Search

This article presents a study evaluating student perceptions of learning experiences creating ArcGIS StoryMaps. The Taxonomy of Educational Objectives (Bloom's Taxonomy) provides a framework for organising, analysing, and interpreting a survey completed by 154 students from high school to postgraduate. Using a mix of quantitative and qualitative methods we found student perceptions of the level of learning to be similar across education cohorts in the cognitive domain, exhibit some differences in psychomotor domain, and are markedly different in the affective domain. In terms of what they learned, postgraduates perceive the experience as being mostly about communicating ideas or storytelling more than undergraduates who, in addition, tend to see the experience as preparing maps and working with geographic information systems. Undergraduates tend to conflate gaining knowledge (cognitive) with learning skills (psychomotor), suggesting a greater focus on working with the technology. Most students across all education levels found the learning experience challenging and beneficial (affective) though some students did not. We conclude that while the creation of StoryMaps is good for student retention and offers an effective scaffolding framework for geography and GIS education, it is important for educators to design StoryMap learning activities using clearly defined learning outcomes and assessment rubrics. [ABSTRACT FROM AUTHOR]

With an estimated disease burden of 20.6 million cases in low- and middle-income countries in 2010, typhoid fever remains an enteric disease of public health concern (1,2). Typhoid fever cases [...]

Background: Soil-transmitted helminthiasis (STH) is endemic in Fiji but its prevalence is not known and likely to have changed after a decade of mass drug administration (MDA) for lymphatic filariasis (LF). By linking with LF transmission assessment surveys (LF-TAS), we undertook the first nation-wide assessment of STH in Fijian primary schools, as well as an analysis of factors associated with STH infections. Methodology/Principal findings: A cross-sectional assessment for STH was conducted in all four Divisions of Fiji from 2014 to 2015. In the Western, Central, and Northern Divisions, schools were sub-sampled after LF-TAS, while, in the Eastern Division, schools were selected via simple random sampling. For the diagnosis of STH, stool samples were examined by coproscopy with a single Kato-Katz thick smear (KK) and the formol-ether-acetate concentration technique, except for the samples from the Eastern Division where only KK was used. Mean prevalence of any STH among class 1–2 students at the national level was 10.5% (95% CI: 6.9–15.5). Across the three Divisions via LF-TAS, the prevalence levels for ascariasis were 8.7% (95% CI: 4.3–16.6), hookworm 3.9% (95% CI: 2.3–6.6) and trichuriasis 0%. In the Eastern Division, ascariasis prevalence was 13.3% (95% CI: 6.4–25.6), and hookworm 0.7% (95% CI: 0.2–2.5), with one case of trichuriasis. Among class 3–8 students, ascariasis prevalence was lower. Lower risk of any STH was associated with wearing shoes (adjusted OR 0.54, 95% CI: 0.32–0.90) and having piped water from the Fiji Water Authority at home (adjusted OR 0.48, 95% CI: 0.25–0.92). Conclusions: After a decade of community-based LF-MDA, STH in school-age children in Fiji is now close to 10%, but localities of endemicity remain. Preventive chemotherapy should be maintained in areas with elevated STH prevalence alongside targeted delivery of integrated WASH interventions. LF-TAS has provided an opportunity to develop future public health surveillance platforms. Author summary: Soil-transmitted helminth infections (STH) are common in school-age children in the developing world and can cause morbidity to affected human beings depending on the intensity and duration of infection. In Fiji, where there has been a long history of implementing a program for eliminating lymphatic filariasis (LF) due to inadequate sanitation conditions, there is a need to assess the current epidemiological profile of STH since the LF mass drug administration (MDA) as a community-based intervention may soon stop. By linking with ongoing LF-transmission assessment surveys (LF-TAS), we undertook the first nation-wide assessment of STH in Fijian primary schools. Mean prevalence of STH across three Divisions of Fiji in class 1–2 students chosen for LF-TAS was 12.1% (ascariasis 8.7%, hookworm 3.9%, and trichuriasis 0%). In the remaining Division, the Eastern, ascariasis prevalence was 13.3%, and hookworm 0.7%. Wearing shoes and use of piped water reduced the prevalence of STH. It is concluded that STH in school-age children in Fiji is at low levels, but hot spot localities of elevated STH endemicity remain. Therefore, preventive chemotherapy should be maintained in these localities alongside targeted delivery of appropriate integrated water, sanitation and hygiene interventions. [ABSTRACT FROM AUTHOR]

Introduction: Leptospirosis is a zoonotic disease responsible for over 1 million severe cases and 60,000 deaths annually. The wide range of animal hosts and complex environmental drivers of transmission make targeted interventions challenging, particularly when restricted to regression-based analyses which have limited ability to deal with complexity. In Fiji, important environmental and socio-demographic factors include living in rural areas, poverty, and livestock exposure. This study aims to examine drivers of transmission under different scenarios of environmental and livestock exposures. Methods: Spatial Bayesian networks (SBN) were used to analyse the influence of livestock and poverty on the risk of leptospirosis infection in urban compared to rural areas. The SBN models used a combination of spatially-explicit field data from previous work and publically available census information. Predictive risk maps were produced for overall risk, and for scenarios related to poverty, livestock, and urban/rural setting. Results: While high, rather than low, commercial dairy farm density similarly increased the risk of infection in both urban (12% to 18%) and rural areas (70% to 79%), the presence of pigs in a village had different impact in rural (43% to 84%) compared with urban areas (4% to 24%). Areas with high poverty rates were predicted to have 26.6% and 18.0% higher probability of above average seroprevalence in rural and urban areas, respectively. In urban areas, this represents >300% difference between areas of low and high poverty, compared to 43% difference in rural areas. Conclusions: Our study demonstrates the use of SBN to provide valuable insights into the drivers of leptospirosis transmission under complex scenarios. By estimating the risk of leptospirosis infection under different scenarios, such as urban versus rural areas, these subgroups or areas can be targeted with more precise interventions that focus on the most relevant key drivers of infection. [ABSTRACT FROM AUTHOR]

Leptospirosis is an important zoonotic disease in the Pacific Islands. In Fiji, two successive cyclones and severe flooding in 2012 resulted in outbreaks with 576 reported cases and 7% case-fatality. We conducted a cross-sectional seroprevalence study and used an eco-epidemiological approach to characterize risk factors and drivers for human leptospirosis infection in Fiji, and aimed to provide an evidence base for improving the effectiveness of public health mitigation and intervention strategies. Antibodies indicative of previous or recent infection were found in 19.4% of 2152 participants (81 communities on the 3 main islands). Questionnaires and geographic information systems data were used to assess variables related to demographics, individual behaviour, contact with animals, socioeconomics, living conditions, land use, and the natural environment. On multivariable logistic regression analysis, variables associated with the presence of Leptospira antibodies included male gender (OR 1.55), iTaukei ethnicity (OR 3.51), living in villages (OR 1.64), lack of treated water at home (OR 1.52), working outdoors (1.64), living in rural areas (OR 1.43), high poverty rate (OR 1.74), living <100m from a major river (OR 1.41), pigs in the community (OR 1.54), high cattle density in the district (OR 1.04 per head/sqkm), and high maximum rainfall in the wettest month (OR 1.003 per mm). Risk factors and drivers for human leptospirosis infection in Fiji are complex and multifactorial, with environmental factors playing crucial roles. With global climate change, severe weather events and flooding are expected to intensify in the South Pacific. Population growth could also lead to more intensive livestock farming; and urbanization in developing countries is often associated with urban and peri-urban slums where diseases of poverty proliferate. Climate change, flooding, population growth, urbanization, poverty and agricultural intensification are important drivers of zoonotic disease transmission; these factors may independently, or potentially synergistically, lead to enhanced leptospirosis transmission in Fiji and other similar settings. [ABSTRACT FROM AUTHOR]

A national land cover map derived from moderate resolution imaging spectrometer (MODIS) imagery products was developed for Honduras, Central America. We compared two methods of image classification: a cluster busting (CB) classification technique and a classification and regression tree (CART) algorithm. Field data samples were used to validate the resulting classifications. Inthe classification process, we used: a Google Earth™ sampling scheme, a time series of MODIS's Enhanced Vegetation Index (EVI) and digital elevation data(shuttle radar topography mission, SRTM). The CART classification method provided a more accurate classification (Kappa coefficient, K = 74%, overall model accuracy = 79.6%) while compared to the CB classification (Kappa coefficient, K = 9%, overall model accuracy = 25.1%). The findings are useful to design more accurate MODIS classification protocols in tropical countries. [ABSTRACT FROM PUBLISHER]

Regression models are the standard approaches used in infectious disease epidemiology, but have limited ability to represent causality or complexity. We explore Bayesian networks (BNs) as an alternative approach for modelling infectious disease transmission, using leptospirosis as an example. Data were obtained from a leptospirosis study in Fiji in 2013. We compared the performance of naïve versus expert-structured BNs for modelling the relative importance of animal species in disease transmission in different ethnic groups and residential settings. For BNs of animal exposures at the individual/household level, R 2 for predicted versus observed infection rates were 0.59 for naïve and 0.75–0.93 for structured models of ethnic groups; and 0.54 for naïve and 0.93–1.00 for structured models of residential settings. BNs provide a promising approach for modelling infectious disease transmission under complex scenarios. The relative importance of animal species varied between subgroups, with important implications for more targeted public health control strategies. [ABSTRACT FROM AUTHOR]