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This paper describes a hybrid modelling approach to assess the future development of China's energy system, for both a “hypothetical counterfactual baseline” (HCB) scenario and low carbon (“abatement”) scenarios. The approach combines a technology-rich integrated assessment model (MESSAGE) of China's energy system with a set of sector-specific, bottom-up, energy demand models for the transport, buildings and industrial sectors developed by the Grantham Institute for Climate Change at Imperial College London. By exploring technology-specific solutions in all major sectors of the Chinese economy, we find that a combination of measures, underpinned by low-carbon power options based on a mix of renewables, nuclear and carbon capture and storage, would fundamentally transform the Chinese energy system, when combined with increasing electrification of demand-side sectors. Energy efficiency options in these demand sectors are also important.

The utility of using evolutionary and ecological frameworks to understand the dynamics of infectious diseases is gaining increasing recognition. However, integrating evolutionary ecology and infectious disease epidemiology is challenging because within-host dynamics can have counterintuitive consequences for between-host transmission, especially for vector-borne parasites. A major obstacle to linking within- and between-host processes is that the drivers of the relationships between the density, virulence, and fitness of parasites are poorly understood. By experimentally manipulating the intensity of rodent malaria (Plasmodium berghei) infections in Anopheles stephensi mosquitoes under different environmental conditions, we show that parasites experience substantial density-dependent fitness costs because crowding reduces both parasite proliferation and vector survival. We then use our data to predict how interactions between parasite density and vector environmental conditions shape within-vector processes and onward disease transmission. Our model predicts that density-dependent processes can have substantial and unexpected effects on the transmission potential of vector-borne disease, which should be considered in the development and evaluation of transmission-blocking interventions.