scholarly journals Modeling the spread of the 1918 Influenza pandemic in a Newfoundland community

2015 ◽  
Author(s):  
◽  
Jessica Lea Dimka

Infectious disease epidemics have played and continue to play important roles in human populations. At different geographical levels, the spread of epidemics are affected by multiple demographic, social, cultural, political, economic, and other factors. Variation in these factors often produces different local or regional outcomes, so it is important for researchers to understand how individual behaviors and interactions can produce and explain larger patterns of disease spread. In small, traditional communities, important factors include settlement and household organization, daily behaviors, and relationships among residents. This research uses two computer simulation models to test the relative impact of these factors on disease spread in a small study community in Newfoundland and Labrador in the early 20th century, using data from the 1918 flu pandemic and other archival sources. In the agent-based model, which emphasizes movement to important social spaces, schoolchildren drive the size and timing of epidemics. In the social network model, which reflects important relationships among community residents, epidemics begun by adult women tend to be slower and smaller than epidemics begun by other types of individuals. These results demonstrate that, based on their roles in the community, members of different age and sex groups can strongly affect epidemic outcomes. Further, because simulation models are often used to develop or recommend public health policies or intervention strategies, the different results of the two models indicate the importance of selecting appropriate design features to ensure the best possible recommendations.

2015 ◽  
Vol 25 (2) ◽  
pp. 265-296
Author(s):  
Jessica Dimka ◽  
Carolyn Orbann ◽  
Lisa Sattenspiel

The purpose of this article is twofold. First, the study addresses questions related to the spread and impact of the 1918 influenza pandemic in a small Newfoundland community, focusing on the role of large social institutions including an orphanage, school, and churches. Records indicate, for example, that residents of the orphanage in St. Anthony, our study community, experienced an increased risk of infection at different times during the epidemic than did members of the general community. Further, archival sources show that a variety of public health measures including closure of public gathering spaces were implemented throughout Newfoundland, but evidence suggests that the success of these measures varied. Second, this paper presents an argument for the important role computer simulation models can play in historical research, which is demonstrated using results from simulations focusing on social, demographic, and cultural factors, including behaviours and interactions of community residents. These examples highlight how modelling techniques can be used in historical research to address gaps in archival sources and help direct future research paths, and to test counterfactual scenarios to identify important factors influencing observed outcomes.


2009 ◽  
Vol 89 (3) ◽  
pp. 357-367 ◽  
Author(s):  
E. Smith ◽  
R. Gordon ◽  
C. Bourque ◽  
A. Campbell ◽  
S. Génermont ◽  
...  

The land spreading of manure can result in significant nitrogen (N) losses to the atmosphere through ammonia (NH3) volatilization. It is estimated that agricultural activities, including manure spreading contribute approximately 50% of the total global NH3 emissions. Computer simulation models have been developed in an attempt to predict NH3 losses resulting from manure spreading. Few models have been validated with success and no validation has been completed for conditions found in eastern Canada. The mechanistic model Volt’Air was implemented and tested to estimate NH3 emissions using field-based wind tunnel data from three field locations in eastern Canada. The model was validated using data from 27 wind tunnel trials, which measured NH3 loss over 5-19 d. Sensitivity analysis revealed that Volt’Air was most sensitive to pH. Good overall agreement was observed between measured results and model simulations over 5-19 d (R2 = 0.91, RMSE = 2.9 kg ha-1). Short-term flux simulations (kg ha-1 h-1) within the first 24 h after spreading were underestimated by 29.5% and fluxes on subsequent days were slightly underestimated by 3.7%. Error with Volt’Air appears to be largely confined to the first day following manure application. Volt’Air offers potential for predicting NH3 losses (i.e., 5-19 d) from manure application within eastern Canada. Improving the simulation of short-term pH changes, however, may result in enhanced overall model performance.Key words: Ammonia volatilization, flux, mechanistic model, swine manure, wind tunnels


1996 ◽  
Vol 33 (9) ◽  
pp. 39-47 ◽  
Author(s):  
John W. Davies ◽  
Yanli Xu ◽  
David Butler

Significant problems in sewer systems are caused by gross solids, and there is a strong case for their inclusion in computer simulation models of sewer flow quality. The paper describes a project which considered methods of modelling the movement of gross solids in combined sewers. Laboratory studies provided information on advection and deposition of typical gross solids in part-full pipe flow. Theoretical considerations identified aspects of models for gross solids that should differ from those for dissolved and fine suspended pollutants. The proposed methods for gross solids were incorporated in a pilot model, and their effects on simple simulations were considered.


2020 ◽  
Author(s):  
Laura A Talbot ◽  
E Jeffrey Metter ◽  
Heather King

ABSTRACT During World War I, the 1918 influenza pandemic struck the fatigued combat troops serving on the Western Front. Medical treatment options were limited; thus, skilled military nursing care was the primary therapy and the best indicator of patient outcomes. This article examines the military nursing’s role in the care of the soldiers during the 1918 flu pandemic and compares this to the 2019 coronavirus pandemic.


2014 ◽  
Vol 22 ◽  
pp. S57-S58
Author(s):  
W. Hui ◽  
D.A. Young ◽  
A.D. Rowan ◽  
T.E. Cawston ◽  
C.J. Proctor

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