The global distribution and transmission limits of lymphatic filariasis: past and present
© Cano et al.; licensee BioMed Central Ltd. 2014
Received: 1 July 2014
Accepted: 29 September 2014
Published: 11 October 2014
Lymphatic filariasis (LF) is one of the neglected tropical diseases targeted for global elimination by 2020 and to guide elimination efforts countries have, in recent years, conducted extensive mapping surveys. Documenting the past and present distribution of LF and its environmental limits is important for a number of reasons. Here, we present an initiative to develop a global atlas of LF and present a new global map of the limits of LF transmission.
We undertook a systematic search and assembly of prevalence data worldwide and used a suite of environmental and climatic data and boosted regression trees (BRT) modelling to map the transmission limits of LF.
Data were identified for 66 of the 72 countries currently endemic and for a further 17 countries where LF is no longer endemic. Our map highlights a restricted and highly heterogeneous distribution in sub-Saharan Africa, with transmission more widespread in West Africa compared to east, central and southern Africa where pockets of transmission occur. Contemporary transmission occurs across much of south and South-east Asia and the Pacific. Interestingly, the risk map reflects environmental conditions suitable for LF transmission across Central and South America, including the southern States of America, although active transmission is only known in a few isolated foci. In countries that have eliminated LF, our predictions of environmental suitability are consistent with historical distribution.
The global distribution of LF is highly heterogeneous and geographically targeted and sustained control will be required to achieve elimination. This first global map can help evaluate the progress of interventions and guide surveillance activities.
KeywordsLymphatic filariasis Global distribution Transmission limits Boosted regression tree modelling
Lymphatic filariasis (LF) is a mosquito-borne disease which in its advanced forms can manifest as severe lymphoedema, hydrocele and elephantiasis . The majority of global cases are caused by Wuchereria bancrofti, with Brugia malayi and B. timori as important local causes of the disease in South-east Asia. These nematode parasites are transmitted by various species of mosquito vectors from the genera Anopheles, Aedes, Culex, Mansonia and Ochlerotatus. LF is one of nine infectious diseases targeted for global elimination . The selection of LF for elimination was based on (i) the absence of animal reservoirs for W. bancrofti (the most common form of LF) and only a small animal reservoir for B. malayi (which occurs in restricted foci) ,, (ii) the existence of effective and practical interventions to interrupt transmission, and (iii) availability of an accurate diagnostic tool . The main intervention strategy is mass drug administration (MDA) with albendazole in combination with diethylcarbamazine (DEC) (or ivermectin in countries where onchocerciasis is endemic) to entire communities in districts where the prevalence of LF is equal or more than 1% , supported by vector control to reduce exposure to mosquitoes and morbidity management to alleviate suffering and prevent disability of those affected by the disease ,. During the last half century, several countries have successfully eliminated LF, including Japan, China, South Korea, the Solomon Islands, Egypt and Togo -.
A key component of national elimination programmes is a detailed understanding of the geographical distribution of LF so that all endemic areas can be targeted. Early attempts to map the distribution of LF included detailed literature reviews - or mapping at national or sub-national levels -. Although useful for estimating the global burden of LF , such national estimates belie the highly focal distribution of LF - and cannot be used to geographically target control. The mapping of LF has in recent years been greatly facilitated by the use of simple and rapid detection tests for W. bancrofti (antigen-based test) and Brugia spp (antibody-based test), based on the immuno-chromatographic test (ICT card test), which avoids the need to collect blood at night and the time-consuming preparation and examination of blood slides -. By the end of 2012, 59 out of the 72 endemic countries had completed national mapping surveys . The results of these surveys highlight the marked within-country geographical heterogeneity ,-. LF mapping is ongoing in the remaining endemic countries except Eritrea, where it has not started yet .
To augment available field surveys, a number of recent studies have sought to predict the distribution of LF on the basis of climatic and environmental factors. This approach is predicated on the fact that W. bancrofti is inefficiently transmitted, requiring thousands of infective bites to establish a patent infection , and as such LF is only likely to occur where climatic conditions are suitable to support mosquito vector populations over extended time periods ,. An early attempt to develop a risk map for LF in Africa was by Lindsay and Thomas in 2000, based on data from 32 studies using frequentist logistic regression and coarse-resolution environmental data . More recently, Slater and Michael have used maximum entropy ecological niche modelling  and Bayesian model-based geostatistics  to predict the geographical occurrence and distribution of LF in Africa. Risk maps using environmental factors or spatial interpolation have also been developed at national or sub-national scales in West Africa , Egypt  and India .
Building on this previous work, we describe a new initiative to develop a global atlas of LF infection, which aims to collate all available survey data into a single, freely available resource and describe the historical and contemporary distribution of LF. Understanding these distributions has more than cartographic interest. First, changes in the epidemiology of LF over time can be quantified. Second, factors underlying such changes can be investigated in an effort to assess the degree to which changes are directly related to the scaling-up of interventions or other factors. Third, analysis of the historical risks of infection prior to large-scale intervention can be used to quantify the intervention needs required to reach programme goals , identify factors that contribute to the persistence of transmission, help define the intrinsic sensitivity (receptivity) of transmission to future changes in the intensity and frequency of control -, and provide a basis to stratify surveillance activities. The specific aims of the present paper are (i) to detail the methods and approaches used to develop the database, (ii) to map historical and contemporary distributions of LF, and (iii) to delineate the global transmission limits of LF. The work is conducted within the context of the Global Atlas of Helminth Infections (www.thiswormyworld.org)  which aims to develop a suite of geographical resources and tools for neglected tropical diseases (NTDs).
Approaches to the diagnosis and mapping of LF
Night collection and examination of blood slides is considered the gold standard approach for detecting microfilariae. However, the sensitivity of this approach crucially relies on the volume of blood sampled . Other parasitological methods, such as Knott’s concentration test and membrane filtration , increase the sensitivity of diagnosis but are prohibitively expensive for routine use. Alternatively, the presence of W. bancrofti antigenaemia can be detected using the ICT card test - and presence of specific IgG4 antibodies to Brugia spp can be detected using the Brugia Rapid™ test -. Surveys for the mapping of LF have been based on a variety of sampling designs, including the rapid geographical assessment of Bancroftian filariasis (RAGFIL) method ,, lot quality assurance sampling ,, population-based household surveys  and sentinel site surveys ,,, with the choice of survey methodology dependent on available resources and the stage of the control programme .
Identification of survey data
Our approach to identify suitable data follows that developed originally by Norman Stoll in his seminal work This Wormy World in 1947 , and adopted by efforts to map malaria , as well as soil-transmitted helminth and schistosome infections -. Relevant data on the prevalence of LF were identified through a combination of (i) structured searches of electronic bibliographic databases, (ii) additional searches of the `grey’ literature, including unpublished surveys and government and international archives, and (iii) direct contact with researchers and control programme managers. The online databases PubMed, MEDLINE, EMBASE and SCOPUS were used to identify relevant studies for LF, using the following predefined Medical Subject Heading (MeSH) terms: lymphatic filariasis, bancroftian filariasis, Wuchereria bancrofti, Brugia malayi, Brugia timori, malayan filariasis AND current and former country names. All permutations of MeSH terms were entered, with no restrictions on language or date of publication. The abstracts of returned articles were reviewed and if they did not explicitly report prevalence data, they were discarded. When the abstract was not available, pre-selection was made according to the title. Authors were contacted when additional information was required or when data needed to be disaggregated. Studies were included if they provided: (i) the number of people surveyed, (ii) the number of LF positive cases, (iii) details about the methodology of diagnosis and (iv) details of the specific site where they were conducted, regardless of the administrative level. Surveys reporting only prevalence data without provision of the denominator were also included as these can be used to delineate the limits of transmission. Baseline data from clinical and diagnostic trials fulfilling the inclusion criteria were abstracted, whereas surveys carried out at hospitals, prisons, mental institutions or military facilities were excluded.
Data were extracted into a customized Microsoft Access (Microsoft 2007) database and linked to an identical SQL Server database. Abstracted data included three types of information: (i) epidemiological data on survey method, type of diagnostic method, dates, age range and gender of targeted people, time of survey (day or night), ongoing control activities and number of MDA rounds undertaken in the area at the time of survey, number of people sampled, number of positive individuals and prevalence, diagnostic method used, blood sampling volumes for detection of microfilaraemia and, where available, morbidity data based on hydrocele and/or lymphoedema; (ii) each record was assigned a unique identifier which linked the record to the source publication which was included in an Endnote library (Thomson Reuters 2010), with a pdf copy of each publication obtained; and (iii) all data were linked to first and second administrative units, based on the United Nations’ Second Administrative Level Boundaries (SALB) database  and the GADM version 2 database of Global Administrative Areas .
Geo-positioning of survey data
Environment and demographic covariates
Description of environmental variables used to model the global distribution of lymphatic filariasis transmission
Mean minimum temperature
Mean of average monthly minimum temperature across all 12 months (period 1950-2000)
Annual mean temperature
Mean of average monthly mean temperature across all 12 months (period 1950-2000)
Precipitation in wettest quarter
Total precipitation in the wettest quarter
Precipitation in driest quarter
Total precipitation in the driest quarter
Mean of accumulative precipitation across all 12 months (period 1950-2000)
Indicator of the degree of dryness of the climate at a given location, and result from dividing the mean annual precipitation by the mean annual potential evapo-transpiration
Metres above the sea level obtained by radar imagery
Mean of 8-day composite MODIS images for the period 2001 to 2005. EVI raw values (scale from 0 to 1) have been multiplied by 1,000 for being storage as integers.
Global Land Cover 2006
A simplified version of seven major land cover classes obtained from the UN Global Land Cover (22 classes)
Population density (1995-2015)
Average population density 1995-2015
WHO regions: AFRO/EMRO (African and Eastern Mediterranean regions), AMRO (Americas region), SEARO (South-east Asia) and WPRO (western Pacific)
Cost (in time units) to access to large urban areas
Estimates of population density were obtained from the Gridded Population of the World (GPW) , which was used to classify areas as urban, peri-urban or rural areas, based on the assumption that urban extents (UE) have a population densities ≥1,000 persons/km2, peri-urban >250 persons/km2 within a 15 km distance from UE edge, and rural <250 persons/km2 and/or >15 km from the UE edge . A gridded map of urban accessibility 1 km resolution was obtained from the European Commission Joint Research Centre Global Environment Monitoring Unit (JRC) . This dataset defined urban accessibility as the predicted time taken to travel from that grid cell to a city of ≥50,000 persons in the year 2000 using land- or water-based travel. Finally, a gridded map at 5 km resolution of the main geographic regions (Europe, Asia, Africa and America) was created. Western Pacific countries were grouped upon the Asian region whilst countries located in the Arabian Peninsula were included within the African region.
To bring the spatial resolution of these covariate layers in line with the spatial accuracy of the survey data, covariates were resampled to a common 5 km resolution raster layout based on the WGS-1984 Web Mercator projection using ArcGIS 10.1. (ESRI Inc., Redlands CA, USA). Bilinear interpolation was applied to resample numeric (continuous) raster data sets, whereas nearest neighbour interpolation was used with ordinal raster layers. Possible collinearity between the covariates was explored using cross-correlations. All correlation coefficients were less than 0.7, indicating that covariates were largely orthogonal.
Predicting the probability of LF transmission using boosted regression trees
Boosted regression trees (BRT) modelling was used for mapping the spatial limits of LF transmission. This approach has been shown to have higher predictive accuracy than other distribution models  and has been successfully applied to map dengue  and malaria vector mosquitoes . BRT combines two machine learning approaches; regression trees (simple hierarchical models which allow non-linear effects of predictors) and boosting (fitting ensemble models by iterative improvements on the existing ensemble ,). A first step in the BRT approach is the definition of occurrence and absence data. Records of disease occurrence were defined as surveys during which one or more cases of LF were detected, regardless of diagnostic method used. Absence records were defined as surveys conducted prior to large-scale control activities and from which no cases of LF were reported. Because relatively few absence records were available (prevalence surveys are typically carried out in areas where disease presence is expected), these data were supplemented with pseudo-absence records following a similar procedure to that used for mapping dengue and malaria vectors ,. Five thousand pseudo-absence data points were generated at random in areas known not to be endemic for LF based on expert knowledge -, or those areas considered as unsuitable habitats for mosquito breeding - areas of bare and hyper-arid land, as classified by the GlobCover  and Global Aridity Index datasets . In order to maximise the ability of the model to discriminate between suitable and unsuitable areas, regression weights were used to down-weight pseudo-absence records, so that the summed weights of the absence and pseudo-absence records matched that of the presence records.
In the second stage, eight environmental variables along with altitude, population density, accessibility and macro-geographical regions were used to predict LF occurrence in a single BRT model, in order to explore the relative importance of each factor in explaining the global occurrence of LF (Table 1). Those factors that contributed little (relative contribution <2%) to the single BRT model were disregarded to build the final ensemble BRT model. Thus, six covariates (precipitation in the wettest quarter, annual minimum temperature, population density 1990-2015, elevation, enhanced vegetation index and regions) were subsequently selected and eventually used to build the final risk map.
In order to estimate uncertainty in the model and the resulting risk maps, we finally fitted an ensemble of 120 BRT submodels, each fitted to a random bootstrap of the full dataset. The predicted distributions of LF from each of these submodels were then averaged to generate the final risk map. Predictive performance of each submodel was evaluated using the following statistics: proportion correctly classified (PCC), sensitivity (proportion of presences correctly classified), specificity (proportion of absences correctly classified), Kappa (k) and area under the receiver operator characteristic (AUC). The mean and confidence intervals for each statistic were used to evaluate the predictive performance of the ensemble BRT model. Marginal effect curves were plotted to visualise dependencies between the probability of LF occurrence and each of the covariates. These show the marginal effect of each covariate on the response after averaging the effects of all other covariates. Finally, the relative contribution of each covariate (the percentage of tree branches in each submodel that used the covariate) to the final BRT model was also quantified.
Defining limits of transmission
The resulting predictive map quantifies the environmental suitability for LF transmission. In order to convert this continuous metric into a binary map outlining the limits of transmission, a threshold value of suitability was determined, above which transmission was assumed to be possible. Based on the receiver operating characteristic curve, a threshold value of environmental suitability was chosen which maximised the trade-off between sensitivity, specificity and PCC. Whilst the resulting map delineates environmental suitability for LF transmission, it may include areas where transmission does not actually occur, due either to the disease never having been imported into the area or the consequence of control leading to local elimination. To reflect this, we masked the environmental distribution map to remove areas which are known to be currently non-endemic according to WHO ,, and other sources ,,,,. Non-endemicity was considered when no cases had been reported for the last 10 years and transmission assessment surveys confirmed the interruption of LF transmission.
Characteristics of surveys included in the lymphatic filariasis database
WHO - regions&
Current endemic countries
Countries with data
Number of surveys identified
Indicators concerning to community-level geopositioned surveys
Surveys by period
Type of survey
Of eligible surveys, 7,852 (87.1%) represented disaggregated, community-based surveys of which 7,420 (94.3%) could be geo-positioned: 6,442 to point locations and 978 to small areas, such as households with scattered distributions, small islands and small administrative areas. Data extracted from published sources accounted for 53.2% of included survey locations and were the main source of information in the SEARO and WPRO regions. Grey literature, which included country reports, GAELF reports and other unpublished articles, accounted for 46.8% of survey locations, and were the main source of data in the AFRO/EMRO region. The majority (82.9%) of data points were obtained through mapping or prevalence surveys, whereas 1,141 (15.4%) were sentinel site surveys and 16 transmission assessment surveys. Among mapping/prevalence surveys, 609 (9.9%) surveys were obtained by lot quality assurance sampling (LQAS), mostly conducted after 2000. Finally, 110 surveys derive from a countrywide clinical survey in Thailand, 1949-1950, where lymphoedema of lower limbs were recorded upon systematic population screening by headmen of cantons  - this survey was included as it provided the best nationwide data on occurrence for Thailand.
Factors associated with LF transmission
Global LF transmission map
LF transmission by region
In the Americas region, LF transmission is predicted to occur throughout north and north-east regions of South-America, Central America, major islands in the Caribbean region (Haiti and the Dominican Republic) and marginally in coastal areas of southern United States (Figure 8). LF has been eliminated from 20 countries in the Americas region, and known current endemicity is restricted to Brazil, Guyana and the Hispaniola (Dominican Republic and Haiti) .
Here we present a first global map of the distribution and transmission limits of LF. This work is opportune as it provides a basis for tracking and interpreting progress in control over time and can define the pre-control transmission limits, which, in turn, can inform the intensity and duration of control ,. Our work additionally provides insight to post-MDA surveillance by identifying areas of highest transmission which may be more prone to the resurgence of transmission following cessation of interventions.
In the current analysis we identify the environmental limits of potential transmission. We demonstrate that the probability of LF transmission increases with increasing precipitation, temperature and certain vegetation types but decreases with increasing altitude (Figure 4). These findings are consistent with previous analyses of environmental correlates at continental , and country ,, scales and are, undoubtedly, linked to temperature-related variation in vector survival and parasite development within the vector ,,,. Our risk map, developed using boosted regression tree modelling, shows that the environmental conditions suitable for LF transmission occurs throughout the forest and savannah regions of West Africa, coastal east Africa and Madagascar and restricted foci in central and southern Africa. Suitable environmental conditions also occur across tropical areas of south and South-east Asia and the Pacific as well as large areas of Central and South America, including the southern States of America. Interestingly, however, active transmission in Central and South America is restricted to isolated foci; the possible reasons for this discrepancy are discussed below. Our predictions of environmental suitability in temperate regions are consistent with documented historical distributions prior to large scale intervention and local elimination in Japan, South Korea, and southern China - (Figure 10), the north coast of Australia  and southeastern coast of United States .
The probability of LF transmission is additionally associated with population density. Such an association probably reflects differences in the distribution of different vector species and their habitat preference and susceptibility to LF -. In rural areas of Africa, LF is transmitted by Anopheles species, whereas in urban settings in east Africa and the Nile Delta transmission is by Culex quinquefasciatus,. In West Africa, Culex mosquitoes, although widely distributed , are considered refractory to infection -, although some studies have demonstrated compatibility between West African strains of W. bancrofti and Culex and Mansonia mosquitoes -. Culex transmission also occurs in Asia - and Culex quinquefasciatus is the only vector known in the Americas ,. The true extent of LF transmission in urban settings, especially in sub-Saharan Africa, remains poorly documented ,,, and further work is warranted.
Our work provides interesting insight into the regional distributions of LF. In sub-Saharan Africa, LF transmission is highly heterogeneous (Figure 7), with the highest potential risk in the forest and savannah regions of West Africa and coastal areas of eastern Africa and Madagascar. Scattered and relatively small areas of high-moderate risk are predicted in central Africa. This distribution of LF across Africa corresponds well with the known historical distribution of LF on the continent , and predicts transmission in countries which have yet to be extensively mapped, such as Gabon  or Angola . Our predictions indicate a more geographically restricted distribution of LF (Figure 7) than earlier spatial predictions using environmental factors ,. Our analysis included some 4,624 surveys across most endemic countries in Africa, whereas previous analysis , included fewer than 700 surveys which were mainly concentrated in West Africa, Egypt, Sudan, Kenya, Tanzania and Madagascar; studies which were typically conducted in known areas of transmission. Such paucity and biased clustering of data coupled with the use of regression-based modelling will result in the smoothing of prevalence across large areas and overestimate prevalence in unsurveyed areas ,. Our use of BRT modelling overcomes the geographical bias of data by the use of pseudo absences , which are randomly generated from areas known to be unsuitable for mosquito breeding or non-endemic for LF.
Our risk map predicts widespread environmental suitability of LF in Central and South America, whereas active transmission is known to occur only in isolated foci . We suggest two possible reasons for this discrepancy. First, historically, LF occurred across 20 countries and territories in the region ,, including islands of the Caribbean and coastal areas of southeast Unites States, where indigenous cases were reported as far north as Philadelphia, until 1930s . A combination of intensive vector control and improvements in public sanitary works resulted in the local elimination in these settings. Second, the transmission of LF in the Americas is strongly influenced by historical socioeconomic and demographic factors, rather than environmental factors. Transmission of LF was introduced to the Americas by slaves transported from West Africa to work in sugarcane plantations during the 17th and 18th centuries . Initially, large numbers of slaves were brought to Barbados and Brazil, and subsequently sent to other islands of the Caribbean, to the north American colonies (South Carolina and Virginia) and northern countries of South America (Venezuela, Guyana, French Guiana, and Suriname) ,,. Upon introduction, W. bancrofti readily adapted from transmission by African Anopheles mosquitoes to transmission by Culex mosquitoes commonly found in the overcrowded and insanitary towns and cities of the Americas. However, it appears that transmission has remained restricted to those areas where the disease was firstly introduced. In settings where socioeconomic and sanitary conditions have improved and interventions have been implemented in recent decades, the disease has gradually disappeared, for example in the Caribbean region . In those countries with active transmission today - Brazil, the Dominican Republic, Guyana and Haiti ,, infection occurs mainly in urban settings and is strongly associated with poor socioeconomic conditions -. Future work will explore the interplay of environmental, socioeconomic factors and coverage of interventions on the distribution and prevalence of LF.
The distribution of LF in Asia exhibits marked regional trends. In India, high transmission occurs across the northern Indian (Gangetic) plain which borders Nepal and Bangladesh, eastern and south western coastal areas, areas in the central Deccan region in the south and on the Andaman and Nicobar Islands (Figure 9). Moderate-low transmission occurs in inland areas of southwestern India. Such a distribution is consistent with previous district-level mapping  (Figure 10D) and a previous national-level environmental risk model . The predicted environmental limits for China, Japan and South Korea correspond well with the historical distribution prior to large control and local elimination ,, (Figure 10A-B). Although LF has been declared eliminated in China, the vectors remain and occasional imported cases have been reported , so that long-term surveillance is required to ensure that recrudescence does not occur. In contrast to the predictions for India and east Asia, our environmental-based map overestimates risk in the southeast Asian countries of Vietnam, Cambodia, Thailand and PDR Laos, which are considered to have limited transmission . In Thailand, B. malayi transmission occurs in the south of the country  and W. bancrofti is endemic in the western provinces bordering Myanmar , but control measures implemented since the 1960s have dramatically reduced transmission .
We have sought to conduct an exhaustive search assembly of historical and contemporary data on LF occurrence and prevalence and have used rigorous methodology to predict the occurrence of LF transmission, but recognise a number of limitations. The BRT model presented here is driven by environmental parameters and spatial configuration of habitats that allow persistence of species in landscapes. This modelling approach has been applied successfully to map the distribution of mosquito-borne diseases, such as dengue and malaria, which are transmitted by one mosquito genera with limited species diversity within geographical regions ,. LF is unique among mosquito-borne diseases because it is transmitted by mosquito species belonging to five genera: Aedes, Anopheles, Culex, Mansonia and Ochlerotatus. In Africa, where LF is transmitted principally by Anopheles species, the disease distribution corresponds well with the known historical distribution patterns across the continent. This is not surprising because the environmental factors determining the abundance and distribution of Anopheles mosquitoes across Africa have not changed much in the peri-domestic environment in the past 20 years. However, our model performs less well in areas where LF is transmitted by Culex mosquitoes, especially Culex quinquefasciatus, which is predominately an urban mosquito with breeding habits that are influenced more by human activity than environmental factors ,. It follows, therefore, that environmental factors impact on transmission differently for different mosquito species. For example, precipitation, an important determinant in our environmental model, it likely to affect Anopheles and Culex species differently. While frequent rainfall generally tends to increase the densities of adult mosquitoes by producing breeding sites, their densities may be reduced by the flushing of sites when precipitation is high. It may be that anopheline and culicine mosquitoes differ in their response to heavy rainfall since they breed in different habitats. In areas suitable for transmission by Culex quinquefasciatus, human factors, such as sanitary and housing conditions, may play an important role in transmission. Our model may have therefore overestimated the current limits for LF in Culex-transmitted areas.
We additionally recognise the limitations of the current empirical evidence base, especially in regard to unpublished surveys that found an absence of transmission. We did not perform age correction of prevalence data since our current focus was on the occurrence of transmission. For similar reasons we did not adjust for differences in sensitivity of various diagnostic methods . Future work will seek to model the prevalence of LF infection and will take into account such differences in age patterns and diagnostic method. Finally, our study focused on the environmental limits of LF transmission and, as discussed above, we recognise our model does not capture the socioeconomic and intervention-related dynamics of transmission. This is the subject of ongoing work investigating the spatiotemporal distribution of LF and the degree to which changes are related to the scaling-up of interventions or other factors.
Despite the limitations and caveats acknowledged above, the assembled database represents a unique resource and the global map provides the best currently available indication of the global distribution of LF, past and present. Consistent with the open access approach of the Global Atlas of Helminth Infection, the assembled data and developed maps are publicly available (www.thiswormyworld.org). As the global LF community moves towards elimination, the assembled data maps and model predictions will help track progress and increase the cost-effectiveness of surveillance activities post-control.
aAFRO/EMRO region: Seychelles and Mayotte; AMRO region: Antigua & Barbuda, Costa Rica, Cuba, French Guiana, Martinique, Puerto Rico, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad & Tobago, Venezuela and Virgin Islands, United States of America; and WPRO region: Cook Islands, Palau and Solomon Islands.
Jorge Cano and Maria P Rebollo joint first authors.
We thank all the authors who have provided access to survey data – for a full list of acknowledgements see: www.thiswormyworld.org. We would also like to thank David Addiss and Mark Bradley for their comments at early stages of the work. This work was funded by grants from the Bill & Melinda Gates Foundation (OPP1053338: JC, NG, SWL, SIH, SJB; OPP1033751: JC, RLP, SJB), GlaxoSmithKline (JC, SJB, MJB) and the United Kingdom Department for International Development (MPR, LK-H and MJB) and Senior Research Fellowships from the Wellcome Trust (095066: SIH; 098045: SJB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Taylor MJ, Hoerauf A, Bockarie M: Lymphatic filariasis and onchocerciasis. Lancet. 2010, 376: 1175-1185.PubMedView ArticleGoogle Scholar
- Meeting of the International Task Force for Disease Eradication, January 2014. Wkly Epidemiol Rec. 2014, 89: 153-160.Google Scholar
- Kanjanopas K, Choochote W, Jitpakdi A, Suvannadabba S, Loymak S, Chungpivat S, Nithiuthai S: Brugia malayi in a naturally infected cat from Narathiwat Province, southern Thailand. Southeast Asian J Trop Med Public Health. 2001, 32: 585-587.PubMedGoogle Scholar
- Lek-Uthai U, Tomoen W: Susceptibility of Mansonia uniformis to Brugia malayi microfilariae from infected domestic cat. Southeast Asian J Trop Med Public Health. 2005, 36: 434-441.PubMedGoogle Scholar
- Ottesen EA, Duke BO, Karam M, Behbehani K: Strategies and tools for the control/elimination of lymphatic filariasis. Bull World Health Organ. 1997, 75: 491-503.PubMed CentralPubMedGoogle Scholar
- Preventive Chemotherapy in Human Helminthiasis. 2006, World Health Organization, GenevaGoogle Scholar
- Bockarie MJ, Molyneux DH: The end of lymphatic filariasis?. BMJ. 2009, 338: b1686-PubMedView ArticleGoogle Scholar
- WHO position statement on integrated vector management to control malaria and lymphatic filariasis. Wkly Epidemiol Rec. 2011, 86: 121-127.Google Scholar
- Webber RH, Webber RH: Eradication of Wuchereria bancrofti infection through vector control. Trans R Soc Trop Med Hyg. 1979, 73: 722-724.PubMedView ArticleGoogle Scholar
- Ramzy RM, El Setouhy M, Helmy H, Ahmed ES, Abd Elaziz KM, Farid HA, Shannon WD, Weil GJ: Effect of yearly mass drug administration with diethylcarbamazine and albendazole on bancroftian filariasis in Egypt: a comprehensive assessment. Lancet. 2006, 367: 992-999.PubMedView ArticleGoogle Scholar
- Tada I: Lymphatic filariasis and its control in Japan -the background of success. Trop Med Health. 2011, 39: 15-20.PubMed CentralPubMedGoogle Scholar
- De-Jian S, Xu-Li D, Ji-Hui D: The history of the elimination of lymphatic filariasis in China. Infect Dis Poverty. 2013, 2: 30-PubMed CentralPubMedView ArticleGoogle Scholar
- Sodahlon YK, Dorkenoo AM, Morgah K, Nabiliou K, Agbo K, Miller R, Datagni M, Seim A, Mathieu E: A success story: Togo is moving toward becoming the first Sub-Saharan African nation to eliminate lymphatic filariasis through mass drug administration and countrywide morbidity alleviation. PLoS Negl Trop Dis. 2013, 7: e2080-PubMed CentralPubMedView ArticleGoogle Scholar
- Hawking F: The distribution of Bancroftian filariasis in Africa. Bull World Health Organ. 1957, 16: 581-592.PubMed CentralPubMedGoogle Scholar
- Hawking F, Denham DA: The distribution of human filariasis throughout the world. Part I. the Pacific Region, including New Guinea. Trop Dis Bull. 1976, 73: 347-373.PubMedGoogle Scholar
- Hawking F, Hawking F: The distribution of human filariasis throughout the world. Part II. Asia. Trop Dis Bull. 1976, 73: 967-1016.PubMedGoogle Scholar
- Sasa M: Human Filariasis. A Global Survey of Epidemiology and Control. 1976, University Park Press, BaltimoreGoogle Scholar
- Hawking F: The distribution of human filariasis throughout the world. Part III. Africa. Trop Dis Bull. 1977, 74: 649-679.PubMedGoogle Scholar
- Hawking F: The distribution of human filariasis throughout the world part IV. America. Trop Dis Bull. 1979, 76: 693-710.PubMedGoogle Scholar
- Kimura E, Rim HJ, Dejian S, Weerasooriya M: Filariasis in Asia and Western Pacific Islands. 2005, FAP Journal Ltd, JapanGoogle Scholar
- Brygoo ER: La filariose humain a Madagascar. Arch Inst Pasteur Madagascar. 1958, 26: 23-39.Google Scholar
- OCCGE: Rapport final de la neuviem conference technique de I’OCCGE, 21-25 April 1969. Bobo-Dioulasso, Burkina Faso. 1969.Google Scholar
- Brengues J, Bouchité B, Nelson G, Ouedraogo C, Gbaguidi P, Dyemkouma A, Ochoumare J: La filariose de Bancroft en Afrique de l’Ouest. 1975, ORSTOM, ParisGoogle Scholar
- Kuhlow F, Zielke E: Distribution and prevalence of Wuchereria bancrofti in various parts of Liberia. Tropenmed Parasitol. 1976, 27: 93-100.PubMedGoogle Scholar
- Ou ZY, Luo JM, Luo XC: The filariasis situation in Guangdong Province, China. Southeast Asian J Trop Med Public Health. 1991, 22: 477-488.PubMedGoogle Scholar
- Apiwathnasorn C, Kanjanopas K, Thammapalo S, Loymak S, Samung Y, Prummongkol S, Molyneux D: Application of GIS to the characterization of filariasis transmission in Narathiwat Province. Southeast Asian J Trop Med Public Health. 2003, 34 (Suppl2): 61-66.PubMedGoogle Scholar
- Michael E, Bundy DA, Grenfell BT: Re-assessing the global prevalence and distribution of lymphatic filariasis. Parasitology. 1996, 112 (Pt 4): 409-428.PubMedView ArticleGoogle Scholar
- Hassan AN, Dister S, Beck L: Spatial analysis of lymphatic filariasis distribution in the Nile Delta in relation to some environmental variables using geographic information system technology. J Egypt Soc Parasitol. 1998, 28: 119-131.PubMedGoogle Scholar
- Gyapong JO, Remme JH: The use of grid sampling methodology for rapid assessment of the distribution of bancroftian filariasis. Trans R Soc Trop Med Hyg. 2001, 95: 681-686.PubMedView ArticleGoogle Scholar
- Gyapong JO, Kyelem D, Kleinschmidt I, Agbo K, Ahouandogbo F, Gaba J, Owusu-Banahene G, Sanou S, Sodahlon YK, Biswas G, Kale OO, Molyneux DH, Roungou JB, Thomson MC, Remme J: The use of spatial analysis in mapping the distribution of bancroftian filariasis in four West African countries. Ann Trop Med Parasitol. 2002, 96: 695-705.PubMedView ArticleGoogle Scholar
- Mukoko DA, Pedersen EM, Masese NN, Estambale BB, Ouma JH: Bancroftian filariasis in 12 villages in Kwale district, Coast province, Kenya - variation in clinical and parasitological patterns. Ann Trop Med Parasitol. 2004, 98: 801-815.PubMedView ArticleGoogle Scholar
- Boyd A, Won KY, McClintock SK, Donovan CV, Laney SJ, Williams SA, Pilotte N, Streit TG, de Rochars MV B, Lammie PJ: A community-based study of factors associated with continuing transmission of lymphatic filariasis in Leogane, Haiti. PLoS Negl Trop Dis. 2010, 4: e640-PubMed CentralPubMedView ArticleGoogle Scholar
- Weil GJ, Lammie PJ, Weiss N: The ICT filariasis test: a rapid-format antigen test for diagnosis of bancroftian filariasis. Parasitol Today. 1997, 13: 401-404.PubMedView ArticleGoogle Scholar
- Bhumiratana A, Koyadun S, Suvannadabba S, Karnjanopas K, Rojanapremsuk J, Buddhirakkul P, Tantiwattanasup W: Field trial of the ICT filariasis for diagnosis of Wuchereria bancrofti infections in an endemic population of Thailand. Southeast Asian J Trop Med Public Health. 1999, 30: 562-568.PubMedGoogle Scholar
- Phantana S, Sensathein S, Songtrus J, Klagrathoke S, Phongnin K: ICT filariasis test: a new screening test for Bancroftian filariasis. Southeast Asian J Trop Med Public Health. 1999, 30: 47-51.PubMedGoogle Scholar
- Rahmah N, Taniawati S, Shenoy RK, Lim BH, Kumaraswami V, Anuar AK, Hakim SL, Hayati MI, Chan BT, Suharni M, Ramachandran CP: Specificity and sensitivity of a rapid dipstick test (Brugia Rapid) in the detection of Brugia malayi infection. Trans R Soc Trop Med Hyg. 2001, 95: 601-604.PubMedView ArticleGoogle Scholar
- Supali T, Rahmah N, Djuardi Y, Sartono E, Rückert P, Fischer P: Detection of filaria-specific IgG4 antibodies using Brugia Rapid test in individuals from an area highly endemic for Brugia timori. Acta Trop. 2004, 90: 255-261.PubMedView ArticleGoogle Scholar
- Melrose W, Rahmah N: Use of Brugia Rapid dipstick and ICT test to map distribution of lymphatic filariasis in the Democratic Republic of Timor-Leste. Southeast Asian J Trop Med Public Health. 2006, 37: 22-25.PubMedGoogle Scholar
- Sustaining the drive to overcome the global impact of neglected tropical diseases: second WHO report on neglected diseases. 2013, World Health Organization, GenevaGoogle Scholar
- Sherchand JB, Obsomer V, Thakur GD, Hommel M: Mapping of lymphatic filariasis in Nepal. Filaria J. 2003, 2: 7-PubMed CentralPubMedView ArticleGoogle Scholar
- de Rochars MV B, Milord MD, St Jean Y, Desormeaux AM, Dorvil JJ, Lafontant JG, Addiss DG, Streit TG: Geographic distribution of lymphatic filariasis in Haiti. Am J Trop Med Hyg. 2004, 71: 598-601.Google Scholar
- Ngwira BM, Tambala P, Perez AM, Bowie C, Molyneux DH: The geographical distribution of lymphatic filariasis infection in Malawi. Filaria J. 2007, 6: 12-PubMed CentralPubMedView ArticleGoogle Scholar
- Koroma JB, Bangura MM, Hodges MH, Bah MS, Zhang Y, Bockarie MJ: Lymphatic filariasis mapping by immunochromatographic test cards and baseline microfilaria survey prior to mass drug administration in Sierra Leone. Parasit Vectors. 2012, 5: 10-PubMed CentralPubMedView ArticleGoogle Scholar
- Okorie PN, Ademowo GO, Saka Y, Davies E, Okoronkwo C, Bockarie MJ, Molyneux DH, Kelly-Hope LA: Lymphatic filariasis in Nigeria; Micro-stratification Overlap Mapping (MOM) as a prerequisite for cost-effective resource utilization in control and surveillance. PLoS Negl Trop Dis. 2013, 7: e2416-PubMed CentralPubMedView ArticleGoogle Scholar
- Shiferaw W, Kebede T, Graves PM, Golasa L, Gebre T, Mosher AW, Tadesse A, Sime H, Lambiyo T, Panicker KN, Richards FO, Hailu A: Lymphatic filariasis in western Ethiopia with special emphasis on prevalence of Wuchereria bancrofti antigenaemia in and around onchocerciasis endemic areas. Trans R Soc Trop Med Hyg. 2012, 106: 117-127.PubMedView ArticleGoogle Scholar
- Wijegunawardana NDD, Gunawardene YINS, Manamperi A, Senarathne H, Abeyewickreme W: Geographic information system (GIS) mapping of lymphatic filariasis endemic areas of Gampaha District, Sri Lanka based on epidemiological and entomological screening. Southeast Asian J Trop Med Public Health. 2012, 43: 557-566.PubMedGoogle Scholar
- Southgate BA: Intensity and efficiency of transmission and the development of microfilaraemia and disease: their relationship in lymphatic filariasis. J Tropical Med Hygiene. 1992, 95: 1-12.Google Scholar
- Brooker S, Michael E: The potential of geographical information systems and remote sensing in the epidemiology and control of human helminth infections. Adv Parasitol. 2000, 47: 245-288.PubMedView ArticleGoogle Scholar
- Lindsay SW, Thomas CJ: Mapping and estimating the population at risk from lymphatic filariasis in Africa. Trans R Soc Trop Med Hyg. 2000, 94: 37-45.PubMedView ArticleGoogle Scholar
- Slater H, Michael E: Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling. PLoS One. 2012, 7: e32202-PubMed CentralPubMedView ArticleGoogle Scholar
- Slater H, Michael E: Mapping, Bayesian geostatistical analysis and spatial prediction of lymphatic filariasis prevalence in Africa. PLoS One. 2013, 8: e71574-PubMed CentralPubMedView ArticleGoogle Scholar
- Stanton MC, Molyneux DH, Kyelem D, Bougma RW, Koudou BG, Kelly-Hope LA: Baseline drivers of lymphatic filariasis in Burkina Faso. Geospat Health. 2013, 8: 159-173.PubMedView ArticleGoogle Scholar
- Hassan AN: Bancroftian filariasis: spatial patterns, environmental correlates and landscape predictors of disease risk. J Egypt Soc Parasitol. 2004, 34: 501-513.PubMedGoogle Scholar
- Sabesan S, Raju HK, Srividya A, Das PK: Delimitation of lymphatic filariasis transmission risk areas: a geo-environmental approach. Filaria J. 2006, 5: 12-PubMed CentralPubMedView ArticleGoogle Scholar
- Michael E, Malecela-Lazaro MN, Simonsen PE, Pedersen EM, Barker G, Kumar A, Kazura JW: Mathematical modelling and the control of lymphatic filariasis. Lancet Infect Dis. 2004, 4: 223-234.PubMedView ArticleGoogle Scholar
- Garrett-Jones C: Prognosis for interruption of malaria transmission through assessment of the mosquito’s vectorial capacity. Nature. 1964, 204: 1173-1175.PubMedView ArticleGoogle Scholar
- Duerr HP, Dietz K, Eichner M: Determinants of the eradicability of filarial infections: a conceptual approach. Trends Parasitol. 2005, 21: 88-96.PubMedView ArticleGoogle Scholar
- Poncon N, Tran A, Toty C, Luty AJ, Fontenille D: A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France. Malar J. 2008, 7: 147-PubMed CentralPubMedView ArticleGoogle Scholar
- Gambhir M, Michael E: Complex ecological dynamics and eradicability of the vector borne macroparasitic disease, lymphatic filariasis. PLoS One. 2008, 3: e2874-PubMed CentralPubMedView ArticleGoogle Scholar
- Brooker S, Hotez PJ, Bundy DA: The global atlas of helminth infection: mapping the way forward in neglected tropical disease control. PLoS Negl Trop Dis. 2010, 4: e779-PubMed CentralPubMedView ArticleGoogle Scholar
- Michael E, Malecela MN, Zervos M, Kazura JW: Global eradication of lymphatic filariasis: the value of chronic disease control in parasite elimination programmes. PLoS One. 2008, 3: e2936-PubMed CentralPubMedView ArticleGoogle Scholar
- Eberhard ML, Lammie PJ: Laboratory diagnosis of filariasis. Clin Lab Med. 1991, 11: 977-1010.PubMedGoogle Scholar
- Research on Rapid Geographical Assessment of Bancroftian Filariasis. 1998, World Health Organization, GenevaGoogle Scholar
- Srividya A, Lall R, Ramaiah KD, Ramu K, Hoti SL, Pani SP, Das PK: Development of rapid assessment procedures for the delimitation of lymphatic filariasis-endemic areas. Trop Med Int Health. 2000, 5: 64-71.PubMedView ArticleGoogle Scholar
- Chu BK, Deming M, Biritwum NK, Bougma WR, Dorkenoo AM, El-Setouhy M, Fischer PU, Gass K, Gonzalez de Pena M, Mercado-Hernandez L, Kyelem D, Lammie PJ, Flueckiger RM, Mwingira UJ, Noordin R, Offei Owusu I, Ottesen EA, Pavluck A, Pilotte N, Rao RU, Samarasekera D, Schmaedick MA, Settinayake S, Simonsen PE, Supali T, Taleo F, Torres M, Weil GJ, Won KY: Transmission assessment surveys (TAS) to define endpoints for lymphatic filariasis mass drug administration: a multicenter evaluation. PLoS Negl Trop Dis. 2013, 7: e2584-PubMed CentralPubMedView ArticleGoogle Scholar
- King JD, Eigege A, Umaru J, Jip N, Miri E, Jiya J, Alphonsus KM, Sambo Y, Graves P, Richards F: Evidence for stopping mass drug administration for lymphatic filariasis in some, but not all local government areas of plateau and nasarawa States, Nigeria. Am J Trop Med Hyg. 2012, 87: 272-280.PubMed CentralPubMedView ArticleGoogle Scholar
- Report on the mid-Term Assessment of Microfilaraemia Reduction in Sentinel Sites of 13 Countries of the Global Programme to Eliminate Lymphatic Filariasis. Weekly Epidemiological Record. 2004, 357-368. 357-368, 79Google Scholar
- Msyamboza K, Ngwira B, Banda R, Mkwanda S, Brabin B: Sentinel surveillance of lymphatic filariasis, schistosomiasis soil transmitted helminths and malaria in rural southern Malawi. Malawi Med J. 2010, 22: 12-14.PubMed CentralPubMedView ArticleGoogle Scholar
- Solomon AW, Engels D, Bailey RL, Blake IM, Brooker S, Chen JX, Chen JH, Churcher TS, Drakeley CJ, Edwards T, Fenwick A, French M, Gabrielli AF, Grassl NC, Harding-Esch EM, Holland MJ, Koukounari A, Lammie PJ, Leslie J, Mabey DC, Rhajaoui M, Secor WE, Stothard JR, Wei H, Willingham AL, Zhou XN, Peeling RW: A diagnostics platform for the integrated mapping, monitoring, and surveillance of neglected tropical diseases: rationale and target product profiles. PLoS Negl Trop Dis. 2012, 6: e1746-PubMed CentralPubMedView ArticleGoogle Scholar
- Stoll NR: This wormy world. J Parasitol. 1947, 33: 1-18.PubMedView ArticleGoogle Scholar
- Guerra CA, Hay SI, Lucioparedes LS, Gikandi PW, Tatem AJ, Noor AM, Snow RW: Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project. Malar J. 2007, 6: 17-PubMed CentralPubMedView ArticleGoogle Scholar
- Hay SI, Guerra CA, Gething PW, Patil AP, Tatem AJ, Noor AM, Kabaria CW, Manh BH, Elyazar IR, Brooker S, Smith DL, Moyeed RA, Snow RW: A world malaria map: plasmodium falciparum endemicity in 2007. PLoS Med. 2009, 6: e1000048-PubMed CentralPubMedView ArticleGoogle Scholar
- Brooker S, Rowlands M, Haller L, Savioli L, Bundy DA: Towards an atlas of human helminth infection in sub-Saharan Africa: the use of geographical information systems (GIS). Parasitol Today. 2000, 16: 303-307.PubMedView ArticleGoogle Scholar
- Brooker S, Kabatereine NB, Smith JL, Mupfasoni D, Mwanje MT, Ndayishimiye O, Lwambo NJ, Mbotha D, Karanja P, Mwandawiro C, Muchiri E, Clements AC, Bundy DA, Snow RW: An updated atlas of human helminth infections: the example of East Africa. Int J Health Geogr. 2009, 8: 42-PubMed CentralPubMedView ArticleGoogle Scholar
- Hurlimann E, Schur N, Boutsika K, Stensgaard AS, Laserna de Himpsl M, Ziegelbauer K, Laizer N, Camenzind L, Di Pasquale A, Ekpo UF, Simoonga C, Mushinge G, Saarnak CF, Utzinger J, Kristensen TK, Vounatsou P: Toward an open-access global database for mapping, control, and surveillance of neglected tropical diseases. PLoS Negl Trop Dis. 2011, 5: e1404-PubMed CentralPubMedView ArticleGoogle Scholar
- The Second Administrative Level Boundaries data set project., [http://www.unsalb.org/]
- GADM database of Global Administrative Areas., [http://www.gadm.org/]
- Bing Maps., [http://www.bing.com/maps/]
- NGA-GEOnet Names Server (Country Files)., [http://earth-info.nga.mil/gns/html/index.html]
- Fuzzy Gazetteer., [http://isodp.hof-university.de/fuzzyg/query/]
- Open Street Map., [http://www.openstreetmap.org/]
- Lindsay SW, Denham DA, McGreevy PB: The effect of humidity on the transmission of Brugia pahangi infective larvae to mammalian hosts by Aedes aegypti. Trans R Soc Trop Med Hyg. 1984, 78: 19-22.PubMedView ArticleGoogle Scholar
- Samarawickrema WA, Spears GF, Sone F, Ichimori K, Cummings RF: Filariasis transmission in Samoa. II. Some factors related to the development of microfilariae in the intermediate host. Ann Trop Med Parasitol. 1985, 79: 101-107.PubMedGoogle Scholar
- Lardeux F, Cheffort J: Temperature thresholds and statistical modelling of larval Wuchereria bancrofti (Filariidea:Onchocercidae) developmental rates. Parasitology. 1997, 114 (Pt 2): 123-134.PubMedView ArticleGoogle Scholar
- Lardeux F, Cheffort J: Ambient temperature effects on the extrinsic incubation period of Wuchereria bancrofti in Aedes polynesiensis: implications for filariasis transmission dynamics and distribution in French Polynesia. Med Vet Entomol. 2001, 15: 167-176.PubMedView ArticleGoogle Scholar
- de Souza D, Kelly-Hope L, Lawson B, Wilson M, Boakye D: Environmental factors associated with the distribution of Anopheles gambiae s.s in Ghana; an important vector of lymphatic filariasis and malaria. PLoS One. 2010, 5: e9927-PubMed CentralPubMedView ArticleGoogle Scholar
- Global Climate data., [http://www.worldclim.org/]
- Consortium for Spatial Information., [http://www.cgiar-csi.org/]
- IRI/LDEO Climate Library., [http://iridl.ldeo.columbia.edu/]
- Global Land Cover Map., [http://due.esrin.esa.int/globcover/]
- Gridded Population of the World (GPW), v3., [http://sedac.ciesin.columbia.edu/data/collection/gpw-v3]
- Pullan RL, Brooker SJ: The global limits and population at risk of soil-transmitted helminth infections in 2010. Parasit Vectors. 2012, 5: 81-PubMed CentralPubMedView ArticleGoogle Scholar
- Travel Time to Major Cities: A Global map of Accessibility.], [http://bioval.jrc.ec.europa.eu/products/gam/index.htm]
- Elith JH, Graham CP, Anderson R, Dudík M, Ferrier S, Guisan AJ, Hijmans R, Huettmann FR, Leathwick J, Lehmann A, Li J, Lohmann LG, Loiselle BA, Manion G, Moritz C, Nakamura M, Nakazawa Y, Overton JMC, Townsend Peterson AT, Phillips SJ, Richardson K, Scachetti-Pereira R, Schapire RE, Soberón J, Williams S, Wisz MS, Zimmermann NE: Novel methods improve prediction of species’ distributions from occurrence data. Ecography. 2006, 29: 129-151.View ArticleGoogle Scholar
- Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, Brownstein JS, Hoen AG, Sankoh O, Myers MF, George DB, Jaenisch T, Wint GR, Simmons CP, Scott TW, Farrar JJ, Hay SI: The global distribution and burden of dengue. Nature. 2013, 496: 504-507.PubMed CentralPubMedView ArticleGoogle Scholar
- Sinka ME, Bangs MJ, Manguin S, Rubio-Palis Y, Chareonviriyaphap T, Coetzee M, Mbogo CM, Hemingway J, Patil AP, Temperley WH, Gething PW, Kabaria CW, Burkot TR, Harbach RE, Hay SI: A global map of dominant malaria vectors. Parasit Vectors. 2012, 5: 69-PubMed CentralPubMedView ArticleGoogle Scholar
- De’ath G: Boosted trees for ecological modeling and predictions. Ecology. 2007, 88: 243-251.PubMedView ArticleGoogle Scholar
- Elith J, Leathwick JR, Hastie T: A working guide to boosted regression trees. J Anim Ecol. 2008, 77: 802-813.PubMedView ArticleGoogle Scholar
- Addiss D, Chuke S: Lymphatic Filariasis in the Americas: An Epidemiologic History. Centers for Disease Control and Prevention. 2002Google Scholar
- Organization WH: Global Programme to Eliminate Lymphatic Filariasis. Annual Report on Lymphtic Filariasis 2005. 2003Google Scholar
- Ninth Workshop for Pacific Lymphatic Filariasis Programme Managers. WHO Meeting report, (WP)MVP/PIC/CPC/12/001-E. 2007, vol. RS/2007/GE/20(FIJ)Google Scholar
- Iyengar MO: Filariasis in Thailand. Bull World Health Organ. 1953, 9: 731-766.PubMed CentralPubMedGoogle Scholar
- Rebollo MP, Bockarie MJ: Toward the elimination of lymphatic filariasis by 2020: treatment update and impact assessment for the endgame. Expert Rev Anti-Infect Ther. 2013, 11: 723-731.PubMedView ArticleGoogle Scholar
- Sabesan S, Raju HK, Subramanian S, Srivastava PK, Jambulingam P: Lymphatic filariasis transmission risk map of india. Based on a geo-environmental risk model. Vector Borne Zoonotic Dis. 2013, 13: 657-665.PubMed CentralPubMedView ArticleGoogle Scholar
- Upadhyayula SM, Mutheneni SR, Kumaraswamy S, Kadiri MR, Pabbisetty SK, Yellepeddi VS: Filaria monitoring visualization system: a geographical information system-based application to manage lymphatic filariasis in Andhra Pradesh, India. Vector Borne Zoonotic Dis. 2012, 12: 418-427.PubMedView ArticleGoogle Scholar
- Rao SS, Iyengar MOT: Studies on the influence of season on the development of Filaria bancrofti in Culex fatigans. Indian J Med Res. 1930, 17: 759-781.Google Scholar
- Boreham PFL, Marks EN: Human filariasis in Australia: introduction, investigation and elimination. Proc R Soc Qld. 1986, 97: 23-52.Google Scholar
- Obiamiwe BA: The influence of the gene sb in Culex pipiens on the development of sub-periodic Brugia malayi and Wuchereria bancrofti. Ann Trop Med Parasitol. 1977, 71: 487-490.PubMedGoogle Scholar
- Pothikasikorn J, Bangs MJ, Boonplueang R, Chareonviriyaphap T: Susceptibility of various mosquitoes of Thailand to nocturnal subperiodic Wuchereria bancrofti. J Vector Ecol. 2008, 33: 313-320.PubMedView ArticleGoogle Scholar
- Saeung A, Hempolchom C, Baimai V, Thongsahuan S, Taai K, Jariyapan N, Chaithong U, Choochote W: Susceptibility of eight species members in the Anopheles hyrcanus group to nocturnally subperiodic Brugia malayi. Parasit Vectors. 2013, 6: 5-PubMed CentralPubMedView ArticleGoogle Scholar
- Pedersen EM, Kilama WL, Swai AB, Kihamia CM, Rwiza H, Kisumku UM: Bancroftian filariasis on Pemba Island, Zanzibar, Tanzania: an update on the status in urban and semi-urban communities. Trop Med Int Health. 1999, 4: 295-301.PubMedView ArticleGoogle Scholar
- Maxwell CA, Curtis CF, Haji H, Kisumku S, Thalib AI, Yahya SA: Control of Bancroftian filariasis by integrating therapy with vector control using polystyrene beads in wet pit latrines. Trans R Soc Trop Med Hyg. 1990, 84: 709-714.PubMedView ArticleGoogle Scholar
- Knight KL, Stone A: A Catalog of the Mosquitoes of the World (Diptera: Culicidae). 1977, Langham, MarylandGoogle Scholar
- Subra R, Mouchet J: Culex pipens fatigans Wiedemann in West Africa and its possible role in the transmission of Bancroft’s filariasis. WHO Mimeograph Document. 1967Google Scholar
- Zielke E, Kuhlow F: On the inheritance of susceptibility for infection with Wuchereria bancrofti in Culex pipiens fatigans. Tropenmed Parasitol. 1977, 28: 68-78.PubMedGoogle Scholar
- Jayasekera N, Curtis CF, Zielke E, Kuhlow F, Jansen CG, Chelliah RV: The susceptibility of Liberian Culex quinquefasciatus to Wuchereria bancrofti in Sri Lanka. Tropenmed Parasitol. 1980, 31: 507-511.PubMedGoogle Scholar
- Udonsi JK: Bancroftian filariasis in the Igwun Basin, Nigeria. An epidemiological, parasitological, and clinical study in relation to the transmission dynamics. Acta Trop. 1988, 45: 171-179.PubMedGoogle Scholar
- Anosike JC, Onwuliri CO: Experimental Wuchereria bancrofti infection of Culex quinquefasciatus and Aedes aegypti. Angew Parasitol. 1992, 33: 139-142.PubMedGoogle Scholar
- Anosike JC, Nwoke BE, Ajayi EG, Onwuliri CO, Okoro OU, Oku EE, Asor JE, Amajuoyi OU, Ikpeama CA, Ogbusu FI, Meribe CO: Lymphatic filariasis among the Ezza people of Ebonyi State, Eastern Nigeria. Ann Agric Environ Med. 2005, 12: 181-186.PubMedGoogle Scholar
- Ughasi J, Bekard HE, Coulibaly M, Adabie-Gomez D, Gyapong J, Appawu M, Wilson MD, Boakye DA: Mansonia africana and Mansonia uniformis are vectors in the transmission of Wuchereria bancrofti lymphatic filariasis in Ghana. Parasit Vectors. 2012, 5: 89-PubMed CentralPubMedView ArticleGoogle Scholar
- Joe LK, Chow CY, Winoto RM, Rusad S, Rusad M: [Filariasis in Djakarta, Indonesia]. Am J Trop Med Hyg. 1958, 7: 280-284.PubMedGoogle Scholar
- Surendran K, Pani SP, Soudarssanane MB, Srinivasa DK, Bordolai PC, Subramanian S: Natural history, trend of prevalence and spectrum of manifestations of Bancroftian filarial disease in Pondicherry (South India). Acta Trop. 1996, 61: 9-18.PubMedView ArticleGoogle Scholar
- Arunachalam N, Mariappan T, Vijayakumar KN, Sabesan S, Panicker KN: Mattancherry urban agglomeration, a diminishing focus of lymphatic filariasis in Kerala. J Commun Dis. 1996, 28: 168-170.PubMedGoogle Scholar
- Jr TJD, Bhattacharya NC: Clinical manifestations of Bancroftian filariasis in a suburb of Calcutta, India. Am J Trop Med Hyg. 1976, 25: 64-73.Google Scholar
- Oemijati S, Desowitz RS, Partono F, Pant CP, Mechfudin H, Sajidiman H: Studies on filariasis in the Pacific. 4. The application of the membrane filter concentration technique to a survey of Wuchereria bancrofti filariasis in Kepu district, Jakarta, Indonesia. Southeast Asian J Trop Med Public Health. 1975, 6: 186-189.PubMedGoogle Scholar
- Oemijati S: Current status of filariasis in Indonesia. Southeast Asian J Trop Med Public Health. 1993, 24 (Suppl 2): 2-4.PubMedGoogle Scholar
- Bonfim C, Lessa F, Oliveira C, Evangelista MJ, do Espirito Santo M, Meireles E, Pereira JC, Medeiros Z: [The occurrence and distribution of lymphatic filariasis in Greater Metropolitan Recife: the case of an endemic area in Jaboatao dos Guararapes, Pernambuco, Brazil]. Cad Saude Publica. 2003, 19: 1497-1505.PubMedView ArticleGoogle Scholar
- Braga C, Dourado I, Ximenes R, Miranda J, Alexander N: Bancroftian filariasis in an endemic area of Brazil: differences between genders during puberty. Rev Soc Bras Med Trop. 2005, 38: 224-228.PubMedGoogle Scholar
- Terranella A, Eigiege A, Gontor I, Dagwa P, Damishi S, Miri E, Blackburn B, McFarland D, Zingeser J, Jinadu MY, Richards FO: Urban lymphatic filariasis in central Nigeria. Ann Trop Med Parasitol. 2006, 100: 163-172.PubMedView ArticleGoogle Scholar
- Gbakima AA, Appawu MA, Dadzie S, Karikari C, Sackey SO, Baffoe-Wilmot A, Gyapong J, Scott AL: Lymphatic filariasis in Ghana: establishing the potential for an urban cycle of transmission. Trop Med Int Health. 2005, 10: 387-392.PubMedView ArticleGoogle Scholar
- Richard-Lenoble D, Kombila M, Carme B, Gilles JC, Delattre PY: [Prevalence of human filariasis with microfilaremia in Gabon]. Bull Soc Pathol Exot Filiales. 1980, 73: 192-199.PubMedGoogle Scholar
- Casaca VM: [Contribution to the study of bancrofti filariasis in Angola. 1. Possibilities of its existence and probable distribution. 2. Bibliographic review and personal observations. An Inst Med Trop (Lisb). 1966, 23: 127-132.Google Scholar
- Reddy S, Dávalos LM: Geographical sampling bias and its implications for conservation priorities in Africa. J Biogeography. 2003, 30: 1719-1727.View ArticleGoogle Scholar
- Kadmon R, Farber O, Danin A: Effect of roadside bias on the accuracy of predictive maps produced by bioclimatic models. Ecol Appl. 2004, 14: 401-413.View ArticleGoogle Scholar
- Phillips SJ, Dudik M, Elith J, Graham CH, Lehmann A, Leathwick J, Ferrier S: Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecol Appl. 2009, 19: 181-197.PubMedView ArticleGoogle Scholar
- Schneider MC, Aguilera XP, Barbosa da Silva J, Ault SK, Najera P, Martinez J, Requejo R, Nicholls RS, Yadon Z, Silva JC, Leanes LF, Periago MR: Elimination of neglected diseases in Latin America and the Caribbean: a mapping of selected diseases. PLoS Negl Trop Dis. 2011, 5: e964-PubMed CentralPubMedView ArticleGoogle Scholar
- Laurence BR: The global dispersal of Bancroftian filariasis. Parasitol Today. 1989, 5: 260-264.PubMedView ArticleGoogle Scholar
- Rawlins SC, Lammie P, Tiwari T, Pons P, Chadee DD, Oostburg BF, Baboolal S: Lymphatic filariasis in the Caribbean region: the opportunity for its elimination and certification. Rev Panam Salud Publica. 2000, 7: 319-324.PubMedView ArticleGoogle Scholar
- Lymphatic Filariasis Elimination in the Americas: 12th Regional Program Managers Meeting. 2014, The Dominican Republic: Pan American Health Organization, Santo DomingoGoogle Scholar
- Raccurt CP, Lowrie RC, Katz SP, Duverseau YT: Epidemiology of Wuchereria bancrofti in Leogane, Haiti. Trans R Soc Trop Med Hyg. 1988, 82: 721-725.PubMedView ArticleGoogle Scholar
- Lymphatic Filariasis Elimination in the Americas: First Regional Program Managers Meeting. 2000, The Dominican Republic: Pan American Health Organization, Santo DomingoGoogle Scholar
- Bonfim C, Netto MJ, Pedroza D, Portugal JL, Medeiros Z: A socioenvironmental composite index as a tool for identifying urban areas at risk of lymphatic filariasis. Trop Med Int Health. 2009, 14: 877-884.PubMedView ArticleGoogle Scholar
- Sabesan S, Palaniyandi M, Das PK, Michael E: Mapping of lymphatic filariasis in India. Ann Trop Med Parasitol. 2000, 94: 591-606.PubMedGoogle Scholar
- Global programme to eliminate lymphatic filariasis. Wkly Epidemiol Rec. 2008, 83: 333-348.Google Scholar
- Kimura E, Itoh M: Filariasis in Japan some 25 years after its eradication. Trop Med Health. 2011, 39: 57-63.PubMed CentralPubMedView ArticleGoogle Scholar
- Zhang XC, Huang SY, Deng ZH, Ou ZY, Wu WP, Luo XC, Chen XX, Zhang QM, Lin RX, Ruan CW, Wang JL, Cui HE: [Follow-up survey on the imported cases of lymphatic filariasis in Guangdong Province]. Zhongguo Ji Sheng Chong Xue Yu Ji Sheng Chong Bing Za Zhi. 2008, 26: 409-411.PubMedGoogle Scholar
- Sudomo M, Chayabejara S, Duong S, Hernandez L, Wu WP, Bergquist R: Elimination of lymphatic filariasis in Southeast Asia. Adv Parasitol. 2010, 72: 205-233.PubMedView ArticleGoogle Scholar
- Nuchprayoon S, Sanprasert V, Porksakorn C, Nuchprayoon I: Prevalence of bancroftian filariasis on the Thai-Myanmar border. Asian Pac J Allergy Immunol. 2003, 21: 179-188.PubMedGoogle Scholar
- Brady OJ, Gething PW, Bhatt S, Messina JP, Brownstein JS, Hoen AG, Moyes CL, Farlow AW, Scott TW, Hay SI: Refining the global spatial limits of dengue virus transmission by evidence-based consensus. PLoS Negl Trop Dis. 2012, 6: e1760-PubMed CentralPubMedView ArticleGoogle Scholar
- Knudsen AB, Slooff R: Vector-borne disease problems in rapid urbanization: new approaches to vector control. Bull World Health Organ. 1992, 70: 1-6.PubMed CentralPubMedGoogle Scholar
- Adeleke MA, Mafiana CF, Idowu AB, Adekunle MF, Sam-Wobo SO: Mosquito larval habitats and public health implications in Abeokuta, Ogun State, Nigeria. Tanzan J Health Res. 2008, 10: 103-107.PubMedGoogle Scholar
- McCarthy JS, Lustigman S, Yang G-J, Barakat RM, García HH, Sripa B, Willingham AL, Prichard RK, Basáñez M-G: A research agenda for helminth diseases of humans: diagnostics for control and elimination programmes. PLoS Negl Trop Dis. 2012, 6: e1601-PubMed CentralPubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.