Health care systems need to be resilient to deal with disasters like the global spread of the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) on top of serving the changing needs of a multi-morbid, ageing and often dispersed population. This paper identifies, discusses and augments critical dimensions of resilience retrieved from the academic literature. It pulls together an integrated concept of resilience characterised by organisational capabilities. Our concept does not focus on the micro-level like most resilience literature in health care but addresses the system level with many stakeholders involved. Distinguishing exogenous shocks to the health care system into adverse events and planned innovations provides the basis for our conclusions and insights. It becomes apparent only when dealing with planned interventions that transformative capabilities are indispensable to cope with sudden increases in health care pressures. Due to the current focus on absorptive and adaptive resilience, organisations over-rely on management capabilities that cannot generate a lasting increase in functionality. Therefore, reducing the resilience discussion to bouncing back from adverse events could deceive organisations into cultivating a suboptimal mix of organisational capabilities lacking transformative capabilities, which pave the way for a structural change that aims at a sustainably higher functionality.

HIV/AIDS affects over 40 million people worldwide, and more than 70% of these people live in Africa. Mother-to-child transmission of HIV accounts for over 90% of all HIV infections in children under the age of 15 years. However, implementing HIV prevention policies in Africa is extremely difficult because of the poor medical and socio-economic infrastructure. In this paper, we present a discrete-event simulation model that evaluates the relative benefits of two potentially affordable interventions aimed at preventing mother-to-child transmission of HIV, namely anti-retroviral treatment at childbirth and/or bottlefeeding strategies. The model uses rural Tanzanian data and compares different treatment policies. Our results demonstrate that strategic guidelines about breastfeeding are highly dependent on the assumed increase in infant mortality due to bottlefeeding, the efficacy of anti-retroviral treatment at childbirth, and the maternal health stage. The cost of averted infections, though low by Western standards, may represent significant obstacles to policy implementation in developing countries.

Developing decision support systems for emergency situations is a complex and challenging task. These difficulties are compounded further in the case of cross-border emergencies, which often require the coordination and collaboration of independent agencies. These agencies have different structures and resources in place, and follow their own internal policies and procedures. If a number of countries have been affected, agencies may not even share the same language. Large-scale disasters, whether natural, deliberate, or accidental do not respect borders and come with a high risk to human life and a variety of economic and health impacts. Thus, it is the aim of the S-HELP (Securing-Health Emergency Learning Planning) project to develop a decision support tool-set that supports multi-agency decision-making during cross-border emergencies. S-HELP seeks to provide a tool-set that supports rapid and effective decision-making across all stages of the emergency management lifecycle (i.e. mitigation, preparedness, response, and recovery). To address the challenges associated with multi-agency emergency management, a holistic framed approach to healthcare preparedness, response, and recovery is proposed. This holistic framework has been created to guide the development of the S-HELP solution. The framework integrates a number of components important in the phased iterative development of an emergency management decision support system, such as, interoperability standards, risk communication, spatial data management, agile development, healthcare responder training, and scenario development for system evaluation.