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Abstract Background Seasonal floods pose a commonly-recognised barrier to women’s access to maternal services, resulting in increased morbidity and mortality. Despite their importance, previous GIS models of healthcare access have not adequately accounted for floods. This study developed new methodologies for incorporating flood depths, velocities, and extents produced with a flood model into network- and raster-based health access models. The methodologies were applied to the Barotse Floodplain to assess flood impact on women’s walking access to maternal services and vehicular emergency referrals for a monthly basis between October 2017 and October 2018. Methods Information on health facilities were acquired from the Ministry of Health. Population density data on women of reproductive age were obtained from the High Resolution Settlement Layer. Roads were a fusion of OpenStreetMap and data manually delineated from satellite imagery. Monthly information on floodwater depth and velocity were obtained from a flood model for 13-months. Referral driving times between delivery sites and EmOC were calculated with network analysis. Walking times to the nearest maternal services were calculated using a cost-distance algorithm. Results The changing distribution of floodwaters impacted the ability of women to reach maternal services. At the peak of the dry season (October 2017), 55%, 19%, and 24% of women had walking access within 2-hrs to their nearest delivery site, EmOC location, and maternity waiting shelter (MWS) respectively. By the flood peak, this dropped to 29%, 14%, and 16%. Complete inaccessibility became stark with 65%, 76%, and 74% unable to access any delivery site, EmOC, and MWS respectively. The percentage of women that could be referred by vehicle to EmOC from a delivery site within an hour also declined from 65% in October 2017 to 23% in March 2018. Conclusions Flooding greatly impacted health access, with impacts varying monthly as the floodwave progressed. Additional validation and application to other regions is still needed, however our first results suggest the use of a hydrodynamic model permits a more detailed representation of floodwater impact and there is great potential for generating predictive models which will be necessary to consider climate change impacts on future health access.

Abstract Regional optimisation of malaria vector control approaches requires detailed understanding both of the species composition of Anopheles mosquito communities, and how they vary over spatial and temporal scales. Knowledge of vector community dynamics is particularly important in settings where ecohydrological conditions fluctuate seasonally and inter-annually, such as the Barotse floodplain of the upper Zambezi river. DNA barcoding of anopheline larvae sampled in the 2019 wet season revealed the predominance of secondary vector species, with An. coustani comprising > 80% of sampled larvae and distributed ubiquitously across all ecological zones. Extensive larval sampling, plus a smaller survey of adult mosquitoes, identified geographic clusters of primary vectors, but represented only 2% of anopheline larvae. Comparisons with larval surveys in 2017/2018 and a contemporaneous independent 5-year dataset from adult trapping corroborated this paucity of primary vectors across years, and the consistent numerical dominance of An. coustani and other secondary vectors in both dry and wet seasons, despite substantial inter-annual variation in hydrological conditions. This marked temporal consistency of spatial distribution and anopheline community composition presents an opportunity to target predominant secondary vectors outdoors. Larval source management should be considered, alongside prevalent indoor-based approaches, amongst a diversification of vector control approaches to more effectively combat residual malaria transmission.

Abstract 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.

INTRODUCTION: Hypertension is a longstanding problem in Zambia, yet little is known about its prevalence and risk factors, particularly in rural and urban settings. Identifying geographical variations in hypertension is important to enhance the health of adult Zambians regardless of where they live. Therefore, the purpose of this study was to compare the prevalence of hypertension and related risk factors between rural (n = 130) and urban (n = 131) communities in Western Province, Zambia. METHODS: this cross-sectional study included urban and rural adult Zambians attending health checks who completed a modified World Health Organization (WHO) survey, and had blood pressure and anthropometric measurements completed. Descriptive statistics were used to summarize demographic and risk factor variables. Chi-square tests of association were used to analyze relationships between categorical variables, t-tests to analyze relationships between continuous variables and logistic regression to examine associations of hypertension with selected risk factors. RESULTS: the prevalence of hypertension in rural Zambians was double (46.9%) that of urban Zambians (22.9%). Increasing age, not engaging in walking/biking, and alcohol intake within the last 30 days were associated with an increased likelihood of hypertension in rural Zambians while eating vegetables more days during the week was associated with a decreased likelihood of hypertension in rural Zambians. Body Mass Index (BMI) was significantly associated with an increased likelihood of hypertension in urban Zambians. CONCLUSION: modifiable risk factors (such as BMI, dietary intake, and physical activity) are associated with hypertension prevalence in this population, indicating opportunities for screening and other prevention measures.

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.