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Mosquito-borne diseases cause a huge burden on public health worldwide. The viruses that cause these diseases impact the behavioural traits of mosquitoes, including locomotion and feeding. Understanding these traits can help in improving existing epidemiological models and developing effective mosquito traps. However, it is difficult to understand the flight behaviour of mosquitoes due to their small sizes, complicated poses, and seemingly random moving patterns. Currently, no open-source tool is available that can detect and track resting or flying mosquitoes. Our work presented in this paper provides a detection and trajectory estimation method using the Mask RCNN algorithm and spline interpolation, which can efficiently detect mosquitoes and track their trajectories with higher accuracy. The method does not require special equipment and works excellently even with low-resolution videos. Considering the mosquito size, the proposed method's detection performance is validated using a tracker error and a custom metric that considers the mean distance between positions (estimated and ground truth), pooled standard deviation, and average accuracy. The results showed that the proposed method could successfully detect and track the flying (≈ 96% accuracy) as well as resting (100% accuracy) mosquitoes. The performance can be impacted in the case of occlusions and background clutters. Overall, this research serves as an efficient open-source tool to facilitate further examination of mosquito behavioural traits. [ABSTRACT FROM AUTHOR]

Aedes aegypti mosquitoes carrying self-spreading, virus-blocking Wolbachia bacteria are being deployed to suppress dengue transmission. However, there are challenges in applying this technology in extreme environments. We introduced two Wolbachia strains into Ae. aegypti from Saudi Arabia for a release program in the hot coastal city of Jeddah. Wolbachia reduced infection and dissemination of dengue virus (DENV2) in Saudi Arabian mosquitoes and showed complete maternal transmission and cytoplasmic incompatibility. Wolbachia reduced egg hatch under a range of environmental conditions, with the Wolbachia strains showing differential thermal stability. Wolbachia effects were similar across mosquito genetic backgrounds but we found evidence of local adaptation, with Saudi Arabian mosquitoes having lower egg viability but higher adult desiccation tolerance than Australian mosquitoes. Genetic background effects will influence Wolbachia invasion dynamics, reinforcing the need to use local genotypes for mosquito release programs, particularly in extreme environments like Jeddah. Our comprehensive characterization of Wolbachia strains provides a foundation for Wolbachia-based disease interventions in harsh climates. Author summary: Wolbachia bacteria live inside the cells of many insects including mosquitoes. Wolbachia strains can block the transmission of dengue and other arboviruses transmitted by Aedes mosquitoes and are being introduced around the world for disease control. The success of this strategy relies on the ability of Wolbachia to spread locally by causing cytoplasmic incompatibility (embryo death when infected males mate with uninfected females), on Wolbachia having limited fitness costs in local mosquito hosts, and on Wolbachia persisting in the local mosquito background in the environmental conditions that mosquitoes encounter. Here we comprehensively assess the feasibility of using two Wolbachia strains in releases with Aedes aegypti mosquitoes in the challenging environment of Jeddah, Saudi Arabia. We show effective dengue virus blocking and incompatibility in both strains in the local mosquito genetic background but higher fitness costs for one strain which may offset its ability to maintain higher infection levels under the fluctuating temperatures expected in Jeddah. We find that the Jeddah Ae. aegypti are more resistant to desiccation, highlighting the importance of establishing infections in the local genetic background. These findings directly inform the employment of Wolbachia strategies in Jeddah and emphasize the value of testing the local context. [ABSTRACT FROM AUTHOR]

In treating depression and anxiety, just over half of all clients respond. Monitoring and obtaining early client feedback can allow for rapidly adapted treatment delivery and improve outcomes. This study seeks to develop a state-of-the-art deep-learning framework for predicting clinical outcomes in internet-delivered Cognitive Behavioural Therapy (iCBT) by leveraging large-scale, high-dimensional time-series data of client-reported mental health symptoms and platform interaction data. We use de-identified data from 45,876 clients on SilverCloud Health, a digital platform for the psychological treatment of depression and anxiety. We train deep recurrent neural network (RNN) models to predict whether a client will show reliable improvement by the end of treatment using clinical measures, interaction data with the iCBT program, or both. Outcomes are based on total improvement in symptoms of depression (Patient Health Questionnaire-9, PHQ-9) and anxiety (Generalized Anxiety Disorder-7, GAD-7), as reported within the iCBT program. Using internal and external datasets, we compare the proposed models against several benchmarks and rigorously evaluate them according to their predictive accuracy, sensitivity, specificity and AUROC over treatment. Our proposed RNN models consistently predict reliable improvement in PHQ-9 and GAD-7, using past clinical measures alone, with above 87% accuracy and 0.89 AUROC after three or more review periods, outperforming all benchmark models. Additional evaluations demonstrate the robustness of the achieved models across (i) different health services; (ii) geographic locations; (iii) iCBT programs, and (iv) client severity subgroups. Results demonstrate the robust performance of dynamic prediction models that can yield clinically helpful prognostic information ready for implementation within iCBT systems to support timely decision-making and treatment adjustments by iCBT clinical supporters towards improved client outcomes., Competing Interests: AE, JP, DK, and DR are employees of SilverCloud Health. GD is a cofounder of SilverCloud Health and has a minority shareholding in the company. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Prasad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In India, and many low-middle income countries (LMICs), emergency medicine (EM) remains a poorly defined specialty and an unregulated field of clinical practice. Recognition of the attitudes, understanding, and expectations of patients presenting to Indian EDs will be crucial to the continued development of EM as a specialty. This is a multicenter, prospective, cross sectional study of adult and pediatric patients presenting to the ED in three geographically distinct regions of India. Participants were surveyed about their expectations regarding the type of care that they expected to receive, previous treatment options they have utilized, basic understanding of ED operations, factors contributing to their decision to seek ED care, and basic demographic information. 779 patients were approached to participate in the study, of which 698 (90%) completed the survey. Common ways that patients reported learning about the ED were referral from another healthcare provider (45%) and recommendation by a family member (61%). Participants chose the ED was because they thought they would be seen quickly (89%), would receive acute pain management (45%), their regular outpatient care was closed (45%), or were sent by another doctor (45%). Patients expected to wait 0.3 hours (18 minutes) on average to see a doctor in the ED. Over 75% or patients expected to see a specialist consultant in the ED and 12% expected to see their personal physician. Eighty-five percent of patients were triaged as moderate or high acuity, and 74% of patients were admitted. This study found that ED in India is utilized by a population with an extremely high acuity of medical illness that attempts to access healthcare through multiple avenues. Patients most frequently visit the ED due to a referral from another healthcare provider or family member. Most patients are aware of the existence of the ED, though understanding of available services may be lacking. Future research should focus on community outreach and education initiatives on ED services., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Davey et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)