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Fallon Owens posted an update 6 months ago
individual behaviours and on the implementation of public health interventions by the political decision makers. A positive result has, per se, no practical value for individuals since the probability of being really infected by the virus is low. The uncertainty associated with the different estimates (sensitivity, specificity and disease prevalence) play a double role it is a key factor in defining the informative content of the test result and it might guide the individual actions and the public policy decisions.As the Coronavirus situation (COVID-19) continues to evolve, many questions concerning the factors relating to the diffusion and severity of the disease remain unanswered.Whilst opinions regarding the weight of evidence for these risk factors, and the studies published so far are often inconclusive or offer contrasting results, the role of comorbidities in the risk of serious adverse outcomes in patients affected with COVID-19 appears to be evident since the outset. Hypertension, diabetes, and obesity are under discussion as important factors affecting the severity of disease. Air pollution has been considered to play a role in the diffusion of the virus, in the propagation of the contagion, in the severity of symptoms, and in the poor prognosis. Accumulating evidence supports the hypothesis that environmental particulate matter (PM) can trigger inflammatory responses at molecular, cellular, and organ levels, sustaining respiratory, cardiovascular, and dysmetabolic diseases.To better understand the intricate 2 and other respiratory viruses. This work is intended to assist in the development of appropriate investigative approaches to protect public health.Air pollution is one of the leading causes of death worldwide, with adverse effects related both to short-term and long-term exposure. It has also recently been linked to COVID-19 pandemic. To analyze this possible association in Italy, studies on the entire area of the peninsula are necessary, both urban and non-urban areas. Therefore, there is a need for a homogeneous and applicable exposure assessment tool throughout the country.Experiences of high spatio-temporal resolution models for Italian territory already exist for PM estimation, using space-time predictors, satellite data, air quality monitoring data.This work completes the availability of these estimations for the most recent years (2016-2019) and is also applied to nitrogen oxides and ozone. The spatial resolution is 1×1 km.The model confirms its capability of capturing most of PM variability (R2=0.78 and 0.74 for PM10 e PM2.5, respectively), and provides reliable estimates also for ozone (R2=0.76); for NO2 the model performance is lower (R2=0.57). The model estimations were used to calculate the PWE (population-weighted exposure) as the annual mean, weighted on the resident population in each individual cell, which represents the estimation of the Italian population’s chronic exposure to air pollution.These estimates are ready to be used in studies on the association between chronic exposure to air pollution and COVID-19 pathology, as well as for investigations on the role of air pollution on the health of the Italian population.The determinants of the risk of becoming infected by SARS-CoV-2, contracting COVID-19, and being affected by the more serious forms of the disease have been generally explored in merely qualitative terms. It seems reasonable to argue that the risk patterns for COVID-19 have to be usefully studied in quantitative terms too, whenever possible applying the same approach to the relationship ‘dose of the exposure vs pathological response’ commonly used for chemicals and already followed for several biological agents to SARS-CoV-2, too. Such an approach is of particular relevance in the fields of both occupational epidemiology and occupational medicine, where the identification of the sources of a dangerous exposure and of the web of causation of a disease is often questionable and questioned it is relevant when evaluating the population risk, too. Specific occupational scenarios, basically involving health workers, exhibit important proportions of both subjects simply infected by SARS-CoV-2 and of ill subjects wit possible, of surface contaminations too) and of viral loads in biological matrixes is proposed, with the subsequent construction of a scenario-exposure matrix. A scenario-exposure matrix for SARS-CoV-2 may represent a useful tool for research and practical risk management purposes, helping to understand the possibly critical circumstances for which no direct exposure measure is available (this is an especially frequent case, in contexts of low socio-economic level) and providing guidance to determine evidence-based public health strategies.
one of the most affected European countries by the COVID-19 epidemic is Italy; data show the strong geographical heterogeneity of the epidemic.
to propose an analysis strategy to ascertain the non-random nature of the spatial spread of COVID-19 cases infection and identify any territorial aggregations, in order to enhance contact tracing activities in specific areas of the Lazio Region (Central Italy) and a large urban area as Rome.
all cases of COVID-19 of the Lazio Region notified to the Regional Service for Epidemiology, Surveillance, and Control of Infectious Diseases (Seresmi) with daily updates from the beginning of the epidemic to April 27, 2020 were considered. The analyses were carried out considering two periods (the first from the beginning of the epidemic to April 6 and the second from the beginning of the epidemic to April 27) and two different levels of spatial aggregation the entire Lazio region excluding the Municipality of Rome, where the 377 municipalities represent the area units, andphase of the epidemic and a useful contribution to epidemiological surveillance during the COVID-19 epidemic in a specific territory.
to describe the first wave of the COVID-19 pandemic with a focus on undetected cases and to evaluate different post-lockdown scenarios.
the study introduces a SEIR compartmental model, taking into account the region-specific fraction of undetected cases, the effects of mobility restrictions, and the personal protective measures adopted, such as wearing a mask and washing hands frequently.
the model is experimentally validated with data of all the Italian regions, some European countries, and the US.
the accuracy of the model results is measured through the mean absolute percentage error (MAPE) and Lewis criteria; fitting parameters are in good agreement with previous literature.
the epidemic curves for different countries and the amount of undetected and asymptomatic cases are estimated, which are likely to represent the main source of infections in the near future. The model is applied to the Hubei case study, which is the first place to relax mobility restrictions. HDAC inhibitor drugs Results show different possible scenarios.
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