Ovarian extracellular matrix-based hydrogel for human ovarian follicle survival in vivo: A pilot work.

To successfully assemble a bio-engineered ovary, we need to create a three-dimensional matrix able to accommodate isolated follicles and cells. The goal of this study was to develop an extracellular matrix hydrogel (oECM) derived from decellularized bovine ovaries able to support, in combination with alginate, human ovarian follicle survival and growth in vitro. Two different hydrogels (oECM1, oECM2) were produced and compared in terms of decellularization efficiency (dsDNA), ECM preservation (collagen and glycosaminoglycan levels), ultrastructure, rigidity, and cytotoxicity. oECM2 showed significantly less dsDNA, greater retention of glycosaminoglycans and better rigidity than oECM1. Isolated human ovarian follicles were then encapsulated in four selected hydrogel combinations: (1) 100% oECM2, (2) 90% oECM2 + 10% alginate, (3) 75% oECM2 + 25% alginate, and (4) 100% alginate. After 1 week of in vitro culture, follicle recovery rate, viability, and growth were analyzed. On day 7 of in vitro culture, follicle recovery rates were 0%, 23%, 65%, 82% in groups 1-4, respectively, rising proportionally with increased alginate content. However, there was no difference in follicle viability or growth between groups 2 and 3 and controls (group 4). In conclusion, since pure alginate cannot be used to graft preantral follicles due to its poor revascularization and degradation after grafting, oECM2 hydrogel combined with alginate may provide a new and promising alternative to graft isolated human follicles in a bio-engineered ovary.

An interactive application for malaria elimination transmission and costing in the Asia-Pacific.

Leaders in the Asia-Pacific have endorsed an ambitious target to eliminate malaria in the region by 2030. The emergence and spread of artemisinin drug resistance in the Greater Mekong Subregion makes elimination urgent and strategic for the global goal of malaria eradication. Mathematical modelling is a useful tool for assessing and comparing different elimination strategies and scenarios to inform policymakers. Mathematical models are especially relevant in this context because of the wide heterogeneity of regional, country and local settings, which means that different strategies are needed to eliminate malaria. However, models and their predictions can be seen as highly technical, limiting their use for decision making. Simplified applications of models are needed to allow policy makers to benefit from these valuable tools. This paper describes a method for communicating complex model results with a user-friendly and intuitive framework. Using open-source technologies, we designed and developed an interactive application to disseminate the modelling results for malaria elimination. The design was iteratively improved while the application was being piloted and extensively tested by a diverse range of researchers and decision makers. This application allows several target audiences to explore, navigate and visualise complex datasets and models generated in the context of malaria elimination. It allows widespread access, use of and interpretation of models, generated at great effort and expense as well as enabling them to remain relevant for a longer period of time. It has long been acknowledged that scientific results need to be repackaged for larger audiences. We demonstrate that modellers can include applications as part of the dissemination strategy of their findings. We highlight that there is a need for additional research in order to provide guidelines and direction for designing and developing effective applications for disseminating models.

Malaria elimination transmission and costing in the Asia-Pacific: Developing an investment case.

Background: The Asia-Pacific region has made significant progress against malaria, reducing cases and deaths by over 50% between 2010 and 2015. These gains have been facilitated in part, by strong political and financial commitment of governments and donors. However, funding gaps and persistent health system challenges threaten further progress. Achieving the regional goal of malaria elimination by 2030 will require an intensification of efforts and a plan for sustainable financing. This article presents an investment case for malaria elimination to facilitate these efforts. Methods: A transmission model was developed to project rates of decline of Plasmodium falciparum and Plasmodium vivax malaria and the output was used to determine the cost of the interventions that would be needed for elimination by 2030. In total, 80 scenarios were modelled under various assumptions of resistance and intervention coverage. The mortality and morbidity averted were estimated and health benefits were monetized by calculating the averted cost to the health system, individual households, and society. The full-income approach was used to estimate the economic impact of lost productivity due to premature death and illness, and a return on investment was computed. Results: The study estimated that malaria elimination in the region by 2030 could be achieved at a cost of USD 29.02 billion (range: USD 23.65-36.23 billion) between 2017 and 2030. Elimination would save over 400,000 lives and avert 123 million malaria cases, translating to almost USD 90 billion in economic benefits. Discontinuing vector control interventions and reducing treatment coverage rates to 50% will result in an additional 845 million cases, 3.5 million deaths, and excess costs of USD 7 billion. Malaria elimination provides a 6:1 return on investment. Conclusion: This investment case provides compelling evidence for the benefits of continued prioritization of funding for malaria and can be used to develop an advocacy strategy.

Correction: Hitting a Moving Target: A Model for Malaria Elimination in the Presence of Population Movement.

[This corrects the article DOI: 10.1371/journal.pone.0144990.].

Sensitivity to model structure: a comparison of compartmental models in epidemiology.

Compartmental models have provided a framework for understanding disease transmission dynamics for over 100 years. The predictions from these models are often policy relevant and need to be robust to model assumptions, parameter values and model structure. A selection of compartmental models with the same parameter values but different model structures (ranging from simple structures to complex ones) were compared in the absence and presence of several policy interventions to assess sensitivity to model structure. Models were fitted to data to assess if this might reduce this sensitivity. The compartmental models produced wide-ranging estimates of outcome measures but when fitted to data, the estimates obtained were robust to model structure. This finding suggests that there may be an argument for selecting simple models over complex ones, but the complexity of the model should be determined by the purpose of the model and the use to which it will be put.

Hitting a Moving Target: A Model for Malaria Elimination in the Presence of Population Movement.

South Africa is committed to eliminating malaria with a goal of zero local transmission by 2018. Malaria elimination strategies may be unsuccessful if they focus only on vector biology, and ignore the mobility patterns of humans, particularly where the majority of infections are imported. In the first study in Mpumalanga Province in South Africa designed for this purpose, a metapopulation model is developed to assess the impact of their proposed elimination-focused policy interventions. A stochastic, non-linear, ordinary-differential equation model is fitted to malaria data from Mpumalanga and neighbouring Maputo Province in Mozambique. Further scaling-up of vector control is predicted to lead to a minimal reduction in local infections, while mass drug administration and focal screening and treatment at the Mpumalanga-Maputo border are predicted to have only a short-lived impact. Source reduction in Maputo Province is predicted to generate large reductions in local infections through stemming imported infections. The mathematical model predicts malaria elimination to be possible only when imported infections are treated before entry or eliminated at the source suggesting that a regionally focused strategy appears needed, for achieving malaria elimination in Mpumalanga and South Africa.