During Ebola and Marburg outbreaks, treatment centers are essential for patient care and controlling transmission. While clinical care advancements have been well-documented, the design of these centers has been less explored. This study addresses this gap by analyzing technical drawings of 48 treatment centers constructed between 2014 and 2023, using a reverse-engineering approach. The findings highlight a shift toward smaller, more manageable centers, with improved privacy and infection control features. This review offers a framework for the future development of treatment center designs to enhance outbreak management. Key contributions include the identification of trends in center size and layout, providing a foundation for future design standards that can be applied in managing infectious disease outbreaks. The study emphasizes the need for continuous adaptation in treatment center design to meet outbreak demands and calls for future research to develop indicators that measure the impact of design on health outcomes and patient experiences.

During Lassa fever outbreaks, Treatment Centres (TCs) are critical for patient care and transmission control, yet their design remains underexplored. The study analyses three TC in Nigeria, using a reverse-engineering approach. Findings reveal major differences in capacity, zoning, and service integration, with implications for infection control, staff safety, and inclusivity. Recurring layout trends and critical gaps are identified. A set of spatial indicators is proposed and cross-case results are translated into design principles for LF centres. The work offers a framework for developing design standards to strengthen outbreak management, and highlights the need for adaptable facilities and future research to define indicators linking design with health outcomes and patient experience.

Health emergencies linked to epidemic outbreaks in vulnerable contexts require rapid and effective architectural responses. Natural ventilation represents a key strategy for infection control and indoor comfort, yet traditional airflow calculation methods require climatic and construction data, which are often unavailable or incomplete. In emergency situations, this results in the inapplicability of such methods and creates a critical information gap. This study proposes a simplified equation to estimate airflow rate (Q) in single-sided and cross-ventilation configurations, based on openable surface area and a reference Effective Window Air Speed (EWAS). Two infectious disease treatment centers were modeled and simulated using EnergyPlus (E+) under five climatic scenarios—two real and three hypothetical—characterized by low, medium, and high wind exposure. Simulation results were compared with existing formulas and with the proposed simplified equation. Although the simplified model introduces a margin of error compared with dynamic simulations, it provides meaningful estimates, with mean deviations typically in the 20–35% range, lower in single-sided conditions and higher for cross-ventilation under medium-to-high wind exposure. The study demonstrates that an ultra-simplified approach can serve as a support tool for the design of temporary healthcare facilities in resource-limited contexts, where rapidity and data accessibility are essential.