A systematic review of human and animal leptospirosis in the Pacific Islands reveals pathogen and reservoir diversity

Background The Pacific Islands have environmental conditions highly favourable for transmission of leptospirosis, a neglected zoonosis with highest incidence in the tropics, and Oceania in particular. Recent reports confirm the emergence and outbreaks of leptospirosis in the Pacific Islands, but the epidemiology and drivers of transmission of human and animal leptospirosis are poorly documented, especially in the more isolated and less developed islands. Methodology/Principal findings We conducted a systematic review of human and animal leptospirosis within 25 Pacific Islands (Pls) in Polynesia, Melanesia, Micronesia, as well as Easter Island and Hawaii. We performed a literature search using four international databases for articles published between January 1947 and June 2017. We further included grey literature available on the internet. We identified 148 studies describing leptospirosis epidemiology, but the number of studies varied significantly between Pls. No data were available from four Pls. Human leptospirosis has been reported from 13 Pls, with 63% of all studies conducted in Hawaii, French Polynesia and New Caledonia. Animal leptospirosis has been investigated in 19 Pls and from 14 host species, mainly pigs (18% of studies), cattle (16%) and dogs (11%). Only 13 studies provided information on both human and animal leptospirosis from the same location. Serology results were highly diverse in the region, both in humans and animals. Conclusions/Significance Our study suggests that, as in other tropical regions, leptospirosis is widespread in the Pls while showing some epidemiological heterogeneity. Data are scarce or absent from many Pls. Rodents, cattle, pigs and dogs are all likely to be important carriers, but the relative importance of each animal species in human infection needs to be clarified. Epidemiological surveys with appropriate sampling design, pathogen typing and data analysis are needed to improve our understanding of transmission patterns and to develop effective intervention strategies

Bayesian networks in infectious disease ecoepidemiology

Globally, infectious diseases are responsible for a significant burden on human health. Drivers of disease transmission depend on interactions between humans, the environment, vectors, carriers, and pathogens; transmission dynamics are therefore potentially highly complex. Research in infectious disease eco-epidemiology has been rapidly gaining momentum because of the rising global importance of disease emergence and outbreaks, and growing understanding of the intimate links between human health and the environment. The scientific community is increasingly recognising the need for multidisciplinary translational research, integrated approaches, and innovative methods and tools to optimise risk prediction and control measures. Environmental health experts have also identified the need for more advanced analytical and biostatistical approaches to better determine causality, and deal with unknowns and uncertainties inherent in complex systems. In this paper, we discuss the use of Bayesian networks in infectious disease eco-epidemiology, and the potential for developing dynamic tools for public health decision-making and improving intervention strategies

Lymphatic Filariasis in 2016 in American Samoa: Identifying Clustering and Hotspots Using Non-Spatial and Three Spatial Analytical Methods

Background: American Samoa completed seven rounds of mass drug administration from 2000–2006 as part of the Global Programme to Eliminate Lymphatic Filariasis (LF). However, resurgence was confirmed in 2016 through WHO-recommended school-based transmission assessment survey and a community-based survey. This paper uses data from the 2016 community survey to compare different spatial and non-spatial methods to characterise clustering and hotspots of LF. Method: Non-spatial clustering of infection markers (antigen [Ag], microfilaraemia [Mf], and antibodies (Ab [Wb123, Bm14, Bm33]) was assessed using intra-cluster correlation coefficients (ICC) at household and village levels. Spatial dependence, clustering and hotspots were examined using semivariograms, Kulldorf’s scan statistic and Getis-Ord Gi* statistics based on locations of surveyed households. Results: The survey included 2671 persons (750 households, 730 unique locations in 30 villages). ICCs were higher at household (0.20–0.69) than village levels (0.10–0.30) for all infection markers. Semivariograms identified significant spatial dependency for all markers (range 207–562 metres). Using Kulldorff’s scan statistic, significant spatial clustering was observed in two previously known locations of ongoing transmission: for all markers in Fagali’i and all Abs in Vaitogi. Getis-Ord Gi* statistic identified hotspots of all markers in Fagali’i, Vaitogi, and Pago Pago-Anua areas. A hotspot of Ag and Wb123 Ab was identified around the villages of Nua-Seetaga-Asili. Bm14 and Bm33 Ab hotspots were seen in Maleimi and Vaitogi-Ili’ili-Tafuna. Conclusion: Our study demonstrated the utility of different non-spatial and spatial methods for investigating clustering and hotspots, the benefits of using multiple infection markers, and the value of triangulating results between method

Comparison of immunochromatographic test (ICT) and filariasis test strip (FTS) for detecting lymphatic filariasis antigen in American Samoa, 2016

Circulating filarial antigen (Ag) prevalence, measured using rapid point-of-care tests, is the standard indicator used for monitoring and surveillance in the Global Program to Eliminate Lymphatic Filariasis. In 2015, the immunochromatographic test (ICT) was replaced with the filariasis test strip (FTS), which has higher reported sensitivity. Despite differences in sensitivity, no changes in recommended surveillance targets were made when the FTS was introduced. In 2016, we conducted lymphatic filariasis surveys in American Samoa using FTS, which found higher Ag prevalence than previous surveys that used ICT. To determine whether the increase was real, we assessed the concordance between FTS and ICT results by paired testing of heparinised blood from 179 individuals (63% FTS-positive). ICT had 93.8% sensitivity and 100% specificity for identifying FTS-positive persons, and sensitivity was not associated with age, gender, or presence of microfilariae. Based on these findings, if ICT had been used in the 2016 surveys, the results and interpretation would have been similar to those reported using FTS. American Samoa would have failed Transmission Assessment Survey (TAS) of Grade 1 and 2 children with either test, and community prevalence would not have been significantly different (4.1%, 95% CI, 3.3–4.9% with FTS vs. predicted 3.8%, 95%, CI: 3.1–4.6% with ICT)

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

Detecting and confirming residual hotspots of lymphatic filariasis transmission in American Samoa 8 years after stopping Mass Drug Administration

The Global Programme to Eliminate Lymphatic Filariasis (LF) aims to eliminate the disease as a public health problem by 2020 by conducting mass drug administrations (MDA) and controlling morbidity. Once elimination targets have been reached, surveillance is critical for ensuring that programmatic gains are sustained and challenges include timely identification of residual areas of transmission. WHO guidelines encourage cost-efficient surveillance, such as integration with other population-based surveys. In American Samoa, where LF is caused by Wuchereria bancrofti, and Aedes polynesiensis is the main vector, the LF elimination program has made significant progress. Seven rounds of MDA (albendazole and diethycarbamazine) were completed from 2000 to 2006, and Transmission Assessment Surveys were passed in 2010/2011 and 2015. However, a seroprevalence study using an adult serum bank collected in 2010 detected two potential residual foci of transmission, with Og4C3 antigen (Ag) prevalence of 30.8% and 15.6%. We conducted a follow up study in 2014 to verify if transmission was truly occurring by comparing seroprevalence between residents of suspected hotspots and residents of other villages. In adults from non-hotspot villages (N=602), seroprevalence of Ag (ICT or Og4C3), Bm14 antibody (Ab) and Wb 123 Ab were 1.2% (95% CI 0.6-2.6%), 9.6% (95% CI 7.5-12.3%) and 10.5% (95% CI 7.6-14.3%), respectively. Comparatively, adult residents of Fagali'i (N=38) had significantly higher seroprevalence of Ag (26.9%, 95% CI 17.3-39.4%), Bm14 Ab (43.4%, 95% CI 32.4-55.0%), and Wb123 Ab 55.2% (95% CI 39.6-69.8%). Adult residents of Ili'ili/Vaitogi/Futiga (N=113) also had higher prevalence of Ag and Ab, but differences were not statistically significant. The presence of transmission was demonstrated by 1.1% Ag prevalence (95% CI 0.2% to 3.1%) in 283 children aged 7-13 years who lived in one of the suspected hotspost, including a 9 year old child. Our results provide field evidence that integrating LF surveillance with other surveys is effective and feasible for identifying potential hostpots, and conducting surveillance at worksites provides an efficient method of sampling large populations of adults

Triple-drug treatment is effective for lymphatic filariasis microfilaria clearance in Samoa

Following the first triple-drug mass drug administration (MDA) for lymphatic filariasis in Samoa in 2018, unexpected persistence of microfilaria (Mf) positivity in 18 (15%) of 121 antigen-positive persons was observed in a nationwide household survey 1–2 months later. Of the 18 Mf positive persons, 14 reported taking the MDA, raising concerns about MDA efficacy. In 2019, 5–6 months after the 2018 survey, a monitored treatment study was done to evaluate directly observed weight-based treatment in these Mf positive individuals. Mf presence and density were assessed before and 7 days after treatment, using 1 mL membrane filtered venous blood, and 60 uL thick blood films on slides prepared from venous or fingerprick blood. All 14 participants were still Mf positive on filters from venous blood pre-treatment samples, but two were negative by slide made from the same samples. Mf were cleared completely by day 7 in 12 of 13 participants followed up, and by day 30 in the remaining participant. Filtered blood using EDTA samples (to reduce clumping of Mf) is preferred over slides alone for improving the likelihood of detecting Mf and estimating their density. The triple-drug MDA strategy was effective at clearing Mf when given and taken at the correct dose

Spatial distribution and populations at risk of A. lumbricoides and T. trichiura co-infections and infection intensity classes: an ecological study.

BACKGROUND: Soil-transmitted helminth (STH) infections are highly prevalent in the Philippines. Mapping the prevalence and high-intensity of STH co-infections can help guide targeted intervention programmes to reduce morbidity, especially among vulnerable school-aged children. In this study, we aimed to predict the spatial distribution of the prevalence of Ascaris lumbricoides and Trichuris trichiura co-infection and infection intensity classes in the Philippines to identify populations most in need of interventions. METHODS: Data on STH infections from 29,919 individuals during the nationwide parasitological survey in 2005 to 2007 were included in the analysis. To geographically predict the prevalence of A. lumbricoides and T. trichiura co-infections and infection intensity classes, Bayesian multinomial geostatistical models were built including age, sex, environmental variables and a geostatistical random effect. The number of individuals co-infected and belonging to each of the infection intensity classes in 2017 was forecast by combining our predictive prevalence maps with population density maps. RESULTS: Our models showed that school-aged children (5-19 years) are most at risk of A. lumbricoides and T. trichiura co-infections and of moderate/high infection intensity compared to other age groups. We identified target provinces where the likelihood of STH-associated morbidity was highest: Luzon (Bulacan, Benguet, Cavite, Sorsogon, Metropolitan Manila, Pampanga and Rizal), the Visayas (Cebu, Iloilo, Leyte and Negros Occidental), and in Mindanao (Agusan Del Norte, Davao Del Sur, Davao Oriental, Lanao Del Sur, Maguindanao, Misamis Oriental, Sulu and Zamboanga Del Sur). Luzon had the highest estimated number of school-aged children with A. lumbricoides and T. trichiura co-infections (estimated total 89,400), followed by the Visayas (38,300) and Mindanao (20,200). CONCLUSIONS: Our study provided epidemiological evidence to highlight national priority areas for controlling co-infections and high intensity infections in the Philippines. Our maps could assist more geographically targeted interventions to reduce the risk of STH-associated morbidity in the Philippines

Potential strategies for strengthening surveillance of lymphatic filariasis in American Samoa after mass drug administration: reducing ‘number needed to test’ by targeting older age groups, hotspots, and household members of infected persons

Under the Global Programme to Eliminate Lymphatic Filariasis (LF), American Samoa conducted mass drug administration (MDA) from 2000–2006. Despite passing Transmission Assessment Surveys (TAS) in 2011/2012 and 2015, American Samoa failed TAS-3 in 2016, with antigen (Ag) prevalence of 0.7% (95%CI 0.3–1.8%) in 6–7 year-olds. A 2016 community survey (Ag prevalence 6.2% (95%CI 4.4–8.5%) in age ≥8 years) confirmed resurgence. Using data from the 2016 survey, this study aims to i) investigate antibody prevalence in TAS-3 and the community survey, ii) identify risk factors associated with being seropositive for Ag and anti-filarial antibodies, and iii) compare the efficiency of different sampling strategies for identifying seropositive persons in the post-MDA setting. Antibody prevalence in TAS-3 (n = 1143) were 1.6% for Bm14 (95%CI 0.9–2.9%), 7.9% for Wb123 (95%CI 6.4–9.6%), and 20.2% for Bm33 (95%CI 16.7–24.3%); and in the community survey (n = 2507), 13.9% for Bm14 (95%CI 11.2–17.2%), 27.9% for Wb123 (95%CI 24.6–31.4%), and 47.3% for Bm33 (95%CI 42.1–52.6%). Multivariable logistic regression was used to identify risk factors for being seropositive for Ag and antibodies. Higher Ag prevalence was found in males (adjusted odds ratio [aOR] 3.01), age ≥18 years (aOR 2.18), residents of Fagali’i (aOR 15.81), and outdoor workers (aOR 2.61). Ag prevalence was 20.7% (95%CI 9.7–53.5%) in households of Ag-positive children identified in TAS-3. We used NNTestav (average number needed to test to identify one positive) to compare the efficiency of the following strategies for identifying persons who were seropositive for Ag and each antibody: i) TAS of 6–7 year-old children, ii) population representative surveys of older age groups, and iii) targeted surveillance of subpopulations at higher risk of being seropositive (older ages, householders of Ag-positive TAS children, and known hotspots). For Ag, NNTestav ranged from 142.5 for TAS, to <5 for households of index children. NNTestav was lower in older ages, and highest for Ag, followed by Bm14, Wb123 and Bm33 antibodies. We propose a multi-stage surveillance strategy, starting with population-representative sampling (e.g. TAS or population representative survey of older ages), followed by strategies that target subpopulations and/or locations with low NNTestav. This approach could potentially improve the efficiency of identifying remaining infected persons and residual hotspots. Surveillance programs should also explore the utility of antibodies as indicators of transmission

Spatial epidemiological approaches to inform leptospirosis surveillance and control: a systematic review and critical appraisal of methods

Leptospirosis is a global zoonotic disease that the transmission is driven by complex geographical and temporal variation in demographics, animal hosts and socioecological factors. This results in complex challenges for the identification of high‐risk areas. Spatial and temporal epidemiological tools could be used to support leptospirosis control programs, but the adequacy of its application has not been evaluated. We searched literature in six databases including PubMed, Web of Science, EMBASE, Scopus, SciELO and Zoological Record to systematically review and critically assess the use of spatial and temporal analytical tools for leptospirosis and to provide general framework for its application in future studies. We reviewed 115 articles published between 1930 and October 2018 from 41 different countries. Of these, 65 (56.52%) articles were on human leptospirosis, 39 (33.91%) on animal leptospirosis and 11 (9.5%) used data from both human and animal leptospirosis. Spatial analytical (n = 106) tools were used to describe the distribution of incidence/prevalence at various geographical scales (96.5%) and to explored spatial patterns to detect clustering and hot spots (33%). A total of 51 studies modelled the relationships of various variables on the risk of human (n = 31), animal (n = 17) and both human and animal infection (n = 3). Among those modelling studies, few studies had generated spatially structured models and predictive maps of human (n = 2/31) and animal leptospirosis (n = 1/17). In addition, nine studies applied time‐series analytical tools to predict leptospirosis incidence. Spatial and temporal analytical tools have been greatly utilized to improve our understanding on leptospirosis epidemiology. Yet the quality of the epidemiological data, the selection of covariates and spatial analytical techniques should be carefully considered in future studies to improve usefulness of evidence as tools to support leptospirosis control. A general framework for the application of spatial analytical tools for leptospirosis was proposed