Adaptive data-driven age and patch mixing in contact networks with recurrent mobility.

Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form contacts if they meet in patch C. We build upon their approach to address three potential gaps that remain, outlined in the bullets below. We describe the steps required to implement our approach in detail, and present step-wise results of an example application to generate contact matrices for SARS-CoV-2 transmission modelling in Ontario, Canada. We also provide methods for deriving the mobility matrix based on GPS mobility data (appendix).•Our approach includes a distribution of contacts by age that is responsive to the underlying age distributions of the mixing populations.•Our approach maintains different age mixing patterns by contact type, such that changes to the numbers of different types of contacts are appropriately reflected in changes to overall age mixing patterns.•Our approach distinguishes between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch, and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch.

Simultaneous synthesis of H2, O2, and N2 via an innovatory energy system in Coronavirus pandemic time: Design, techno-economic assessment, and optimization approaches.

In this work, an innovative integrated system that is incorporated from solid oxide electrolysis cells and an oxygen separator membrane is assessed and optimized from the techno-economic aspects to respond to oxygen, hydrogen, and nitrogen demands for hospitals and other health care applications. Besides, a parametric comparison is conducted to apprehend the weights of parameters changes on the performance of criteria. Relying on the assessments, from the hydrogen production of 1 kg/s, 23.19 kg/s of oxygen, and 50.22 kg/s of nitrogen are produced. The parametric study shows that by raising the working temperature of the electrolyzer, the cell voltage variation has descending trend and the power consumption of the system is decreased by 19%. Finally, the results of multi-criteria optimization on the Pareto front reveal that in the optimal case, the system payback period is attained at about 5.32 years and the exergy efficiency of 92.47%, which are improved 16.6% and 16.2% compared to the base case, sequentially. Consequently, this system is proposed to consider as a cost-effective and reliable option towards its vital and valuable productions, in the pandemic period and after's.

Adaptive data-driven age and patch mixing in contact networks with recurrent mobility

Graphical Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form contacts if they meet in patch C. We build upon their approach to address three potential gaps that remain, outlined in the bullets below. We describe the steps required to implement our approach in detail, and present step-wise results of an example application to generate contact matrices for SARS-CoV-2 transmission modelling in Ontario, Canada. We also provide methods for deriving the mobility matrix based on GPS mobility data (appendix).

Simultaneous Synthesis of H2, O2, and N2 via an Innovatory Energy System in Coronavirus Pandemic Time: Design, Techno-economic Assessment, and Optimization Approaches

In this work, an innovative integrated system that is incorporated from solid oxide electrolysis cells and an oxygen separator membrane is assessed and optimized from the techno-economic aspects to respond to oxygen, hydrogen, and nitrogen demands for hospitals and other health care applications. Besides, a parametric comparison is conducted to apprehend the weights of parameters changes on the performance of criteria. Relying on the assessments, from the hydrogen production of 1 kg/s, 23.19 kg/s of oxygen, and 50.22 kg/s of nitrogen are produced. The parametric study shows that by raising the working temperature of the electrolyzer, the cell voltage variation has descending trend and the power consumption of the system is decreased by 19%. Finally, the results of multi-criteria optimization on the Pareto front reveal that in the optimal case, the system payback period is attained at about 5.32 years and the exergy efficiency of 92.47%, which are improved 16.6% and 16.2% compared to the base case, sequentially. Consequently, this system is proposed to consider as a cost-effective and reliable option towards its vital and valuable productions, in the pandemic period and after’s.

Écart de mobilité : estimation des seuils de mobilité requis pour maîtriser le SRAS-CoV-2 au Canada.

CONTEXTE: Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d'ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité). MÉTHODES: Nous avons procédé à une analyse de séries chronologiques sur l'incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d'une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l'aide d'un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l'écart de mobilité pour le SRAS-CoV-2. RÉSULTATS: Au cours des 51 semaines de l'étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l'écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20­1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l'été (69 %, écart interquartile [EI] 67 %­70 %), et a chuté à 54 % pendant l'hiver 2021 (EI 52 %­55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020. INTERPRÉTATION: La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu'à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada.

BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures.

Point-of-Use Rapid Detection of SARS-CoV-2: Nanotechnology-Enabled Solutions for the COVID-19 Pandemic.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 pandemic that has been spreading around the world since December 2019. More than 10 million affected cases and more than half a million deaths have been reported so far, while no vaccine is yet available as a treatment. Considering the global healthcare urgency, several techniques, including whole genome sequencing and computed tomography imaging have been employed for diagnosing infected people. Considerable efforts are also directed at detecting and preventing different modes of community transmission. Among them is the rapid detection of virus presence on different surfaces with which people may come in contact. Detection based on non-contact optical techniques is very helpful in managing the spread of the virus, and to aid in the disinfection of surfaces. Nanomaterial-based methods are proven suitable for rapid detection. Given the immense need for science led innovative solutions, this manuscript critically reviews recent literature to specifically illustrate nano-engineered effective and rapid solutions. In addition, all the different techniques are critically analyzed, compared, and contrasted to identify the most promising methods. Moreover, promising research ideas for high accuracy of detection in trace concentrations, via color change and light-sensitive nanostructures, to assist fingerprint techniques (to identify the virus at the contact surface of the gas and solid phase) are also presented.