ETIDIOH - NEW

Summary Background DR Congo has the highest global burden of mpox , a disease caused by infection with the monkeypox virus . The incidence has risen since 1980, but recent analyses of epidemiological trends are lacking. We aimed to describe trends in suspected and confirmed mpox cases in DR Congo using epidemiological and laboratory mpox surveillance data collected from 2010 to 2023, and provide insights that can better inform the targeting and monitoring of control strategies. Methods We analysed aggregated national epidemiological surveillance data and individual-level laboratory data from 2010 to 2023. We calculated incidence based on suspected cases, case-fatality ratios, and percentage of laboratory-confirmed cases and assessed geospatial trends. Demographic and seasonal trends were investigated using generalised additive mixed models. Findings Between Jan 1, 2010, and Dec 31, 2023, a total of 60 967 suspected cases and 1798 suspected deaths from mpox were reported in DR Congo ( c...

Abstract We present a stochastic metapopulation transmission model that simulates the spread of H5N1 avian influenza through individual dairy cows in 35,974 dairy herds in the continental United States . Transmission is enabled through the movement of cattle between herds , as indicated from Interstate Certificates of Veterinary Inspection (ICVI) data. We estimate the rates of under-reporting by state and present the anticipated rates of positivity for cattle tested at the point of exportation over time. We investigate the likely impact of intervention methods to date on the underlying epidemiological dynamics, demonstrating that current interventions have had insufficient impact , preventing only a mean 175.2 reported outbreaks. Our model predicts that the majority of the disease burden is, as of January 2025, concentrated within West Coast states , due to the network of cattle movements and distribution of the respective dairy populations . We quantify the extent of uncertainty in th...

Abstract The generation time , representing the interval between infections in primary and secondary cases , is essential for understanding and predicting the transmission dynamics of seasonal influenza , including the real-time effective reproduction number (Rt). However, comprehensive generation time estimates for seasonal influenza, especially since the 2009 influenza pandemic, are lacking. We estimated the generation time utilizing data from a 7-site case-ascertained household study in the United States over two influenza seasons, 2021/2022 and 2022/2023. More than 200 individuals who tested positive for influenza and their household contacts were enrolled within 7 days of the first illness in the household. All participants were prospectively followed for 10 days, completing daily symptom diaries and collecting nasal swabs, which were then tested for influenza via RT-PCR. We analyzed these data by modifying a previously published Bayesian data augmentation approach that imputes in...