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Article ; Online: Prediction of Ross River virus incidence in Queensland, Australia

Wei Qian / David Harley / Kathryn Glass / Elvina Viennet / Cameron Hurst

PeerJ, Vol 10, p e

building and comparing models

2022 Volume 14213

Abstract: Transmission of Ross River virus (RRV) is influenced by climatic, environmental, and socio-economic factors. Accurate and robust predictions based on these factors are necessary for disease prevention and control. However, the complicated transmission ... ...

Abstract	Transmission of Ross River virus (RRV) is influenced by climatic, environmental, and socio-economic factors. Accurate and robust predictions based on these factors are necessary for disease prevention and control. However, the complicated transmission cycle and the characteristics of RRV notification data present challenges. Studies to compare model performance are lacking. In this study, we used RRV notification data and exposure data from 2001 to 2020 in Queensland, Australia, and compared ten models (including generalised linear models, zero-inflated models, and generalised additive models) to predict RRV incidence in different regions of Queensland. We aimed to compare model performance and to evaluate the effect of statistical over-dispersion and zero-inflation of RRV surveillance data, and non-linearity of predictors on model fit. A variable selection strategy for screening important predictors was developed and was found to be efficient and able to generate consistent and reasonable numbers of predictors across regions and in all training sets. Negative binomial models generally exhibited better model fit than Poisson models, suggesting that over-dispersion in the data is the primary factor driving model fit compared to non-linearity of predictors and excess zeros. All models predicted the peak periods well but were unable to fit and predict the magnitude of peaks, especially when there were high numbers of cases. Adding new variables including historical RRV cases and mosquito abundance may improve model performance. The standard negative binomial generalised linear model is stable, simple, and effective in prediction, and is thus considered the best choice among all models.
Keywords	Ross River virus ; Prediction ; Modelling ; Exposures ; Disease incidence ; Over-dispersion ; Medicine ; R
Subject code	310
Language	English
Publishing date	2022-11-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Lymphatic filariasis endgame strategies

Callum Shaw / Angus McLure / Patricia M Graves / Colleen L Lau / Kathryn Glass

PLoS Neglected Tropical Diseases, Vol 17, Iss 5, p e

Using GEOFIL to model mass drug administration and targeted surveillance and treatment strategies in American Samoa.

2023 Volume 0011347

Abstract: American Samoa underwent seven rounds of mass drug administration (MDA) for lymphatic filariasis (LF) from 2000-2006, but subsequent surveys found evidence of ongoing transmission. American Samoa has since undergone further rounds of MDA in 2018, 2019, ... ...

Abstract	American Samoa underwent seven rounds of mass drug administration (MDA) for lymphatic filariasis (LF) from 2000-2006, but subsequent surveys found evidence of ongoing transmission. American Samoa has since undergone further rounds of MDA in 2018, 2019, and 2021; however, recent surveys indicate that transmission is still ongoing. GEOFIL, a spatially-explicit agent-based LF model, was used to compare the effectiveness of territory-wide triple-drug MDA (3D-MDA) with targeted surveillance and treatment strategies. Both approaches relied on treatment with ivermectin, diethylcarbamazine, and albendazole. We simulated three levels of whole population coverage for 3D-MDA: 65%, 73%, and 85%, while the targeted strategies relied on surveillance in schools, workplaces, and households, followed by targeted treatment. In the household-based strategies, we simulated 1-5 teams travelling village-to-village and offering antigen (Ag) testing to randomly selected households in each village. If an Ag-positive person was identified, treatment was offered to members of all households within 100m-1km of the positive case. All simulated interventions were finished by 2027 and their effectiveness was judged by their 'control probability'-the proportion of simulations in which microfilariae prevalence decreased between 2030 and 2035. Without future intervention, we predict Ag prevalence will rebound. With 3D-MDA, a 90% control probability required an estimated ≥ 4 further rounds with 65% coverage, ≥ 3 rounds with 73% coverage, or ≥ 2 rounds with 85% coverage. While household-based strategies were substantially more testing-intensive than 3D-MDA, they could offer comparable control probabilities with substantially fewer treatments; e.g. three teams aiming to test 50% of households and offering treatment to a 500m radius had approximately the same control probability as three rounds of 73% 3D-MDA, but used < 40% the number of treatments. School- and workplace-based interventions proved ineffective. Regardless of strategy, reducing Ag ...
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: COVID-19 vaccination strategies in settings with limited rollout capacity

Gizem Mayis Bilgin / Kamalini Lokuge / Ernest Jabbie / Syarifah Liza Munira / Kathryn Glass

BMC Public Health, Vol 23, Iss 1, Pp 1-

a mathematical modelling case study in Sierra Leone

2023 Volume 8

Abstract: Abstract Background COVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity. Methods We developed a deterministic compartmental ... ...

Abstract	Abstract Background COVID-19 vaccine coverage in low- and middle-income countries continues to be challenging. As supplies increase, coverage is increasingly becoming determined by rollout capacity. Methods We developed a deterministic compartmental model of COVID-19 transmission to explore how age-, risk-, and dose-specific vaccine prioritisation strategies can minimise severe outcomes of COVID-19 in Sierra Leone. Results Prioritising booster doses to older adults and adults with comorbidities could reduce the incidence of severe disease by 23% and deaths by 34% compared to the use of these doses as primary doses for all adults. Providing a booster dose to pregnant women who present to antenatal care could prevent 38% of neonatal deaths associated with COVID-19 infection during pregnancy. The vaccination of children is not justified unless there is sufficient supply to not affect doses delivered to adults. Conclusions Our paper supports current WHO SAGE vaccine prioritisation guidelines (released January 2022). Individuals who are at the highest risk of developing severe outcomes should be prioritised, and opportunistic vaccination strategies considered in settings with limited rollout capacity.
Keywords	COVID-19 ; SARS-CoV-2 ; Mathematical model ; Vaccination ; Vaccine allocation ; Vaccine prioritisation ; Public aspects of medicine ; RA1-1270
Subject code	610
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Epidemiological models for predicting Ross River virus in Australia

Wei Qian / Elvina Viennet / Kathryn Glass / David Harley

PLoS Neglected Tropical Diseases, Vol 14, Iss 9, p e

A systematic review.

2020 Volume 0008621

Abstract: Ross River virus (RRV) is the most common and widespread arbovirus in Australia. Epidemiological models of RRV increase understanding of RRV transmission and help provide early warning of outbreaks to reduce incidence. However, RRV predictive models have ...

Abstract	Ross River virus (RRV) is the most common and widespread arbovirus in Australia. Epidemiological models of RRV increase understanding of RRV transmission and help provide early warning of outbreaks to reduce incidence. However, RRV predictive models have not been systematically reviewed, analysed, and compared. The hypothesis of this systematic review was that summarising the epidemiological models applied to predict RRV disease and analysing model performance could elucidate drivers of RRV incidence and transmission patterns. We performed a systematic literature search in PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus for studies of RRV using population-based data, incorporating at least one epidemiological model and analysing the association between exposures and RRV disease. Forty-three articles, all of high or medium quality, were included. Twenty-two (51.2%) used generalised linear models and 11 (25.6%) used time-series models. Climate and weather data were used in 27 (62.8%) and mosquito abundance or related data were used in 14 (32.6%) articles as model covariates. A total of 140 models were included across the articles. Rainfall (69 models, 49.3%), temperature (66, 47.1%) and tide height (45, 32.1%) were the three most commonly used exposures. Ten (23.3%) studies published data related to model performance. This review summarises current knowledge of RRV modelling and reveals a research gap in comparing predictive methods. To improve predictive accuracy, new methods for forecasting, such as non-linear mixed models and machine learning approaches, warrant investigation.
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Subject code	310
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Spatial and Temporal Patterns of Ross River Virus in Queensland, 2001–2020

Wei Qian / Cameron Hurst / Kathryn Glass / David Harley / Elvina Viennet

Tropical Medicine and Infectious Disease, Vol 6, Iss 145, p

2021 Volume 145

Abstract: Ross River virus (RRV), the most common human arbovirus infection in Australia, causes significant morbidity and substantial medical costs. About half of Australian cases occur in Queensland. We describe the spatial and temporal patterns of RRV disease ... ...

Abstract	Ross River virus (RRV), the most common human arbovirus infection in Australia, causes significant morbidity and substantial medical costs. About half of Australian cases occur in Queensland. We describe the spatial and temporal patterns of RRV disease in Queensland over the past two decades. RRV notifications, human population data, and weather data from 2001 to 2020 were analysed by the Statistical Area Level 2 (SA2) area. Spatial interpolation or linear extrapolation were used for missing weather values and the estimated population in 2020, respectively. Notifications and incidence rates were analysed through space and time. During the study period, there were 43,699 notifications in Queensland. The highest annual number of notifications was recorded in 2015 (6182), followed by 2020 (3160). The average annual incidence rate was 5 per 10,000 people and the peak period for RRV notifications was March to May. Generally, SA2 areas in northern Queensland had higher numbers of notifications and higher incidence rates than SA2 areas in southern Queensland. The SA2 areas with high incidence rates were in east coastal areas and western Queensland. The timely prediction may aid disease prevention and routine vector control programs, and RRV management plans are important for these areas.
Keywords	epidemiology ; Ross River virus ; spatial pattern ; temporal pattern ; disease burden ; Medicine ; R
Subject code	333
Language	English
Publishing date	2021-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Developing a prediction model to estimate the true burden of respiratory syncytial virus (RSV) in hospitalised children in Western Australia

Amanuel Tesfay Gebremedhin / Alexandra B. Hogan / Christopher C. Blyth / Kathryn Glass / Hannah C. Moore

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 12

Abstract: Abstract Respiratory syncytial virus (RSV) is a leading cause of childhood morbidity, however there is no systematic testing in children hospitalised with respiratory symptoms. Therefore, current RSV incidence likely underestimates the true burden. We ... ...

Abstract	Abstract Respiratory syncytial virus (RSV) is a leading cause of childhood morbidity, however there is no systematic testing in children hospitalised with respiratory symptoms. Therefore, current RSV incidence likely underestimates the true burden. We used probabilistically linked perinatal, hospital, and laboratory records of 321,825 children born in Western Australia (WA), 2000–2012. We generated a predictive model for RSV positivity in hospitalised children aged < 5 years. We applied the model to all hospitalisations in our population-based cohort to determine the true RSV incidence, and under-ascertainment fraction. The model’s predictive performance was determined using cross-validated area under the receiver operating characteristic (AUROC) curve. From 321,825 hospitalisations, 37,784 were tested for RSV (22.8% positive). Predictors of RSV positivity included younger admission age, male sex, non-Aboriginal ethnicity, a diagnosis of bronchiolitis and longer hospital stay. Our model showed good predictive accuracy (AUROC: 0.87). The respective sensitivity, specificity, positive predictive value and negative predictive values were 58.4%, 92.2%, 68.6% and 88.3%. The predicted incidence rates of hospitalised RSV for children aged < 3 months was 43.7/1000 child-years (95% CI 42.1–45.4) compared with 31.7/1000 child-years (95% CI 30.3–33.1) from laboratory-confirmed RSV admissions. Findings from our study suggest that the true burden of RSV may be 30–57% higher than current estimates.
Keywords	Medicine ; R ; Science ; Q
Subject code	360
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The changing epidemiology of shigellosis in Australia, 2001-2019.

Aaliya F Ibrahim / Kathryn Glass / Deborah A Williamson / Benjamin G Polkinghorne / Danielle J Ingle / Rose Wright / Martyn D Kirk

PLoS Neglected Tropical Diseases, Vol 17, Iss 3, p e

2023 Volume 0010450

Abstract: Shigellosis is an increasing cause of gastroenteritis in Australia, with prolonged outbreaks reported in remote Aboriginal and Torres Strait Islander (hereafter "First Nations") communities and among men who have sex with men (MSM) in major cities. To ... ...

Abstract	Shigellosis is an increasing cause of gastroenteritis in Australia, with prolonged outbreaks reported in remote Aboriginal and Torres Strait Islander (hereafter "First Nations") communities and among men who have sex with men (MSM) in major cities. To determine associations between Shigella species and demographic and geographic factors, we used multivariate negative binomial regression to analyse national case notifications of shigellosis from 2001 to 2019. Between 2001 and 2019, Australian states and territories reported 18,363 shigellosis cases to the National Notifiable Diseases Surveillance System (NNDSS), of which age, sex and organism information were available for >99% (18,327/18,363) of cases. Of the cases included in our analysis, 42% (7,649/18,327) were S. sonnei, 29% (5,267/18,327) were S. flexneri, 1% (214/18,327) were S. boydii, less than 1% (87/18,327) were S. dysenteriae, and species information was unknown for 28% (5,110/18,327) of cases. Males accounted for 54% (9,843/18,327) of cases, and the highest proportion of cases were in children aged 0-4 years (19%; 3,562/18,327). Crude annual notification rates ranged from 2.2 cases per 100,000 in 2003 and 2011 to 12.4 cases per 100,000 in 2019. Nationally, notification rates increased from 2001 to 2019 with yearly notification rate ratios of 1.04 (95% CI 1.02-1.07) for S. boydii and 1.05 (95% CI 1.04-1.06) for S. sonnei. Children aged 0-4 years had the highest burden of infection for S. flexneri, S. sonnei and S. boydii; and males had a higher notification rate for S. sonnei (notification rate ratio 1.24, 95% CI 1.15-1.33). First Nations Australians were disproportionately affected by shigellosis, with the notification rate in this population peaking in 2018 at 92.1 cases per 100,000 population. Over the study period, we also observed a shift in the testing method used to diagnose shigellosis, with culture independent diagnostic testing (CIDT) increasing from 2014; this also coincided with an increase in notifications of untyped Shigella. This ...
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Subject code	360
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Geostatistical mapping of the seasonal spread of under-reported dengue cases in Bangladesh.

Sifat Sharmin / Kathryn Glass / Elvina Viennet / David Harley

PLoS Neglected Tropical Diseases, Vol 12, Iss 11, p e

2018 Volume 0006947

Abstract: Geographical mapping of dengue in resource-limited settings is crucial for targeting control interventions but is challenging due to the problem of zero-inflation because many cases are not reported. We developed a negative binomial generalised linear ... ...

Abstract	Geographical mapping of dengue in resource-limited settings is crucial for targeting control interventions but is challenging due to the problem of zero-inflation because many cases are not reported. We developed a negative binomial generalised linear mixed effect model accounting for zero-inflation, spatial, and temporal random effects to investigate the spatial variation in monthly dengue cases in Bangladesh. The model was fitted to the district-level (64 districts) monthly reported dengue cases aggregated over the period 2000 to 2009 and Bayesian inference was performed using the integrated nested Laplace approximation. We found that mean monthly temperature and its interaction with mean monthly diurnal temperature range, lagged by two months were significantly associated with dengue incidence. Mean monthly rainfall at two months lag was positively associated with dengue incidence. Densely populated districts and districts bordering India or Myanmar had higher incidence than others. The model estimated that 92% of the annual dengue cases occurred between August and September. Cases were identified across the country with 94% in the capital Dhaka (located almost in the middle of the country). Less than half of the affected districts reported cases as observed from the surveillance data. The proportion reported varied by month with a higher proportion reported in high-incidence districts, but dropped towards the end of high transmission season.
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Language	English
Publishing date	2018-11-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Cost of whole genome sequencing for non-typhoidal Salmonella enterica.

Laura Ford / Kathryn Glass / Deborah A Williamson / Vitali Sintchenko / Jennifer M B Robson / Emily Lancsar / Russell Stafford / Martyn D Kirk

PLoS ONE, Vol 16, Iss 3, p e

2021 Volume 0248561

Abstract: Background While whole genome sequencing (WGS) may be more expensive than traditional testing and polymerase chain reaction (PCR), simple cost comparisons ignore the potential for WGS to reduce the societal costs of non-typhoidal Salmonella enterica ... ...

Abstract	Background While whole genome sequencing (WGS) may be more expensive than traditional testing and polymerase chain reaction (PCR), simple cost comparisons ignore the potential for WGS to reduce the societal costs of non-typhoidal Salmonella enterica through public health action to prevent illness. Methods We determined how many cases the use of WGS data would need to prevent to be cost-equal to serotyping and MLVA, or culture independent testing based on PCR in Australia. We then examined the costs and cost-savings of current typing methods compared with WGS in outbreak scenarios. Results A median of 275 (90% CrI -55-775) or 1.9% (90% CrI -0.4%-5.4%) of notified serotyped Salmonella cases would need to be prevented for WGS to be cost-equal to current typing methods and 1,550 (90% CrI 820-2,725) or 9.6% of all notified Salmonella cases would need to be prevented to be cost-equal to PCR. WGS is likely to result in cost savings in prolonged outbreaks, where data can support earlier public health action. Conclusions Despite currently having a higher cost per isolate, routine WGS of Salmonella was no more expensive than existing typing methods or PCR where >2% of illness was averted.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Interaction of Mean Temperature and Daily Fluctuation Influences Dengue Incidence in Dhaka, Bangladesh.

Sifat Sharmin / Kathryn Glass / Elvina Viennet / David Harley

PLoS Neglected Tropical Diseases, Vol 9, Iss 7, p e

2015 Volume 0003901

Abstract: Local weather influences the transmission of the dengue virus. Most studies analyzing the relationship between dengue and climate are based on relatively coarse aggregate measures such as mean temperature. Here, we include both mean temperature and daily ...

Abstract	Local weather influences the transmission of the dengue virus. Most studies analyzing the relationship between dengue and climate are based on relatively coarse aggregate measures such as mean temperature. Here, we include both mean temperature and daily fluctuations in temperature in modelling dengue transmission in Dhaka, the capital of Bangladesh. We used a negative binomial generalized linear model, adjusted for rainfall, anomalies in sea surface temperature (an index for El Niño-Southern Oscillation), population density, the number of dengue cases in the previous month, and the long term temporal trend in dengue incidence. In addition to the significant associations of mean temperature and temperature fluctuation with dengue incidence, we found interaction of mean and temperature fluctuation significantly influences disease transmission at a lag of one month. High mean temperature with low fluctuation increases dengue incidence one month later. Besides temperature, dengue incidence was also influenced by sea surface temperature anomalies in the current and previous month, presumably as a consequence of concomitant anomalies in the annual rainfall cycle. Population density exerted a significant positive influence on dengue incidence indicating increasing risk of dengue in over-populated Dhaka. Understanding these complex relationships between climate, population, and dengue incidence will help inform outbreak prediction and control.
Keywords	Arctic medicine. Tropical medicine ; RC955-962 ; Public aspects of medicine ; RA1-1270
Subject code	541
Language	English
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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