scholarly journals Trial on Presumption of Causative Organisms Based on Epidemiological Data of Food Poisoning in Japan. 1. Preparation of Presumptive Tables on Causative Organisms due to Clinical Symptoms and Incubation Period of Patients.

1995 ◽  
Vol 12 (3) ◽  
pp. 187-192 ◽  
Author(s):  
Kazuo ABE ◽  
Kunihiro SHINAGAWA
Keyword(s):  
Incubation Period ◽  
Clinical Symptoms ◽  
Food Poisoning ◽  
Epidemiological Data

scholarly journals Allergy—A New Role for T Cell Superantigens of Staphylococcus aureus?

Toxins ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 176 ◽  
Author(s):  
Goran Abdurrahman ◽  
Frieder Schmiedeke ◽  
Claus Bachert ◽  
Barbara M. Bröker ◽  
Silva Holtfreter
Keyword(s):  
Staphylococcus Aureus ◽  
T Cell ◽  
Toxic Shock Syndrome ◽  
Clinical Symptoms ◽  
Severe Disease ◽  
Food Poisoning ◽  
Epidemiological Data ◽  
Atopic Disease ◽  
Cell Receptor ◽  
Toxic Shock

Staphylococcus aureus superantigens (SAgs) are among the most potent T cell mitogens known. They stimulate large fractions of T cells by cross-linking their T cell receptor with major histocompatibility complex class-II molecules on antigen presenting cells, resulting in T cell proliferation and massive cytokine release. To date, 26 different SAgs have been described in the species S. aureus; they comprise the toxic shock syndrome toxin (TSST-1), as well as 25 staphylococcal enterotoxins (SEs) or enterotoxin-like proteins (SEls). SAgs can cause staphylococcal food poisoning and toxic shock syndrome and contribute to the clinical symptoms of staphylococcal infection. In addition, there is growing evidence that SAgs are involved in allergic diseases. This review provides an overview on recent epidemiological data on the involvement of S. aureus SAgs and anti-SAg-IgE in allergy, demonstrating that being sensitized to SEs—in contrast to inhalant allergens—is associated with a severe disease course in patients with chronic airway inflammation. The mechanisms by which SAgs trigger or amplify allergic immune responses, however, are not yet fully understood. Here, we discuss known and hypothetical pathways by which SAgs can drive an atopic disease.

scholarly journals Clinical and epidemiological characteristics of tick-borne borreliosis in the Krasnodar Krai

2014 ◽  
Vol 19 (1) ◽  
pp. 4-11
Author(s):  
M. G. Avdeeva ◽  
D. Yu. Moshkova ◽  
L. P. Blazhnyaya ◽  
V. N. Gorodin ◽  
S. V Zotov ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Clinical Symptoms ◽  
Early Period ◽  
Epidemiological Data ◽  
Course Of Disease ◽  
Krasnodar Krai ◽  
Natural Foci ◽  
The Republic ◽  
Epidemiological Characteristics ◽  
The City

The purpose of the study the improvement of early diagnostics of Lyme disease on the based of clinical and epidemiological analysis of the main clinical forms of the acute course of the disease in new natural foci in the Krasnodar Krai. Patients and methods. There was analyzed the clinical course of disease and epidemiological data for 207 patients in the early period of acute course of Lyme disease within the period from 2004 to 2013. Results. In the territory of the Krasnodar Krai and the Republic of Adygea there has formed a set of foci of tick-borne borreliosis (TB), i.e. Lyme disease (LD). The infection of cases is observed not only in the natural foci of disease, but also within the city limits. The disease is registered mainly in the erythematous form (74% of patients), non-erythematous form accounts for 26%. The average age of patients was 41,1±1,83, years, males 38%, females 62%. In the non-erythematous form initial clinical symptoms are recorded in average in 11,6 ± 2,20 days after tick suction; in the erythematous form in 6,4 ± 0,70 days ( p

Dementia with Lewy bodies and Parkinson’s disease dementia

2013 ◽  
Author(s):  
Arvid Rongve ◽  
Dag Aarsland
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dementia With Lewy Bodies ◽  
Clinical Symptoms ◽  
Imaging Techniques ◽  
Lewy Bodies ◽  
Epidemiological Data ◽  
Parkinson’S Disease Dementia ◽  
Esterase Inhibitors ◽  
Staging Systems

Dementia with Lewy bodies and Parkinson’s disease dementia belong to the α-synucleinopathies, a family of diseases pathologically characterized by aggregation of α-synuclein in Lewy bodies in the brain. In this chapter we present the epidemiological data for both conditions including new data on MCI. Clinical diagnostic criteria are reviewed and the different neuropathology staging systems for DLB and PDD and the most important genetic findings are considered. Biomarkers in DLB and PDD with particular focus on imaging techniques like CIT-SPECT and MRI are described. Important clinical symptoms in both conditions are presented in detail and the most important clinical differential diagnoses are discussed. Pharmacological and non- pharmacological treatment of different symptoms in both conditions are discussed with particular emphasis on the choline esterase inhibitors and antipsychotic medications.New data on memantine are presented.

scholarly journals Epidemiology and Clinical Symptoms Related to Seasonal Coronavirus Identified in Patients with Acute Respiratory Infections Consulting in Primary Care over Six Influenza Seasons (2014–2020) in France

Viruses ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 630
Author(s):  
Shirley Masse ◽  
Lisandru Capai ◽  
Natacha Villechenaud ◽  
Thierry Blanchon ◽  
Rémi Charrel ◽  
...  
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Clinical Features ◽  
Clinical Symptoms ◽  
Respiratory Infections ◽  
Epidemiological Data ◽  
Influenza Surveillance ◽  
Respiratory Pathogens ◽  
Detection Rates ◽  
Representative Samples

There is currently debate about human coronavirus (HCoV) seasonality and pathogenicity, as epidemiological data are scarce. Here, we provide epidemiological and clinical features of HCoV patients with acute respiratory infection (ARI) examined in primary care general practice. We also describe HCoV seasonality over six influenza surveillance seasons (week 40 to 15 of each season) from the period 2014/2015 to 2019/2020 in Corsica (France). A sample of patients of all ages presenting for consultation for influenza-like illness (ILI) or ARI was included by physicians of the French Sentinelles Network during this period. Nasopharyngeal samples were tested for the presence of 21 respiratory pathogens by real-time RT-PCR. Among the 1389 ILI/ARI patients, 105 were positive for at least one HCoV (7.5%). On an annual basis, HCoVs circulated from week 48 (November) to weeks 14–15 (May) and peaked in week 6 (February). Overall, among the HCoV-positive patients detected in this study, HCoV-OC43 was the most commonly detected virus, followed by HCoV-NL63, HCoV-HKU1, and HCoV-229E. The HCoV detection rates varied significantly with age (p = 0.00005), with the age group 0–14 years accounting for 28.6% (n = 30) of HCoV-positive patients. Fever and malaise were less frequent in HCoV patients than in influenza patients, while sore throat, dyspnoea, rhinorrhoea, and conjunctivitis were more associated with HCoV positivity. In conclusion, this study demonstrates that HCoV subtypes appear in ARI/ILI patients seen in general practice, with characteristic outbreak patterns primarily in winter. This study also identified symptoms associated with HCoVs in patients with ARI/ILI. Further studies with representative samples should be conducted to provide additional insights into the epidemiology and clinical features of HCoVs.

scholarly journals Does incubation period of COVID-19 vary with age? A study of epidemiologically linked cases in Singapore

2020 ◽  
Vol 148 ◽  
Author(s):  
W. Y. T. Tan ◽  
L. Y. Wong ◽  
Y. S. Leo ◽  
M. P. H. S. Toh
Keyword(s):  
Public Health ◽  
Incubation Period ◽  
Elderly Person ◽  
Epidemiological Data ◽  
Positive Case ◽  
Epidemiological Investigation ◽  
Inclusion Criteria ◽  
Health Measures ◽  
Trained Personnel ◽  
Close Contacts

Abstract This study estimates the incubation period of COVID-19 among locally transmitted cases, and its association with age to better inform public health measures in containing COVID-19. Epidemiological data of all PCR-confirmed COVID-19 cases from all restructured hospitals in Singapore were collected between 23 January 2020 and 2 April 2020. Activity mapping and detailed epidemiological investigation were conducted by trained personnel. Positive cases without clear exposure to another positive case were excluded from the analysis. One hundred and sixty-four cases (15.6% of patients) met the inclusion criteria during the defined period. The crude median incubation period was 5 days (range 1–12 days) and median age was 42 years (range 5–79 years). The median incubation period among those 70 years and older was significantly longer than those younger than 70 years (8 vis-à-vis 5 days, P = 0.040). Incubation period was negatively correlated with day of illness in both groups. These findings support current policies of 14-day quarantine periods for close contacts of confirmed cases and 28 days for monitoring infections in known clusters. An elderly person who may have a longer incubation period than a younger counterpart may benefit from earlier and proactive testing, especially after exposure to a positive case.

scholarly journals Patterns, Associated Factors, and Clinical Outcomes of Poisoning among Poisoning Cases Presented to Selected Hospitals in Western Ethiopia: Hospital-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ashenafi Habte Woyessa ◽  
Thanasekaran Palanichamy
Keyword(s):  
Clinical Outcomes ◽  
Associated Factors ◽  
Food Poisoning ◽  
Sampling Technique ◽  
Epidemiological Data ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Back Ground ◽  
Household Chemicals ◽  
Western Ethiopia

Back Ground. Epidemiological data related to poisoning is very limited in Ethiopia. Therefore, this study was carried out to assess the patterns, associated factors, and clinical outcomes of poisoning among poisoned cases brought to selected hospitals in western Ethiopia. Methodology. Hospital-based prospective cross-sectional study design was employed. Five administrative zones in west Ethiopia were selected as geographical clusters. Area sampling technique was utilized to select the hospitals. Finally, consecutive sampling technique was used to recruit the study participants. Since the objective of this study was to determine the pattern and outcome of poisoning during the specified study period, no specific sampling size determination was employed. As such, all of the 211 poisoned cases presented to the selected hospitals during the specific study period were consecutively included. Data were collected using a comprehensively organized and pretested interviewer-administered questionnaire. Results. The broad types of poisoning were identified in about 193 (91.47%) cases of poisoning in this study. Pesticides exposure and food poisoning have, respectively, contributed for 32.70% and 20.91% of the poisoning incidence. On the other hand, chemical from industry has contributed the least percentage (2.81%). Out of a total of 24 agents identified, 26.80% of the agents were organophosphates followed by raw meat (18.40%). Difference in the incidence of poisoning was also observed as seasons in a year change. Among the victims who have taken household materials as a poisoning agent, about 47.87% of them have taken the agents during daytime. The remaining cases of poisoning developed by household chemicals occurred at night. More than half (54.98%) of the poisoned patients have encountered the incidents inside their home. Regarding the final poisoning outcome, about 7.10% poisoning cases in this study died of the poisonings. Factors such as place, time, intention, and source of poisoning were observed to determine poisoning outcomes. Although poisoning attempt was lesser among urban residents as compared to rural community, rural dwellers were four times more likely to die of poisoning they had attempted (AOR: 4.072 (1.197–13.85)). Conclusion. This study has clearly showed that the incidence of poisoning was varied with seasonal variations. The encountered poisonings ended up with mixed clinical outcomes, which were also affected by patients’ demographic and clinical characteristics. Fertilizers, unclean food items, household materials, and drugs have caused majority of the poisonings. Creating community awareness and designing sound prevention strategies are recommended to reduce morbidity and mortality related to poisoning.

scholarly journals Arterial and Venous Thrombosis Complicated in COVID-19: A Retrospective Single Center Analysis in Japan

2021 ◽  
Vol 8 ◽  
Author(s):  
Seiya Oba ◽  
Tadashi Hosoya ◽  
Miki Amamiya ◽  
Takahiro Mitsumura ◽  
Daisuke Kawata ◽  
...  
Keyword(s):  
Risk Factors ◽  
Venous Thrombosis ◽  
Clinical Symptoms ◽  
Epidemiological Data ◽  
Japanese Patients ◽  
University Hospital ◽  
Bleeding Complications ◽  
Protein Mutants ◽  
Tokyo Medical ◽  
D Dimer

Background: Thrombosis is a characteristic complication in coronavirus disease 2019 (COVID-19). Since coagulopathy has been observed over the entire clinical course, thrombosis might be a clue to understanding the specific pathology in COVID-19. Currently, there is limited epidemiological data of COVID-19-associated thrombosis in the Japanese population and none regarding variant strains of SARS-CoV-2. Here, we elucidate the risk factors and the pattern of thrombosis in COVID-19 patients.Methods: The patients consecutively admitted to Tokyo Medical and Dental University Hospital with COVID-19 were retrospectively analyzed. SARS-CoV-2 variants of concern/interest (VOC/VOI) carrying the spike protein mutants E484K, N501Y, or L452R were identified by PCR-based analysis. All thrombotic events were diagnosed by clinical symptoms, ultrasonography, and/or radiological tests.Results: Among the 516 patients, 32 patients experienced 42 thromboembolic events. Advanced age, severe respiratory conditions, and several abnormal laboratory markers were associated with the development of thrombosis. While thrombotic events occurred in 13% of the patients with a severe respiratory condition, those events still occurred in 2.5% of the patients who did not require oxygen therapy. Elevated D-dimer and ferritin levels on admission were independent risk factors of thrombosis (adjusted odds ratio 9.39 and 3.11, 95% confidence interval 2.08–42.3, and 1.06–9.17, respectively). Of the thrombotic events, 22 were venous, whereas 20 were arterial. While patients with thrombosis received anticoagulation and antiinflammatory therapies with a higher proportion, the mortality rate, organ dysfunctions, and bleeding complications in these patients were higher than those without thrombosis. The incidence of thrombosis in COVID-19 became less frequent over time, such as during the replacement of the earlier strains of SARS-CoV-2 by VOC/VOI and during increased use of anticoagulatory therapeutics.Conclusion: This study elucidated that elevated D-dimer and ferritin levels are useful biomarkers of thrombosis in COVID-19 patients. The comparable incidence of arterial thrombosis with venous thrombosis and the development of thrombosis in less severe patients required further considerations for the management of Japanese patients with COVID-19. Further studies would be required to identify high-risk populations and establish appropriate interventions for thrombotic complications in COVID-19.

scholarly journals Detecting pathogen exposure during the non-symptomatic incubation period using physiological data

2017 ◽  
Author(s):  
Lauren Milechin ◽  
Shakti Davis ◽  
Tejash Patel ◽  
Mark Hernandez ◽  
Greg Ciccarelli ◽  
...  
Keyword(s):  
Early Detection ◽  
Incubation Period ◽  
Clinical Symptoms ◽  
Characteristic Curve ◽  
Contact Tracing ◽  
Physiological Data ◽  
False Alarms ◽  
Waveform Data ◽  
Random Forest Classification ◽  
Pathogen Exposure

AbstractEarly pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states during the incubation period using subtle, sub-clinical physiological markers. Starting with high-resolution physiological waveform data from non-human primate studies of viral (Ebola, Marburg, Lassa, and Nipah viruses) and bacterial (Y. pestis) exposure, we processed the data to reduce short-term variability and normalize diurnal variations, then provided these to a supervised random forest classification algorithm and post-classifier declaration logic step to reduce false alarms. In most subjects detection is achieved well before the onset of fever; subject cross-validation across exposure studies (varying viruses, exposure routes, animal species, and target dose) lead to 51h mean early detection (at 0.93 area under the receiver-operating characteristic curve [AUCROC]). Evaluating the algorithm against entirely independent datasets for Lassa, Nipah, andY. pestisexposures un-used in algorithm training and development yields a mean 51h early warning time (at AUCROC=0.95). We discuss which physiological indicators are most informative for early detection and options for extending this capability to limited datasets such as those available from wearable, non-invasive, ECG-based sensors.

scholarly journals Epidemiological analysis of 67 local COVID-19 clusters in Sichuan Province, China

2020 ◽  
Author(s):  
Suling Mao ◽  
Ting Huang ◽  
Heng Yuan ◽  
Min Li ◽  
Xiaomei Huang ◽  
...  
Keyword(s):  
Incubation Period ◽  
Attack Rate ◽  
Clinical Symptoms ◽  
Close Contact ◽  
Sichuan Province ◽  
Information Support ◽  
Protective Effects ◽  
Systemic Symptoms ◽  
And Control ◽  
Epidemiological Characteristics

Abstract Background This study was intended to investigate the epidemiological characteristics of COVID-19 clusters and the severity distribution of clinical symptoms of involved cases in Sichuan Province, so as to provide information support for the development and adjustment of strategies for the prevention and control of local clusters.Methods The epidemiological characteristics of 67 local clusters of COVID-19 cases in Sichuan Province reported as of March 17, 2020 were described and analyzed. Information about all COVID-19 clusters and involved cases was acquired from the China Information System for Disease Control and Prevention and analyzed with the epidemiological investigation results taken into account.Results The clusters were temporally and regionally concentrated. Clusters caused by imported cases from Wuhan and other provinces except Wuhan accounted for 73.13%; familial clusters accounted for 68.66%; the average attack rate was 8.54%, and the average secondary attack rate was 6.11%; the median incubation period was 8.5 d;a total of 28 cases met the criteria for incubation period determination, and in the 28 cases, the incubation period was > 14 d in 21.43% (6/28). a total of 226 confirmed cases were reported in the 67 clusters. Ten cases were exposed before the confirmed cases they contacted with developed clinical symptoms, and the possibility of exposure to other infection sources was ruled out; two clusters were caused by asymptomatic carriers; confirmed cases mainly presented with fever, respiratory and systemic symptoms; a gradual decline in the severity of clinical symptoms was noted with the increase of the case generation.Conclusions Population movement and gathering restrictions and strict close contact management measures will significantly contribute to the identification and control of cases. Transmission during the incubation period and asymptomatic infections have been noted. Studies on the pathogenicity and transmissibility in these populations and on COVID-19 antibody levels and protective effects in healthy people and cases are required.

scholarly journals The Effect of Information-Driven Resource Allocation on the Propagation of Epidemic with Incubation Period

2022 ◽  
Author(s):  
Xuzhen Zhu ◽  
Yuxin Liu ◽  
Xiaochen Wang ◽  
Yuexia Zhang ◽  
Shengzhi Liu ◽  
...  
Keyword(s):  
Phase Transition ◽  
Resource Allocation ◽  
Incubation Period ◽  
Information Diffusion ◽  
Clinical Symptoms ◽  
Order Type ◽  
Epidemic Spreading ◽  
Epidemic Threshold ◽  
Scale Free ◽  
Related Information

Abstract In the pandemic of COVID-19, there are exposed individuals who are infected but lack distinct clinical symptoms. In addition, the diffusion of related information drives aware individuals to spontaneously seek resources for protection. The special spreading characteristic and coevolution of different processes may induce unexpected spreading phenomena. Thus we construct a three-layered network framework to explore how information-driven resource allocation affects SEIS (Susceptible-Exposed-Infected-Susceptible) epidemic spreading. The analyses utilizing microscopic Markov chain approach reveal that the epidemic threshold depends on the topology structure of epidemic network, and the processes of information diffusion and resource allocation. Conducting extensive Monte Carlo simulations, we find some crucial phenomena in the coevolution of information diffusion, resource allocation and epidemic spreading. Firstly, when E-state (exposed state, without symptoms) individuals are infectious, long incubation period results in more E-state individuals than I-state (infected state, with obvious symptoms) individuals. Besides, when E-state individuals have strong or weak infectious capacity, increasing incubation period have an opposite effect on epidemic propagation. Secondly, the short incubation period induces the first-order phase transition. But enhancing the efficacy of resources would convert the phase transition to a second-order type. Finally, comparing the coevolution in networks with different topologies, we find setting the epidemic layer as scale-free network can inhibit the spreading of the epidemic.

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