| Popis: |
The second largest Ebola Virus Disease outbreak in history was declared on August 1, 2018, by the Ministry of Health of The Democratic Republic of Congo. This epidemic affected the eastern most part of DRC, spanning the provinces of North Kivu, South Kivu, and Ituri. Lasting over 15 months, the outbreak resulted in 3470 cases (probable and confirmed) and 2287 deaths (CDC 2019). In collaboration with the University of Kinshasa, we obtained individual-level data spanning almost the entirety of the epidemic, presenting us with the unique opportunity of analyzing long-term Ebola epidemic dynamics and the effect of public health intervention. Exploratory analysis uncovered that this epidemic comprised many smaller, more isolated outbreaks, with pronounced spatial-temporal patterns. To reflect this, the data was split into three temporal segments. A statistical model for the data analysis was based on the new methodology known as Dynamic Survival Analysis (DSA), derived from the general stochastic model of spread of infection across a network of interconnected individuals (nodes). A key feature of the statistical model is that, unlike general stochastic network models, it does not require knowledge of the susceptible population size, the disease prevalence in the community, or the epidemic curve shape. The DSA-based model was applied to all three segments of the full epidemic, attempting to combine information across the three distinct waves of infections. The fitting of the model was based on individual data of infection and recovery times in each wave, and the estimated parameter values suggested that the epidemic was brought to an end because of increased effort in Ebola cases identification and prompt isolation. According to our findings, the time from infection onset to hospitalization was significantly decreased over the three waves, helping to contain the spread of disease. |
