Suchergebnisse

Background The 2018–2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces in the Democratic Republic of the Congo (DRC) is the largest ever recorded in the DRC. It has been declared a Public Health Emergency of International Concern. The outbreak emerged in a region of chronic conflict and insecurity, and directed attacks against health care workers may have interfered with disease response activities. Our study characterizes and quantifies the broader conflict dynamics over the course of the outbreak by pairing epidemiological and all available spatial conflict data. Methods We build a set of conflict variables by mapping the spatial locations of all conflict events and their associated deaths in each of the affected health zones in North Kivu and Ituri, eastern DRC, before and during the outbreak. Using these data, we compare patterns of conflict before and during the outbreak in affected health zones and those not affected. We then test whether conflict is correlated with increased EVD transmission at the health zone level. Findings The incidence of conflict events per capita is ~ 600 times more likely in Ituri and North Kivu than for the rest of the DRC. We identified 15 time periods of substantial uninterrupted transmission across 11 health zones and a total of 120 bi-weeks. We do not find significant short-term associations between the bi-week reproduction numbers and the number of conflicts. However, we do find that the incidence of conflict per capita was correlated with the incidence of EVD per capita at the health zone level for the entire outbreak (Pearson's r = 0.33, 95% CI 0.05–0.57). In the two provinces, the monthly number of conflict events also increased by a factor of 2.7 in Ebola-affected health zones (p value Conclusion We characterized the association between variables documenting broad conflict levels and EVD transmission. Such assessment is important to understand if and how such conflict variables could be used to inform the outbreak response. We found that while these ...

Background: Since late 2015, an epidemic of Yellow fever virus (YFV) has caused over 6,554 suspected cases in Angola and the Democratic Republic of Congo, including 387 deaths. We sought to understand the spatial spread of this YFV outbreak to optimise the use of the limited available vaccine stock. Methods: We jointly analysed datasets describing the epidemic of YFV, vector suitability, human demography and mobility in Central Africa in order to understand and predict the expansion of YFV. We used a standard logistic model to infer the district YFV infection risk over the course of the epidemic in the region. Findings: Early spread of YFV was characterized by fast exponential growth (doubling time of 5-7 days) and fast spatial expansion (49 districts reporting cases after only three months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (0·52, 95% CI: 0·34, 0·66). The further away locations were from Luanda the later the invasion date (0·60, 95% CI: 0·52, 0·66). Districts with higher population densities also featured higher risks of sustained transmission. A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others. If at the start of the epidemic sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Interpretation: Our findings reveal the contributions of ecological and demographic factors to the ongoing spread of the YFV outbreak and provide estimates for where vaccines may be prioritised, although other constraints (e.g. vaccine supply and delivery) need to be accounted for before such insights may be translated into policy.