Some Quantitative Studies in Epidemiology

Ross, Ronald

doi:10.1038/087466a0

Cited by 95 publications

(65 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mathematical models of infectious disease transmission have been in use for over a century (4). These models have been developed to study the dynamic properties of disease transmission (5-7), determine the biological characteristics of specific pathogens (8,9), and analyze historical transmission behavior during documented outbreak events (10).…”

mentioning

confidence: 99%

Forecasting seasonal outbreaks of influenza

Shaman

Karspeck

2012

Proc. Natl. Acad. Sci. U.S.A.

381

451

View full text Add to dashboard Cite

Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of realtime, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.Kalman filter | absolute humidity W orldwide, influenza produces 3-5 million severe illnesses annually and kills an estimated 250,000-500,000 people (1). In temperate regions, influenza characteristically recurs during winter when absolute humidity levels are low (2, 3), but at present our ability to predict important details of these seasonal influenza outbreaks is limited. Indeed, much public health benefit could be gleaned from early, skillful prediction of the onset, peak, duration, and magnitude of local influenza outbreaks.Mathematical models of infectious disease transmission have been in use for over a century (4). These models have been developed to study the dynamic properties of disease transmission (5-7), determine the biological characteristics of specific pathogens (8,9), and analyze historical transmission behavior during documented outbreak events (10).More recently, infectious disease model simulations have been performed retrospectively in conjunction with statistical filtering methods to provide maximum-likelihood parameter estimation (11, 12) and improved epidemic simulation through time and physical space (13-16). Filtering techniques iteratively update, or adjust, model simulation estimates of the dynamic state, e.g., population infection rates, using real-world observations of that state, as the model is integrated through time. Because the state is only intermittently, or partially, observed-i.e., infections may be observed only for some locations and times, and some state variables, such as population susceptibility rates, may not be observed at all-and because these partial observations themselves contain error, the filter endeavors to balance the relative information contained in the observations and the model simulation. At the same time, the filtering process can also be used to estimate epidemiologically significant parameters within a model. These same filtering techniques, by constraining the model state and parameters, can potentially be used to e...

show abstract

mentioning

confidence: 99%

Forecasting seasonal outbreaks of influenza

Shaman

Karspeck

2012

Proc. Natl. Acad. Sci. U.S.A.

381

451

View full text Add to dashboard Cite

show abstract

“…There is a long history of mathematical models of malaria starting with Ronald Ross' first ordinary differential equation (ODE) model for the proportion of infectious humans and mosquitoes [26]. Most models developed since then have been similar deterministic population-based models [2,3,10,24,25] although recently stochastic individual-based simulation models have increased in prominence [17,28].…”

Section: Introductionmentioning

confidence: 99%

Modelling the effects of malaria infection on mosquito biting behaviour and attractiveness of humans

2016

View full text Add to dashboard Cite

We develop and analyse a deterministic population-based ordinary differential equation of malaria transmission to consider the impact of three common assumptions of malaria models: (1) malaria infection does not change the attractiveness of humans to mosquitoes; (2) exposed mosquitoes (infected with malaria but not yet infectious to humans) have the same biting rate as susceptible mosquitoes; and (3) mosquitoes infectious to humans have the same biting rate as susceptible mosquitoes. We calculate the basic reproductive number, R 0 , for this model and show the existence of a transcritical bifurcation at R 0 = 1, in common with most epidemiological models. We further show that for some sets of parameter values, this bifurcation can be backward (subcritical). We show with numerical simulations that increasing the relative attractiveness of infectious humans, increases R 0 but reduces the equilibrium prevalence of infectious humans; decreasing the biting rate of exposed mosquitoes increases R 0 and the equilibrium prevalence of infectious humans and mosquitoes; and increasing the biting rate of infectious mosquitoes has no impact on R 0 or the equilibrium prevalence of infectious humans, but decreases the infectious prevalence of infectious mosquitoes. These analyses of a simple malaria model show that common assumptions around the relative attractiveness of infectious humans and the relative biting rates of exposed and infectious mosquitoes can have substantial and counter-intuitive effects on malaria transmission dynamics.

show abstract

“…Modelling parasite transmission has made enormous strides since the seminal models of Ross for describing malaria transmission developed during the early 1900s (Ross, 1911). McDonald's use of the early malaria models to show that killing adult mosquitoes would be particularly effective in reducing infection transmission was a major advance in demonstrating the usefulness of theoretical analysis and population dynamics modelling in particular for guiding parasite control programmes, and since then parasite transmission models have also been used to guide the onchocerciasis control programme in Africa (Habbema et al, 1992), as well as for investigating best strategies for controlling a host of other parasites, including tuberculosis, trachoma and lately helminth infections, such as schistosomiasis and filariasis (Chan et al, 1995;Laing et al, 2007;Michael et al, 2004).…”

Section: Prefacementioning

confidence: 99%

Modelling Parasite Transmission and Control

2010

Advances in Experimental Medicine and Biology

View full text Add to dashboard Cite

All rights reserved.No part of this book may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission LQ ZULWLQJ IURP WKH SXEOLVKHU ZLWK WKH H[FHSWLRQ RI DQ\ PDWHULDO VXSSOLHG VSHFL¿FDOO\ IRU WKH SXUSRVH RI being entered and executed on a computer system; for exclusive use by the Purchaser of the work.Printed in the USA. :KLOH WKH DXWKRUV HGLWRUV DQG SXEOLVKHU EHOLHYH WKDW GUXJ VHOHFWLRQ DQG GRVDJH DQG WKH VSHFL¿FDWLRQV DQG usage of equipment and devices, as set forth in this book, are in accord with current recommend ations and practice at the time of publication, they make no warranty, expressed or implied, with respect to material described in this book. In view of the ongoing research, equipment development, changes in governmental regulations and the rapid accumulation of information relating to the biomedical sciences, the reader is urged to carefully review and evaluate the information provided herein.

show abstract

Some Quantitative Studies in Epidemiology

Cited by 95 publications

References 0 publications

Forecasting seasonal outbreaks of influenza

Forecasting seasonal outbreaks of influenza

Modelling the effects of malaria infection on mosquito biting behaviour and attractiveness of humans

Modelling Parasite Transmission and Control

Contact Info

Product

Resources

About