Ottar N. Bjørnstad
PROFESSOR of Entomology and Biology | Pennsylvania State University
University Park, PA, UNITED STATES
Ottar N. Bjørnstad is an expert in ecology, infectious disease dynamics, and theoretical and computational biology.
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Industry Expertise (2)
Health and Wellness
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Areas of Expertise (4)
Theoretical and Computational Biology
Infectious Disease Dynamics
Ecology
Molecular, Cellular and Integrative Biosciences
Biography
Ottar N. Bjørnstad is a theoretical ecologist working as a professor in the Departments of Entomology and Biology. His main interests are population ecology and population dynamics with particular emphasis on mathematical and computational aspects. He is also an adjunct professor in the Department of Statistics, and carry out research in statistical ecology and in methods for analyzing spatiotemporal data.
Education (3)
University of Oslo: Ph.D., Ecology 1997
University of Oslo: M.S., Zoology 1993
University of Oslo: B.A., Biology 1991
Links (2)
Articles (5)
Essential information: Uncertainty and optimal control of Ebola outbreaks
Proceedings of the National Academy of Sciences
Shou-Li Li, Ottar N Bjørnstad, Matthew J Ferrari, Riley Mummah, Michael C Runge, Christopher J Fonnesbeck, Michael J Tildesley, William JM Probert, Katriona Shea
2017 Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.
The geography of spatial synchrony
Ecology Letters
Jonathan A Walter, Lawrence W Sheppard, Thomas L Anderson, Jude H Kastens, Ottar N Bjørnstad, Andrew M Liebhold, Daniel C Reuman
2017 Spatial synchrony, defined as correlated temporal fluctuations among populations, is a fundamental feature of population dynamics, but many aspects of synchrony remain poorly understood. Few studies have examined detailed geographical patterns of synchrony; instead most focus on how synchrony declines with increasing linear distance between locations, making the simplifying assumption that distance decay is isotropic. By synthesising and extending prior work, we show how geography of synchrony, a term which we use to refer to detailed spatial variation in patterns of synchrony, can be leveraged to understand ecological processes including identification of drivers of synchrony, a long-standing challenge. We focus on three main objectives: (1) showing conceptually and theoretically four mechanisms that can generate geographies of synchrony; (2) documenting complex and pronounced geographies of synchrony in two important study systems; and (3) demonstrating a variety of methods capable of revealing the geography of synchrony and, through it, underlying organism ecology. For example, we introduce a new type of network, the synchrony network, the structure of which provides ecological insight. By documenting the importance of geographies of synchrony, advancing conceptual frameworks, and demonstrating powerful methods, we aim to help elevate the geography of synchrony into a mainstream area of study and application.
The importance of temperature fluctuations in understanding mosquito population dynamics and malaria risk
Open Science
Lindsay M Beck-Johnson, William A Nelson, Krijn P Paaijmans, Andrew F Read, Matthew B Thomas, Ottar N Bjørnstad
2017 Temperature is a key environmental driver of Anopheles mosquito population dynamics; understanding its central role is important for these malaria vectors. Mosquito population responses to temperature fluctuations, though important across the life history, are poorly understood at a population level. We used stage-structured, temperature-dependent delay-differential equations to conduct a detailed exploration of the impacts of diurnal and annual temperature fluctuations on mosquito population dynamics. The model allows exploration of temperature-driven temporal changes in adult age structure, giving insights into the population’s capacity to vector malaria parasites. Because of temperature-dependent shifts in age structure, the abundance of potentially infectious mosquitoes varies temporally, and does not necessarily mirror the dynamics of the total adult population. In addition to conducting the first comprehensive theoretical exploration of fluctuating temperatures on mosquito population dynamics, we analysed observed temperatures at four locations in Africa covering a range of environmental conditions. We found both temperature and precipitation are needed to explain the observed malaria season in these locations, enhancing our understanding of the drivers of malaria seasonality and how temporal disease risk may shift in response to temperature changes. This approach, tracking both mosquito abundance and age structure, may be a powerful tool for understanding current and future malaria risk.
Human mobility and the spatial transmission of influenza in the United States
PLoS computational biology
Vivek Charu, Scott Zeger, Julia Gog, Ottar N Bjørnstad, Stephen Kissler, Lone Simonsen, Bryan T Grenfell, Cécile Viboud
2017 Seasonal influenza epidemics offer unique opportunities to study the invasion and re-invasion waves of a pathogen in a partially immune population. Detailed patterns of spread remain elusive, however, due to lack of granular disease data. Here we model high-volume city-level medical claims data and human mobility proxies to explore the drivers of influenza spread in the US during 2002–2010. Although the speed and pathways of spread varied across seasons, seven of eight epidemics likely originated in the Southern US. Each epidemic was associated with 1–5 early long-range transmission events, half of which sparked onward transmission. Gravity model estimates indicate a sharp decay in influenza transmission with the distance between infectious and susceptible cities, consistent with spread dominated by work commutes rather than air traffic. Two early-onset seasons associated with antigenic novelty had particularly localized modes of spread, suggesting that novel strains may spread in a more localized fashion than previously anticipated.
Anthropogenically driven environmental changes shift the ecological dynamics of hemorrhagic fever with renal syndrome
PLoS pathogens
Huaiyu Tian, Pengbo Yu, Ottar N Bjørnstad, Bernard Cazelles, Jing Yang, Hua Tan, Shanqian Huang, Yujun Cui, Lu Dong, Chaofeng Ma, Changan Ma, Sen Zhou, Marko Laine, Xiaoxu Wu, Yanyun Zhang, Jingjun Wang, Ruifu Yang, Nils Chr Stenseth, Bing Xu
2017 Zoonoses are increasingly recognized as an important burden on global public health in the 21st century. High-resolution, long-term field studies are critical for assessing both the baseline and future risk scenarios in a world of rapid changes. We have used a three-decade-long field study on hantavirus, a rodent-borne zoonotic pathogen distributed worldwide, coupled with epidemiological data from an endemic area of China, and show that the shift in the ecological dynamics of Hantaan virus was closely linked to environmental fluctuations at the human-wildlife interface. We reveal that environmental forcing, especially rainfall and resource availability, exert important cascading effects on intra-annual variability in the wildlife reservoir dynamics, leading to epidemics that shift between stable and chaotic regimes. Our models demonstrate that bimodal seasonal epidemics result from a powerful seasonality in transmission, generated from interlocking cycles of agricultural phenology and rodent behavior driven by the rainy seasons.