disease patterns
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2022 ◽  
Vol 4 ◽  
Author(s):  
Michael Rapp ◽  
Moritz Kulessa ◽  
Eneldo Loza Mencía ◽  
Johannes Fürnkranz

Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can spread to a larger population. Instead of detecting unexpected increases of infections by monitoring confirmed cases, syndromic surveillance aims at the detection of cases with early symptoms, which allows a more timely disclosure of outbreaks. However, the definition of these disease patterns is often challenging, as early symptoms are usually shared among many diseases and a particular disease can have several clinical pictures in the early phase of an infection. As a first step toward the goal to support epidemiologists in the process of defining reliable disease patterns, we present a novel, data-driven approach to discover such patterns in historic data. The key idea is to take into account the correlation between indicators in a health-related data source and the reported number of infections in the respective geographic region. In an preliminary experimental study, we use data from several emergency departments to discover disease patterns for three infectious diseases. Our results show the potential of the proposed approach to find patterns that correlate with the reported infections and to identify indicators that are related to the respective diseases. It also motivates the need for additional measures to overcome practical limitations, such as the requirement to deal with noisy and unbalanced data, and demonstrates the importance of incorporating feedback of domain experts into the learning procedure.


2021 ◽  
Author(s):  
Dong Wang ◽  
Lujia Guan ◽  
xin Dong ◽  
Xiaofan Zhu ◽  
Zhaohui Tong

Abstract Background Relapsing polychondritis (RP) is a rare autoimmune disease affected various cartilage, Patients with tracheal cartilage involvement are different from other patients. The objectives of this study were to allocated RP patients into two subgroups by chest computed tomography (CT) and compare the clinical features and disease patterns of each group.Methods A retrospective cohort study collected RP patients hospitalized at the Beijing Chao-Yang Hospital between January 2012 - August 2021. Patients were divided into two groups: respiratory involvement group and non-respiratory involvement group according to chest CT.Results In our study, respiratory involvement found in 59.7% (n=43) patients, which had higher rate of costochondritis, fewer rate of Inflammatory eye disease and auricular chondritis than those in non-respiratory involvement. Compared with non-respiratory involvement subgroup, The incidence of pulmonary infection marginally increased and those inflammatory indexes except for CAR were significantly higher in respiratory involvement subgroup, further subgroup analysis found that there was no significant relationship between inflammatory indexes and pulmonary infection. Finally, 5 patients died during the follow-up in this cohort with a median follow-up time of 6 years (range 3-8 years).Conclusion 59.7% of patients had respiratory involvement according to chest CT findings in our cohort, which had a strong inverse relationship between respiratory and auricular, ocular involvement. Increase inflammatory indexes were not correlated with pulmonary infection, suggesting that patients with respiratory involvement had a higher disease activity index of RP. The probability of survival was not found significant in two subgroups.


2021 ◽  
Vol 40 (4) ◽  
pp. 79-86
Author(s):  
Semen V. Prokopenko ◽  
Natalya V. Isayeva ◽  
Anna F. Bezdeneznykh ◽  
Galina Yu. Alekseevich ◽  
Elena V. Lukianova ◽  
...  

Mechanisms of the impact of the new coronavirus infection on nervous system that leads to various neurological complications, including strokes, and disease patterns and prognosis for stroke patients with COVID-19 are actively discussed in the literature. The aim of the research was a comparison of clinical outcomes in stroke patients with SARS-CoV-2 infection and without. Random sampling of patients with stroke and laboratory-confirmed coronavirus infection SARS-CoV-2 (50 patients) was analyzed retrospectively. The control group consisted of 49 patients with stroke who did not have COVID-19. Patients in both groups were comparable by age, sex, rate of variation and type of stroke, localization of stroke and rating on the Rankin scale before the disease. The results showed that diabetes mellitus significantly more often (more than twice) occurred in stroke patients with COVID-19 (16%) in comparison with the control (7%). Atherosclerosis of brachiocephalic arteries prevailed in acute stroke patients without COVID-19 (88%). The mortality rate in acute stroke patients with COVID-19 was higher (22%) than among those without this infection (6%). At the same time, patients without a combination with COVID-19 had more severe disability on the Rankin scale three points (moderate disability) while patients with COVID-19 were discharged with two points on the Rankin scale (slight disability). Probably, this is since SARS-CoV-2 infection more often led to the lethal oucome in patients with more severe stroke and the survived patients were less disabled. Probably in increased samples these differences will be reversed. Thus, this research confirmed data that the association of stroke and COVID-19 significantly worsens clinical outcomes of stroke (2 tables, bibliography: 10 refs)


Author(s):  
Melandri Vlok ◽  
Hallie Buckley

The processes of human mobility have been well demonstrated to influence the spread of infectious disease globally in the present and the past. However, to date, paleoepidemiological research has focused more on factors of residential mobility and population density as drivers for epidemiological shifts in prehistoric infectious disease patterns. A strong body of epidemiological literature exists for the dynamics of infectious disease spread through networks of mobility and interaction. We review the epidemiological theory of infectious disease spread and propose frameworks for application of this theory to bioarchaeology. We outline problems with current definitions of prehistoric mobility and propose a framework shift with focus on population interactions as nodes for disease transmission. To conceptualize this new framework, we produced a theoretical model that considers the interplay between climate suitability, population density, residential mobility, and human interaction levels to influence infectious disease patterns in prehistoric assemblages. We then tested observable effects of this model in paleoepidemiological data from Asia (n = 343). Relative risk ratio analysis and correlations were used to test the impact of population interaction, residential mobility, population density, climate, and subsistence on the prevalence and diversity of infectious diseases. Our statistical results showed higher levels of population interaction led to significantly higher prevalence of infectious disease in sedentary populations and a significant increase in pathogen diversity in mobile populations. We recommend that population interaction be included as an important component of infectious disease analysis of prehistoric population health alongside other biosocial factors, such as sedentism and population density.   Daar is goed gedemonstreer dat die prosesse van menslike mobiliteit die verspreiding van aansteeklike siektes wêreldwyd in die hede en in die verlede beïnvloed. Maar tot op hede het paleo-epidemiologiese navorsing egter meer gefokus op faktore van residensiële mobiliteit en bevolkingsdigtheid as dryfvere vir epidemiologiese verskuiwings in die prehistoriese infeksiesiektepatrone. Sterk epidemiologiese literatuur bestaan vir die dinamika van aansteeklike siektes wat versprei word deur netwerke van mobiliteit en interaksie. Ons ondersoek die epidemiologiese teorie van die verspreiding van aansteeklike siektes en stel raamwerke voor vir die toepassing van hierdie teorie op die bioargeologie. Ons skets probleme met huidige definisies van prehistoriese mobiliteit en stel ‘n raamwerk verskuiwing voor met die fokus op bevolkings-interaksies as nodusse vir oordrag van siektes. Om hierdie nuwe raamwerk te konseptualiseer, het ons ‘n teoretiese model vervaardig wat die wisselwerking tussen klimaatsgeskiktheid, bevolkingsdigtheid, residensiële mobiliteit en menslike interaksievlakke oorweeg om die infeksiesiektepatrone in prehistoriese samestellings te beïnvloed. Daarna het ons die waarneembare effekte van hierdie model getoets in paleo-epidemiologiese data uit Asië (n = 343). Relatiewe risiko-verhoudingsanalise en korrelasies is gebruik om die impak van bevolkings-interaksie, residensiële mobiliteit, bevolkingsdigtheid, klimaat en bestaan op die voorkoms en diversiteit van aansteeklike siektes te toets. Ons statistiese resultate het gedemonstreer dat hoër vlakke van bevolkings-interaksie gelei het tot aansienlik hoër voorkoms van aansteeklike siektes in sittende bevolkings en ‘n beduidende toename in patogeen diversiteit in mobiele bevolkings. Ons beveel aan dat bevolkings-interaksie ingesluit word as ‘n belangrike komponent van die aantstekingsiekte-ontleding van die prehistoriese bevolkingsgesondheid, tesame met ander biososiale faktore soos sedentisme en bevolkingsdigtheid.


2021 ◽  
Author(s):  
Yue Sun ◽  
Dai-Feng Li ◽  
Yin-Li Zhang ◽  
Liang Xu ◽  
Tian-Fang Li

Abstract Objectives To study the characteristics and prognosis of dermatomyositis (DM) with different initial symptoms. Patients and methods: A retrospective analysis was performed on the patients who were first diagnosed with DM from 1 Jan. 2019 to 1 Jan. 2021. According to different initial symptoms, patients were divided into five groups, including rash, myasthenia, arthritis, respiratory symptom and atypical symptom group. Clinical and laboratory data were recorded. All patients were followed up until 31st May 2021. Results In total 136 patients, rash (40%) was the most common initial symptoms of DM, followed by respiratory symptoms (22%), arthritis (20%), muscle weakness (10%) and atypical symptoms (8%). Rash groups and atypical groups had a higher positive rate of anti-TIF1γ antibodies than arthritis groups and respiratory symptom groups (P < 0.05). Respiratory symptom and arthritis groups had a higher positive rate of anti-Ro52 antibodies than rash and myasthenia groups (P < 0.05). Respiratory groups had a higher incidence of ILD than rash and atypical groups. The FVC and DLCO in respiratory group were significantly lower than rash, arthritis and atypical groups (P < 0.05). The 3-year survival rate of rash groups was significantly higher than myasthenia groups and arthritis groups (P < 0.05). Conclusions DM patients with different initial manifestations had different pulmonary function tests, myositis antibodies and prognosis.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 500-501
Author(s):  
Jennifer Ailshire ◽  
Catherine Garcia

Abstract Latinos are often treated as an amalgamated group without respect to Latinos' composition included in sampling designs in different periods. This matters because the Latino population is continuously changing over time with respect to migration patterns, socioeconomic status, sociocultural characteristics, and geographic dispersion across the U.S., which may influence disease patterns in later life. We use data from the Health and Retirement Study and the National Health Interview Survey to investigate changes in older Latinos' composition by examining five birth cohorts. Results indicate that there have been significant demographic and health changes over time among older Latinos, with later-born cohorts more racially and ethnically diverse, more educated, and exhibiting a higher prevalence of hypertension, diabetes, and obesity. Understanding these shifting dynamics is imperative for crafting strategies and public policies that meet this group's health needs, reduce the cost of health care, and increase the quality of life for older Latinos.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 335-336
Author(s):  
Maria Ukhanova ◽  
Sheila Markwardt ◽  
Jon Furuno ◽  
Laura Davis ◽  
Brie Noble ◽  
...  

Abstract Sex differences in prescribing potentially inappropriate medications (PIMs) for various multimorbidity patterns are not well understood. This study sought to identify sex specific risk of PIMs in older adults with cardiovascular-metabolic patterns. Secondary analysis of the Health and Retirement Study interview data (2004-2014; n=6,341, ≥65 y/o) linked to Medicare claims data was conducted. Four multimorbidity patterns were identified based on the list of 20 chronic conditions and included: ‘cardiovascular-metabolic only’, ‘cardiovascular-metabolic plus other physical conditions’, ‘cardiovascular-metabolic plus mental conditions’, and ‘no cardiovascular-metabolic disease’ patterns. Presence of PIM prescribing was identified using the 2015 American Geriatrics Society Beers Criteria, limited to the list of medications to avoid in older adults. Chi-square tests and logistic regressions were used to identify sex differences in prescribing PIMs across multimorbidity patterns: (1) for PIMs overall and (2) for each PIM drug class. Results indicate that on average women were prescribed PIMs more often than men (39.4% and 32.8%, respectively). Women with cardiovascular-metabolic plus other physical patterns (Adj.OR=1.25, 95% CI: 1.07-1.45) and cardiovascular-metabolic plus mental patterns (Adj.OR=1.25, 95% CI: 1.06-1.48) had higher odds of PIM compared to men, however, there were no sex differences in PIM prescribing in the cardiovascular-metabolic only patterns (Adj.OR=1.13, 95% CI: 0.79-1.62). There was variation by sex across different PIM drug classes. Our study emphasizes the need to further reduce PIM prescribing among older adults, and identifies target populations for potential interventions to improve medication prescribing practices.


2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 948-948
Author(s):  
Stacey Voll ◽  
Graciela Muniz-Terrera ◽  
Scott Hofer

Abstract The aim of this study is the first step in our understanding of the uniqueness and stability of multmorbdity disease patterns for different generations. The unique historical context that each generation has been exposed to is thought to have systemic health impacts and differences in epidemiological make-up (Clouston et al. 2021). Literature suggests that multimorbidity disease patterns, are similar across countries (Hernandez et al, 2021 – in press) and observational points, and that migration into complex disease clusters is more common as people age (Cassell et al, 2018, Kingston et al. 2018). Most commonly reported are Cardiovascular and Metabolic disease clusters which lead to lower quality of life, mortality and morbidity (Kudesia, 2021). We asked: Do multimorbidity disease patterns differ for unique generations? Using the ELSA, the disease clusters of three cohorts were examined; an older cohort, born 1921-1930, a middle cohort born 1931-1940 a younger cohort born 1941-1950 and the ”newest” cohort, born 1951-1960. Self-reported dementia and memory problems lead a specific cluster for the middle cohort, those born in 1931-1940, but not for the other cohorts. While disease patterns were different between sex for other clusters, the disease cluster of dementia and memory problems held similar disease patterns for males and females, with a prevalence of 3%. The dementia/memory problem cluster loaded with cardio/metabolic diseases. This suggests that complex multimorbidity for the British 1931-1940 cohort has had an impact related to dementia and memory problem diagnoses for this specific generation, for males and females alike.


2021 ◽  
pp. 030913252110520
Author(s):  
Brian King ◽  
Andrea Rishworth

Medical geography and health geography have made significant contributions to studies of human health by addressing the spatial patterns of disease exposure, location of health care services, and place-specific processes producing health and wellbeing. Human geography and human-environment geography have also contributed with emerging attention to the body, uncertainty, and health and environment interactions. What remains understudied are the co-occurrence of multiple disease patterns, including the relationships between infectious disease and addiction. We review geographic research on infectious disease and addiction to advance a theoretical framework that emphasizes the centrality of complexity, uncertainty, difference, and care in shaping human health.


Author(s):  
Melandri Vlok ◽  
Hallie Buckley

The processes of human mobility have been well demonstrated to influence the spread of infectious disease globally in the present and the past. However, to date, paleoepidemiological research has focused more on factors of residential mobility and population density as drivers for epidemiological shifts in prehistoric infectious disease patterns. A strong body of epidemiological literature exists for the dynamics of infectious disease spread through networks of mobility and interaction. We review the epidemiological theory of infectious disease spread and propose frameworks for application of this theory to bioarchaeology. We outline problems with current definitions of prehistoric mobility and propose a framework shift with focus on population interactions as nodes for disease transmission. To conceptualize this new framework, we produced a theoretical model that considers the interplay between climate suitability, population density, residential mobility, and human interaction levels to influence infectious disease patterns in prehistoric assemblages. We then tested observable effects of this model in paleoepidemiological data from Asia (n = 343). Relative risk ratio analysis and correlations were used to test the impact of population interaction, residential mobility, population density, climate, and subsistence on the prevalence and diversity of infectious diseases. Our statistical results showed higher levels of population interaction led to significantly higher prevalence of infectious disease in sedentary populations and a significant increase in pathogen diversity in mobile populations. We recommend that population interaction be included as an important component of infectious disease analysis of prehistoric population health alongside other biosocial factors, such as sedentism and population density.   Daar is goed gedemonstreer dat die prosesse van menslike mobiliteit die verspreiding van aansteeklike siektes wêreldwyd in die hede en in die verlede beïnvloed. Maar tot op hede het paleo-epidemiologiese navorsing egter meer gefokus op faktore van residensiële mobiliteit en bevolkingsdigtheid as dryfvere vir epidemiologiese verskuiwings in die prehistoriese infeksiesiektepatrone. Sterk epidemiologiese literatuur bestaan vir die dinamika van aansteeklike siektes wat versprei word deur netwerke van mobiliteit en interaksie. Ons ondersoek die epidemiologiese teorie van die verspreiding van aansteeklike siektes en stel raamwerke voor vir die toepassing van hierdie teorie op die bio-argeologie. Ons skets probleme met huidige definisies van prehistoriese mobiliteit en stel ‘n raamwerk verskuiwing voor met die fokus op bevolkings-interaksies as nodusse vir oordrag van siektes. Om hierdie nuwe raamwerk te konseptualiseer, het ons ‘n teoretiese model vervaardig wat die wisselwerking tussen klimaatsgeskiktheid, bevolkingsdigtheid, residensiële mobiliteit en menslike interaksievlakke oorweeg om die infeksiesiektepatrone in prehistoriese samestellings te beïnvloed. Daarna het ons die waarneembare effekte van hierdie model getoets in paleo-epidemiologiese data uit Asië (n = 343). Relatiewe risiko-verhoudingsanalise en korrelasies is gebruik om die impak van bevolkings-interaksie, residensiële mobiliteit, bevolkingsdigtheid, klimaat en bestaan op die voorkoms en diversiteit van aansteeklike siektes te toets. Ons statistiese resultate het gedemonstreer dat hoër vlakke van bevolkings-interaksie gelei het tot aansienlik hoër voorkoms van aansteeklike siektes in sittende bevolkings en ‘n beduidende toename in patogeen diversiteit in mobiele bevolkings. Ons beveel aan dat bevolkings-interaksie ingesluit word as ‘n belangrike komponent van die aantstekingsiekte-ontleding van die prehistoriese bevolkingsgesondheid, tesame met ander biososiale faktore soos sedentisme en bevolkingsdigtheid.


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