Distributed GIS for automated natural hazard zonation mapping internet-SMS warning towards sustainable society

Today, open systems are needed for real time analysis and warnings on geo-hazards and over time can be achieved using Open Source Geographical Information System (GIS)-based platform such as GeoNode which is being contributed to by developers around the world. To develop on an open source platform is a very vital component for better disaster information management as far as spatial data infrastructures are concerned and this would be extremely vital when huge databases are to be created and consulted regularly for city planning at different scales, particularly satellite images and maps of locations. There is a big need for spatially referenced data creation, analysis, and management. Some of the salient points that this research would be able to definitely contribute with GeoNode, being an open source platform, are facilitating the creation, sharing, and collaborative use of geospatial data. The objective is development of an automated natural hazard zonation system with Internet-short message service (SMS) warning utilizing geomatics for sustainable societies. A concept of developing an internet-resident geospatial geohazard warning system has been put forward in this research, which can communicate alerts via SMS. There has been a need to develop an automated integrated system to categorize hazard and issue warning that reaches users directly. At present, no web-enabled warning system exists which can disseminate warning after hazard evaluation at one go and in real time. The objective of this research work has been to formalize a notion of an integrated, independent, generalized, and automated geo-hazard warning system making use of geo-spatial data under popular usage platform. In this paper, a model of an automated geo-spatial hazard warning system has been elaborated. The functionality is to be modular in architecture having GIS-graphical user interface (GUI), input, understanding, rainfall prediction, expert, output, and warning modules. A simplified but working prototype of the system without the GIS-GUI module has been already tested, validated, and reported. Through this paper, a significantly enhanced system integrated with web-enabled-geospatial information has been proposed, and it can be concluded that an automated hazard warning system has been conceptualized and researched. However, now the scope is to develop it further

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

North West Provincial Director of Health Services

The latter parts of 2007 and early months of 2008 witnessed an alarming number of deaths due to a Leptospirosis outbreak in Sri Lanka (1). An unusual number of patients presenting with symptoms of fever, headache or myalgia concentrated in particular geographic areas (North Central and North Western Province in Sri Lanka) could have signalled the epidemiologists of an abnormal event with the help of a quicker surveillance programme leading to possible implementation of optimal strategies which could possibly have minimized the early deaths and even prevented the progression of the outbreak. The present day paper-based disease surveillance and notification systems in Sri Lanka (2) , confined to a set of notifiable diseases, often require 15-30 days to communicate data and for the central Epidemiology Unit to process it. This latency does not allow for timely detection of disease outbreaks and it limits the ability of the health system to effectively respond and mitigate their consequences. Therefore it negatively affects the health status of the work force and productivity of the country. The Real Time Bio-surveillance Program (RTBP) is a pilot study aiming to introduce modern technology to the Health Department of Sri Lanka t

Human benzene metabolism following occupational and environmental exposures.

We previously reported evidence that humans metabolize benzene via two enzymes, including a hitherto unrecognized high-affinity enzyme that was responsible for an estimated 73% of total urinary metabolites [sum of phenol (PH), hydroquinone (HQ), catechol (CA), E,E-muconic acid (MA), and S-phenylmercapturic acid (SPMA)] in nonsmoking females exposed to benzene at sub-saturating (ppb) air concentrations. Here, we used the same Michaelis-Menten-like kinetic models to individually analyze urinary levels of PH, HQ, CA and MA from 263 nonsmoking Chinese women (179 benzene-exposed workers and 84 control workers) with estimated benzene air concentrations ranging from less than 0.001-299 ppm. One model depicted benzene metabolism as a single enzymatic process (1-enzyme model) and the other as two enzymatic processes which competed for access to benzene (2-enzyme model). We evaluated model fits based upon the difference in values of Akaike's Information Criterion (DeltaAIC), and we gauged the weights of evidence favoring the two models based upon the associated Akaike weights and Evidence Ratios. For each metabolite, the 2-enzyme model provided a better fit than the 1-enzyme model with DeltaAIC values decreasing in the order 9.511 for MA, 7.379 for PH, 1.417 for CA, and 0.193 for HQ. The corresponding weights of evidence favoring the 2-enzyme model (Evidence Ratios) were: 116.2:1 for MA, 40.0:1 for PH, 2.0:1 for CA and 1.1:1 for HQ. These results indicate that our earlier findings from models of total metabolites were driven largely by MA, representing the ring-opening pathway, and by PH, representing the ring-hydroxylation pathway. The predicted percentage of benzene metabolized by the putative high-affinity enzyme at an air concentration of 0.001 ppm was 88% based upon urinary MA and was 80% based upon urinary PH. As benzene concentrations increased, the respective percentages of benzene metabolized to MA and PH by the high-affinity enzyme decreased successively to 66 and 77% at 0.1 ppm, 20 and 58% at 1 ppm, and 2.7 and 17% at 10 ppm. This indicates that the putative high-affinity enzyme was active primarily below 1 ppm and favored the ring-opening pathway

Urinary benzene as a biomarker of exposure among occupationally exposed and unexposed subjects

Urinary benzene (UB) was investigated as a biomarker of exposure among benzene-exposed workers and unexposed subjects in Shanghai, China. Measurements were performed via headspace solid phase microextraction of 0.5 ml of urine specimens followed by gas chromatography-mass spectrometry. This assay is simple and more sensitive than other methods (detection limit 0.016 microg benzene/l urine). The median daily benzene exposure was 31 p.p.m. (range 1.65-329 p.p.m.). When subjects were divided into controls (n = 41), those exposed to 31 p.p.m. benzene (n = 20), the median UB levels were 0.069, 4.95 and 46.1 microg/l, respectively (Spearman r = 0.879, P < 0.0001). A linear relationship was observed between the logarithm of UB and the logarithm of benzene exposure in exposed subjects according to the following equation: ln(UB, microg/l) = 0.196 + 0.709 ln (exposure, p.p.m.) (r = 0.717, P < 0.0001). Considering all subjects, linear relationships were also observed between the logarithm of UB and the corresponding logarithms of four urinary metabolites of benzene, namely t,t-muconic acid (r = 0.938, P < 0.0001), phenol (r = 0.826, P < 0.0001), catechol (r = 0.812, P < 0.0001) and hydroquinone (r = 0.898, P: < 0.0001). Ratios of individual metabolite levels to total metabolites versus UB provide evidence of competitive inhibition of CYP450 enzymes leading to increased production of phenol and catechol at the expense of hydroquinone and muconic acid. Among control subjects UB was readily detected with a mean level of 0.145 microg/l (range 0.027-2.06 microg/l), compared with 5.63 microg/l (range 0.837-26.38 microg/l) in workers exposed to benzene below 10 p.p.m. (P < 0.0001). This suggests that UB is a good biomarker for exposure to low levels of benzene