An evaluation of LLIN physical integrity and population attitudes towards net use, care and handling during the Magude project in southern Mozambique.

BACKGROUND: The Magude Project assessed the feasibility of eliminating malaria in Magude district, a low transmission setting in southern Mozambique, using a package of interventions, including long-lasting insecticidal nets (LLINs). As the efficacy of LLINs depends in part on their physical integrity, this metric was quantified for Olyset® Nets post mass-distribution, in addition to net use, care and handling practices and other risk factors associated with net physical integrity. METHODS: Nets were collected during a cross-sectional net evaluation, nine months after the Magude project commenced, which was 2 years after the nets were distributed by the National Malaria Control Programme (NMCP). The physical integrity of the nets was assessed by counting and sizing the holes at different positions on each net. A structured questionnaire was administered to assess how the selected net was used and treated (care, wash and repair). Net bio-efficacy was assessed following the standard World Health Organization (WHO) cone bioassay procedures. RESULTS: Out of the 170 Olyset® Nets included in the analysis, 63.5% had been used the night before. The main reason for not using a net was the notion that there were no mosquitoes present. The average number of people using each net was 1.79. Two thirds of the nets had only been washed once or twice since distribution. Most nets (80.9%) were holed and 18% were torn, but none of the risk factors were significantly associated with net integrity, except for presence of mice in the household. Less than half of the participants noticed holes in holed nets, and of those only 38.6% attempted to repair those. None of the six nets that were tested for bio-efficacy passed the WHO threshold of 80% mosquito mortality. CONCLUSION: Overall the majority of Olyset® Nets were in serviceable condition two years post-distribution, but their insecticidal effect may have been lost. This study-together with previous evidence on suboptimal access to and use of LLINs in Magude district-highlights that LLINs as an intervention could have been optimized during the Magude project to achieve maximum intervention impact.

A Smartphone App for Real-Time Assessment of Malaria Prophylaxis Adverse Events.

Background: Growth of international travel to malarial areas over the last decades has contributed to more travelers taking malaria prophylaxis. Travel-related symptoms may be wrongly attributed to malaria prophylaxis and hinder compliance. Here, we aimed to assess the frequency of real-time reporting of symptoms by travelers following malaria prophylaxis using a smartphone app. Method: Adult international travelers included in this single-center study (Barcelona, Spain) used the smartphone Trip Doctor® app developed by our group for real-time tracking of symptoms and adherence to prophylaxis. Results: Six hundred four (n = 604) international travelers were included in the study; 74.3% (449) used the app daily, and for one-quarter of travelers, malaria prophylaxis was prescribed. Participants from the prophylaxis group traveled more to Africa (86.7% vs. 4.3%; p < 0.01) and to high travel medical risk countries (60.8% vs. 18%; p < 0.01) and reported more immunosuppression (30.8% vs. 23.1% p < 0.01). Regarding symptoms, no significant intergroup differences were observed, and no relationship was found between the total number of malarial pills taken and reported symptoms. Conclusions: In our cohort, the number of symptoms due to malaria prophylaxis was not significantly higher than in participants for whom prophylaxis was not prescribed, and the overall proportion of symptoms is higher compared with other studies.

Smart Sensor Control and Monitoring of an Automated Cell Expansion Process.

Immune therapy for cancer patients is a new and promising area that in the future may complement traditional chemotherapy. The cell expansion phase is a critical part of the process chain to produce a large number of high-quality, genetically modified immune cells from an initial sample from the patient. Smart sensors augment the ability of the control and monitoring system of the process to react in real-time to key control parameter variations, adapt to different patient profiles, and optimize the process. The aim of the current work is to develop and calibrate smart sensors for their deployment in a real bioreactor platform, with adaptive control and monitoring for diverse patient/donor cell profiles. A set of contrasting smart sensors has been implemented and tested on automated cell expansion batch runs, which incorporate advanced data-driven machine learning and statistical techniques to detect variations and disturbances of the key system features. Furthermore, a 'consensus' approach is applied to the six smart sensor alerts as a confidence factor which helps the human operator identify significant events that require attention. Initial results show that the smart sensors can effectively model and track the data generated by the Aglaris FACER bioreactor, anticipate events within a 30 min time window, and mitigate perturbations in order to optimize the key performance indicators of cell quantity and quality. In quantitative terms for event detection, the consensus for sensors across batch runs demonstrated good stability: the AI-based smart sensors (Fuzzy and Weighted Aggregation) gave 88% and 86% consensus, respectively, whereas the statistically based (Stability Detector and Bollinger) gave 25% and 42% consensus, respectively, the average consensus for all six being 65%. The different results reflect the different theoretical approaches. Finally, the consensus of batch runs across sensors gave even higher stability, ranging from 57% to 98% with an average consensus of 80%.