Prevalence of hepatitis delta virus infection among hepatitis b virus surface antigen positive patients circulating in the largest province of pakistan

<p>Abstract</p> <p>Background</p> <p>Hepatitis delta virus (HDV) and Hepatitis B virus (HBV) co-infection is well known to induce a spectrum of acute and chronic liver diseases which further advance to cirrhosis, fulminant hepatitis and hepatocellular carcinoma (HCC).</p> <p>Aim</p> <p>The aim of the present study was to determine the prevalence of hepatitis D virus super-infection among hepatitis B surface antigen (HBsAg) positive individuals in the highly populated province of Pakistan which is not well known.</p> <p>Methods</p> <p>Sera samples were subjected to HBsAg and anti-HDV screening and finally anti-HDV and HBsAg positive coinfected samples were used for HDV active RNA confirmation using nested polymerase chain reaction (PCR).</p> <p>Results</p> <p>Out of total 200 HBsAg positive samples by rapid device, 96 (48%) were also found reactive for HBsAg using enzyme linked immunosorbant assay (ELISA). Out of these HBsAg ELISA positive samples, 80 (88.8%) were anti-HDV ELISA positive which were then subjected to PCR. The amplification results further confirmed 24 (30%) samples to be HDV RNA positive. HDV super-infection was more common in male patients than female patients (81% VS 19%).</p> <p>Conclusion</p> <p>The current study shows a high prevalence rate of HDV-HBV co-infection in Pakistan that tends to increase over time.</p

How IoT-Driven Citizen Science Coupled with Data Satisficing Can Promote Deep Citizen Science

To study and understand the importance of Internet of Things-driven citizen science (IoTCS) combined with data satisficing, we set up and undertook a citizen science experiment for air quality (AQ) in four Pakistan cities using twenty-one volunteers. We used quantitative methods to analyse the AQ data. Three research questions (RQ) were posed as follows: Which factors affect CS IoT-CS AQ data quality (RQ1)? How can we make science more inclusive by dealing with the lack of scientists, training and high-quality equipment (RQ2)? Can a lack of calibrated data readings be overcome to yield otherwise useful results for IoT-CS AQ data analysis (RQ3)? To address RQ1, an analysis of related work revealed that multiple causal factors exist. Good practice guidelines were adopted to promote higher data quality in CS studies. Additionally, we also proposed a classification of CS instruments to help better understand the data quality challenges. To answer RQ2, user engagement workshops were undertaken as an effective method to make CS more inclusive and also to train users to operate IoT-CS AQ devices more understandably. To address RQ3, it was proposed that a more feasible objective is that citizens leverage data satisficing such that AQ measurements can detect relevant local variations. Additionally, we proposed several recommendations. Our top recommendations are that: a deep (citizen) science approach should be fostered to support a more inclusive, knowledgeable application of science en masse for the greater good; It may not be useful or feasible to cross-check measurements from cheaper versus more expensive calibrated instrument sensors in situ. Hence, data satisficing may be more feasible; additional cross-checks that go beyond checking if co-located low-cost and calibrated AQ measurements correlate under equivalent conditions should be leveraged

Leadership in strategic information (LSI) building skilled public health capacity in Ethiopia

<p>Abstract</p> <p>Background</p> <p>In many developing countries, including Ethiopia, few have the skills to use data for effective decision making in public health. To address this need, the U.S. Centers for Disease Control and Prevention (CDC), in collaboration with two local Ethiopian organizations, developed a year long Leadership in Strategic Information (LSI) course to train government employees working in HIV to use data from strategic information sources. A process evaluation of the LSI course examined the impact of the training on trainees' skills and the strengths and weaknesses of the course. The evaluation consisted of surveys and focus groups.</p> <p>Findings</p> <p>Trainees' skill sets increased in descriptive and analytic epidemiology, surveillance, and monitoring and evaluation (M and E). Data from the evaluation indicated that the course structure and the M and E module required revision in order to improve outcomes. Additionally, the first cohort had a high attrition rate. Overall, trainees and key stakeholders viewed LSI as important in building skilled capacity in public health in Ethiopia.</p> <p>Conclusion</p> <p>The evaluation provided constructive insight in modifying the course to improve retention and better address trainees' learning needs. Subsequent course attrition rates decreased as a result of changes made based on evaluation findings.</p