PLoS Currents: Outbreaks
http://currents.plos.org/outbreaks/
(Accessed 4 June 2016)

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Research Article
Maintaining Maternal and Child Health Services During the Ebola Outbreak: Experience from Pujehun, Sierra Leone
June 2, 2016 ·
Background: During the Ebola outbreak the overall confidence of the population in the national health system declined in Sierra Leone, with a reduction in the use of health services. The objective of this study is to provide information on understanding of how Ebola impacted maternal and child health services in Sierra Leone. Data come from an operational setting which is representative of the communities affected by the outbreak.
Methods: By integrating hospital registers and contact tracing form data with healthcare workers and local population interviews, the transmission chain was reconstructed. Data on the utilization of maternal and neonatal health services were collected from the local district’s Health Management Information System. The main measures put in place to control the Ebola epidemic were: the organization of a rapid response to the crisis by the local health authorities; triage, contact tracing and quarantine; isolation, clinical management and safe burials; training and community sensitization.
Results: A total of 49 case patients were registered between July and November 2014 in the Pujehun district. Hospitalization rate was 89%. Overall, 74.3% of transmission events occurred between members of the same family, 17.9% in the community and 7.7% in hospital. The mean number of contacts investigated per case raised from 11.5 in July to 25 in September 2014. The 2014 admission trend in the pediatric ward shows a decrease after beginning of June: the reduction was almost significant in the period July-December (p 0.05). The admission in the maternity ward showed no statistical differences in comparison with the previous year (p 0.07). Also the number of deliveries appeared to be similar to the previous year, without significant variations (p 0.41).
Conclusion: The Ebola outbreak reduced the number of patients at hospital level in Pujehun district. However, the activities undertaken to manage Ebola, reduced the spread of infection and the impact of the disease in mothers and children. A number of reasons which may explain these results are presented and discussed.

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Travel Volume to the United States from Countries and U.S. Territories with Local Zika Virus Transmission
May 31, 2016 · Research Article
Introduction: Air, land, and sea transportation can facilitate rapid spread of infectious diseases. In May 2015 the Pan American Health Organization (PAHO) issued an alert regarding the first confirmed Zika virus infection in Brazil. As of March 8, 2016, the U.S. Centers for Disease Control and Prevention (CDC) had issued travel notices for 33 countries and 3 U.S. territories with local Zika virus transmission.
Methods: Using data from five separate datasets from 2014 and 2015, we estimated the annual number of passenger journeys by air and land border crossings to the United States from the 33 countries and 3 U.S. territories listed in the CDC’s Zika travel notices as of March 8, 2016. We also estimated the annual number of passenger journeys originating in and returning to the United States (primarily on cruises) with visits to seaports in areas with local Zika virus transmission. Because of the adverse pregnancy and birth outcomes that have been associated with Zika virus disease, the number of passenger journeys completed by women of childbearing age and pregnant women was also estimated.
Results: An estimated 216.3 million passenger journeys by air, land, and sea are made annually to the United States from areas with local Zika virus transmission (as of March 8). The destination states with the largest numbers of arrivals were Texas (by land) and Florida (by air and sea). An estimated 51.7 million passenger journeys were made by women of childbearing age and an estimated 2.3 million were made by pregnant women.
Conclusion: Travel volume analyses provide important information that can be used to effectively target public health interventions as well as direct public health resources and efforts at local, regional, and country-specific levels.

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Using Phenomenological Models to Characterize Transmissibility and Forecast Patterns and Final Burden of Zika Epidemics
May 31, 2016 · Research Article
Background: The World Health Organization declared the ongoing Zika virus (ZIKV) epidemic in the Americas a Public Health Emergency of International Concern on February 1, 2016. ZIKV disease in humans is characterized by a “dengue-like” syndrome including febrile illness and rash. However, ZIKV infection in early pregnancy has been associated with severe birth defects, including microcephaly and other developmental issues. Mechanistic models of disease transmission can be used to forecast trajectories and likely disease burden but are currently hampered by substantial uncertainty on the epidemiology of the disease (e.g., the role of asymptomatic transmission, generation interval, incubation period, and key drivers). When insight is limited, phenomenological models provide a starting point for estimation of key transmission parameters, such as the reproduction number, and forecasts of epidemic impact.
Methods: We obtained daily counts of suspected Zika cases by date of symptoms onset from the Secretary of Health of Antioquia, Colombia during January-April 2016. We calibrated the generalized Richards model, a phenomenological model that accommodates a variety of early exponential and sub-exponential growth kinetics, against the early epidemic trajectory and generated predictions of epidemic size. The reproduction number was estimated by applying the renewal equation to incident cases simulated from the fitted generalized-growth model and assuming gamma or exponentially-distributed generation intervals derived from the literature. We estimated the reproduction number for an increasing duration of the epidemic growth phase.
Results: The reproduction number rapidly declined from 10.3 (95% CI: 8.3, 12.4) in the first disease generation to 2.2 (95% CI: 1.9, 2.8) in the second disease generation, assuming a gamma-distributed generation interval with the mean of 14 days and standard deviation of 2 days. The generalized-Richards model outperformed the logistic growth model and provided forecasts within 22% of the actual epidemic size based on an assessment 30 days into the epidemic, with the epidemic peaking on day 36.
Conclusion: Phenomenological models represent promising tools to generate early forecasts of epidemic impact particularly in the context of substantial uncertainty in epidemiological parameters. Our findings underscore the need to treat the reproduction number as a dynamic quantity even during the early growth phase, and emphasize the sensitivity of reproduction number estimates to assumptions on the generation interval distribution.