Early transmission dynamics of Ebola virus disease (EVD), West Africa, March to August 2014

Background  The United States was the second country to have a major outbreak of novel influenza A/H1N1 in what has become a new pandemic. Appropriate public health responses to this pandemic depend in part on early estimates of key epidemiological parameters of the virus in defined populations. Methods  We use a likelihood‐based method to estimate the basic reproductive number (R 0) and serial interval using individual level U.S. data from the Centers for Disease Control and Prevention (CDC). We adjust for missing dates of illness and changes in case ascertainment. Using prior estimates for the serial interval we also estimate the reproductive number only. Results  Using the raw CDC data, we estimate the reproductive number to be between 2·2 and 2·3 and the mean of the serial interval (μ) between 2·5 and 2·6 days. After adjustment for increased case ascertainment our estimates change to 1·7 to 1·8 for R 0 and 2·2 to 2·3 days for μ. In a sensitivity analysis making use of previous estimates of the mean of the serial interval, both for this epidemic (μ = 1·91 days) and for seasonal influenza (μ = 3·6 days), we estimate the reproductive number at 1·5 to 3·1. Conclusions  With adjustments for data imperfections we obtain useful estimates of key epidemiological parameters for the current influenza H1N1 outbreak in the United States. Estimates that adjust for suspected increases in reporting suggest that substantial reductions in the spread of this epidemic may be achievable with aggressive control measures, while sensitivity analyses suggest the possibility that even such measures would have limited effect in reducing total attack rates.

We present a method for the simultaneous estimation of the basic reproductive number, R(0), and the serial interval for infectious disease epidemics, using readily available surveillance data. These estimates can be obtained in real time to inform an appropriate public health response to the outbreak. We show how this methodology, in its most simple case, is related to a branching process and describe similarities between the two that allow us to draw parallels which enable us to understand some of the theoretical properties of our estimators. We provide simulation results that illustrate the efficacy of the method for estimating R(0) and the serial interval in real time. Finally, we implement our proposed method with data from three infectious disease outbreaks.

An outbreak of Ebola disease was reported from Gulu district, Uganda, on 8 October 2000. The outbreak was characterized by fever and haemorrhagic manifestations, and affected health workers and the general population of Rwot-Obillo, a village 14 km north of Gulu town. Later, the outbreak spread to other parts of the country including Mbarara and Masindi districts. Response measures included surveillance, community mobilization, case and logistics management. Three coordination committees were formed: National Task Force (NTF), a District Task Force (DTF) and an Interministerial Task Force (IMTF). The NTF and DTF were responsible for coordination and follow-up of implementation of activities at the national and district levels, respectively, while the IMTF provided political direction and handled sensitive issues related to stigma, trade, tourism and international relations. The international response was coordinated by the World Health Organization (WHO) under the umbrella organization of the Global Outbreak and Alert Response Network. A WHO/CDC case definition for Ebola was adapted and used to capture four categories of cases, namely, the 'alert', 'suspected', 'probable' and 'confirmed cases'. Guidelines for identification and management of cases were developed and disseminated to all persons responsible for surveillance, case management, contact tracing and Information Education Communication (IEC). For the duration of the epidemic that lasted up to 16 January 2001, a total of 425 cases with 224 deaths were reported countrywide. The case fatality rate was 53%. The attack rate (AR) was highest in women. The average AR for Gulu district was 12.6 cases/10 000 inhabitants when the contacts of all cases were considered and was 4.5 cases/10 000 if limited only to contacts of laboratory confirmed cases. The secondary AR was 2.5% when nearly 5000 contacts were followed up for 21 days. Uganda was finally declared Ebola free on 27 February 2001, 42 days after the last case was reported. The Government's role in coordination of both local and international support was vital. The NTF and the corresponding district committees harmonized implementation of a mutually agreed programme. Community mobilization using community-based resource persons and political organs, such as Members of Parliament was effective in getting information to the public. This was critical in controlling the epidemic. Past experience in epidemic management has shown that in the absence of regular provision of information to the public, there are bound to be deleterious rumours. Consequently rumour was managed by frank and open discussion of the epidemic, providing daily updates, fact sheets and press releases. Information was regularly disseminated to communities through mass media and press conferences. Thus all levels of the community spontaneously demonstrated solidarity and response to public health interventions. Even in areas of relative insecurity, rebel abductions diminished considerably.