11Two dimensional flood inundation models are widely used tools for flood hazard mapping and an 12 essential component of statutory flood risk management guidelines in many countries. Yet we still 13 don't know how much physically complexity a flood inundation model needs for a given problem. 14 Here, three two dimensional explicit hydraulic models, that can be broadly defined as simulating 15 diffusive, inertial or shallow water waves, have been benchmarked using test cases from a recent 16Environment Agency for England and Wales (EA) study, where results from industry models are also 17 available. To ensure consistency the three models were written in the same code and share 18 subroutines for all but the momentum (flow) and time stepping calculations. The diffusive type 19 model required much longer simulation times that the other models, whilst the inertia model was 20 the quickest. For flows that vary gradually in time, differences in simulated velocities and depths due 21 to physical complexity were within 10% of the simulations from a range of industry models. 22Therefore, for flows that vary gradually in time it appears unnecessary to solve the full two 23 dimensional shallow water equations. As expected however, the simpler models were unable to 24 simulate supercritical flows accurately. Finally, implications of the results for future model 25 benchmarking studies are discussed in light of a number of subtle factors that were found to cause 26 significant differences in simulations relative to the choice of model. 27

Providing timely and accurate maps of surface water is valuable for mapping malaria risk and targeting disease control interventions. Radar satellite remote sensing has the potential to provide this information but current approaches are not suitable for mapping African malarial mosquito aquatic habitats that tend to be highly dynamic, often with emergent vegetation. We present a novel approach for mapping both open and vegetated water bodies using serial Sentinel-1 imagery for Western Zambia. This region is dominated by the seasonally inundated Upper Zambezi floodplain that suffers from a number of public health challenges. The approach uses open source segmentation and machine learning (extra trees classifier), applied to training data that are automatically derived using freely available ancillary data. Refinement is implemented through a consensus approach and Otsu thresholding to eliminate false positives due to dry flat sandy areas. The results indicate a high degree of accuracy (mean overall accuracy 92% st dev 3.6) providing a tractable solution for operationally mapping water bodies in similar large river floodplain unforested environments. For the period studied, 70% of the total water extent mapped was attributed to vegetated water, highlighting the importance of mapping both open and vegetated water bodies for surface water mapping.

Background The Barotse floodplains of the upper Zambezi River and its tributaries are a highly dynamic environment, with seasonal flooding and transhumance presenting a shifting mosaic of potential larval habitat and human and livestock blood meals for malaria vector mosquitoes. However, limited entomological surveillance has been undertaken to characterize the vector community in these floodplains and their environs. Such information is necessary as, despite substantial deployment of insecticide-treated nets (ITNs) and indoor residual spraying (IRS) against Anopheles vectors, malaria transmission persists across Barotseland in Zambia’s Western Province. Methods Geographically extensive larval surveys were undertaken in two health districts along 102 km of transects, at fine spatial resolution, during a dry season and following the peak of the successive wet season. Larvae were sampled within typical Anopheles flight range of human settlements and identified through genetic sequencing of cytochrome c oxidase I and internal transcribed spacer two regions of mitochondrial and nuclear DNA. This facilitated detailed comparison of taxon-specific abundance patterns between ecological zones differentiated by hydrological controls. Results An unexpected paucity of primary vectors was revealed, with An. gambiae s.l. and An. funestus representing < 2% of 995 sequenced anophelines. Potential secondary vectors predominated in the vector community, primarily An. coustani group species and An. squamosus. While the distribution of An. gambiae s.l. in the study area was highly clustered, secondary vector species were ubiquitous across the landscape in both dry and wet seasons, with some taxon-specific relationships between abundance and ecological zones by season. Conclusions The diversity of candidate vector species and their high relative abundance observed across diverse hydro-ecosystems indicate a highly adaptable transmission system, resilient to environmental variation and, potentially, interventions that target only part of the vector community. Larval survey results imply that residual transmission of malaria in Barotseland is being mediated predominantly by secondary vector species, whose known tendencies for crepuscular and outdoor biting renders them largely insensitive to prevalent vector control methods.

BackgroundInterpreting evaluations of complex interventions can be difficult without sufficient description of key intervention content. We aimed to develop an implementation package for primary care which could be delivered using typically available resources and could be adapted to target determinants of behaviour for each of four quality indicators: diabetes control, blood pressure control, anticoagulation for atrial fibrillation and risky prescribing. We describe the development and prospective verification of behaviour change techniques (BCTs) embedded within the adaptable implementation packages.MethodsWe used an over-lapping multi-staged process. We identified evidence-based, candidate delivery mechanisms—mainly audit and feedback, educational outreach and computerised prompts and reminders. We drew upon interviews with primary care professionals using the Theoretical Domains Framework to explore likely determinants of adherence to quality indicators. We linked determinants to candidate BCTs. With input from stakeholder panels, we prioritised likely determinants and intervention content prior to piloting the implementation packages. Our content analysis assessed the extent to which embedded BCTs could be identified within the packages and compared them across the delivery mechanisms and four quality indicators.ResultsEach implementation package included at least 27 out of 30 potentially applicable BCTs representing 15 of 16 BCT categories. Whilst 23 BCTs were shared across all four implementation packages (e.g. BCTs relating to feedback and comparing behaviour), some BCTs were unique to certain delivery mechanisms (e.g. ‘graded tasks’ and ‘problem solving’ for educational outreach). BCTs addressing the determinants ‘environmental context’ and ‘social and professional roles’ (e.g. ‘restructuring the social and ‘physical environment’ and ‘adding objects to the environment’) were indicator specific. We found it challenging to operationalise BCTs targeting ‘environmental context’, ‘social influences’ and ‘social and professional roles’ within our chosen delivery mechanisms.ConclusionWe have demonstrated a transparent process for selecting, operationalising and verifying the BCT content in implementation packages adapted to target four quality indicators in primary care. There was considerable overlap in BCTs identified across the four indicators suggesting core BCTs can be embedded and verified within delivery mechanisms commonly available to primary care. Whilst feedback reports can include a wide range of BCTs, computerised prompts can deliver BCTs at the time of decision making, and educational outreach can allow for flexibility and individual tailoring in delivery.Electronic supplementary materialThe online version of this article (10.1186/s13012-017-0704-7) contains supplementary material, which is available to authorized users.

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