A first nation-wide assessment of soil-transmitted helminthiasis in Fijian primary schools, and factors associated with the infection, using a lymphatic filariasis transmission assessment survey as surveillance platform.

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.

Predictive risk mapping of an environmentally-driven infectious disease using spatial Bayesian networks: A case study of leptospirosis in Fiji.

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.

Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study.

BACKGROUND: Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji. METHODS: We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate. FINDINGS: The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each covariate. Maximum rainfall had the least variation across space (median OR 1·30, IQR 1·27-1·35), and distance to river varied the most (1·45, 1·35-2·05). The predictive risk map indicated that the highest risk was in the interior of Viti Levu, and the agricultural region and southern end of Vanua Levu. INTERPRETATION: GWLR provided a valuable method for modelling spatial heterogeneity of covariates for leptospirosis infection and their relative importance over space. Results of GWLR could be used to inform more place-specific interventions, particularly for diseases with strong environmental or sociodemographic drivers of transmission. FUNDING: WHO, Australian National Health & Medical Research Council, University of Queensland, UK Medical Research Council, Chadwick Trust.

Island-Wide Surveillance of Gastrointestinal Protozoan Infection on Fiji by Expanding Lymphatic Filariasis Transmission Assessment Surveys as an Access Platform.

As part of lymphatic filariasis (LF) transmission assessment surveys (TAS) on Fiji, an island-wide assessment of gastrointestinal protozoan infection was performed by inspection of a concomitant stool sample collection to investigate the distribution of parasitic protozoa. All grade 1 and 2 students of 69 schools on the two main islands were targeted in two phases (one in the Western Division and the other in the Central and Northern Divisions, except Taveuni sub-Division of Northern), where fecal samples of 1,800 students were available for coproscopy using formalin-ether-acetate concentration. The overall prevalence of Giardia infection was 1.6%, having 2.2% in Western and 0.8% in Central/Northern Divisions (P = 0.094). The school-level prevalence of giardiasis ranged from 0% to 15.4%, and hotspot analysis using the Getis-Ord Gi* method detected spatial heterogeneity of giardiasis prevalence in schools around Lautoka (Z-score = 3.36, P value < 0.05), an area affected by Cyclone Kofi in February 2014. Any protozoan infection prevalence was 4.9% in Western and 4.4% in Central/Northern Divisions (P = 0.825). Real-time polymerase chain reaction analysis to confirm the findings from a parasitological examination of a 10% stool archive in 95% ethanol from Western Division revealed an elevated prevalence of giardiasis up to 22.4%, the presence of Entamoeba histolytica, and the absence of Cryptosporidium parvum. Obtaining stool samples alongside LF TAS is a convenient access platform for cosurveillance of gastrointestinal protozoan infection and has pinpointed hitherto unknown hotspots of giardiasis in urban city centers of Fiji. This calls for greater attention to apply tailored water, sanitation and hygiene measures for the control of these parasites.

Role of Environmental Factors in Shaping Spatial Distribution of Salmonella enterica Serovar Typhi, Fiji.

Fiji recently experienced a sharp increase in reported typhoid fever cases. To investigate geographic distribution and environmental risk factors associated with Salmonella enterica serovar Typhi infection, we conducted a cross-sectional cluster survey with associated serologic testing for Vi capsular antigen-specific antibodies (a marker for exposure to Salmonella Typhi in Fiji in 2013. Hotspots with high seroprevalence of Vi-specific antibodies were identified in northeastern mainland Fiji. Risk for Vi seropositivity increased with increased annual rainfall (odds ratio [OR] 1.26/quintile increase, 95% CI 1.12-1.42), and decreased with increased distance from major rivers and creeks (OR 0.89/km increase, 95% CI 0.80-0.99) and distance to modeled flood-risk areas (OR 0.80/quintile increase, 95% CI 0.69-0.92) after being adjusted for age, typhoid fever vaccination, and home toilet type. Risk for exposure to Salmonella Typhi and its spatial distribution in Fiji are driven by environmental factors. Our findings can directly affect typhoid fever control efforts in Fiji.

A cross-sectional seroepidemiological survey of typhoid fever in Fiji.

Fiji, an upper-middle income state in the Pacific Ocean, has experienced an increase in confirmed case notifications of enteric fever caused by Salmonella enterica serovar Typhi (S. Typhi). To characterize the epidemiology of typhoid exposure, we conducted a cross-sectional sero-epidemiological survey measuring IgG against the Vi antigen of S. Typhi to estimate the effect of age, ethnicity, and other variables on seroprevalence. Epidemiologically relevant cut-off titres were established using a mixed model analysis of data from recovering culture-confirmed typhoid cases. We enrolled and assayed plasma of 1787 participants for anti-Vi IgG; 1,531 of these were resident in mainland areas that had not been previously vaccinated against S. Typhi (seropositivity 32.3% (95%CI 28.2 to 36.3%)), 256 were resident on Taveuni island, which had been previously vaccinated (seropositivity 71.5% (95%CI 62.1 to 80.9%)). The seroprevalence on the Fijian mainland is one to two orders of magnitude higher than expected from confirmed case surveillance incidence, suggesting substantial subclinical or otherwise unreported typhoid. We found no significant differences in seropositivity prevalences by ethnicity, which is in contrast to disease surveillance data in which the indigenous iTaukei Fijian population are disproportionately affected. Using multivariable logistic regression, seropositivity was associated with increased age (odds ratio 1.3 (95% CI 1.2 to 1.4) per 10 years), the presence of a pit latrine (OR 1.6, 95%CI 1.1 to 2.3) as opposed to a septic tank or piped sewer, and residence in settlements rather than residential housing or villages (OR 1.6, 95% CI 1.0 to 2.7). Increasing seropositivity with age is suggestive of low-level endemic transmission in Fiji. Improved sanitation where pit latrines are used and addressing potential transmission routes in settlements may reduce exposure to S. Typhi. Widespread unreported infection suggests there may be a role for typhoid vaccination in Fiji, in addition to public health management of cases and outbreaks.

Human Leptospirosis Infection in Fiji: An Eco-epidemiological Approach to Identifying Risk Factors and Environmental Drivers for Transmission.

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.