The importance of need-altruism and kin-altruism to blood donor behaviour for black and white people.

BACKGROUND: Need-altruism (a preference to help people in need) and kin-altruism (a preference to help kin over non-kin) underlie two hypotheses for voluntary blood donation: (i) Need-altruism underlies motivations for volunteer blood donation and (ii) Black people express a stronger preference for kin-altruism, which is a potential barrier to donation. This paper tests these hypotheses and explores how need- and kin-altruism are associated with wider altruistic motivations, barriers, and strategies to encourage donation. METHODS: We assessed need- and kin-altruism, other mechanisms-of-altruism (e.g., reluctant-altruism), barriers, strategies to encourage donation, donor status, and willingness-to-donate across four groups based on ethnicity (Black; White), nationality (British; Nigerian), and country-of-residence: (i) Black-British people (n = 395), and Black-Nigerian people (ii) in the UK (n = 97) or (iii) across the rest of the world (n = 101), and (v) White-British people in the UK (n = 452). We also sampled a Black-Nigerian Expert group (n = 60). RESULTS: Need-altruism was higher in donors and associated with willingness-to-donate in non-donors. Levels of kin-altruism did not differ between Black and White people, but need-altruism was lower in Black-British people. Kin-altruism was associated with a preference for incentives, and need-altruism with a preference for recognition (e.g., a thank you) as well as an increased willingness-to-donate for Black non-donors. Need-altruism underlies a blood-donor-cooperative-phenotype. CONCLUSION: Need-altruism is central to blood donation, in particular recruitment. Lower need-altruism may be a specific barrier for Black-British people. Kin-altruism is important for Black non-donors. The blood donor cooperative phenotype deserves further consideration. Implications for blood services are discussed.

Seroprevalence, co-infection and risk of transmission of Hepatitis B and D virus among hospital attendees in two South-western states in Nigeria.

Infection with both Hepatitis B (HBV) and D (HDV) virus causes more severe liver damage than HBV alone. Superinfections among chronic HBV infected cohorts often lead to HDV persistence with rapid progression to cirrhosis, necessitating continuous surveillance to determine their prevalence and relative contribution to liver pathology. A cross-sectional study among hospital outpatients in Ekiti and Osunstates was conducted using random sampling technique. Blood samples were collected from 410 participants and tested for HBV serological markers. All samples positive for HBsAg samples were tested for Hepatitis D virus antigen (HDAg), serum anti-HDV IgM, and serum anti-HDV IgG using enzyme-linked immunosorbent assay kits. The prevalence of HBV infection among the 410 samples was 12.4% (CI 9.5-15.9). Past HBV exposure was detected in 120 (29.2%), while 147(35.8%) were susceptible to HBV infection. Among the HBsAg positive individuals, 9.8% were hepatitis D antigen (HDAg) positive, while 3.9% and 1.9% were positive for IgG anti-HDV and IgM anti-HDV, respectively. Risk factors associated with HBV infections in this study were multiple sexual partners and sharing of sharp objects. Our investigation has verified the endemicity of HBV in Nigeria and revealed that HBV- HDV co-infection is highly prevalent in south-west Nigeria.

Day-ahead combined economic and emission dispatch with spinning reserve consideration using moth swarm algorithm for a data centre load.

Dynamic combined economic and emission dispatch is an important task in the power system that examines the optimal allocation of power generation resources that yield the least possible fuel and emission costs. In this study, the Moth Swarm Algorithm has been proposed for solving the combined economic and emission dispatch problem for a 24-hour period. The model has been implemented on a test system made up of a combination of thermal and solar photovoltaic plants, while also considering spinning reserve allocation. The results obtained are presented in comparison with commonly used state-of-the-art methods like Moth Flame Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, and Tunicate Swarm Algorithm. Two test systems have been considered in the model implementation. The first system consists of a combination of six thermal plants and thirteen solar plants whose load demand is the hourly energy demand of an anonymous data centre in South Africa. The second test system is made up of three thermal plants and thirteen solar plants to service its unique hourly load demand. Results showed that the proposed MSA gave preference to solar photovoltaic generation over thermal generation given that environmental impact minimization is a major component of the overall objective function. The proposed MSA also scheduled thermal generators to provide the required spinning reserve capacity since solar energy is intermittent in nature. Overall, analyses show that the proposed MSA outperformed the other methods in finding the best fuel, emission, solar generation, and spinning reserve costs that best serve the energy demand of the data centre and the second test system for the 24-hour period.

BioNessie(G) - a Grid enabled biochemical networks simulation environment.

The simulation of biochemical networks provides insight and understanding about the underlying biochemical processes and pathways used by cells and organisms. BioNessie is a biochemical network simulator which has been developed at the University of Glasgow. This paper describes the simulator and focuses in particular on how it has been extended to benefit from a wide variety of high performance compute resources across the UK through Grid technologies to support larger scale simulations.

Assessment of PMTCT Success Rates Based on Antiretroviral Interventions and Feeding Options: A Prospective Cohort Study.

BACKGROUND: The success of any prevention of mother-to-child transmission (PMTCT) program is assessed by the proportion of HIV-exposed infants that sero-convert at the end of all risk exposures. Although adopting the best feeding option for HIV-exposed infants is one of the factors that impact PMTCT outcomes, there is limited data on the assessment of PMTCT success rates based on antiretroviral interventions and feeding options. This study assesses the success rate of PMTCT service based on antiretroviral interventions and feeding options. METHODS: Eighty-five HIV-infected mothers previously in care were enrolled in a prospective cohort study. Folders and structured questionnaires were used to extract data on mother-infant pair and the first CD4, count of infected mothers on enrolment at PMTCT clinic. Dry blood spot samples were obtained from exposed infants for early infant diagnosis. Results were analyzed using the SPSS software. RESULTS: The mean age of enrolled mothers was 31.3 ± 4.4 years, and an average CD4+ T-lymphocyte count of 368.6 ± 216.2 cells/µl. Seven (8.2%) of the HIV-exposed infants were positive for HIV-1 based on early infant diagnosis results. Overall PMTCT success rate (PMTCTSR) was 91.8%. HIV-1 prevalence of 5.0%, 0% and 21.1% was found among infants of patients who opted for breastfeeding, replacement feeding, and mixed feeding respectively thus yielding PMTCT success rates of 95%, 100% and 78.9%. Pediatric antiretroviral interventions success rates in HIV-exposed infants was 95.8%, 80.0% and 66.7% based on age groups ≤ 6 months, > 6 ≤ 12 months, and > 12 ≤ 18 months respectively. CONCLUSION AND GLOBAL HEALTH IMPLICATIONS: Quality PMTCT service is vital for successful prevention of mother-to-child transmission of HIV. Implementation of more dynamic approaches such as adherence to option B+ guidelines in PMTCT service in our settings can further reduce mother-to-child transmission of HIV and improve outcomes.

Development of grid frameworks for clinical trials and epidemiological studies.

E-Health initiatives such as electronic clinical trials and epidemiological studies require access to and usage of a range of both clinical and other data sets. Such data sets are typically only available over many heterogeneous domains where a plethora of often legacy based or in-house/bespoke IT solutions exist. Considerable efforts and investments are being made across the UK to upgrade the IT infrastructures across the National Health Service (NHS) such as the National Program for IT in the NHS (NPFIT) [1]. However, it is the case that currently independent and largely non-interoperable IT solutions exist across hospitals, trusts, disease registries and GP practices - this includes security as well as more general compute and data infrastructures. Grid technology allows issues of distribution and heterogeneity to be overcome, however the clinical trials domain places special demands on security and data which hitherto the Grid community have not satisfactorily addressed. These challenges are often common across many studies and trials hence the development of a re-usable framework for creation and subsequent management of such infrastructures is highly desirable. In this paper we present the challenges in developing such a framework and outline initial scenarios and prototypes developed within the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project [2].