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SUMMARY:Investigating the effects of childhood vaccination: Rotavirus in C
hile
DTSTART;VALUE=DATE-TIME:20180712T011000Z
DTEND;VALUE=DATE-TIME:20180712T013000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-345@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Katia Vogt-Geisse (Universidad Adolfo Ibáñez)\nRot
avirus is a viral disease - mainly transmitted by the fecal-oral mode - th
at is the leading cause of severe acute gastroenteritis among infants and
children less than 5 years of age. The symptoms vary from mild to severe d
iarrhea with fever and vomiting that may produce rapid dehydration. In mos
t of the cases\, severe symptoms require hospitalization and eventually ca
n lead to death.\n\nThere exist two licensed rotavirus vaccines that have
proven to be safe and effective to prevent rotavirus infections in young c
hildren and infants. However\, Chile's national childhood immunization pro
gram does not currently include vaccination against rotavirus. The disease
is responsible for 47% of the hospitalizations of children less than 3 ye
ars of age in Chile\, which represents an important social and economic bu
rden for the country. We present an ongoing study that is one of the first
steps into making public health recommendations for rotavirus control and
prevention in Chile\, using mathematical models. We developed an ordinary
differential equations model that describes the disease dynamics of rotav
irus and analyzes the effect of vaccination into the country's hospitaliza
tion incidence.\n\nhttps://conferences.maths.unsw.edu.au/event/2/contribut
ions/345/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/345/
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SUMMARY:A structured population model with diffusion in structure space
DTSTART;VALUE=DATE-TIME:20180712T003000Z
DTEND;VALUE=DATE-TIME:20180712T005000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-491@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Fabio A. Milner (School of Mathematical and Statisti
cal Sciences\, Arizona State University)\nA structured population model is
described and analyzed\, in which individual dynamics is stochastic. The
model consists of a PDE of advection-diffusion type in the structure varia
ble. The population may represent\, for example\, the density of infected
individuals structured by pathogen density $x$\, $x\\ge0$. The individuals
with density $x=0$ are not infected\, but rather susceptible or recovered
. Their dynamics is described by an ODE with a source term that is the exa
ct flux from the diffusion and advection as $x\\to0^+$. Infection/reinfect
ion is then modelled moving a fraction of these individuals into the infec
ted class by distributing them in the structure variable through a probabi
lity density function. Existence of a global-in-time solution is proven\,
as well as a classical bifurcation result about equilibrium solutions: a n
et reproduction number $R_0$ is defined that separates the case of only th
e trivial equilibrium existing when $R_01$. Numerical simulation results a
re provided to show the stabilization towards the positive equilibrium whe
n $R_0>1$ and towards the trivial one when $R_0\n\nhttps://conferences.mat
hs.unsw.edu.au/event/2/contributions/491/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/491/
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SUMMARY:Disease modelling: how to control and prevent epidemic outbreaks
DTSTART;VALUE=DATE-TIME:20180712T013000Z
DTEND;VALUE=DATE-TIME:20180712T015000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-323@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Elena Aruffo ()\nIn recent years vaccination studies
have led to greater understanding and improvements on the development and
distribution of vaccines\, especially with respect to certain childhood d
iseases. However\, while current vaccination campaigns strive to achieve h
erd immunity (a critical threshold of ‘immune’ individuals needed to p
rotect an entire population from infection)\, eradication has not been ach
ieved and populations continue to be affected by childhood diseases global
ly. These outbreaks are usually attributed to the movement of one or more
asymptomatic cases from a country affected by the pathogen in question. Ne
vertheless\, individuals coming from regions with infection-induced immuni
zation can provide protection to the receiving region. Mathematical models
are able to describe the dynamics of an infectious diseases in population
s\, and they can provide important measurements for public health such as
the basic reproductive ratio\, the vaccination threshold needed to achieve
herd immunity\, and project the number of cases that could be observed du
ring an outbreak. In particular\, metapopulation models can be used to tra
ck the movement of individuals through travel or immigration to better und
erstand the movement and persistence of infectious diseases\, and border r
estriction policies. We propose infectious disease models to study the dis
tribution of immunity in a population and how this changes with immigratio
n and travel\, by using a Susceptible-Exposed-Infectious-Recovered framewo
rk. Our work is in collaboration with Public Health Ontario and has been u
sed to better understand the effects of measles immunity in a population.
Our results show that the biggest loss in the susceptible population happe
ns when the infected individual introduced in the population belongs to th
e group of children between 5 and 9 years\, even when vaccination threshol
ds recommended by the WHO are achieved.\n\nhttps://conferences.maths.unsw.
edu.au/event/2/contributions/323/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/323/
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SUMMARY:Infection-acquired versus vaccine-acquired immunity in an SIRWS mo
del
DTSTART;VALUE=DATE-TIME:20180712T005000Z
DTEND;VALUE=DATE-TIME:20180712T011000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-263@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Tiffany Leung (University of Melbourne)\nWaning immu
nity is known to occur for some infectious diseases after natural infectio
n and vaccination. We present a susceptible-infectious-recovered-susceptib
le (SIRS)-type transmission model that includes the waning and boosting of
immunity. We study how the infection prevalence changes with differences
in (i) the durations of infection- and vaccine-acquired immunity and (ii)
the assumed mechanism through which immune boosting acts to extend protect
ion.\n\nOur results show that increasing vaccine uptake always lowers the
proportion of primary infections but may lead to an increase in overall tr
ansmission. Where the boosting of vaccine-acquired immunity delays a prima
ry infection\, the driver of transmission largely remains primary infectio
ns. In contrast\, if immune boosting bypasses a primary infection\, second
ary infections become the main driver of transmission under sufficiently l
ong-lasting vaccine-induced immunity. Our study highlights that for a part
icular disease and associated vaccine\, a detailed understanding of how th
e duration of protection can influence infection prevalence is important a
s we seek to optimise vaccination strategies.\n\nhttps://conferences.maths
.unsw.edu.au/event/2/contributions/263/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/263/
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SUMMARY:Role of household size and community structure on the spread of tu
berculosis
DTSTART;VALUE=DATE-TIME:20180712T021000Z
DTEND;VALUE=DATE-TIME:20180712T023000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-339@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Julien Arino (University of Manitoba\, Winnipeg\, Ma
nitoba (Canada))\nSome northern communities in Canada see inordinately hig
h tuberculosis incidence compared to the rest of the country. Most of the
affected locations are isolated First Nations communities and while this m
eans that the usual argument of tuberculosis as an indicator disease of po
verty is applicable\, it does not explain the specifics of the situation.
To try to understand the role of the various factors at play\, we focus on
two specific aspects: household size and community structure. We investig
ate this using a simple discrete-time model for households\, which we stud
y analytically and with numerical simulations. \nThis is joint work with R
yan Sherbo.\n\nhttps://conferences.maths.unsw.edu.au/event/2/contributions
/339/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/339/
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SUMMARY:Dynamical models of tuberculosis transmission and optimal treatmen
t strategies in the Republic of Korea and Philippines
DTSTART;VALUE=DATE-TIME:20180712T015000Z
DTEND;VALUE=DATE-TIME:20180712T021000Z
DTSTAMP;VALUE=DATE-TIME:20200813T145859Z
UID:indico-contribution-60-268@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Eunok Jung (Konkuk University)\nIn this talk\, we wi
ll present several mathematical models of tuberculosis (TB) based on the r
eported data in the Republic of Korea and Philippines\, and also propose t
he optimal treatment strategies depending on the various scenarios in each
country. Korea has ranked the highest TB incidence among members of the O
rganization for Economic Cooperation and Development (OECD). TB is the six
th leading cause of morbidity and mortality in the Philippines. The least-
square curve fitting have been used for best fitting the parameters in our
models to the observed data. To determine the optimal intervention strate
gy which is reducing the number of exposed and infectious individuals and
the cost of control measures\, optimal control theory was used [1]. Import
ant issues has been addressed from our research: implementing the smoking
controls\, not with TB controls\, can derive significant reduction of the
incidence of TB transmission [3]. We suggested the rearrangement of the Ko
rean government TB budget based on optimal treatment strategies from model
ling [2]. Finally\, in the Philippines enhancing active finding control is
a significant control factor to curtail the spread of TB [4]. \n\n[1]
Sunhwa Choi\, Eunok Jung\, Sungim Whang\, A dynamic model for tuberculosis
transmission and optimal treatment strategies in South Korea\, *JTB* 279
(2011) 120-131\n[2] Sunhwa Choi\, Eunok Jung\, Optimal Tuberculosis Preven
tion and Control Strategy from a Mathematical Model Based on Real Data\, *
BMB* (2014) 76:1566-1589\n[3] Sunhwa Choi\, Eunok Jung\, Seok-Min Lee\, Op
timal intervention strategy for prevention tuberculosis using a smoking-tu
berculosis model\, *JTB* 380 (2015) 256-270\n[4] Soyoung Kim\, Aurelio A.
de los Reyes V\, Eunok Jung\, Mathematical Model and Intervention Strategi
es for Mitigating Tuberculosis in the Philippines\, *JTB* 443 (2017) 100-1
12\n\nhttps://conferences.maths.unsw.edu.au/event/2/contributions/268/
LOCATION:University of Sydney New Law School/--107
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/268/
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