Abstract: Social media has become an important source of information for the public and the media profession. Some social issues raised on social media are picked up by journalists to report on other platforms. This relationship between social media and mainstream media can sometimes drive public debate or stimulate social movements. The question to examine is in what situations can social media conversations raise awareness and stimulate change on public issues. This study addresses the communication patterns of social media conversations driving covert issues into mainstream media and leading to social advocacy movements. In methodological terms, the study findings are based on a content analysis of Facebook, Twitter, news websites and television media reports on three different case studies – saving Bryde’s whale, protests against a government proposal to downsize the Office of Knowledge Management and Development in Thailand, and a dengue fever campaign. These case studies were chosen because they represent issues that most members of the public do not pay much attention to but social media conversations stimulated public debate and calls to action. This study found: 1) Collective social media conversations can stimulate public debate and encourage change at three levels – awareness, public debate, and action of policy and social change. The level depends on the communication patterns of online users and media coverage. 2) Patterns of communication have to be designed to combine social media conversations, online opinion leaders, mainstream media coverage and call to both online and offline action to motivate social change. Thus, this result suggests that social media is a powerful platform for collective communication and setting the agenda on public issues for mainstream media. However, for social change to succeed, social media should be used to mobilize online movements to move offline too.
Abstract: Dengue is a mosquito-borne viral disease endemic in
many countries in the tropics and sub-tropics. The state of Punjab in
India shows cyclical and seasonal variation in dengue cases. The
Case Fatality Rate of Dengue has ranged from 0.6 to 1.0 in the past
years. The department has initiated review of the cases that have died
due to dengue in order to know the exact cause of the death in a case
of dengue. The study has been undertaken to know the other
associated co-morbidities and factors causing death in a case of
dengue. The study used the predesigned proforma on which the
records (medical and Lab) were recorded and reviewed by the expert
committee of the doctors. This study has revealed that cases of
dengue having co-morbidities have longer stay in hospital. Fluid
overload and co-morbidities have been found as major factors leading
to death, however, in a confirmed case of dengue hepatorenal
shutdown was found to be major cause of mortality. The data
obtained will help in sensitizing the treating physicians in order to
decrease the mortality due to dengue in future.
Abstract: This paper describes the development of a DNA-based
nanobiosensor to detect the dengue virus in mosquito using
electrically active magnetic (EAM) nanoparticles as concentrator and
electrochemical transducer. The biosensor detection encompasses
two sets of oligonucleotide probes that are specific to the dengue
virus: the detector probe labeled with the EAM nanoparticles and the
biotinylated capture probe. The DNA targets are double hybridized to
the detector and the capture probes and concentrated from
nonspecific DNA fragments by applying a magnetic field.
Subsequently, the DNA sandwiched targets (EAM-detector probe–
DNA target–capture probe-biotin) are captured on streptavidin
modified screen printed carbon electrodes through the biotinylated
capture probes. Detection is achieved electrochemically by measuring
the oxidation–reduction signal of the EAM nanoparticles. Results
indicate that the biosensor is able to detect the redox signal of the
EAM nanoparticles at dengue DNA concentrations as low as 10
ng/μl.
Abstract: Dengue outbreaks are affected by biological,
ecological, socio-economic and demographic factors that vary over
time and space. These factors have been examined separately and still
require systematic clarification. The present study aimed to investigate
the spatial-temporal clustering relationships between these factors and
dengue outbreaks in the northern region of Sri Lanka. Remote sensing
(RS) data gathered from a plurality of satellites were used to develop
an index comprising rainfall, humidity and temperature data. RS data
gathered by ALOS/AVNIR-2 were used to detect urbanization, and a
digital land cover map was used to extract land cover information.
Other data on relevant factors and dengue outbreaks were collected
through institutions and extant databases. The analyzed RS data and
databases were integrated into geographic information systems,
enabling temporal analysis, spatial statistical analysis and space-time
clustering analysis. Our present results showed that increases in the
number of the combination of ecological factor and socio-economic
and demographic factors with above the average or the presence
contribute to significantly high rates of space-time dengue clusters.
Abstract: We used mathematical model to study the
transmission of dengue disease. The model is developed in which
the human population is separated into two populations, pregnant and
non-pregnant humans. The dynamical analysis method is used for
analyzing this modified model. Two equilibrium states are found and
the conditions for stability of theses two equilibrium states are
established. Numerical results are shown for each equilibrium state.
The basic reproduction numbers are found and they are compared by
using numerical simulations.
Abstract: Identifying parameters in an epidemic model is one
of the important aspect of modeling. In this paper, we suggest a
method to identify the transmission rate by using the multistage
Adomian decomposition method. As a case study, we use the data of
the reported dengue fever cases in the city of Shah Alam, Malaysia.
The result obtained fairly represents the actual situation. However, in
the SIR model, this method serves as an alternative in parameter
identification and enables us to make necessary analysis for a smaller
interval.
Abstract: Mathematical models can be used to describe the
dynamics of the spread of infectious disease between susceptibles
and infectious populations. Dengue fever is a re-emerging disease in
the tropical and subtropical regions of the world. Its incidence has
increased fourfold since 1970 and outbreaks are now reported quite
frequently from many parts of the world. In dengue endemic regions,
more cases of dengue infection in pregnancy and infancy are being
found due to the increasing incidence. It has been reported that
dengue infection was vertically transmitted to the infants. Primary
dengue infection is associated with mild to high fever, headache,
muscle pain and skin rash. Immune response includes IgM antibodies
produced by the 5th day of symptoms and persist for 30-60 days. IgG
antibodies appear on the 14th day and persist for life. Secondary
infections often result in high fever and in many cases with
hemorrhagic events and circulatory failure. In the present paper, a
mathematical model is proposed to simulate the succession of dengue
disease transmission in pregnancy and infancy. Stability analysis of
the equilibrium points is carried out and a simulation is given for the
different sets of parameter. Moreover, the bifurcation diagrams of our
model are discussed. The controlling of this disease in infant cases is
introduced in the term of the threshold condition.
Abstract: The effect of a time delay on the transmission on
dengue fever is studied. The time delay is due to the presence of an
incubation period for the dengue virus to develop in the mosquito
before the mosquito becomes infectious. The conditions for the
existence of a Hopf bifurcation to limit cycle behavior are
established. The conditions are different from the usual one and they
are based on whether a particular third degree polynomial has
positive real roots. A theorem for determining whether for a given
set of parameter values, a critical delay time exist is given. It is
found that for a set of realistic values of the parameters in the model,
a Hopf bifurcation can not occur. For a set of unrealistic values of
some of the parameters, it is shown that a Hopf bifurcation can occur.
Numerical solutions using this last set show the trajectory of two of
the variables making a transition from a spiraling orbit to a limit
cycle orbit.
Abstract: The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease.
Abstract: “Dengue" is an African word meaning “bone
breaking" because it causes severe joint and muscle pain that feels
like bones are breaking. It is an infectious disease mainly transmitted
by female mosquito, Aedes aegypti, and causes four serotypes of
dengue viruses. In recent years, a dramatic increase in the dengue
fever confirmed cases around the equator-s belt has been reported.
Several conventional indices have been designed so far to monitor the
transmitting vector populations known as House Index (HI),
Container Index (CI), Breteau Index (BI). However, none of them
describes the adult mosquito population size which is important to
direct and guide comprehensive control strategy operations since
number of infected people has a direct relationship with the vector
density. Therefore, it is crucial to know the population size of the
transmitting vector in order to design a suitable and effective control
program. In this context, a study is carried out to report a new
statistical index, ABURAS Index, using Poisson distribution based
on the collection of vector population in Jeddah Governorate, Saudi Arabia.
Abstract: Dengue fever is prevalent in Malaysia with numerous
cases including mortality recorded over the years. Public education
on the prevention of the desease through various means has been
carried out besides the enforcement of legal means to eradicate
Aedes mosquitoes, the dengue vector breeding ground. Hence, other
means need to be explored, such as predicting the seasonal peak
period of the dengue outbreak and identifying related climate factors
contributing to the increase in the number of mosquitoes. Simulation
model can be employed for this purpose. In this study, we created a
simulation of system dynamic to predict the spread of dengue
outbreak in Hulu Langat, Selangor Malaysia. The prototype was
developed using STELLA 9.1.2 software. The main data input are
rainfall, temperature and denggue cases. Data analysis from the graph
showed that denggue cases can be predicted accurately using these
two main variables- rainfall and temperature. However, the model
will be further tested over a longer time period to ensure its
accuracy, reliability and efficiency as a prediction tool for dengue
outbreak.
Abstract: The incidences of dengue hemorrhagic disease (DHF)
over the long term exhibit a seasonal behavior. It has been
hypothesized that these behaviors are due to the seasonal climate
changes which in turn induce a seasonal variation in the incubation
period of the virus while it is developing the mosquito. The standard
dynamic analysis is applied for analysis the Susceptible-Exposed-
Infectious-Recovered (SEIR) model which includes an annual
variation in the length of the extrinsic incubation period (EIP). The
presence of both asymptomatic and symptomatic infections is
allowed in the present model. We found that dynamic behavior of the
endemic state changes as the influence of the seasonal variation of
the EIP becomes stronger. As the influence is further increased, the
trajectory exhibits sustained oscillations when it leaves the chaotic
region.
Abstract: Dengue fever has become a major concern for health
authorities all over the world particularly in the tropical countries.
These countries, in particular are experiencing the most worrying
outbreak of dengue fever (DF) and dengue haemorrhagic fever
(DHF). The DF and DHF epidemics, thus, have become the main
causes of hospital admissions and deaths in Malaysia. This paper,
therefore, attempts to examine the environmental factors that may
influence the recent dengue outbreak. The aim of this study is twofold,
firstly is to establish a statistical model to describe the
relationship between the number of dengue cases and a range of
explanatory variables and secondly, to identify the lag operator for
explanatory variables which affect the dengue incidence the most.
The explanatory variables involved include the level of cloud cover,
percentage of relative humidity, amount of rainfall, maximum
temperature, minimum temperature and wind speed. The Poisson and
Negative Binomial regression analyses were used in this study. The
results of the analyses on the 915 observations (daily data taken from
July 2006 to Dec 2008), reveal that the climatic factors comprising of
daily temperature and wind speed were found to significantly
influence the incidence of dengue fever after 2 and 3 weeks of their
occurrences. The effect of humidity, on the other hand, appears to be
significant only after 2 weeks.
Abstract: Dengue, a disease found in most tropical and
subtropical areas of the world. It has become the most common
arboviral disease of humans. This disease is caused by any of four
serotypes of dengue virus (DEN1-DEN4). In many endemic
countries, the average age of getting dengue infection is shifting
upwards, dengue in pregnancy and infancy are likely to be
encountered more frequently. The dynamics of the disease is studied
by a compartmental model involving ordinary differential equations
for the pregnant, infant human and the vector populations. The
stability of each equilibrium point is given. The epidemic dynamic is
discussed. Moreover, the numerical results are shown for difference
values of dengue antibody.
Abstract: A climate dependent model is proposed to simulate
the population of Aedes aegypti mosquito. In developing the model,
average temperature of Shah Alam, Malaysia was used to determine
the development rate of each stage of the life cycle of mosquito.
Rainfall dependent function was proposed to simulate the hatching
rate of the eggs under several assumptions. The proposed transition
matrix was obtained and used to simulate the population of eggs,
larvae, pupae and adults mosquito. It was found that the peak of
mosquito abundance comes during a relatively dry period following a
heavy rainfall. In addition, lag time between the peaks of mosquito
abundance and dengue fever cases in Shah Alam was estimated.
Abstract: Dengue virus is transmitted from person to person
through the biting of infected Aedes Aegypti mosquitoes. DEN-1,
DEN-2, DEN-3 and DEN-4 are four serotypes of this virus. Infection
with one of these four serotypes apparently produces permanent
immunity to it, but only temporary cross immunity to the others. The
length of time during incubation of dengue virus in human and
mosquito are considered in this study. The dengue patients are
classified into infected and infectious classes. The infectious human
can transmit dengue virus to susceptible mosquitoes but infected
human can not. The transmission model of this disease is formulated.
The human population is divided into susceptible, infected, infectious
and recovered classes. The mosquito population is separated into
susceptible, infected and infectious classes. Only infectious
mosquitoes can transmit dengue virus to the susceptible human. We
analyze this model by using dynamical analysis method. The
threshold condition is discussed to reduce the outbreak of this
disease.
Abstract: This study aimed at developing a forecasting model on the number of Dengue Haemorrhagic Fever (DHF) incidence in Northern Thailand using time series analysis. We developed Seasonal Autoregressive Integrated Moving Average (SARIMA) models on the data collected between 2003-2006 and then validated the models using the data collected between January-September 2007. The results showed that the regressive forecast curves were consistent with the pattern of actual values. The most suitable model was the SARIMA(2,0,1)(0,2,0)12 model with a Akaike Information Criterion (AIC) of 12.2931 and a Mean Absolute Percent Error (MAPE) of 8.91713. The SARIMA(2,0,1)(0,2,0)12 model fitting was adequate for the data with the Portmanteau statistic Q20 = 8.98644 ( x20,95= 27.5871, P>0.05). This indicated that there was no significant autocorrelation between residuals at different lag times in the SARIMA(2,0,1)(0,2,0)12 model.
Abstract: Larval survey was carried out in 6 localities in the
urban areas (Putrajaya) and suburban areas (Kuala Selangor) from
January until December 2010. A total of 520 representative
households in 6 localities were selected. Breeding habitats were
sampled outdoors in the surroundings of housing areas. The study
indicated that the most predominant species found in both areas was
Aedes albopictus with the gardening utensil as a preferred breeding
microhabitat for Putrajaya, in contrast to the artificial containers for
Kuala Selangor. From a total of 1083 mosquito larvae species, 984
were Aedes albopictus larvae, 67 positive larvae of Aedes aegypti
and 32 of Culex larvae. Aedes Index and Container Index were
elevated in Putrajaya with 13% and 11% respectively which is higher
than the standard given by the Ministry of Health, Malaysia. This
results implicating dengue-sensitive skewed to the urban areas.
Breteau Index result also above the standard in both study locations.
Abstract: Dengue disease is an infectious vector-borne viral
disease that is commonly found in tropical and sub-tropical regions,
especially in urban and semi-urban areas, around the world and
including Malaysia. There is no currently available vaccine or
chemotherapy for the prevention or treatment of dengue disease.
Therefore prevention and treatment of the disease depend on vector
surveillance and control measures. Disease risk mapping has been
recognized as an important tool in the prevention and control
strategies for diseases. The choice of statistical model used for
relative risk estimation is important as a good model will
subsequently produce a good disease risk map. Therefore, the aim of
this study is to estimate the relative risk for dengue disease based
initially on the most common statistic used in disease mapping called
Standardized Morbidity Ratio (SMR) and one of the earliest
applications of Bayesian methodology called Poisson-gamma model.
This paper begins by providing a review of the SMR method, which
we then apply to dengue data of Perak, Malaysia. We then fit an
extension of the SMR method, which is the Poisson-gamma model.
Both results are displayed and compared using graph, tables and
maps. Results of the analysis shows that the latter method gives a
better relative risk estimates compared with using the SMR. The
Poisson-gamma model has been demonstrated can overcome the
problem of SMR when there is no observed dengue cases in certain
regions. However, covariate adjustment in this model is difficult and
there is no possibility for allowing spatial correlation between risks in
adjacent areas. The drawbacks of this model have motivated many
researchers to propose other alternative methods for estimating the
risk.
Abstract: Dengue fever is an important human arboviral disease. Outbreaks are now reported quite often from many parts of the world. The number of cases involving pregnant women and infant cases are increasing every year. The illness is often severe and complications may occur. Deaths often occur because of the difficulties in early diagnosis and in the improper management of the diseases. Dengue antibodies from pregnant women are passed on to infants and this protects the infants from dengue infections. Antibodies from the mother are transferred to the fetus when it is still in the womb. In this study, we formulate a mathematical model to describe the transmission of this disease in pregnant women. The model is formulated by dividing the human population into pregnant women and non-pregnant human (men and non-pregnant women). Each class is subdivided into susceptible (S), infectious (I) and recovered (R) subclasses. We apply standard dynamical analysis to our model. Conditions for the local stability of the equilibrium points are given. The numerical simulations are shown. The bifurcation diagrams of our model are discussed. The control of this disease in pregnant women is discussed in terms of the threshold conditions.