Quantifying movement patterns and vaccination status of high risk mobile populations in Pakistan and Afghanistan to inform poliovirus risk and vaccination strategy.

BACKGROUND: Stopping serotype 1 wild poliovirus transmission in Pakistan and Afghanistan requires ensuring all children 90% across HRMP type, ethnic group, language and mobility means. CONCLUSION: Large numbers of HRMPs were found across Pakistan, with substantial links throughout the country and with Afghanistan. While vaccination coverage of HRMPs was high, ensuring these populations are consistently vaccinated remains a priority

Routine immunization coverage in Pakistan: a survey of children under 1 year of age in community-based vaccination areas.

Pakistan is one of two countries in which poliovirus remains endemic. Considering the high number of children born every year, reaching and vaccinating new birth cohorts by improving routine immunization coverage in children <1 year of age is crucial to halting virus transmission. In 2015, a community-based vaccination (CBV) strategy, using local community members to enhance vaccine acceptance and improve routine immunization service delivery, was introduced in areas of Pakistan that have never interrupted poliovirus transmission. In order to assess progress towards improving routine immunization, we performed house-to-house immunization surveys across ten CBV areas in 2017 and 2018. In each household, we determined age-appropriate routine antigen coverage for children <1 year of age based on vaccination card and caregiver recall. We surveyed 5,499 and 5,264 children in 2017 and 2018, respectively. Overall, coverage of inactivated poliovirus vaccine (IPV) at 14 weeks of age was 32% in 2017 and 39% in 2018 based on vaccination card and recall. Across the surveyed areas, coverage ranged from 7% in Killa Abdullah to 61% in Peshawar in 2018. Oral poliovirus vaccination coverage decreased with successive vaccination visits, ranging from 66% for the birth dose to 42% for the 14-week dose in 2018. No area reached the target of 80% coverage for any routine antigen. Our findings highlight the need for concerted efforts to improve routine immunization coverage in these critical areas of wild poliovirus transmission

Distribuerade beräkningar med Kubernetes : Användning av Raspberry Pi och Kubernetes för distribuerade matematiska uträkningar

Under de senaste åren har stora datamängder blivit allt vanligare för beslutsfattande och analys. Maskininlärning och matematiska beräkningar är två avgörande metoder som används för detta. Dessa beräkningar kan dock vara tidskrävande, och de kräver högpresterande datorer som är utmanande att skala upp. Raspberry Pi är en liten, kraftfull och billig dator som lämpar sig för parallella beräkningar. Kubernetes är en öppen källkodsplattform för att hantera containerbaserade applikationer som tillåter automatisk skalning av mjukvaruapplikationer. Genom att kombinera Raspberry Pi med Kubernetes kan ett kostnadseffektivt och skalbart system för matematiska beräkningar och maskininlärning skapas. I denna studie undersöks möjligheten att bygga ett kostnadseffektivt och skalbart system för matematiska beräkningar och maskininlärning med hjälp av Raspberry Pi och Kubernetes. Det kommer att göras teoretisk forskning kring Kubernetes och Raspberry Pi, designa ett system för matematiska beräkningar och maskininlärning, implementera systemet genom att installera och konfigurera Kubernetes på flera Raspberry Pi:s, mäta och utvärdera systemets prestanda och skalbarhet samt presentera studiens resultat. Resultatet visade att användningen av Raspberry Pi i kombination med Kubernetes för att utföra matematiska beräkningar är både kostnadseffektiv och skalbar. När det gäller prestanda kunde systemet hantera intensiva beräkningsuppgifter på ett tillfredsställande sätt, vilket visar sin potential som en lösning för storskalig dataanalys. Förbättringar i systemdesign och mjukvaruoptimering kan ytterligare öka effektiviteten och prestandaIn the recent years, large data sets have become more often used for decision-making and analysis. Machine learning and mathematical calculations are two crucial methods employed for this. However, these computations may be time-consuming, and they require highperformance computers that are challenging to scale up. Raspberry Pi is a small, powerful, and cheap computer suitable for parallel calculations. Kubernetes is an open-source platform for managing container-based applications that allows automatic scaling of software applications. By combining Raspberry Pi with Kubernetes, a cost-effective and scalable system for mathematical calculations and machine learning can be created. In this study, the possibility of building a cost-effective and scalable system for mathematical calculations and machine learning using Raspberry Pi and Kubernetes is investigated. There will be theoretical research on Kubernetes and Raspberry Pi, design a system for mathematical calculations and machine learning, implement the system by installing and configuring Kubernetes on multiple Raspberry Pi's, measure and evaluate the system's performance and scalability, and present the study's results. The result showed that the use of Raspberry Pi in combination with Kubernetes to perform mathematical calculations is both cost-effective and scalable. In terms of performance, the system was able to handle intensive computational tasks satisfactorily, demonstrating its potential as a solution for large-scale data analysis. Improvements in system design and software optimization can further increase efficiency and performance

Distribuerade beräkningar med Kubernetes : Användning av Raspberry Pi och Kubernetes för distribuerade matematiska uträkningar

Under de senaste åren har stora datamängder blivit allt vanligare för beslutsfattande och analys. Maskininlärning och matematiska beräkningar är två avgörande metoder som används för detta. Dessa beräkningar kan dock vara tidskrävande, och de kräver högpresterande datorer som är utmanande att skala upp. Raspberry Pi är en liten, kraftfull och billig dator som lämpar sig för parallella beräkningar. Kubernetes är en öppen källkodsplattform för att hantera containerbaserade applikationer som tillåter automatisk skalning av mjukvaruapplikationer. Genom att kombinera Raspberry Pi med Kubernetes kan ett kostnadseffektivt och skalbart system för matematiska beräkningar och maskininlärning skapas. I denna studie undersöks möjligheten att bygga ett kostnadseffektivt och skalbart system för matematiska beräkningar och maskininlärning med hjälp av Raspberry Pi och Kubernetes. Det kommer att göras teoretisk forskning kring Kubernetes och Raspberry Pi, designa ett system för matematiska beräkningar och maskininlärning, implementera systemet genom att installera och konfigurera Kubernetes på flera Raspberry Pi:s, mäta och utvärdera systemets prestanda och skalbarhet samt presentera studiens resultat. Resultatet visade att användningen av Raspberry Pi i kombination med Kubernetes för att utföra matematiska beräkningar är både kostnadseffektiv och skalbar. När det gäller prestanda kunde systemet hantera intensiva beräkningsuppgifter på ett tillfredsställande sätt, vilket visar sin potential som en lösning för storskalig dataanalys. Förbättringar i systemdesign och mjukvaruoptimering kan ytterligare öka effektiviteten och prestandaIn the recent years, large data sets have become more often used for decision-making and analysis. Machine learning and mathematical calculations are two crucial methods employed for this. However, these computations may be time-consuming, and they require highperformance computers that are challenging to scale up. Raspberry Pi is a small, powerful, and cheap computer suitable for parallel calculations. Kubernetes is an open-source platform for managing container-based applications that allows automatic scaling of software applications. By combining Raspberry Pi with Kubernetes, a cost-effective and scalable system for mathematical calculations and machine learning can be created. In this study, the possibility of building a cost-effective and scalable system for mathematical calculations and machine learning using Raspberry Pi and Kubernetes is investigated. There will be theoretical research on Kubernetes and Raspberry Pi, design a system for mathematical calculations and machine learning, implement the system by installing and configuring Kubernetes on multiple Raspberry Pi's, measure and evaluate the system's performance and scalability, and present the study's results. The result showed that the use of Raspberry Pi in combination with Kubernetes to perform mathematical calculations is both cost-effective and scalable. In terms of performance, the system was able to handle intensive computational tasks satisfactorily, demonstrating its potential as a solution for large-scale data analysis. Improvements in system design and software optimization can further increase efficiency and performance

Knowledge, Attitude, and Practice Towards COVID-19 Among Abudwak Population, Galmudug, Somalia

The objective of this study is to assess the knowledge, attitude and practice towards COVID-19 among Abudwak Population in Somalia. Cross-sectional study was conducted in this study. Total of 420 participants (214 male and 206 female) were enrolled and analyzed using SPSS version 20. The knowledge of study participants were good and have clear concept of COVID-19 pandemic. Most of the respondent 184 (45%) have heard COVID-19 from social media as the main source of the knowledge. The majority of participant 342(81.4%) has good knowledge the way of transmit of COVID-19. In term of attitude mean score of the respondent their age group &gt;40 years (3.41 16?"&gt; 1.24) were higher than the respondent age group &lt; 25 years (2.98 16?"&gt; 1.14). In the case of month income, income group &gt;800 per month have practice scores (4.45 16?"> 1.25) which is higher than to the income group <200 per month (3.91 16?"&gt; 1.16). It is suggested that community should continue to strengthen the knowledge, attitude, and practice towards against the COVID-19 or any new emerging infectious disease, so that Somalia can win the battle against the disease. Keynote: COVID-19, Knowledge, Attitude, Practice, Abudwak Population. DOI: 10.7176/JHMN/96-03 Publication date: December 31st 2021

Management of project failures in the gaming industry : The normalization approach

In creative industries such as the gaming industry, the failure rate is typically higher in relation to many other industries. This is usually due to the constant need of innovation and the extreme competition in the industry of gaming. Firms in this industry take on multiple innovation projects, which inherently have a high rate of failure. Literature has previously stressed and focused on the importance of failure and how it can enhance learning that can be a crucial asset for any organization. However, failure brings along negative emotions that can slow down or block the learning process of an individual or an organization at large. In an industry where failure is common, it is important for the management to tackle this issue. Therefore, the purpose of this thesis is to explore the approach the management of small gaming firms take in order to normalize failure. In this study, the data has been collected qualitatively while using a thematic analysis to recognize consistent themes and patterns, which arise from the primary data that was collected. By conducting four semi-structured interviews with two different companies (2 interviews each), we found that both companies have a similar attitude regarding project failure. Both companies either expect failure to happen or even encourage it. One of our key findings was that both companies emphasize failing fast, which allows them to save time, money and resources as well as helps some members of the organization to react less emotionally to the termination of a project. Empirical results were then discussed and analyzed by judging whether the actions these companies took can be classified as a way of normalizing failure. We concluded that there was evidence for management employing various methods of action that would eventually lead to normalization of failure. Some of these actions included the fail fast attitude, failure supportive slogans and the thought of planning for failure beforehand

Effect of Inactivated Poliovirus Vaccine Campaigns, Pakistan, 2014–2017

Pakistan began using inactivated poliovirus vaccine alongside oral vaccine in mass campaigns to accelerate eradication of wild-type poliovirus in 2014. Using case-based and environmental surveillance data for January 2014–October 2017, we found that these campaigns reduced wild-type poliovirus detection more than campaigns that used only oral vaccine

High proportion of asymptomatic and presymptomatic COVID-19 infections in air passengers to Brunei

We report early findings from COVID-19 cases in Brunei suggesting a remarkably high proportion of asymptomatic (12%) and presymptomatic (30%) cases. This proportion was even higher in imported cases. These have implications for measures to prevent onward local transmission and should prompt reconsideration of current testing protocols and safe de-escalation of social distancing measures.</jats:p