Challenges in dengue research: A computational perspective

This is the final version of the article. Available from Wiley via the DOI in this record.The dengue virus is now the most widespread arbovirus affecting human populations, causing significant economic and social impact in South America and South-East Asia. Increasing urbanization and globalization, coupled with insufficient resources for control, misguided policies or lack of political will, and expansion of its mosquito vectors are some of the reasons why interventions have so far failed to curb this major public health problem. Computational approaches have elucidated on dengue's population dynamics with the aim to provide not only a better understanding of the evolution and epidemiology of the virus but also robust intervention strategies. It is clear, however, that these have been insufficient to address key aspects of dengue's biology, many of which will play a crucial role for the success of future control programmes, including vaccination. Within a multiscale perspective on this biological system, with the aim of linking evolutionary, ecological and epidemiological thinking, as well as to expand on classic modelling assumptions, we here propose, discuss and exemplify a few major computational avenues—real-time computational analysis of genetic data, phylodynamic modelling frameworks, within-host model frameworks and GPU-accelerated computing. We argue that these emerging approaches should offer valuable research opportunities over the coming years, as previously applied and demonstrated in the context of other pathogens.JL, AW and SG received funding from the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. 268904 - DIVERSITY. MR was supported by a Royal Society University Research Fellowship. NRF by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 204311/Z/16/Z). WT has received funding from a doctoral scholarship from the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership

Multiple Cytokines Are Released When Blood from Patients with Tuberculosis Is Stimulated with Mycobacterium tuberculosis Antigens

Mycobacterium tuberculosis (Mtb) infection may cause overt disease or remain latent. Interferon gamma release assays (IGRAs) detect Mtb infection, both latent infection and infection manifesting as overt disease, by measuring whole-blood interferon gamma (IFN-γ) responses to Mtb antigens such as early secreted antigenic target-6 (ESAT-6), culture filtrate protein 10 (CFP-10), and TB7.7. Due to a lack of adequate diagnostic standards for confirming latent Mtb infection, IGRA sensitivity for detecting Mtb infection has been estimated using patients with culture-confirmed tuberculosis (CCTB) for whom recovery of Mtb confirms the infection. In this study, cytokines in addition to IFN-γ were assessed for potential to provide robust measures of Mtb infection.Cytokine responses to ESAT-6, CFP-10, TB7.7, or combinations of these Mtb antigens, for patients with CCTB were compared with responses for subjects at low risk for Mtb infection (controls). Three different multiplexed immunoassays were used to measure concentrations of 9 to 20 different cytokines. Responses were calculated by subtracting background cytokine concentrations from cytokine concentrations in plasma from blood stimulated with Mtb antigens.Two assays demonstrated that ESAT-6, CFP-10, ESAT-6+CFP-10, and ESAT-6+CFP-10+TB7.7 stimulated the release of significantly greater amounts of IFN-γ, IL-2, IL-8, MCP-1 and MIP-1β for CCTB patients than for controls. Responses to combination antigens were, or tended to be, greater than responses to individual antigens. A third assay, using whole blood stimulation with ESAT-6+CFP-10+TB7.7, revealed significantly greater IFN-γ, IL-2, IL-6, IL-8, IP-10, MCP-1, MIP-1β, and TNF-α responses among patients compared with controls. One CCTB patient with a falsely negative IFN-γ response had elevated responses with other cytokines.Multiple cytokines are released when whole blood from patients with CCTB is stimulated with Mtb antigens. Measurement of multiple cytokine responses may improve diagnostic sensitivity for Mtb infection compared with assessment of IFN-γ alone

Syndromic approach to arboviral diagnostics for global travelers as a basis for infectious disease surveillance

Background Arboviruses have overlapping geographical distributions and can cause symptoms that coincide with more common infections. Therefore, arbovirus infections are often neglected by travel diagnostics. Here, we assessed the potential of syndrome-based approaches for diagnosis and surveillance of neglected arboviral diseases in returning travelers. Method To map the patients high at risk of missed clinical arboviral infections we compared the quantity of all arboviral diagnostic requests by physicians in the Netherlands, from 2009 through 2013, with a literature-based assessment of the travelers’ likely exposure to an arbovirus. Results 2153 patients, with travel and clinical history were evaluated. The diagnostic assay for dengue virus (DENV) was the most commonly requested (86%). Of travelers returning from Southeast Asia with symptoms compatible with chikungunya virus (CHIKV), only 55% were tested. For travelers in Europe, arbovirus diagnostics were rarely requested. Over all, diagnostics for most arboviruses were requested only on severe clinical presentation. Conclusion Travel destination and syndrome were used inconsistently for triage of diagnostics, likely resulting in vast under-diagnosis of arboviral infections of public health significance. This study shows the need for more awareness among physicians and standardization of syndromic diagnostic algorithm

The ATLAS SCT Optoelectronics and the Associated Electrical Services

The requirements for the optical links of the ATLAS SCT are described. From the individual detector modules to the first patch panel, the electrical services are integrated with the optical links to aid in mechanical design, construction and integration. The system architecture and critical elements of the system are described. The optical links for the ATLAS SCT have been assembled and mounted onto the carbon fibre support structures. The performance of the system as measured during QA is summarised and compared to the final performance obtained after mounting modules onto the support structures

Climate change and the emergence of vector-borne diseases in Europe: Case study of dengue fever

Background: Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios. Methods. We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence. Results: The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy. Conclusions: This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world

Does equalization of family sizes reduce genetic adaptation to captivity?

Genetic adaptation to captive environments is likely to reduce the reproductive fitness of endangered species when they are reintroduced into natural environments. Equalization of family sizes is predicted to halve genetic adaptation to captivity as it removes selection among families and is recommended in captive management of threatened species. This prediction was evaluated by comparing the reproductive fitnesses of replicate populations of Drosophila maintained using either equal (EFS) or variable family sizes (VFS) for 25 generations in captivity under uncrowded conditions on a medium containing CuSO₄. After 25 generations, EFS populations produced 8.8% more offspring per pair than their outbred base population on CuSO₄ medium, while VFS produced 17.5% more. Consequently, the rate of genetic adaptation to captivity in EFS was about half that in VFS, as predicted. In simulated ‘wild’ conditions (crowded, competitive conditions on medium lacking CuSO₄), both treatments showed much lower reproductive fitness than their outbred base population, the reductions being 38% in EFS populations and 43% in VFS populations. Surprisingly, reproductive fitness of the two treatments did not differ significantly under these conditions. These results raise doubts about the ability of equalization of family sizes to reduce genetic deterioration that adversely affects reintroduction success for captive populations of endangered species.7 page(s

Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals

Irina-Maria Popescu,1 Madalin-Marius Margan,2 Mariana Anghel,1 Alexandra Mocanu,3 Sorina Maria Denisa Laitin,1 Roxana Margan,4 Ionut Dragos Capraru,1 Alexandra-Andreea Tene,5 Emanuela-Georgiana Gal-Nadasan,6 Daniela Cirnatu,5,7 Gratiana Nicoleta Chicin,5,8 Cristian Oancea,9 Andrei Anghel10 1Department of Infectious Diseases, Discipline of Epidemiology, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 2Department of Functional Sciences, Discipline of Public Health, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 3Department of Infectious Diseases, Discipline of Infectious Diseases, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 4Department of Functional Sciences, Discipline of Physiology, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 5Regional Center of Public Health Timisoara, Timisoara, Romania; 6Department of Balneology, Medical Rehabilitation and Rheumatology, Discipline of Medical Rehabilitation, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 7Department of Medicine, “Vasile Goldis” Western University, Faculty of Medicine, Arad, Romania; 8Department of Epidemiology, Infectious Diseases and Preventive Medicine, “Vasile Goldis” Western University, Faculty of Medicine, Arad, Romania; 9Center for Research and Innovation in Precision Medicine of Respiratory Disease, “Victor Babes” University of Medicine and Pharmacy, Timisoara, Romania; 10Department of Biochemistry and Pharmacology, Discipline of Biochemistry, “Victor Babes” University of Medicine and Pharmacy, Timisoara, RomaniaCorrespondence: Madalin-Marius Margan, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square, No. 2, Timisoara, 300041, Romania, Tel +40 726 277 354, Email [email protected]: Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and low-risk groups.Patients and Methods: The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timișoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form.Results: Increased age (cOR=1.09, 95% CI: 1.06– 1.11, p< 0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96– 6.08, p< 0.001), renal disease (cOR=4.26, 95% CI: 2.13– 8.52, p< 0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71– 11.01, p< 0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57– 34.10, p< 0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05– 1.15, p< 0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09– 1.21, p< 0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004– 1.009, p< 0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813– 0.877, p< 0.001); cut-off value = 0.12; sensitivity = 72.3%; specificity = 83.9%.Conclusion: This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.Keywords: ANC, CRP, risk profiling, unfavourable outcom