| 1. |
- Stanaway, Jeffrey D., et al.
(författare)
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Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: A systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1923-1994
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Tidskriftsartikel (refereegranskat)abstract
- Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk-outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk-outcome pairs, and new data on risk exposure levels and risk- outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.
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| 2. |
- Holloway, Bronwen, et al.
(författare)
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Antibiotic use before, during and after seeking care for acute febrile illness at a hospital outpatient department : a cross-sectional study from rural India
- 2022
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Ingår i: Antibiotics. - : MDPI AG. - 2079-6382. ; 11:5
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Tidskriftsartikel (refereegranskat)abstract
- Antibiotic resistance is a naturally occurring phenomenon, but the misuse and overuse of antibiotics is accelerating the process. This study aimed to quantify and compare antibiotic use before, during, and after seeking outpatient care for acute febrile illness in Ujjain, India. Data were collected through interviews with patients/patient attendants. The prevalence and choice of antibiotics is described by the WHO AWaRe categories and Anatomical Therapeutic Chemical classes, comparing between age groups. Units of measurement include courses, encounters, and Defined Daily Doses (DDDs). The antibiotic prescription during the outpatient visit was also described in relation to the patients’ presumptive diagnosis. Of 1000 included patients, 31.1% (n = 311) received one antibiotic course, 8.1% (n = 81) two, 1.3% (n = 13) three, 0.4% (n = 4) four, 0.1% (n = 1) five, and the remaining 59.0% (n = 590) received no antibiotics. The leading contributors to the total antibiotic volume in the DDDs were macrolides (30.3%), combinations of penicillins, including β-lactamase inhibitors (18.8%), tetracyclines (14.8%), fluoroquinolones (14.6%), and third-generation cephalosporins (13.7%). ‘Watch’ antibiotics accounted for 72.3%, 52.7%, and 64.0% of encounters before, during, and after the outpatient visit, respectively. Acute viral illness accounted for almost half of the total DDDs at the outpatient visit (642.1/1425.3, 45.1%), for which the macrolide antibiotic azithromycin was the most frequently prescribed antibiotic (261.3/642.1, 40.7%).
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| 5. |
- Holloway, Bronwen, et al.
(författare)
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Utilisation of diagnostics in India : a rapid ethnographic study exploring context and behaviour
- 2020
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Ingår i: BMJ Open. - : BMJ PUBLISHING GROUP. - 2044-6055. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To explore factors that influence behaviour in the utilisation of diagnostics by caregivers of sick children. Utilisation is defined as a caregiver assisting a child to get diagnostic tests done and return for follow-up of results. Understanding these experiences may help inform the development of interventions and implementation strategies to improve the use of diagnostics, thereby target treatment and optimise antibiotic use.Design: A rapid ethnographic qualitative study using 3 months of unstructured observations, 1 month of structured observations of diagnostic utilisation and 43 semi-structured interviews. Transcripts were coded and analysed using inductive thematic analysis. Findings were explored from a behavioural perspective through the lens of the 'Capability, Opportunity, Motivation and Behaviour' (COM-B) model for understanding behaviour. The multiple methods of investigation applied allowed for triangulation and cross-validation of the findings.Setting: The paediatric outpatient department of a teaching hospital in rural, central India.Participants: Caregivers of sick children attending the paediatric outpatient department who were sent for one or more diagnostic test.Results: Three key themes were identified that influenced caregivers' behaviour. Caregivers trusted and understood the importance of diagnostics but their acceptance wavered depending on the severity of illness and preference to treat their child directly with medicines. Caregivers struggled to access diagnostics, describing delays in testing, receiving results and follow-up, further complicated by travel time, distance and competing priorities such as work. Diagnostics were relatively cheap compared with other healthcare facilities however, the cost of the test, travel expenses and wages lost for missing work, were barriers to getting the tests done and returning for follow-up.Conclusions. Diagnostics are generally accepted and their purpose understood, however, the organisation of diagnostic services, direct and indirect costs hinder caregivers from using diagnostics. Improvements in accessibility and affordability may increase caregiver motivation to use diagnostics and return for follow-up.
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| 6. |
- Kasundriya, Sunil Kumar, et al.
(författare)
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Incidence and Risk Factors for Severe Pneumonia in Children Hospitalized with Pneumonia in Ujjain, India
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:13
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Tidskriftsartikel (refereegranskat)abstract
- Childhood pneumonia is a major public health problem. The aim of this prospective hospital-based study is to determine the incidence and risk factors for community-acquired severe pneumonia in children in Ujjain, India. The study includes 270 children, 161 (60%) boys and 109 (40%) girls, aged between 2 months and 5 years with World Health Organization defined and radiologically confirmed severe pneumonia. Considering the 270 children, 64% (95% confidence interval (CI) 57.9-69.4) have severe pneumonia. The following are identified as risk factors for severe pneumonia from the generalized logistic regression model: Born premature (adjusted odds ratio (AOR) 7.50; 95% CI 2.22-25.31;p= 0.001); history of measles (AOR 6.35; 95% CI 1.73-23.30;p= 0.005); incomplete vaccination (AOR 2.66; 95% CI 1.09-6.48;p= 0.031); acyanotic congenital heart disease (AOR 9.21; 95% CI 2.29-36.99;p= 0.002); home treatment tried (AOR 3.84; 95% CI 1.42-10.39;p= 0.008); living in a kuchha house (AOR 3.89; 95% CI 1.51-10.01;p= 0.027); overcrowding (AOR 4.50; 95% CI 1.75-11.51;p= 0.002);poor ventilation in living area (AOR 16.37; 95% CI 4.67-57.38;p< 0.001); and practicing open defecation (AOR 16.92; 95% CI 4.95-57.85;p< 0.001). Awareness of these risk factors can reduce mortality due to severe pneumonia.
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| 7. |
- Khandelwal, Navneet, et al.
(författare)
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Determinants of motor, language, cognitive, and global developmental delay in children with complicated severe acute malnutrition at the time of discharge : An observational study from Central India
- 2020
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 15:6
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Tidskriftsartikel (refereegranskat)abstract
- Background Undernutrition leads to impaired psychosocial and cognitive development. This study explored the developmental status of children with complicated severe acute malnutrition (SAM) and correlated it with various risk factors for SAM. Methods and findings We recruited 100 children with SAM and no other associated significant health issues during the recovery phase of treatment using the Bayley Scales of Infant and Toddler Development III prior to discharge from the nutritional rehabilitation unit in R D Gardi Medical College, Ujjain, Central India. We also assessed composite developmental scores, developmental age equivalents, and average differences in developmental age. Risk factors for developmental delay were identified in children with complicated SAM. The results revealed that 75%, 75%, and 63% of children with SAM exhibited delay in motor (mean score: 78.22), language (mean score: 83.97), and cognitive (mean score: 78.06) domains, respectively. A total of 63% children exhibited delay by an average of 4-7 months in the total developmental age. The proportion of children with delay in motor, language, and cognitive domains was determined. An increased risk of global developmental delay was observedin children with a low birth weight (adjusted odds ratio [aOR]: 18.06, 95%CI: 2.08-156.56; P = 0.009), having working mothers (aOR: 17.54, 95%CI: 3.02-102.59; P = 0.001), weight-for-age less than three standard deviations (aOR: 6.09, 95%CI: 1.08-34.10; P = 0.04), and presence of severe anemia (aOR: 16.34, 95%CI: 2.94-90.73; P = 0.001). Conclusions The results indicated that children with SAM exhibit developmental delay across all domains. Identifying multiple modifiable risk factors for developmental delay in children with SAM will be helpful in devising early interventional strategies in low-middle income countries; however, the exact timing of such interventions should be investigated.
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| 8. |
- Lin, Chih-Yuan, 1987-
(författare)
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A timing approach to network-based anomaly detection for SCADA systems
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Supervisory Control and Data Acquisition (SCADA) systems control and monitor critical infrastructure in society, such as electricity transmission and distribution systems. Modern SCADA systems are increasingly adopting open architectures, protocols, and standards and being connected to the Internet to enable remote control. A boost in sophisticated attacks against SCADA systems makes SCADA security a pressing issue. An Intrusion Detection System (IDS) is a security countermeasure that monitors a network and tracks unauthenticated activities inside the network. Most commercial IDSs used in general IT systems are signature-based, by which an IDS compares the system behaviors with known attack patterns. Unfortunately, recent attacks against SCADA systems exploit zero-day vulnerabilities in SCADA devices which are undetectable by signature-based IDSs.This thesis aims to enhance SCADA system monitoring by anomaly detection that models normal behaviors and finds deviations from the model. With anomaly detection, zero-day attacks are possible to detect. We focus on modeling the timing attributes of SCADA traffic for two reasons: (1) the timing regularity fits the automation nature of SCADA systems, and (2) the timing information (i.e., arrival time) of a packet is captured and sent by a network driver where an IDS is located. Hence, it’s less prone to intentional manipulation by an attacker, compared to the payload of a packet.This thesis first categorises SCADA traffic into two groups, request-response and spontaneous traffic, and studies data collected in three different protocol formats (Modbus, Siemens S7, and IEC-60870-5-104). The request-response traffic is generated by a polling mechanism. For this type of traffic, we model the inter-arrival times for each command and response pair with a statistical approach. Results presented in this thesis show that request-response traffic exists in several SCADA traffic sets collected from systems with different sizes and settings. The proposed statistical approach for request-response traffic can detect attacks having subtle changes in timing, such as a single packet insertion and TCP prediction for two of the three SCADA protocols studied.The spontaneous traffic is generated by remote terminal units when they see significant changes in measurement values. For this type of traffic, we first use a pattern mining approach to find the timing characteristics of the data. Then, we model the suggested attributes with machine learning approaches and run it on traffic collected in a real power facility. We test our anomaly detection model with two types of attacks. One causes persistent anomalies and another only causes intermittent ones. Our anomaly detector exhibits a 100% detection rate with at most 0.5% false positive rate for the attacks with persistent anomalies. For the attacks with intermittent anomalies, we find our approach effective when (1) the anomalies last for a longer period (over 1 hour), or (2) the original traffic has relatively low volume.
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| 9. |
- Lin, Chih-Yuan, 1987-
(författare)
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Network-based Anomaly Detection for SCADA Systems : Traffic Generation and Modeling
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Supervisory Control and Data Acquisition (SCADA) systems control and monitor critical infrastructure in society, such as electricity transmission and distribution systems. Modern SCADA systems are increasingly adopting open standards and being connected to the Internet to enable remote control. A boost in sophisticated attacks against SCADA systems makes SCADA security a pressing issue. An Intrusion Detection System (IDS) is a security countermeasure that monitors a network and tracks unauthenticated activities inside the network. Most commercial IDSs used in general IT systems are signature-based, by which an IDS compares the system behaviors with known attack patterns. Unfortunately, recent attacks against SCADA systems exploit zero-day vulnerabilities which are undetectable by signature-based IDSs. This thesis aims to enhance SCADA system monitoring by network-based anomaly detection that models normal behaviors and finds deviations from the model. With network-based anomaly detection, zero-day attacks are possible to detect. There are two main challenges for network-based anomaly detection. The first challenge is the potentially large number of false positives coming from benign traffic that just deviates from the trained model due to the noises. To address this challenge, this thesis proposes several traffic modeling approaches based on statistics and machine learning techniques for the regular communication patterns in SCADA traffic. The second challenge is the lack of open datasets to evaluate the proposed approaches. Consequently, this thesis proposes a traffic generation framework. For traffic modeling, this thesis first categorises SCADA traffic into two groups, request-response and non-requested traffic, and studies data collected in a diverse set of protocol for-mats (Modbus, Siemens S7, S7+, MMS, IEC-60870-5-104). The request-response traffic is generated by a polling mechanism. For this type of traffic, we model the inter-arrival times for each request and response pair with a statistical approach. Results presented in this thesis show that request-response traffic exists in several SCADA traffic sets collected from systems with different sizes and settings. The proposed statistical approach for request-response traffic can detect attacks having subtle changes in timing. The non-requested traffic is generated by remote terminal units at predefined times or when they see significant changes in measurement values. For this type of traffic, we first use a pattern mining approach to find the timing characteristics of the data. Then, we model the suggested attributes with machine learning approaches. We test our anomaly detection model with two types of attacks. One causes persistent anomalies and another only causes intermittent ones. Our anomaly detector exhibits a 100% detection rate with at most 0.5% false positive rate for the attacks with persistent anomalies. For the attacks with intermittent anomalies, we find our approach effective when anomalous patterns last for a longer period (over 30 minutes). For traffic generation, this thesis conducts a comparative analysis between network traces collected from testbeds and a real power utility. The analysis shows that the testbed traffic may be prone to overly regular patterns. This is considered to be the result of lack of plausible human interactions within the testbed. Therefore, this thesis proposes a traffic generation framework built upon a virtual testbed. The framework provides programmable BOTs to mimic human activities such as commands from the operators and attacks.
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| 10. |
- Lozano, Rafael, et al.
(författare)
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Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017
- 2018
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Ingår i: The Lancet. - : Elsevier. - 1474-547X .- 0140-6736. ; 392:10159, s. 2091-2138
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Tidskriftsartikel (refereegranskat)abstract
- Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030.
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