703 research outputs found
Choices in vaccine trial design in epidemics of emerging infections.
No full textIn a Policy Forum, Marc Lipsitch and colleagues discuss trial design issues in infectious disease outbreaks
Center for Forecasting & Outbreak Analytics (CFA) 101 for Industry Event
No full textThe Center for Forecasting & Outbreak Analytics (CFA) hosted this event to connect with industry leaders and share information about the new center. The agenda for the day includes a keynote speech from Dr. Nirav Shah, presentations by CFA leadership, and panels of industry leaders focused on technology relevant to disease forecasting, modeling, and outbreak analytics.cfa-101-industry-final-slides-508.pdfOpening Remarks \u2013 Alison Kelly -- Introduction to CFA: Purpose, Mission, Vision \u2013 Dylan George -- Center for Forecasting and Outbreak Analytics Keynote Speaker: Nirav Shah, -- Predict Division Overview \u2013 Marc Lipsitch -- Inform Division Overview \u2013 Caitlin Rivers -- Technology & Innovation Division Overview \u2013 Rebecca Kahn, CDC/CFA -- Industry Panel: Data, Analytics, and Technology Requirements to Transform Health Emergency Response / Michelle Holko, Ethan Berke, Caitlin Rivers, Dylan George (moderator).20221136
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Erratum for Lipsitch and Inglesby, Moratorium on Research Intended To Create Novel Potential Pandemic Pathogens
No full textVersion of Recor
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Absolute humidity and the seasonal onset of influenza in the continental United States
No full textCorrections
18 Mar 2010: Shaman J, Pitzer VE, Viboud C, Grenfell BT, Lipsitch M (2010) Correction: Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States. PLOS Biology 8(3): 10.1371/annotation/35686514-b7a9-4f65-9663-7baefc0d63c0.
15 Mar 2010: Shaman J, Pitzer VE, Viboud C, Grenfell BT, Lipsitch M (2010) Correction: Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States. PLOS Biology 8(3): 10.1371/annotation/9ddc5251-72a1-4eba-ae35-9ab04488527b.Much of the observed wintertime increase of mortality in temperate regions is attributed to seasonal influenza. A recent reanalysis of laboratory experiments indicates that absolute humidity strongly modulates the airborne survival and transmission of the influenza virus. Here, we extend these findings to the human population level, showing that the onset of increased wintertime influenza-related mortality in the United States is associated with anomalously low absolute humidity levels during the prior weeks. We then use an epidemiological model, in which observed absolute humidity conditions temper influenza transmission rates, to successfully simulate the seasonal cycle of observed influenza-related mortality. The model results indicate that direct modulation of influenza transmissibility by absolute humidity alone is sufficient to produce this observed seasonality. These findings provide epidemiological support for the hypothesis that absolute humidity drives seasonal variations of influenza transmission in temperate regions
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Infectious Disease Modeling: Enhancing Epidemic Preparedness and Response
No full textRecent outbreaks of Ebola, Zika, and COVID-19, among others, have shown how infectious diseases can decimate economies and destroy lives. Infectious disease models are important tools for preparing for, preventing, and responding to such epidemics. Here, we use infectious disease modeling to analyze past outbreaks, prepare for future outbreaks, and respond to ongoing outbreaks, with the goal of informing public health response.
We first analyze past Ebola and cholera outbreaks and build a simulation model to understand the role the incubation period, the time between exposure and symptom onset, has on epidemic trajectory. We find that diseases with longer incubation periods, such as Ebola, where infected individuals can travel further before becoming infectious, result in more long-distance sparking events and less predictable disease trajectories, as compared to the more predictable wave-like spread of diseases with shorter incubation periods, such as cholera. Second, we assess if augmenting classical randomized controlled trials of vaccines with pathogen sequence and contact tracing data can permit these trials to estimate vaccine efficacy against infectiousness, or the reduction in onward transmission from a vaccinated person who is infected compared to an unvaccinated infected person. Through simulations of a transmission model and a vaccine trial, we find that these data sources enhance identifiability of this key measure of vaccine efficacy. Finally, we simulate studies of SARS-CoV-2 seroprotection. We find that in studies assessing whether seropositivity confers protection against future infection, time varying epidemic dynamics can cause confounding; it is therefore necessary to adjust for geographic location and time of enrollment in order to reduce bias. These methods and findings demonstrate how infectious disease modeling can be used to enhance epidemic preparedness and response
Emerg Infect Dis
No full textThe need to stem the growing problem of antimicrobial resistance has prompted multiple, sometimes conflicting, calls for changes in the use of antimicrobial agents. One source of disagreement concerns the major mechanisms by which antibiotics select resistant strains. For infections like tuberculosis, in which resistance can emerge in treated hosts through mutation, prevention of antimicrobial resistance in individual hosts is a primary method of preventing the spread of resistant organisms in the community. By contrast, for many other important resistant pathogens, such as penicillin-resistant Streptococcus pneumoniae, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococcus faecium resistance is mediated by the acquisition of genes or gene fragments by horizontal transfer; resistance in the treated host is a relatively rare event. For these organisms, indirect, population-level mechanisms of selection account for the increase in the prevalence of resistance. These mechanisms can operate even when treatment has a modest, or even negative, effect on an individual host's colonization with resistant organisms
Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
No full textAuteurs : Stephen M. Kissler, Christine Tedijanto, Edward Goldstein, Yonatan H. Grad, Marc Lipsitch et al. Production : revue Science. Revue scientifique généraliste américaine publiée par l'Association américaine pour l'avancement des sciences (AAAS). Diffusion : site de la revue Science. Date : 14 avril 2020 Abstract. It is urgent to understand the future of severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) transmission. We used estimates of seasonality, immunity, an..
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Understanding Epidemiologic Risks for Infectious Disease Control
No full textAs of April 2020, the coronavirus disease 2019 (COVID-19) pandemic has already irreversibly changed our perception of the field of infectious diseases. The first two chapters in this thesis were completed in the pre-2020 era, when we focused on developing tools to inform tuberculosis (TB) control programs in high-burden countries. The last chapter is our quick response to the emerging COVID-19 pandemic, in which we described the disease burden on healthcare resources in cities in China and explored its implication for cities in the United States.
One common theme in all three chapters is our focus on epidemiologic risks. In Lima, Peru, can we predict the risk of disease progression among household contacts of TB patients to better their clinical management (Chapter 1)? In India, how can we use information about the distribution of TB risk factors to identify populations who were missed by disease surveillance systems (Chapter 2)? And finally, how to translate experience from one city to another during a pandemic, when the underlying populations have potentially different risk profiles (Chapter 3)?
While TB continues to plague our most vulnerable population, knowledge about risk and risk factors for the COVID-19 will start to accumulate. The enclosed three chapters are our exploration of how epidemiologic risks could help with infectious disease control programs.Epidemiolog
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Spatial Epidemiology of Yaws and Tuberculosis and Implications for Public Health Interventions
No full textDecision making about what role, if any, spatially targeted interventions should play in infectious disease elimination programs is complex and depends on a range of considerations, including the underlying spatial epidemiology of the disease. This dissertation investigates the spatial epidemiology of yaws and tuberculosis. It also explores the implications of spatial epidemiology on the relative merits of a spatially targeted approach to yaws eradication versus a population-wide approach. The first chapter analyzes patterns of spatial-temporal clustering of yaws on Lihir Island, Papua New Guinea. We found that clusters of yaws typically transcend village boundaries and we argue that villages may be epidemiologically linked to a degree such that mass drug administration (MDA) may be more effectively implemented at a spatial scale larger than the individual village. The second chapter uses a stochastic compartmental model of yaws transmission to investigate how total targeted treatment (TTT) performs compared to MDA in different settings. We found that the performance of TTT is improved when there is little mixing between subpopulations and when there is spatial heterogeneity in transmissibility, but even in these settings, our model suggests that MDA can achieve the same result as TTT more quickly and probably at lower cost. The third chapter uses tuberculosis whole-genome sequence data from Lima, Peru to explore the spatial scale at which transmission occurs. We found that transmission risk was highly elevated at short spatial distances but that long-distance transmission events occur, too. Taken together, these 3 studies illustrate a range of tools that can be used to better understand the dynamics of infectious diseases in space and to understand the implications of spatial epidemiology for the design of public health programs.Epidemiolog
Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China
No full textAuteurs : Joseph T. Wu, Kathy Leung, Mary Bushman, Nishant Kishore, Rene Niehus, Pablo M. de Salazar, Benjamin J. Cowling, Marc Lipsitch & Gabriel M. Leung Production : Nature Medicine, revue scientifique mensuelle à comité de lecture spécialisée dans tous les domaines concernant la recherche biomédicale. Diffusion : site de la revue Nature Medicine. Date : 19 mars 2020. As of 29 February 2020 there were 79,394 confirmed cases and 2,838 deaths from COVID-19 in mainland China. Of th..
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