Progress in Research on SARS-CoV-2 Infection Causing Neurological Diseases and Its Infection Mechanism
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COVID-19 has spread rapidly worldwide since its outbreak and has now become a major public health problem. More and more evidence indicates that SARS-CoV-2 may not only affect the respiratory system but also cause great harm to the central nervous system. Therefore, it is extremely important to explore in-depth the impact of SARS-CoV-2 infection on the nervous system. In this paper, the possible mechanisms of SARS-CoV-2 invading the central nervous system during COVID-19, and the neurological complications caused by SARS-CoV-2 infection were reviewed.Keywords:
Coronavirus
Surveillance of general outbreaks of infectious gastroenteritis was introduced in 1998 by the Food Safety Authority of Ireland (FSAI), in co-operation with the eight health boards. A total of 67 general outbreaks of gastroenteritis in Ireland were reported to the FSAI in 1998 and 1999. Over 1900 people were ill as a result of these outbreaks. Four percent required hospitalisation and there were two deaths. The duration of the outbreaks varied between one day and 38 days. Salmonellae (44%) and small round structured viruses (SRSV) (12%) were the most commonly reported pathogens. In 25% of the outbreaks the aetiology was unknown. The commonest settings were restaurants, hotels and take-aways, which accounted for 45% (30/67) of all outbreaks. Sixteen percent of all outbreaks occurred in hospitals and residential institutions. Over half of the outbreaks were reported to be foodborne, 63% of which were due to various serotypes of Salmonella enterica. Eggs were implicated as the vehicle of infection in 13% of all outbreaks. An infected food handler was identified in almost one third of outbreaks, although it could not be established if this had contributed directly to the outbreak.
Salmonella Food Poisoning
Etiology
Salmonella enterica
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Etiology
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Abstract Enteroinvasive Escherichia coli (EIEC) outbreaks are uncommon in Europe. In June 2014, two EIEC outbreaks occurred in Nottingham, UK, within 2 days; outbreak A was linked to a takeaway restaurant and outbreak B to a wedding party. We conducted 2 analytical studies: a case–control study for outbreak A and a cohort study for outbreak B. We tested microbiological and environmental samples, including by using whole-genome sequencing. For both outbreaks combined, we identified 157 probable case-patients; 27 were laboratory-confirmed as EIEC O96:H19–positive. Combined epidemiologic, microbiological, and environmental findings implicated lettuce as the vehicle of infection in outbreak A, but the source of the organism remained unknown. Whole-genome sequencing identified the same organism in cases from both outbreaks, but no epidemiologic link was confirmed. These outbreaks highlight that EIEC has the capacity to cause large and severe gastrointestinal disease outbreaks and should be considered as a potential pathogen in foodborne outbreaks in Europe.
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Abstract Background The origins of Ebola disease outbreaks remain enigmatic. Historically outbreaks have been attributed to spillover events from wildlife. However, recent data suggest that some outbreaks may originate from human-to-human transmission of prior outbreak strains instead of spillover. Clarifying the origins of Ebola disease outbreaks could improve detection and mitigation of future outbreaks. Methods We reviewed the origins of all Ebola disease outbreaks from 1976 to 2022 to analyze the earliest cases and characteristics of each outbreak. The epidemiology and phylogenetic relationships of outbreak strains were used to further identify the likely source of each outbreak. Results From 1976 to 2022 there were 35 Ebola disease outbreaks with 48 primary/index cases. While the majority of outbreaks were associated with wildlife spillover, resurgence of human-to-human transmission could account for roughly a quarter of outbreaks caused by Ebola virus. Larger outbreaks were more likely to lead to possible resurgence, and nosocomial transmission was associated with the majority of outbreaks. Conclusions While spillover from wildlife has been a source for many Ebola disease outbreaks, multiple outbreaks may have originated from flare-ups of prior outbreak strains. Improving access to diagnostics as well as identifying groups at risk for resurgence of ebolaviruses will be crucial to preventing future outbreaks.
Ebolavirus
Ebola Hemorrhagic Fever
Spillover effect
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Objective To understand the characteristics of influenza-like illness(ILI) outbreaks in Yunnan province and provide evidence for the development of scientific and effective control measures.Methods The data of ILI outbreaks in Yunnan in 2009 were collected and analyzed Results Totally 72 ILI outbreaks occurred in Yunnan,resulting in 7 628 ILI cases.The attack rate ranged from 1.79% to 49.45%.The disease occurred all the year round with peak in Autumn.Twenty six outbreaks occurred in Zhaotong,Sixty eight outbreaks occurred in schools.The influenza viruses were isolated from the cases in 37 out of 54 outbreaks,including influenza H3N2 virus(in 12 outbreaks),influenza B virus(in 11 outbreaks),2009 pandemic influenza A(H1N1) virus(in 9 outbreaks) and influenza A(H1N1) virus(in 5 outbreaks).The interval between the finding of the first case and the response and the duration of epidemic was positive correlated.(r=0.896,P0.05).Conclusion More ILI outbreaks occurred in Yunnan in 2009 than in 2008,and 94% of the outbreaks occurred in schools.It is necessary to strengthen the ILI outbreak surveillance and reporting in schools and improve the sample collection and laboratory detection.
Influenza-like illness
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Pandemic
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All outbreaks of infectious intestinal disease reported to the authorities were entered on a computer database with outbreak control teams being established to investigate larger or more significant incidents. The outbreak database and, when set up, the notes of outbreak team meetings were examined for the 279 outbreaks reported in a three-year period (2003-2005). Faeces specimens submitted as part of an outbreak were examined for microbial pathogens and the results cross-matched to the outbreak number. Almost half of the general outbreaks reported (137) occurred in long-term care facilities for the elderly, 51 outbreaks were recorded in hospitals and 31 occurred in the wider community. In 76 outbreaks no specimen was logged. A microbial cause was confirmed in about one-third of outbreaks, with noroviruses being the most common (19%). Salmonellas accounted for 12 of the 21 community outbreaks linked to social events and all were foodborne. Suggestions for improving notification and surveillance are discussed.
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Objective To analyze the surveillance results of outbreaks of influenza-like illness(ILI) in Shenzhen from 2010 to 2011,to know the epidemic trend of ILI,and to provide a scientific basis for ILI prevention and treatment. Methods The study was conducted on the surveillance data of ILI outbreaks in Shenzhen from 2010 to 2011. Results A total of 226 ILI outbreaks were reported in Shenzhen from 2010 to 2011.2,026 cases of ILI were identified during the outbreaks,with the average incidence rate of 14.2%.64 ILI outbreaks were reported in December,followed by 56 outbreaks in March and 39 outbreaks in April.201 out of 226 outbreaks were tested positive for influenza,consisting of 171 outbreaks for type B(85.0%),17 outbreaks for novel H1N1(8.5%),and 13 outbreaks for seasonal type A(6.5%). Conclusions The intensity of influenza circulation was medium during the period of 2010-2011,and the peak of influenza activity occurred in March,April and December.
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The Nervous system can be broken into two main areas. the Central Nervous System (CNS); and the Peripheral Nervous System. The central nervous system is composed of the brain and spinal column. The peripheral nervous system has several functions: carry signals between the CNS and the body relay instructions from the brain to other parts of the body to control functions and responses relay instructions about the internal and external environments to the brain
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Abstract Influenza viruses have caused disease outbreaks in human societies for a long time. Influenza often has rapid onset and relatively short duration, both in the individual and in the population. The case fatality rate varies for different strains of the virus, as do the effects on total mortality. Outbreaks related to coronavirus infections have recently become a global concern but much less is known about the dynamics of these outbreaks and their effects on mortality. In this work, disease outbreaks in Sweden, in the time period of 1860-2020, are characterized and compared to the currently ongoing COVID-19 outbreak. The focus is on outbreaks with a sharp increase in all-cause mortality. Outbreak onset is defined as the time point when deaths counts starts to increase consistently for a period of 10 days. The duration of the outbreak is defined as the time period in which mortality rates are elevated. Excess mortality is estimated by standard methods. In total there were 15 outbreaks detected in the time period, the first 14 were likely caused by influenza virus infections, the last by SARS-CoV-2. The mortality dynamics of the SARS-CoV-2 outbreak is shown to be similar to outbreaks due to influenza virus, and in terms of the number of excess deaths, it is the worst outbreak in Sweden since the ’Spanish flu’ of 1918-1919.
Case fatality rate
Incubation period
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Pandemic
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