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Browsing by Author "Rivers, Caitlin"

Now showing 1 - 8 of 8
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    2014 OA Week Panel
    Rivers, Caitlin; Matheis, Christian; Lazar, Iuliana M.; Sutherland, Michelle; Tideman, Nicolaus; Wynne, Randolph H. (2014-10-31)
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    Accuracy of epidemiological inferences based on publicly available information: retrospective comparative analysis of line lists of human cases infected with influenza A(H7N9) in China
    Lau, Eric H. Y.; Zheng, Jiandong; Tsang, Tim K.; Liao, Qiaohong; Lewis, Bryan L.; Brownstein, John S.; Sanders, Sharon; Wong, Jessica Y.; Mekaru, Sumiko R.; Rivers, Caitlin; Wu, Peng; Jiang, Hui; Li, Yu; Yu, Jianxing; Zhang, Qian; Chang, Zhaorui; Liu, Fengfeng; Peng, Zhibin; Leung, Gabriel M.; Feng, Luzhao; Cowling, Benjamin J.; Yu, Hongjie (2014-05-28)
    Background Appropriate public health responses to infectious disease threats should be based on best-available evidence, which requires timely reliable data for appropriate analysis. During the early stages of epidemics, analysis of ‘line lists’ with detailed information on laboratory-confirmed cases can provide important insights into the epidemiology of a specific disease. The objective of the present study was to investigate the extent to which reliable epidemiologic inferences could be made from publicly-available epidemiologic data of human infection with influenza A(H7N9) virus. Methods We collated and compared six different line lists of laboratory-confirmed human cases of influenza A(H7N9) virus infection in the 2013 outbreak in China, including the official line list constructed by the Chinese Center for Disease Control and Prevention plus five other line lists by HealthMap, Virginia Tech, Bloomberg News, the University of Hong Kong and FluTrackers, based on publicly-available information. We characterized clinical severity and transmissibility of the outbreak, using line lists available at specific dates to estimate epidemiologic parameters, to replicate real-time inferences on the hospitalization fatality risk, and the impact of live poultry market closure. Results Demographic information was mostly complete (less than 10% missing for all variables) in different line lists, but there were more missing data on dates of hospitalization, discharge and health status (more than 10% missing for each variable). The estimated onset to hospitalization distributions were similar (median ranged from 4.6 to 5.6 days) for all line lists. Hospital fatality risk was consistently around 20% in the early phase of the epidemic for all line lists and approached the final estimate of 35% afterwards for the official line list only. Most of the line lists estimated >90% reduction in incidence rates after live poultry market closures in Shanghai, Nanjing and Hangzhou. Conclusions We demonstrated that analysis of publicly-available data on H7N9 permitted reliable assessment of transmissibility and geographical dispersion, while assessment of clinical severity was less straightforward. Our results highlight the potential value in constructing a minimum dataset with standardized format and definition, and regular updates of patient status. Such an approach could be particularly useful for diseases that spread across multiple countries.
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    Estimating Human Cases of Avian Influenza A(H7N9) from Poultry Exposure
    Rivers, Caitlin; Lum, Kristian; Lewis, Bryan L.; Eubank, Stephen (PLOS, 2013-05-15)
    In March 2013 an outbreak of avian influenza A(H7N9) was first recognized in China. To date there have been 130 cases in human, 47% of which are in men over the age of 55.The influenza strain is a novel subtype not seen before in humans; little is known about zoonotic transmission of the virus, but it is hypothesized that contact with poultry in live bird markets may be a source of exposure. The purpose of this study is to estimate the transmissibility of the virus from poultry to humans by estimating the amount of time shoppers, farmers, and live bird market retailers spend exposed to poultry each day. Results suggest that increased risk among older men is not due to greater exposure time at live bird markets.
  • Innovation networks and social contagion in East Africa
    Gunter, J.; Rivers, Caitlin; Eubank, Stephen; Moore, Keith M.; Kuhlman, C.; Lamb, Jennifer Nicole; Norton, James B.; Omondi, Emmanuel C.; Ojok, R. L.; Sikuku, Dominic Ngosia; Ashilenje, Dennis S.; Odera, J. (2012)
    This study seeks to understand the pathway by which new technology and the associated knowledge passes through community networks in western Kenya and eastern Uganda. Previous research in the region emphasizes the importance of community support to promote widespread adoption of Conservation Agriculture practices. We will simulate complex contagions of information in these networks using the simulation platform EpiSimdemics. This work complements and expands on the growing body of research that uses network analysis to study the effects of network structure and social contagion on complex health and social systems.
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    Modeling Emerging Infectious Diseases for Public Health Decision Support
    Rivers, Caitlin (Virginia Tech, 2015-05-05)
    Emerging infectious diseases (EID) pose a serious threat to global public health. Computational epidemiology is a nascent subfield of public health that can provide insight into an outbreak in advance of traditional methodologies. Research in this dissertation will use fuse nontraditional, publicly available data sources with more traditional epidemiological data to build and parameterize models of emerging infectious diseases. These methods will be applied to avian influenza A (H7N9), Middle Eastern Respiratory Syndrome Coronavirus (MERS-CoV), and Ebola virus disease (EVD) outbreaks. This effort will provide quantitative, evidenced-based guidance for policymakers and public health responders to augment public health operations.
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    Modeling the Ebola Outbreak in West Africa, August 4th 2014 update
    Lewis, Bryan L.; Rivers, Caitlin; Eubank, Stephen; Marathe, Marathe; Barrett, Christopher L. (2014)
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    Opinion: Mathematical models: A key tool for outbreak response
    Lofgren, Eric T.; Halloran, M. Elizabeth; Rivers, Caitlin; Drake, John M.; Porco, Travis C.; Lewis, Bryan L.; Yang, Wan; Vespignani, Alessandro; Shaman, Jeffrey; Eisenberg, Joseph N.S.; Eisenberg, Marisa C.; Marathe, Madhav V.; Scarpino, Samuel V.; Alexander, Kathleen A.; Meza, Rafael; Ferrari, Matthew J.; Hyman, James M.; Meyers, Lauren Ancel; Eubank, Stephen (NAS, 2015-01-13)
    The 2014 outbreak of Ebola in West Africa is unprecedented in its size and geographic range, and demands swift, effective action from the international community. Understanding the dynamics and spread of Ebola is critical for directing interventions and extinguishing the epidemic; however, observational studies of local conditions have been incomplete and limited by the urgent need to direct resources to patient care. Mathematical and computational models can help address this deficiency through work with sparse observations, inference on missing data, and incorporation of the latest information. These models can clarify how the disease is spreading and provide timely guidance to policymakers. However, the use of models in public health often meets resistance (1), from doubts in peer review about the utility of such analyses to public skepticism that models can contribute when the means to control an epidemic are already known (2). Even when they are discussed in a positive light, models are often portrayed as arcane and largely inaccessible thought experiments (3). However, the role of models is crucial: they can be used to quantify the effect of mitigation efforts, provide guidance on the scale of interventions required to achieve containment, and identify factors that fundamentally influence the course of an outbreak.
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    What Factors Might Have Led to the Emergence of Ebola in West Africa?
    Alexander, Kathleen A.; Sanderson, Claire E.; Marathe, Madhav V.; Lewis, Bryan L.; Rivers, Caitlin; Lofgren, Eric T.; Eubank, Stephen; Eisenberg, Marisa C.; Drake, John M.; Shaman, Jeffrey (PLOS, 2015-06-04)
    An Ebola outbreak of unprecedented scope emerged in West Africa in December 2013 and presently continues unabated in the countries of Guinea, Sierra Leone, and Liberia. Ebola is not new to Africa, and outbreaks have been confirmed as far back as 1976. The current West African Ebola outbreak is the largest ever recorded and differs dramatically from prior outbreaks in its duration, number of people affected, and geographic extent. The emergence of this deadly disease in West Africa invites many questions, foremost among these: why now, and why in West Africa? Here, we review the sociological, ecological, and environmental drivers that might have influenced the emergence of Ebola in this region of Africa and its spread throughout the region. Containment of the West African Ebola outbreak is the most pressing, immediate need. A comprehensive assessment of the drivers of Ebola emergence and sustained human-to-human transmission is also needed in order to prepare other countries for importation or emergence of this disease. Such assessment includes identification of country-level protocols and interagency policies for outbreak detection and rapid response, increased understanding of cultural and traditional risk factors within and between nations, delivery of culturally embedded public health education, and regional coordination and collaboration, particularly with governments and health ministries throughout Africa. Public health education is also urgently needed in countries outside of Africa in order to ensure that risk is properly understood and public concerns do not escalate unnecessarily. To prevent future outbreaks, coordinated, multiscale, early warning systems should be developed that make full use of these integrated assessments, partner with local communities in high-risk areas, and provide clearly defined response recommendations specific to the needs of each community.