How did primary health care in Beira experience Cyclone Idai?

Beira, the biggest city of Mozambique's Sofala province, was struck by Cyclone Idai on 14 March 2019, with devastating impacts. The floods along with the cyclone destroyed road infrastructure and health facilities and disrupted primary health care (PHC) service delivery. In addition, destruction of farmland and food stocks resulted in malnutrition; the abundance of water fostered the reproduction of mosquitos, exacerbating the burden of malaria; and problems with water and sanitation led to epidemics of cholera. The exact role and contribution of human-induced climate change is very difficult to quantify, but there is little doubt that climate change is driving more frequent and severe cyclones, such as Idai. Considering the current climatic changes, it is expected that climate hotspots such as Beira will only experience more frequent extreme weather events. In these settings, with high risks but low adaptive capacity, dedicated efforts are required to strengthen PHC with a focus on preparedness for disasters. This should entail community awareness and education, strengthening infrastructure and service provision, as well as collaboration with important stakeholders across other sectors.Contribution: Using a case study approach, this article contributes climate resilient PHC for better preparedness to service continuity.

Observer-based state feedback for enhanced insulin control of type 'i' diabetic patients

During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type ‘I’ diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink.