Understanding the transmission dynamics of infectious diseases is crucial for designing effective public health interventions. The 2022 Ebola virus disease (EVD) outbreak in Uganda, caused by the Sudan virus strain, provided an opportunity to assess how targeted measures could mitigate the spread of a highly fatal virus. With no approved vaccines available, policymakers implemented lockdowns in the hardest-hit districts, Mubende and Kassanda, to curb transmission. This study aims to provide valuable insights into the effectiveness of such interventions using a data-driven modeling approach.

Despite the rapid response, uncertainty remained regarding the impact of lockdowns on disease progression. Early interventions can sometimes lead to unintended consequences, such as increased transmission due to delayed adherence or higher case detection. Moreover, previous models often overlooked intra-household transmission, a key factor in early outbreak spread. Addressing these gaps is critical for refining epidemic control strategies in resource-limited settings.

To bridge this gap, we employed a Community-Household SEIR model with time-varying transmission rates, capturing outbreak dynamics across three phases: pre-lockdown, early lockdown (1–3 weeks), and extended lockdown (4–6 weeks). Our findings reveal that sustained interventions significantly reduce transmission, emphasizing the importance of prolonged and well-implemented measures. By integrating mathematical modeling with empirical data, this study provides a robust framework for guiding future epidemic responses and strengthening public health preparedness.