An Evaluation Method for Unsupervised Anomaly Detection Algorithms

In data mining, anomaly detection aims at identifying the observations which do not conform to an expected behavior. To date, a large number of techniques for anomaly detection have been proposed and developed. These techniques have been successfully applied to many real world applications such as fraud detection for credit cards and intrusion detection in network security. However, there are very little research relating to the method for evaluating the goodness of unsupervised anomaly detection techniques. In this paper, the authors introduce a method for evaluating the performance of unsupervised anomaly detection techniques. The method is based on the application of internal validation metrics in clustering algorithms to anomaly detection. The experiments were conducted on a number of benchmarking datasets. The results are compared with the result of a recent proposed approach that shows that some proposed metrics are very consistent when being used to evaluate the performance of unsupervised anomaly detection algorithms

Semantically-based crossover in genetic programming: application to real-valued symbolic regression

We investigate the effects of semantically-based crossover operators in genetic programming, applied to real-valued symbolic regression problems. We propose two new relations derived from the semantic distance between subtrees, known as semantic equivalence and semantic similarity. These relations are used to guide variants of the crossover operator, resulting in two new crossover operators—semantics aware crossover (SAC) and semantic similarity-based crossover (SSC). SAC, was introduced and previously studied, is added here for the purpose of comparison and analysis. SSC extends SAC by more closely controlling the semantic distance between subtrees to which crossover may be applied. The new operators were tested on some real-valued symbolic regression problems and compared with standard crossover (SC), context aware crossover (CAC), Soft Brood Selection (SBS), and No Same Mate (NSM) selection. The experimental results show on the problems examined that, with computational effort measured by the number of function node evaluations, only SSC and SBS were significantly better than SC, and SSC was often better than SBS. Further experiments were also conducted to analyse the perfomance sensitivity to the parameter settings for SSC. This analysis leads to a conclusion that SSC is more constructive and has higher locality than SAC, NSM and SC; we believe these are the main reasons for the improved performance of SSC

A DOUBLE-SHRINK AUTOENCODER FOR NETWORK ANOMALY DETECTION

The rapid development of the Internet and the wide spread of its applications has affected many aspects of our life. However, this development also makes the cyberspace more vulnerable to various attacks. Thus, detecting and preventing these attacks are crucial for the next development of the Internet and its services. Recently, machine learning methods have been widely adopted in detecting network attacks. Among many machine learning methods, AutoEncoders (AEs) are known as the state-of-the-art techniques for network anomaly detection. Although, AEs have been successfully applied to detect many types of attacks, it is often unable to detect some difficult attacks that attempt to mimic the normal network traffic. In order to handle this issue, we propose a new model based on AutoEncoder called Double-Shrink AutoEncoder (DSAE). DSAE put more shrinkage on the normal data in the middle hidden layer. This helps to pull out some anomalies that are very similar to normal data. DSAE are evaluated on six well-known network attacks datasets. The experimental results show that our model performs competitively to the state-of-the-art model, and often out-performs this model on the attacks group that is difficult for the previous methods

Constrained Twin Variational Auto-Encoder for Intrusion Detection in IoT Systems

Intrusion detection systems (IDSs) play a critical role in protecting billions of IoT devices from malicious attacks. However, the IDSs for IoT devices face inherent challenges of IoT systems, including the heterogeneity of IoT data/devices, the high dimensionality of training data, and the imbalanced data. Moreover, the deployment of IDSs on IoT systems is challenging, and sometimes impossible, due to the limited resources such as memory/storage and computing capability of typical IoT devices. To tackle these challenges, this article proposes a novel deep neural network/architecture called Constrained Twin Variational Auto-Encoder (CTVAE) that can feed classifiers of IDSs with more separable/distinguishable and lower-dimensional representation data. Additionally, in comparison to the state-of-the-art neural networks used in IDSs, CTVAE requires less memory/storage and computing power, hence making it more suitable for IoT IDS systems. Extensive experiments with the 11 most popular IoT botnet datasets show that CTVAE can boost around 1% in terms of accuracy and Fscore in detection attack compared to the state-of-the-art machine learning and representation learning methods, whilst the running time for attack detection is lower than 2E-6 seconds and the model size is lower than 1 MB. We also further investigate various characteristics of CTVAE in the latent space and in the reconstruction representation to demonstrate its efficacy compared with current well-known methods

THÀNH PHẦN LOÀI KHU HỆ CÁ VÙNG BIỂN VEN BỜ TỈNH QUẢNG NGÃI

Three surveys were carried out in May, August and December 2014 at 7 sampling location to determine species composition of fish fauna in the coastal waters of Quang Ngai province (the Central Vietnam). A total number of 178 species of fishes were identified belonging to 125 genera, 68 families and 13 orders. Analysis of community structure of fish fauna showed that Perciformes order was the most popular, making up 71.9%; Tetraodontiformes (8.4%); Pleuronectiformes (5.6%). Serranidae family was the most abundant with 14 species, making up 7.9% of the total number of species; Carangidae: 12 species (6.7%); Lutjanidae, Gobiidae had the same number of species with 9 species (5.1%); Scombridae: 7 species (3.9%); Soleidae: 6 species (3.4%); Haemulidae, Mullidae, Tetraodontidae: 5 species (2.8%);... Cluster analysing based on the Bray-Curtis similarity index of nine fish faunas (Thai Binh, Son Tra, Thu Bon, Quang Nam, Nha Phu-Binh Cang, Ben Tre and Tra Vinh) showed that fish composition of the coastal estuaries of Tra Vinh and Ben Tre had the highest similarity (80%), subsequently fish fauna of Quang Ngai had similarity with that of Nha Phu-Binh Cang (39%), Quang Ngai and Quang Nam (42%), Quang Nam and Nha Phu-Binh Cang (41%), Quang Nam and Son Tra (38%), Thai Binh and Ben Tre (37%), Quang Ngai and Son Tra (36%). The result was also classified into two distinct groups of 7 fish faunas: Group 1-Tra Vinh, Ben Tre and Thai Binh; group 2-Quang Ngai, Quang Nam, Nha Phu-Binh Cang and Son Tra. The species richness (Margalef’s index) of Quang Ngai (34.2) was less abundant than other areas, the highest species richness belonged to Tra Vinh (38.2), Thai Binh (38.0), Quang Nam (37.8), Nha Phu-Binh Cang (35.1), Son Tra (30.9), Ben Tre (29.4). The diversity of species composition according to the level taxa in each region showed the characteristic of each fish fauna.Thực hiện 3 chuyến khảo sát thu mẫu thành phần loài cá vùng biển ven bờ tỉnh Quảng Ngãi trong năm 2014 tại 7 điểm thu mẫu. Kết quả đã ghi nhận được 178 loài thuộc 13 bộ, 68 họ và 125 giống. Phân tích cấu trúc quần xã khu hệ cá cho thấy: Bộ cá vược Perciformes là bộ cá phổ biến nhất chiếm 71,9%; tiếp đến là bộ cá nóc 8,4%; bộ cá bơn 5,6%; các bộ còn lại mỗi bộ có số loài, giống và họ rất ít. Các họ chiếm ưu thế về loài: Họ cá mú (Serranidae) 14 loài chiếm 7,9% tổng số loài; cá khế (Carangidae) 12 loài (6,7%); cá hồng (Lutjanidae), cá bống trắng (Gobiidae) 9 loài (5,1%); cá thu ngừ (Scombridae) 7 loài (3,9%); cá bơn sọc (Solidae) 6 loài (3,4%); cá sạo (Haemulidae), cá phèn (Mullidae), cá nóc (Tetraodontidae) 5 loài (2,8%);... So sánh với 6 khu hệ cá cửa sông vùng biển ven bờ của Việt Nam (Thái Bình, Sơn Trà, Quảng Nam, Nha Phu-Bình Cang, Bến Tre và Trà Vinh) ghi nhận, vùng ven biển cửa sông Trà Vinh và Bến Tre có mức tương đồng cao nhất 80%; tiếp đến là Quảng Ngãi và Nha Phu-Bình Cang 39%; Quảng Ngãi và Quảng Nam 42%; Quảng Nam và Nha Phu-Bình Cang 41%; Thái Bình và Bến Tre 37%; Quảng Nam và Sơn Trà 38%; Quảng Ngãi và Sơn Trà 36%. Phân tích nhóm cho thấy thành phần loài thuộc 7 khu hệ cá hình thành nên 2 nhóm: Nhóm 1: Trà Vinh, Bến Tre và Thái Bình; nhóm 2: Quảng Ngãi, Quảng Nam, Nha Phu-Bình Cang và Sơn Trà. Độ giàu có về loài của Quảng Ngãi đạt (34,2), Trà Vinh cao nhất (38,2), tiếp đến Thái Bình (38,0), Quảng Nam (37,9), Nha Phu-Bình Cang (35,1), Sơn Trà (30,9), Bến Tre (29,4). Tính đa đạng về thành phần loài cá theo các bậc taxon trên từng vùng thể hiện tính đặc trưng riêng cho từng khu hệ

CÁ MÚ GIỐNG VÀ BẢO VỆ BÃI GIỐNG Ở ĐẦM THỊ NẠI, VỊNH QUY NHƠN VÀ ĐẦM CÙ MÔNG

The wild grouper fingerling have provided the important seed source for the development of commercial fish farming. Among the wild grouper fingerling collected in the Thi Nai lagoon, Quy Nhon bay (Binh Dinh) and Cu Mong lagoon (Phu Yen), 7 species of grouper have been identified as Banded grouper (Epinephelus amblycephalus), Yellow grouper (E. awoara), Longtooth grouper (E. bruneus), Malabar grouper (E. malabaricus), Sixbar grouper (E. sexfasciatus), Orange-spotted grouper (E. coioides) and grouper (Epinephelus sp.); in which three species of Longtooth grouper, Malabar grouper and Orange-spotted grouper were endangered in Red List Categories Criteria of IUCN as VU and NT. The Malabar grouper seed makes up a high proportion of over 30%. The total length of the juveniles is different between species, ranging from an average of 25.0 mm to 116.82 mm; Orange-spotted grouper is 112.48 mm in total length; four grouper species Banded grouper, Yellow grouper, Longtooth grouper and Malabar grouper are longer than 30 mm in total length with 31.96, 32.23, 33.78 and 33.86 mm respectively. The Sixbar grouper and grouper (Epinephelus sp.) are smaller than 30 mm. The catching of grouper fingerling is distributed in wide area, along the bank, mangroves in the lagoon, along the western shore of the Quy Nhon bay, from Ghenh Rang to the southern part of the coast and along the Cu Mong lagoon (from south to southwest). The production of grouper seed fluctuates irregularly, 3 - 4 million seeds per year for highest yields, alternating with very low yields. The protection of nursing grounds is necessary with the solution of selective catching and limiting artisanal fishing.Cá mú giống khai thác tự nhiên đã cung cấp nguồn giống quan trọng cho việc phát triển nuôi cá thương phẩm. Nguồn cá mú giống khai thác tự nhiên ở vùng đầm Thị Nại, vịnh Quy Nhơn (Bình Định) và đầm Cù Mông (Phú Yên) đã xác định được 7 loài là cá mú chấm vạch (Epinephelus amblycephalus), cá song gio (E. awoara), cá song nâu (E. bruneus), cá mú điểm gai (E. malabaricus), cá mú sau sọc (E. sexfasciatus), cá mú mè (E. coioides) và cá song (Epinephelus sp); trong đó có ba loài là cá song nâu (E. bruneus), cá mú điểm gai (E. malabaricus) và cá mú mè (E. coioides) là những loài được IUCN xếp ở mức nguy cấp bậc VU và NT. Con giống cá mú điểm gai chiếm tỉ lệ khá cao trên 30%. Chiều dài toàn thân trung bình cá giống của các loài khác nhau, từ 25,0 - 116,82 mm; cá mú mè  có chiều dài toàn thân lớn nhất đếm 112,48 mm, ba loài cá mú chấm vạch, cá song gio và cá mú điểm gai có chiều dài lớn hơn 30 mm tưong ứng là 31,96; 32,23; 33,78 và 33,86 mm. Hai loài còn lại là cá mú sáu sọc và cá song đều có kích thước nhỏ hơn 30 mm. Vùng khai thác cá mú giống khá rộng; dọc theo các cồn, dãi cây ngập mặn trong đầm Thị Nại, ven bờ phía bắc lên phía tây của vịnh Quy Nhơn; nơi tập trung khai thác ở ven gần bờ phía tây vịnh, từ Ghềnh Ráng kéo dài vào đến khu vực phía nam và vùng dọc bờ của đầm Cù Mông (từ phía nam đến tây nam). Sản lượng khai thác các mú giống biến động khá thất thường, năm có sản lượng cao lên đến 3 - 4 triệu con/năm, xen kẽ có năm sản lượng rất thấp. Việc bảo vệ bãi giống là cần thiết với các giải pháp khai thác có chọn lọc và hạn chế khai thác tận thu

Global, regional, and national incidence of six major immune-mediated inflammatory diseases: findings from the global burden of disease study 2019

BACKGROUND: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. METHODS: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. FINDINGS: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. INTERPRETATION: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. FUNDING: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38)

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. METHODS: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. FINDINGS: Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. INTERPRETATION: As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

Global, regional, and national incidence of six major immune-mediated inflammatory diseases : findings from the global burden of disease study 2019

DATA SHARING STATEMENT : Data used for the analyses are publicly available from the Institute of Health Metrics and Evaluation (http://www.healthdata.org/; http:// ghdx.healthdata.org/gbd-results-tool).BACKGROUND : The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. METHODS : We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. FINDINGS : In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. INTERPRETATION : The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively.The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. Support from Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital; Shaqra University; the School of Pharmacy, University of Botswana; the Indian Council of Medical Research (ICMR); an Australian National Health and Medical Research Council (NHMRC) Investigator Fellowship; the Italian Center of Precision Medicine and Chronic Inflammation in Milan; the Department of Environmental Health Engineering of Isfahan University of Medical Sciences, Isfahan, Iran; National Health and Medical Research Council (NHMRC), Australia; Jazan University, Saudi Arabia; the Clinician Scientist Program of the Clinician Scientist Academy (UMEA) of the University Hospital Essen; AIMST University, Malaysia; the Department of Community Medicine, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India; a Kornhauser Research Fellowship at The University of Sydney; the National Research, Development and Innovation Office Hungary; Taipei Medical University; CREATE Hope Scientific Fellowship from Lung Foundation Australia; the National Institute for Health and Care Research Manchester Biomedical Research Centre and an NIHR Clinical Lectureship in Respiratory Medicine; Kasturba Medical College, Mangalore and Manipal Academy of Higher Education, Manipal; Author Gate Publications; the Cleveland Clinic Foundation and Nassau University Medical center; the Italian Ministry of Health (RRC); King Abdulaziz University (DSR), Jeddah, and King Abdulaziz City for Science & Technology (KACSAT), Saudi Arabia, Science & Technology Development Fund (STDF), and US-Egypt Science & Technology joint Fund: The Academy of Scientific Research and Technology (ASRT), Egypt; partially supported by the Centre of Studies in Geography and Spatial Planning; the International Center of Medical Sciences Research (ICMSR), Islamabad Pakistan; Ain Shams University and the Egyptian Fulbright Mission Program; the Belgian American Educational Foundation; Health Data Research UK; the Spanish Ministry of Science and Innovation, Institute of Health Carlos III, CIBERSAM, and INCLIVA; the Clinical Research Development Unit, Imam Reza Hospital, Mashhad University of Medical Sciences; Shaqra University; Saveetha Institute of Medical and Technical Sciences and SRM Institute of Science and Technology; University of Agriculture, Faisalabad-Pakistan; the Chinese University of Hong Kong Research Committee Postdoctoral Fellowship Scheme; the institutional support of the Department of Microbiology and Immunology, Faculty of Pharmacy, Zagazig University, Egypt; the European (EU) and Developing Countries Clinical Trials Partnership, the EU Horizon 2020 Framework Programme, UK-National Institute for Health and Care Research, the Mahathir Science Award Foundation and EU-EDCTP.http://www.thelancet.comam2024School of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein