemiological studies during the early phase of the coronavirus (COVID-19) pandemics reported different level of people's risk perception in different countries. There is a paucity of data on perceived high risk of COVID-19 and associated factors in Ethiopia. We sought to assess the prevalence of community's perceived high risk about COVID-19 infections and associated factors among Gondar town community.MethodsA cross-sectional study was carried out from April 20 to 27, 2020 in Gondar town community, Northwest Ethiopia. Multistage cluster sampling technique was used to recruit 635 participants. Structured and pre-tested questionnaire was used to collect the data. Descriptive statistics, bivariate and multivariable binary logistic regression were used to summarize the results.ResultsA total of 623 participants were considered in the analysis with a response rate of 98.1%. The prevalence of coronavirus high risk perceptions of the respondents was found to be 23.11% (95% CI; 19.80%-26.43%). Age above 45 years (AOR = 1.41, 95%CI; 1.19-2.66), college and above educational level (AOR = 0.28, 95%CI; 0.21-0.98), and poor knowledge towards COVID-19 virus (AOR = 1.57, 95%CI; 1.09-2.23) were significantly associated with perceived high risk about COVID-19.ConclusionsThe prevalence of perceived high risk of COVID-19 was found to be low. Factors such as age, educational status, and knowledge about COVID-19 virus were found to be independent predictors of perceived high risk towards COVID-19. Government and non-government organizations should use formal and informal means of educating the community

Adherence towards COVID-19 mitigation measures and its associated factors among Gondar City residents: A community-based cross-sectional study in Northwest Ethiopia.

BackgroundConsidering its pandemicity and absence of effective treatment, authorities across the globe have designed various mitigation strategies to combat the spread of COVID-19. Although adherence towards preventive measures is the only means to tackle the virus, reluctance to do so has been reported to be a major problem everywhere. Thus, this study aimed to assess the community's adherence towards COVID-19 mitigation strategies and its associated factors among Gondar City residents, Northwest Ethiopia.MethodsA community-based cross-sectional study was employed among 635 respondents from April 20-27, 2020. Cluster sampling technique was used to select the study participants. Data were collected using an interviewer-administered structured questionnaire. Epi-Data version 4.6 and STATA version 14 were used for data entry and analysis, respectively. Binary logistic regressions (Bivariable and multivariable) were performed to identify statistically significant variables. Adjusted odds ratio with 95% CI was used to declare statistically significant variables on the basis of p ResultsThe overall prevalence of good adherence towards COVID-19 mitigation measures was 51.04% (95%CI: 47.11, 54.96). Female respondents [AOR: 2.39; 95%CI (1.66, 3.45)], receiving adequate information about COVID-19 [AOR: 1.58; 95%CI (1.03, 2.43)], and favorable attitude towards COVID-19 preventive measures were significantly associated with good adherence towards COVID-19 mitigation measures. Whereas, those respondents who had high risk perception of COVID-19 were less likely to adhere towards COVID-19 mitigation measures [AOR: 0.61; 95% CI (0.41, 0.92)].ConclusionsThe findings have indicated that nearly half of the study participants had poor adherence towards COVID-19 mitigation measures. Sex, level of information exposure, attitude towards COVID-19 preventive measures, and risk perception of COVID-19 were factors which significantly influenced the adherence of the community towards COVID-19 mitigation measures. Therefore, it is crucial to track adherence responses towards the COVID-19 preventive measures, scale up the community's awareness of COVID-19 prevention and mitigation strategies through appropriate information outlets, mainstream media, and rely on updating information from TV, radio, and health care workers about COVID-19