Australian Mathematical Society (AustMS): E-Journals
Not a member yet
3379 research outputs found
Sort by
Development of multivariate quality control and quality assurance models for antenatal care service in Indonesia
No full textNeonatal mortality rate (NMR) is an increasingly important public health issue in many developing countries. With an estimated 154 preterm births per 1,000 live births in 2010, Indonesia was ranked 5th highest for preterm births in the world. Estimated birth weight is a significant indicator of the optimal growth, survival and future well-being of newborns. Low birth weight (LBW) is well documented as one of the factors that contributes most to neonatal mortality and it can be caused by preterm birth.
Access to routine data on estimated foetal weight (EFW) at a given gestation age (GA) is required to develop a foetal growth chart. Lack of access to such data is one of the reasons for the absence of a standard foetal growth chart in Indonesian antenatal care (ANC) practices. Consistent monitoring of EFW using a foetal growth chart allows early detection of growth abnormalities and can initiate interventions to ensure safe delivery. Low performance of ANC services in measuring and documenting the key performance indicators (KPIs) for maternal and foetal risk assessment is one of the major barriers to reducing NMR in Indonesia.
This research has developed statistical quality assurance systems to assess the efficacy of the current performance of ANC services in reducing NMR, particularly among Indonesian rural primary health care centres. This includes identification of the most significant KPIs during pregnancy. To optimize the practical applicability of the research outcomes, a data measuring and recording model that provides a more reliable medical database for the national health system was developed. This was followed by initiating scientific and technical training among urban and rural midwives to improve the quality of routine ANC data collection tasks for maternal and foetal risk assessment and development of a foetal growth chart.
The training has equipped nineteen urban and rural midwives in South Kalimantan province with the scientific knowledge and technical abilities to carry out routine collection of ANC data. The ANC information on 4,946 women (retrospective cohort study) and 381 women (prospective cohort study) has been used to assess the impact of the scientific and technical training, particularly its impact on the ability of midwives in settings with limited resources to collect and record the KPIs for maternal and foetal risk assessment and the data for developing the proposed foetal growth chart.
The results show that the training has significantly improved the average amount of recorded data for maternal and foetal risk assessment (from 17.5 to 62.1%, p-value < 0.0005) and for developing the foetal growth chart (from 33.4 to 89.1%, p-value < 0.0005). Midwives’ views regarding factors which affect their ability to successfully complete the data documentation tasks have also been explored. Lack of awareness, high workload and insufficient skills and facilities are the main reasons for gaps in the data.
This research has developed reliable regression models that can easily be implemented in rural primary health care centres to accurately predict EFW at a given GA in the absence of ultrasound facilities. Multiple comparison criteria showed that the proposed models are more accurate than the existing clinical and ultrasound models in predicting foetal weight between 35 and 41 weeks of GA, and much more accurate at earlier GAs. The results also indicate that foetal weight can be best predicted by the measurement of maternal fundal height (FH). The model based on FH can be utilised in rural areas where advanced health equipment such as ultrasound is not always accessible.
Prior to the development of a new foetal growth chart, the research reviewed the existing growth charts for EFW. The potential challenges in utilising such surveillance tools in Indonesia were also investigated. The results showed that the customised and standard foetal growth charts for EFW used internationally had been developed and highly recommended for use without local data being available. Moreover, limited access to ultrasound measurement of foetal biometric characteristics hindered foetal weight estimation using the existing models. Low levels of recording of the minimum database requirements on individual maternal, foetal and neonatal characteristics also made the existing customised charts less applicable in the local setting.
For the first time an alternative foetal growth chart for EFW, which only requires information on FH, has been developed to monitor and identify unusual growth of a foetus. The efficacy of the proposed chart has been assessed by using it to look for abnormal patterns of foetal growth in the data recorded for normal and LBW newborns The results highlighted the effectiveness of the developed growth chart for risk assessment during pregnancy to prevent the occurrence of LBW delivery. Using prospective data, it was shown that the proposed chart can effectively detect signs of abnormality between 20 and 41 weeks of GA. It was also shown that the existing foetal growth chart does not fit Indonesian data in the absence of ultrasound information.
This research has also evaluated the prediction accuracy of the ultrasound-based prediction models used in the development of the existing foetal growth charts for EFW and compared them with the proposed clinical-based prediction model using the Indonesian data. The results showed that the proposed model has comparable ability, and is even more effective at earlier GAs in predicting foetal weight than the existing models. This justifies the utilisation of the proposed prediction model in the development of the new foetal growth chart.
The outcome of this research provides a useful administrative and scientific guideline for the expansion of health services programs and for the more effective distribution of limited government resources in rural area. It includes analysis of where further aid investments are likely to best impact on reducing the NMR. The outcome also aids midwives in identifying the key risk factors and types of clinical interventions required prior to delivery to reduce the mortality rate.
 
Option pricing under the fractional stochastic volatility model
No full textWe investigate the European call option pricing problem under the fractional stochastic volatility model. The stochastic volatility model is driven by both fractional Brownian motion and standard Brownian motion. We obtain an analytical solution of the European option price via the Itô’s formula for fractional Brownian motion, Malliavin calculus, derivative replication and the fundamental solution method. Some numerical simulations are given to illustrate the impact of parameters on option prices, and the results of comparison with other models are presented.
doi:10.1017/S144618112100022
Finite maturity American-style stock loans with regime-switching volatility
No full textWe study finite maturity American-style stock loans under a two-state regime-switching economy. We present a thorough semi-analytic discussion of the optimal redeeming prices, the values and the fair service fees of the stock loans, under the assumption that the volatility of the underlying is in a state of uncertainty. Numerical experiments are carried out to show the effects of the volatility regimes and other loan parameters.
doi:10.1017/S144618112100025
Retraction - Ancient solutions of codimension two surfaces with curvature pinching
No full texthttp://dx.doi.org/10.1017/S000497271200033
Some homological properties of Fourier algebras on homogeneous spaces
No full texthttp://dx.doi.org/10.1017/S000497271200033
Metrical problems in Diophantine approximation
No full texthttp://dx.doi.org/10.1017/S000497271200033
A -analogue of a Dwork-type supercongruence
No full textRecently, by making use of the `creative microscoping' method, Guo and Zudilin proved a lot of Dwork-type supercongruences,
including some conjectures of Swisher. In this paper, applying Guo and Zudilin's method, we prove a new Dwork-type supercongruence,
which is a generalization of some conjectures of Swisher and was originally conjectured by the authors in a previous paper
Modelling and monitoring maternal mortality rate in South Sudan: Modelling and monitoring maternal mortality rate (MMR) in South Sudan
No full textAbstract
Reducing the Maternal Mortality Rate (MMR) is considered by the international community as one of the eight Millennium Development Goals (MDGs). South Sudan is amongst the countries with the highest MMR. The risk of a pregnant woman dying is as high as one in seven. Socio-economic, macroeconomic, and physiological factors have been found to contribute to high mortality rates. This study deployed statistical analysis tools to identify and rank the Key Performance Indicators (KPIs) responsible for high MMR in South Sudan, monitor the trend of MMR, and model MMR in terms of the most significant socio-economic, macroeconomic, and physiological KPIs. Time-series analysis was used to monitor the MMR trend. The results of this analysis indicated that there was a general declining trend in HIV+/AIDS, non-HIV+/AIDS, and total maternal mortality rate during the period of study. However, the decline in HIV+/AIDS maternal mortality rate is much slower than the non-HIV+/AIDS maternal mortality rate. Trend analysis also shows that non-HIV+/AIDS MMR accounts for about two-thirds of the total MMR.
Skilled Assistant at Birth (SAB), General Fertility Rate (GFR), and Gross Domestic Product (GDP) were identified as the most significant socio-economic predictors of MMR in South Sudan. The most influential physiological KPIs were identified as hemorrhaging followed by indirect causes (anemia, malaria, HIV/AIDS, and heart disease), sepsis (infection), prolonged (obstructed) labor, and unsafe abortion.
Logarithmic multi-regression and Poisson regression models were used to model MMR in terms of SAB, GFR, and GDP and the most influential physiological KPIs. Data collected at the Juba Teaching Hospital (JTH) between 1986 and 2015 was used to develop the predicting models and assess the MMR trend.
Accuracy criteria such as coefficient of determination and mean error were used to compare the predicting error of these models. The results indicated that log regression can predict MMR in terms of socio-economic factors with fewer mean prediction errors.
Results also show that logarithmic multi-regression models provide distinct evidence that increasing SAB and decreasing GFR (while leaving the GDP constants at 1772) could reduce MMR in South Sudan by 2030 to the lower and upper target levels proposed by UN agencies.
The statistical analysis shows that increasing SAB by 1.22% per year would reduce MMR by 1.4% (95% CI [0.4%–5%]) and decreasing GFR by 1.22% per year would reduce MMR by 1.8% (95% CI [0.5%–6.26%]).
The numerical results indicate that the top five physiological causes contributed 97.43% to the variation in maternal mortality rate (due to physiological causes). Analysis of the predicting errors shows that Poisson regression can describe MMR in terms of physiological factors more accurately than the Log-regression model. Therefore, Poisson regression was used to assess the impact of physiological causes on MMR.
Judging by their corresponding variance inflation factor and p-value, the conclusion is that all five causes are statistically significant. However, based on literature recommendations, the study developed two reduced Poisson regressions based on hemorrhaging only, and hemorrhaging and unsafe abortion. To reduce the impact of the sample size and downward trend in MMR on the reliability of the developed reduced Poisson model, a repeated random sample selection was used 30 times, using Bernoulli distribution, with a probability of 0.67 to randomly select two-thirds of the data to build the models and one-third to assess the efficacy. The proposed reduced model was developed based on the average coefficients of the 30 models.
The findings indicate that the proposed reduced Poisson regression model with R2 of 90.27% can predict MMR for a given level of hemorrhaging with a mean error of -34.5517 and a 0.0151 standard error of the mean. Moreover, the reduced model based on hemorrhaging and unsafe abortion explains 92.68% of the variation in MMR due to physiological causes.
For the first time, this study deployed optimization procedures to develop lower and upper yearly profile limits for maternal mortality rates, targeting the UN recommended lower and upper MMR levels by 2030. The MMR profile limits were accompanied by optimal yearly values of SAB and GFR level profile limits. The study also developed yearly optimal profile limits for MMR, due to physiological causes of hemorrhaging and unsafe abortion, accompanied by a yearly optimal level of hemorrhaging and unsafe abortion.
This study generated a database; having access to the electronic database and optimal level predictors that significantly influence the maternal mortality rate will aid the government in making informed evidence-based decisions on resource allocation and intervention plans to reduce the risk of maternal death.
The project also investigated and outlined the steps taken by the South Sudan Government and international agencies to reduce MMR during the past few years. The recommended policies, implemented policies, and the impact of implemented policies in South Sudan and other countries that aim to reduce MMR, have been thoroughly explored.
The government has taken positive steps to reduce MMR by targeting these KPIs. The lack of properly trained personnel is a major problem in maternal healthcare. Thus, the government has implemented policies to increase the number of health professional students and graduates.
The analysis also shows that the health development plan had a budget increase of 87% for the period 2012–2016. The increased budget was used to significantly improve healthcare facilities by increasing the number of primary healthcare units (PHCU), primary healthcare centers (PHCC), and specialized hospitals, as well as improving roads, infrastructure, and communication networks. The budget also extended to education for females and increasing women quote in all government institutions. These policies were responsible for the significant downward trend in MMR, especially between 2013 and 2017. A list of recommendations for administrative strategies and policies has been provided.
This project has contributed to new knowledge and practice by producing a simple, yet effective, system for monitoring and improving the antenatal care process as well as reliable and effective models to forecast South Sudanese MMR, which might be applied in other countries.