ORCID Profile
0000-0001-9017-1978
Current Organisations
Monash University
,
Nanyang Technological University
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Publisher: Oxford University Press (OUP)
Date: 06-2021
DOI: 10.1111/RSSC.12484
Abstract: As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low-prevalence areas are increasingly needed. For low-burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in areas with both routine surveillance data and prevalence surveys, models that make use of the spatial information from prevalence point-surveys might make more accurate predictions. Using case studies in Indonesia, Senegal and Madagascar, we compare the out-of-s le mean absolute error for two methods for incorporating point-level, spatial information into disaggregation regression models. The first simply fits a binomial-likelihood, logit-link, Gaussian random field to prevalence point-surveys to create a new covariate. The second is a multi-likelihood model that is fitted jointly to prevalence point-surveys and polygon incidence data. We find that in most cases there is no difference in mean absolute error between models. In only one case, did the new models perform the best. More generally, our results demonstrate that combining these types of data has the potential to reduce absolute error in estimates of malaria incidence but that simpler baseline models should always be fitted as a benchmark.
Publisher: Springer Science and Business Media LLC
Date: 10-02-2020
DOI: 10.1186/S12916-019-1486-3
Abstract: Many malaria-endemic areas experience seasonal fluctuations in case incidence as Anopheles mosquito and Plasmodium parasite life cycles respond to changing environmental conditions. Identifying location-specific seasonality characteristics is useful for planning interventions. While most existing maps of malaria seasonality use fixed thresholds of rainfall, temperature, and/or vegetation indices to identify suitable transmission months, we construct a statistical modelling framework for characterising the seasonal patterns derived directly from monthly health facility data. With data from 2669 of the 3247 health facilities in Madagascar, a spatiotemporal regression model was used to estimate seasonal patterns across the island. In the absence of catchment population estimates or the ability to aggregate to the district level, this focused on the monthly proportions of total annual cases by health facility level. The model was informed by dynamic environmental covariates known to directly influence seasonal malaria trends. To identify operationally relevant characteristics such as the transmission start months and associated uncertainty measures, an algorithm was developed and applied to model realisations. A seasonality index was used to incorporate burden information from household prevalence surveys and summarise ‘how seasonal’ locations are relative to their surroundings. Positive associations were detected between monthly case proportions and temporally lagged covariates of rainfall and temperature suitability. Consistent with the existing literature, model estimates indicate that while most parts of Madagascar experience peaks in malaria transmission near March–April, the eastern coast experiences an earlier peak around February. Transmission was estimated to start in southeast districts before southwest districts, suggesting that indoor residual spraying should be completed in the same order. In regions where the data suggested conflicting seasonal signals or two transmission seasons, estimates of seasonal features had larger deviations and therefore less certainty. Monthly health facility data can be used to establish seasonal patterns in malaria burden and augment the information provided by household prevalence surveys. The proposed modelling framework allows for evidence-based and cohesive inferences on location-specific seasonal characteristics. As health surveillance systems continue to improve, it is hoped that more of such data will be available to improve our understanding and planning of intervention strategies.
Publisher: Elsevier BV
Date: 07-2019
Publisher: Public Library of Science (PLoS)
Date: 23-08-2023
DOI: 10.1371/JOURNAL.PGPH.0002134
Abstract: Access to medical treatment for fever is essential to prevent morbidity and mortality in in iduals and to prevent transmission of communicable febrile illness in communities. Quantification of the rates at which treatment is accessed is critical for health system planning and a prerequisite for disease burden estimates. In this study, national data on the proportion of children under five years old with fever who were taken for medical treatment were collected from all available countries in Africa, Latin America, and Asia (n = 91). We used generalised additive mixed models to estimate 30-year trends in the treatment-seeking rates across the majority of countries in these regions (n = 151). Our results show that the proportions of febrile children brought for medical treatment increased steadily over the last 30 years, with the greatest increases occurring in areas where rates had originally been lowest, which includes Latin America and Caribbean, North Africa and the Middle East (51 and 50% increase, respectively), and Sub-Saharan Africa (23% increase). Overall, the aggregated and population-weighted estimate of children with fever taken for treatment at any type of facility rose from 61% (59–64 95% CI) in 1990 to 71% (69–72 95% CI) in 2020. The overall population-weighted average for fraction of treatment in the public sector was largely unchanged during the study period: 49% (42–58 95% CI) sought care at public facilities in 1990 and 47% (44–52 95% CI) in 2020. Overall, the findings indicate that improvements in access to care have been made where they were most needed, but that despite rapid initial gains, progress can plateau without substantial investment. In 2020 there remained significant gaps in care utilisation that must be factored in when developing control strategies and deriving disease burden estimates.
Publisher: Springer Science and Business Media LLC
Date: 05-10-2018
Publisher: Elsevier BV
Date: 07-2019
Publisher: Design Research Society
Date: 10-09-2020
Publisher: Springer Science and Business Media LLC
Date: 20-10-2020
DOI: 10.1186/S12936-020-03446-8
Abstract: Anti-malarial drugs play a critical role in reducing malaria morbidity and mortality, but their role is mediated by their effectiveness. Effectiveness is defined as the probability that an anti-malarial drug will successfully treat an in idual infected with malaria parasites under routine health care delivery system. Anti-malarial drug effectiveness (AmE) is influenced by drug resistance, drug quality, health system quality, and patient adherence to drug use its influence on malaria burden varies through space and time. This study uses data from 232 efficacy trials comprised of 86,776 infected in iduals to estimate the artemisinin-based and non-artemisinin-based AmE for treating falciparum malaria between 1991 and 2019. Bayesian spatiotemporal models were fitted and used to predict effectiveness at the pixel-level (5 km × 5 km). The median and interquartile ranges (IQR) of AmE are presented for all malaria-endemic countries. The global effectiveness of artemisinin-based drugs was 67.4% (IQR: 33.3–75.8), 70.1% (43.6–76.0) and 71.8% (46.9–76.4) for the 1991–2000, 2006–2010, and 2016–2019 periods, respectively. Countries in central Africa, a few in South America, and in the Asian region faced the challenge of lower effectiveness of artemisinin-based anti-malarials. However, improvements were seen after 2016, leaving only a few hotspots in Southeast Asia where resistance to artemisinin and partner drugs is currently problematic and in the central Africa where socio-demographic challenges limit effectiveness. The use of artemisinin-based combination therapy (ACT) with a competent partner drug and having multiple ACT as first-line treatment choice sustained high levels of effectiveness. High levels of access to healthcare, human resource capacity, education, and proximity to cities were associated with increased effectiveness. Effectiveness of non-artemisinin-based drugs was much lower than that of artemisinin-based with no improvement over time: 52.3% (17.9–74.9) for 1991–2000 and 55.5% (27.1–73.4) for 2011–2015. Overall, AmE for artemisinin-based and non-artemisinin-based drugs were, respectively, 29.6 and 36% below clinical efficacy as measured in anti-malarial drug trials. This study provides evidence that health system performance, drug quality and patient adherence influence the effectiveness of anti-malarials used in treating uncomplicated falciparum malaria. These results provide guidance to countries’ treatment practises and are critical inputs for malaria prevalence and incidence models used to estimate national level malaria burden.
Publisher: SAGE Publications
Date: 15-01-2023
Abstract: Horse racing is a highly dangerous activity that imposes the compulsory wearing of jockeys’ safety vests. Although “design thinking” has gained popularity in many fields (e.g., business, health, information technology, education), product innovation is still not used widely in the design of some of the personal protective equipment available to jockeys. This article discusses about an Australian design case study on jockeys’ safety vests that used a qualitative research approach along with user experience design principles, which led to consider a revision of this framework to accommodate design dependencies in terms of a suggested dependency-based user experience design framework. Hence, this article calls for further research in this field.
Publisher: The Royal Society
Date: 13-04-2022
Abstract: Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species—questions rarely answerable from in idual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these erse dynamics can be clustered into four ‘dynamical archetypes’, each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.
Publisher: Frontiers Media SA
Date: 21-06-2023
DOI: 10.3389/FSPOR.2023.1167110
Abstract: While the term “safety vests” has been used to capture these products to reduce the potential for harm in jockeys under the Personal Protective Equipment (PPE) umbrella, much of the research in this area has focused on factors typically echoing health, well-being, physiological and cognitive function, and performance of horse riders with very little work about examining how its design may reduce the severity of jockeys' injuries. Due to the recent advances in technology and wearable sensors, the author considered a qualitative study focusing on the analysis of a real-life ex le involving end and co-dependent users in the design development of jockeys' safety vests. This little article offers an overview of the most popular jockeys' injuries, why there is a need for better protection, and also describes how data were collected and present a summary of the key findings to encourage future research in this field, aiming to create a new prototype. High-impact sports may potentially create severe injuries or deaths to athletes: thus, there is a strong faith in the application of wearable sensor data and data science to also enhance jockeys' safety vest performance.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Michele Nguyen.