Informal mhealth at scale in Africa: Opportunities and challenges.

The extraordinary global growth of digital connectivity has generated optimism that mobile technologies can help overcome infrastructural barriers to development, with 'mobile health' (mhealth) being a key component of this. However, while 'formal' (top-down) mhealth programmes continue to face challenges of scalability and sustainability, we know relatively little about how health-workers are using their own mobile phones informally in their work. Using data from Ghana, Ethiopia and Malawi, we document the reach, nature and perceived impacts of community health-workers' (CHWs') 'informal mhealth' practices, and ask how equitably these are distributed. We implemented a mixed-methods study, combining surveys of CHWs across the three countries, using multi-stage proportional-to-size sampling (N = 2197 total), with qualitative research (interviews and focus groups with CHWs, clients and higher-level stake-holders). Survey data were weighted to produce nationally- or regionally-representative samples for multivariate analysis; comparative thematic analysis was used for qualitative data. Our findings confirm the limited reach of 'formal' compared with 'informal' mhealth: while only 15% of CHWs surveyed were using formal mhealth applications, over 97% reported regularly using a personal mobile phone for work-related purposes in a range of innovative ways. CHWs and clients expressed unequivocally enthusiastic views about the perceived impacts of this 'informal health' usage. However, they also identified very real practical challenges, financial burdens and other threats to personal wellbeing; these appear to be borne disproportionately by the lowest-paid cadre of health-workers, especially those serving rural areas. Unlike previous small-scale, qualitative studies, our work has shown that informal mhealth is already happening at scale, far outstripping its formal equivalent. Policy-makers need to engage seriously with this emergent health system, and to work closely with those on the ground to address sources of inequity, without undermining existing good practice.

A random effects model for the identification of differential splicing (REIDS) using exon and HTA arrays.

BACKGROUND: Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events do occur which have been linked to genetic disorders, such as several types of cancer and neurodegenerative diseases (Fan et al., Theor Biol Med Model 3:19, 2006). Therefore, understanding the mechanism of alternative splicing and identifying the difference in splicing events between diseased and healthy tissue is crucial in biomedical research with the potential of applications in personalized medicine as well as in drug development. RESULTS: We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events. Based on a set of scores, an exon score and an array score, a decision regarding alternative splicing can be made. The model enables the ability to distinguish a differential expressed gene from a differential spliced exon. The proposed model was applied to three case studies concerning both exon and HTA arrays. CONCLUSION: The REIDS model provides a work flow for the identification of alternative splicing events relying on the established linear mixed model. The model can be applied to different types of arrays.

Willingness to pay for a dengue vaccine and its associated determinants in Indonesia: A community-based, cross-sectional survey in Aceh.

Vaccination strategies are being considered as a part of dengue prevention programs in endemic countries. To accelerate the introduction of dengue vaccine into the public sector program and private markets, understanding the private economic benefits of a dengue vaccine is therefore essential. The aim of this study was to assess the willingness to pay (WTP) for a dengue vaccine among community members in Indonesia and its associated explanatory variables. A community-based, cross-sectional survey was conducted in nine regencies of Aceh province, Indonesia, from November 2014 to March 2015. A pre-tested validated questionnaire was used to facilitate the interviews. To assess the explanatory variables influencing participants' WTP for a dengue vaccine, a linear regression analysis was employed. We interviewed 677 healthy community members; 476 participants (87.5% of the total) were included in the final analysis. An average individual was willing to pay around US-$ 4 (mean: US-$ 4.04; median: US-$ 3.97) for a dengue vaccine. Our final multivariate model revealed that working as a civil servant, living in the city, and having good knowledge on dengue viruses, a good attitude towards dengue, and good preventive practice against dengue virus infection were associated with a higher WTP (P<0.05). Our model suggests that marketing efforts should be directed to community members who are working in the suburbs especially as farmers. In addition, the results of our study underscore the need for low-cost quality vaccines, public sector subsidies for vaccinations, and intensifying efforts to further educate and encourage households regarding other dengue preventive measures, using trusted individuals as facilitators.

The relationship between economic status, knowledge on dengue, risk perceptions and practices.

The reemergence of dengue as an important public health problem reflects the difficulties in sustaining vertically organized, effective, control programs and the need for community-based strategies for Aedes aegypti control that result in behavioral change. We aimed to disentangle the relationships between underlying determinants of dengue related practices. We conducted a cross-sectional study in 780 households in La Lisa, Havana, Cuba. A questionnaire and an observation guide were administrated to collect information on variables related to economic status, knowledge on dengue, risk perception and practices associated with Aedes aegypti breading sites. To test a conceptual model that hypothesized direct relationships among all these constructs, we first used Exploratory Factor Analysis with Principal Component Analysis to establish the relationship between observed variables and the underlying latent variables. Subsequently, we tested whether the observed data supported the conceptual model through Confirmatory Factor Analysis. Exploratory Factor Analysis indicated that the items measured could be reduced into five factors with an eigenvalue >1.0: Knowledge on dengue, Intradomiciliar risk practices, Peridomiciliar risk practices, Risk perception and Economic status. The proportion of the total variance in the data explained by these five factors was 74.3%. The Confirmatory Factor Analysis model differed from our hypothesized conceptual model. Only Knowledge on dengue had a significant, direct, positive, effect on Practices. There was also a direct association of Economic status with Knowledge on dengue, but not with Risk perception and Practices. Clarifying the relationship between direct and indirect determinants of dengue related practices contributes to a better understanding of the potential effect of Information Education and Communication on practices and on the reduction of Aedes aegypti breeding sites and provides inputs for designing a community based strategy for dengue control.

A mathematical model for HIV and hepatitis C co-infection and its assessment from a statistical perspective.

The hepatitis C virus (HCV) and the human immunodeficiency virus (HIV) are a clear threat for public health, with high prevalences especially in high risk groups such as injecting drug users. People with HIV infection who are also infected by HCV suffer from a more rapid progression to HCV-related liver disease and have an increased risk for cirrhosis and liver cancer. Quantifying the impact of HIV and HCV co-infection is therefore of great importance. We propose a new joint mathematical model accounting for co-infection with the two viruses in the context of injecting drug users (IDUs). Statistical concepts and methods are used to assess the model from a statistical perspective, in order to get further insights in: (i) the comparison and selection of optional model components, (ii) the unknown values of the numerous model parameters, (iii) the parameters to which the model is most 'sensitive' and (iv) the combinations or patterns of values in the high-dimensional parameter space which are most supported by the data. Data from a longitudinal study of heroin users in Italy are used to illustrate the application of the proposed joint model and its statistical assessment. The parameters associated with contact rates (sharing syringes) and the transmission rates per syringe-sharing event are shown to play a major role.