Komodo dragon attacks are rare occurrences, especially in the United States. Attacks are believed to be highly infectious and venomous, leading to demise of its prey. We present a case of a 43-year-old female zookeeper attacked by an adult dragon leading to tendon and neurovascular injuries.

Background Globally, pollen allergy is a major public health problem, but a fundamental knowledge gap exists on the effect of climate change on pollen allergies. The annual herbaceous plant common ragweed (Ambrosia artemisiifolia) is highly invasive; it thrives on disturbed land, with each plant producing up to 62 000 seeds per year. Ragweed is particularly harmful for public health because each plant produces up to 1 billion grains per year. Our study aims to quantify the consequences of climate change on pollen allergy in people in Europe.Methods We used a process-based model to estimate the change in the distribution of ragweed plants across Europe under climate change. A second model simulated plant invasion, pollen production, pollen release, and the atmospheric distribution of pollen to estimate current and future ragweed pollen levels. These findings were translated into two different measures of health burden: pollen sensitisation rates and changes in allergy symptoms. Changes in pollen sensitisation rates were estimated using a dose-response curve generated from a systematic review and from current and future population data across Europe (baseline 1986-2005, future 2041-60). Changes in allergy symptoms were modelled by obtaining dose-response relationships between pollen and symptoms from a cohort of 85 sensitised individuals in Croatia. These relationships were then applied to future pollen loads, which considered two different regional climate and pollen models, two greenhouse gas emissions scenarios (representative concentration pathways 4•5 and 8•5), and three different plant invasion scenarios. A second set of health effects (sensitisation rates and allergy symptoms) were obtained from future pollen models.Findings We estimated that sensitisation to ragweed will more than double in Europe, from a baseline estimate of 33 million people (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005) to 77 million by 2041-60. According to our projections, sensitisation will increase in countries with an existing ragweed problem (eg, by 27% in Hungary, 26% in Croatia, and 21% in Serbia), but the greatest proportional increases will occur where sensitisation is uncommon (an increase of 235% in Germany, 292% in Poland, and 231% in France). Higher pollen concentrations and a longer pollen season might also increase the severity of symptoms.Interpretation Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread might be an important adaptation strategy in response to climate change.

<p>Dengue fever is now present in over 150 countries world-wide, affecting 390 million people per year. In Vietnam the number of cases has increased by 100% since 2000, and 2019 exhibited exceptional high numbers of reported dengue fever cases. Transmission of this mosquito-borne disease is dependent on a variety of climate and socio-economic factors. Among those water availability plays a crucial role in creating or destroying suitable mosquito breeding grounds.</p><p>At present mitigating actions are taken based on reported dengue fever cases and local knowledge, leading to a reactive rather than proactive approach of disease control. By combining Earth Observation and vector-borne disease modelling expertise we have developed D-MOSS (Dengue Model Forecasting Satellite based System). The D-MOSS system is funded by the UK Space Agency’s International Partnership Programme and aims to predict the likelihood of future dengue epidemics for Vietnam on a province scale with a lead time of up to six months.</p><p>D-MOSS integrates multiple stressors such as water availability, land-cover, precipitation and temperature with data of past dengue fever incidents.  This information is used to develop statistical models of disease incidence, that can then be used to forecast dengue outbreaks based on seasonal weather and hydrological forecasts.  It is the first fully integrated dengue fever forecasting system incorporating Earth Observation data and seasonal climate forecasts to routinely issue warnings. </p><p>D-MOSS takes the form of a web-based platform.  The system’s architecture is based on open and non-proprietary software, where possible, and on flexible deployment into platforms including cloud-based virtual storage and application processing. Working closely with public health authorities in Vietnam enabled us to develop a system tailored to the local needs and decision making procedures.</p>

<p>The current increase in the volume and quality of Earth Observation (EO) data being collected by satellites offers the potential to contribute to applications across a wide range of scientific domains. It is well established that there are correlations between characteristics that can be derived from EO satellite data, such as land surface temperature or land cover, and the incidence of some diseases. Thanks to the reliable frequent acquisition and rapid distribution of EO data it is now possible for this field to progress from using EO in retrospective analyses of historical disease case counts to using it in operational forecasting systems.</p><p>However, bringing together EO-based and non-EO-based datasets, as is required for disease forecasting and many other fields, requires carefully designed data selection, formatting and integration processes. Similarly, it requires careful communication between collaborators to ensure that the priorities of that design process match the requirements of the application.</p><p>Here we will present work from the D-MOSS (Dengue forecasting MOdel Satellite-based System) project. D-MOSS is a dengue fever early warning system for South and South East Asia that will allow public health authorities to identify areas at high risk of disease epidemics before an outbreak occurs in order to target resources to reduce spreading of epidemics and improve disease control. The D-MOSS system uses EO, meteorological and seasonal weather forecast data, combined with disease statistics and static layers such as land cover, as the inputs into a dengue fever model and a water availability model. Water availability directly impacts dengue epidemics due to the provision of mosquito breeding sites. The datasets are regularly updated with the latest data and run through the models to produce a new monthly forecast. For this we have designed a system to reliably feed standardised data to the models. The project has involved a close collaboration between remote sensing scientists, geospatial scientists, hydrologists and disease modelling experts. We will discuss our approach to the selection of data sources, data source quality assessment, and design of a processing and ingestion system to produce analysis-ready data for input to the disease and water availability models.</p>

Background: An iliopsoas abscess is a type of deep pelvic infection that presents as an uncommon cause of back pain. Patients generally present with vague and ambiguous symptoms that pose diagnostic difficulty. This case report describes a 19-year-old female who initially presented with low back pain and lower extremity lumbar radiculopathy secondary to complex iliacus deep pelvic infection. This is the second documented case of lumbar radiculopathy as the presenting symptom for iliopsoas abscess. The patient underwent surgical drainage and debridement and was prescribed intravenous culture-tailored antibiotic therapy for 6 weeks.