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Background Floods are the most frequently occurring natural disaster and constitute a significant public health risk. Several operational satellite-based flood detection systems quantify flooding extent, but it is unclear how far the choice of satellite-based flood product affects the findings of epidemiological studies of associated public health risks. Few studies of flooding’s health impacts have used mixed methods to enrich understanding of these impacts. This study therefore aims to evaluate the relationship between two satellite-derived flood products with outpatient attendance and diarrhoeal disease in northern Ghana, identifying plausible reasons for observed relationships via qualitative interviews. Methods A convergent parallel mixed methods design combined an ecological time series with focus group discussions and key informant interviews. Through an ecological time series component, monthly outpatient attendance and diarrhoea case counts from health facilities in two flood-prone districts for 2016–2020 were integrated with monthly flooding map layers classified via the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite sensors. The relationship between reported diarrhoea and outpatient attendance with flooding was examined using Poisson regression, controlling for seasonality and facility catchment population. Four focus group discussions with affected community members and four key informant interviews with health professionals explored flooding’s impact on healthcare delivery and access. Results Flooding detected via Landsat better predicted outpatient attendance and diarrhoea than flooding via MODIS. Outpatient attendance significantly reduced as LandSat-derived flood area per facility catchment increased (adjusted Incidence Rate Ratio = 0.78, 95% CI: 0.61–0.99, p p Conclusions The significant reduction in outpatient attendance during flooding suggests that flooding impairs healthcare delivery. The relationship is sensitive to the choice of satellite-derived flood product, so future studies should consider integrating multiple sources of satellite imagery for more robust exposure assessment. Health teams and communities should plan spatially targeted flood mitigation and health system adaptation strategies that explicitly address population and workforce mobility issues.

Fall armyworm (FAW) infestation in African countries presents significant threats to maize production. Such infestation has major economic implications in terms of the cost of measures taken at individual and international levels. Today’s problems cannot be solve with the same thinking which created them. Past interventions have generally resulted in policy revision from The MDGs to SDGs with little success. The complex nature of agri-business has necessitated the use of a systemic approach in solving operational problems. The study used a systemic approach to develop systems models that determine the components of current systems and its interaction with policies, social, environmental and economic dimensions of the agriculture industry. Results indicates that only by increasing our appreciation for “systemic approach” that addresses the needs of the present while safeguarding earth’s life-support system, can our social institutions achieve some modicum of effective control and stability. The systems models will help governments and agricultural proponents to anticipate the long-term consequences of their decisions and actions, as well as help to avoid any unintended consequences of policies and strategies such as ‘silo mentality’ and ‘organizational myopia’. As demonstrated in the aforementioned CLD and archetype, agriculture projects will continue to be the engine that develops and empowers the emerging and existing commercial business, and nation building across Africa. This systems thinking approach will provide more clarity in dealing with the complex management challenges and gradually replace the traditional theoretical approach of dealing with agricultural project management.