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WALLABY Pilot Survey: Public release of HI kinematic models for more than 100 galaxies from phase 1 of ASKAP pilot observations

We present the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY) Pilot Phase I Hi kinematic models. This first data release consists of Hi observations of three fields in the direction of the Hydra and Norma clusters, and the NGC 4636 galaxy group.

WALLABY pilot survey: Public release of H i data for almost 600 galaxies from phase 1 of ASKAP pilot observations

We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder.

What Heterogeneities in Individual-level Mobility Are Lost During Aggregation? Leveraging GPS Logger Data to Understand Fine-scale and Aggregated Patterns of Mobility

Human movement drives spatial transmission patterns of infectious diseases. Population-level mobility patterns are often quantified using aggregated data sets, such as census migration surveys or mobile phone data. These data are often unable to quantify individual-level travel patterns and lack the information needed to discern how mobility varies by demographic groups. Individual-level datasets can capture additional, more precise, aspects of mobility that may impact disease risk or transmission patterns and determine how mobility differs across cohorts; however, these data are rare, particularly in locations such as sub-Saharan Africa.

Spatio-temporal dynamics of three diseases caused by Aedes-borne arboviruses in Mexico

The intensity of transmission of Aedes-borne viruses is heterogeneous, and multiple factors can contribute to variation at small spatial scales. Illuminating drivers of heterogeneity in prevalence over time and space would provide information for public health authorities. The objective of this study is to detect the spatiotemporal clusters and determine the risk factors of three major Aedes-borne diseases, Chikungunya virus, Dengue virus, and Zika virus clusters in Mexico.

Malaria treatment for prevention: a modelling study of the impact of routine case management on malaria prevalence and burden

Testing and treating symptomatic malaria cases is crucial for case management, but it may also prevent future illness by reducing mean infection duration. Measuring the impact of effective treatment on burden and transmission via field studies or routine surveillance systems is difficult and potentially unethical. This project uses mathematical modeling to explore how increasing treatment of symptomatic cases impacts malaria prevalence and incidence. 

Biases in Routine Influenza Surveillance Indicators Used to Monitor Infection Incidence and Recommendations for Improvement

Monitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.

Estimating the impact of imported malaria on local transmission in a near elimination setting: a case study from Bhutan

Bhutan has achieved a substantial reduction in both malaria morbidity and mortality over the last two decades and is aiming for malaria elimination certification in 2025. However, a significant percentage of malaria cases in Bhutan are imported (acquired in another country). The aim of the study was to understand how importation drives local malaria transmission in Bhutan.

Childhood-onset type 1 diabetes in Western Australia: An update on incidence and temporal trends from 2001 to 2022

To determine the incidence and incidence trends over 2001-2022 of childhood-onset type 1 diabetes (T1D) in Western Australia and assess the impact of the COVID-19 pandemic.

Mapping tuberculosis prevalence in Ethiopia using geospatial meta-analysis\

Reliable and detailed data on the prevalence of tuberculosis (TB) with sub-national estimates are scarce in Ethiopia. We address this knowledge gap by spatially predicting the national, sub-national and local prevalence of TB, and identifying drivers of TB prevalence across the country.

The ecological determinants of severe dengue: A Bayesian inferential model

Low socioeconomic status (SES), high temperature, and increasing rainfall patterns are associated with increased dengue case counts. However, the effect of climatic variables on individual dengue virus (DENV) serotypes and the extent to which serotype count affects the rate of severe dengue in Mexico have not been studied before.