A geostatistical analysis of the geographic distribution of lymphatic filariasis prevalence in southern India

Spatial-Temporal Analysis of Factors Influencing the Median Urine Iodine Concentration of 8-10-year-old Children in Xinjiang, China 25 Years after Implementation of the Salt Iodization Policy

The iodine status of children has improved and stabilized since China implemented salt iodization measures 25 years ago, but routine monitoring of iodine cannot reflect regional factors that influence the iodine level in children. Therefore, we conducted a regional spatial-temporal analysis of children's median urinary iodine concentration (MUIC) and searched for possible factors that might affect children's iodine levels by mining monitoring data. We analyzed data from Xinjiang collected as part of the "Iodine Deficiency Disease National Monitoring Program" from 2017 to 2020. The study population consisted of 76,268 children who participated in the study. We used global autocorrelation analysis to determine whether the MUIC of children was spatially clustered, local autocorrelation analysis to identify specific clustering areas, local cold and hot spot analysis to verify the reliability of the local autocorrelation results, and a spatial lag model to identify factors affecting the children's MUIC. The MUIC values were 217.70, 227.00, 230.67, and 230.67 µg/L in 2017, 2018, 2019, and 2020, respectively. Global autocorrelation analysis showed that the MUIC of all children in the study was significantly related to region (Z scores all > 1.96, P values all < 0.05) from 2017 to 2020. Partial auto-correlation analysis showed that counties with clusters of high values were mostly concentrated in the southwestern region of Xinjiang, whereas counties with clusters of low values were located in the northern part of Xinjiang. Partial cold spot and hot spot analysis showed the same trend, and there are more overlapping districts and counties in 4 years. Three-dimensional trend analysis indicated that children from the western part of Xinjiang had high levels of urinary iodine. According to spatial lag model, urine iodine concentration level is positively correlated with thyroid volume, average salary, and urbanization rate classification. The MUIC of 8-10-year-old children in Xinjiang was spatially clustered and related to geographic region. Our results show that spatial analysis of survey data combined with geographic technology and public health data can accurately identify areas with abnormal iodine concentrations in children. Additionally, understanding the factors that influence iodine levels in the human population is conducive to improving monitoring methods.

Lymphatic filariasis in Asia: a systematic review and meta-analysis

Lymphatic filariasis (LF) is an important neglected parasitic disease according to the World Health Organization. In this study, we aimed to determine the prevalence of human LF in Asia using a systematic review and meta-analysis approach. Records from 1990 to 2018 in reputable databases including PubMed, Science Direct, Embase, and Cochrane Library were searched using a panel of related keywords. All 48 countries of Asia were searched one by one in combination with the keywords. In all, 41,742 cases identified in this study were included in the analysis. According to our findings, the pooled prevalence of LF in Asia was estimated at 3% (95% CI: [1.7, 5.2]). There was no major trend in the cumulative prevalence of LF over time. Some countries in Asia including China, Japan, Vietnam, and South Korea succeeded in eliminating LF as a public health problem, but others still need to monitor the disease. Based on the initiative of the WHO starting in 2000, some countries in Asia succeeded in eliminating LF as a public health problem. Other countries have taken steps to eliminate the disease with variable degrees of success. These efforts might be affected by issues such as climate change.

Spatiotemporal variability in case fatality ratios for the 2013-2016 Ebola epidemic in West Africa

BACKGROUND

For the 2013-2016 Ebola epidemic in West Africa, the largest Ebola virus disease (EVD) epidemic to date, we aim to analyse the patient mix in detail to characterise key sources of spatiotemporal heterogeneity in the case fatality ratios (CFR).

METHODS

We applied a non-parametric Boosted Regression Trees (BRT) imputation approach for patients with missing survival outcomes and adjusted for model imperfection. Semivariogram analysis and kriging were used to investigate spatiotemporal heterogeneities.

RESULTS

CFR estimates varied significantly between districts and over time over the course of the epidemic. BRT modelling accounted for most of the spatiotemporal variation and interactions in CFR, but moderate spatial autocorrelation remained for distances up to approximately 90 km. Combining district-level CFR estimates and kriged district-level residuals provided the best linear unbiased predicted map of CFR accounting for the both explained and unexplained spatial variation. Temporal autocorrelation was not observed in the district-level residuals from the BRT estimates.

CONCLUSIONS

This study provides new insight into the epidemiology of the 2013-2016 West African Ebola epidemic with a view of informing future public health contingency planning, resource allocation and impact assessment. The analytical framework developed in this analysis, coupled with key domain knowledge, could be deployed in real time to support the response to ongoing and future outbreaks.

Mapping and monitoring for a lymphatic filariasis elimination program: a systematic review

Lymphatic filariasis (LF) is targeted for elimination by the year 2020. The Global Programme for Elimination of LF (GPELF) aims to achieve elimination by interrupting transmission through annual mass drug administration (MDA) of albendazole with ivermectin or diethylcarbamazine. The program has successfully eliminated the disease in 11 of the 72 endemic countries, putting in enormous efforts on systematic planning and implementation of the strategy. Mapping areas endemic for LF is a pre-requisite for implementing MDA, monitoring and evaluation are the components of programme implementation. This review was undertaken to assess how the mapping and impact monitoring activities have evolved to become more robust over the years and steered the LF elimination programme towards its goal. The findings showed that the WHO recommended mapping strategy aided 17 countries to delimit, plan and implement MDA in only those areas endemic for LF thereby saving resources. Availability of serological tools for detecting infection in humans (antigen/antibody assays) and molecular xenomonitoring (MX) in vectors greatly facilitated programme monitoring and evaluation in endemic countries. Results of this review are discussed on how these existing mapping and monitoring procedures can be used for re-mapping of unsurveyed and uncertain areas to ensure there is no resurgence during post-MDA surveillance. Further the appropriateness of the tests (Microfilaria (Mf)/antigenemia (Ag)/antibody(Ab) surveys in humans or MX of vectors for infection) used currently for post-MDA surveillance and their role in the development of a monitoring and evaluation strategy for the recently WHO recommended triple drug regimen in MDA for accelerated LF elimination are discussed.

Continental-scale, data-driven predictive assessment of eliminating the vector-borne disease, lymphatic filariasis, in sub-Saharan Africa by 2020

BACKGROUND

There are growing demands for predicting the prospects of achieving the global elimination of neglected tropical diseases as a result of the institution of large-scale nation-wide intervention programs by the WHO-set target year of 2020. Such predictions will be uncertain due to the impacts that spatial heterogeneity and scaling effects will have on parasite transmission processes, which will introduce significant aggregation errors into any attempt aiming to predict the outcomes of interventions at the broader spatial levels relevant to policy making. We describe a modeling platform that addresses this problem of upscaling from local settings to facilitate predictions at regional levels by the discovery and use of locality-specific transmission models, and we illustrate the utility of using this approach to evaluate the prospects for eliminating the vector-borne disease, lymphatic filariasis (LF), in sub-Saharan Africa by the WHO target year of 2020 using currently applied or newly proposed intervention strategies. METHODS AND RESULTS: We show how a computational platform that couples site-specific data discovery with model fitting and calibration can allow both learning of local LF transmission models and simulations of the impact of interventions that take a fuller account of the fine-scale heterogeneous transmission of this parasitic disease within endemic countries. We highlight how such a spatially hierarchical modeling tool that incorporates actual data regarding the roll-out of national drug treatment programs and spatial variability in infection patterns into the modeling process can produce more realistic predictions of timelines to LF elimination at coarse spatial scales, ranging from district to country to continental levels. Our results show that when locally applicable extinction thresholds are used, only three countries are likely to meet the goal of LF elimination by 2020 using currently applied mass drug treatments, and that switching to more intensive drug regimens, increasing the frequency of treatments, or switching to new triple drug regimens will be required if LF elimination is to be accelerated in Africa. The proportion of countries that would meet the goal of eliminating LF by 2020 may, however, reach up to 24/36 if the WHO 1% microfilaremia prevalence threshold is used and sequential mass drug deliveries are applied in countries.

CONCLUSIONS

We have developed and applied a data-driven spatially hierarchical computational platform that uses the discovery of locally applicable transmission models in order to predict the prospects for eliminating the macroparasitic disease, LF, at the coarser country level in sub-Saharan Africa. We show that fine-scale spatial heterogeneity in local parasite transmission and extinction dynamics, as well as the exact nature of intervention roll-outs in countries, will impact the timelines to achieving national LF elimination on this continent.

Detecting infection hotspots: Modeling the surveillance challenge for elimination of lymphatic filariasis

BACKGROUND

During the past 20 years, enormous efforts have been expended globally to eliminate lymphatic filariasis (LF) through mass drug administration (MDA). However, small endemic foci (microfoci) of LF may threaten the presumed inevitable decline of infections after MDA cessation. We conducted microsimulation modeling to assess the ability of different types of surveillance to identify microfoci in these settings.

METHODS

Five or ten microfoci of radius 1, 2, or 3 km with infection marker prevalence (intensity) of 3, 6, or 10 times background prevalence were placed in spatial simulations, run in R Version 3.2. Diagnostic tests included microfilaremia, immunochromatographic test (ICT), and Wb123 ELISA. Population size was fixed at 360,000 in a 60 x 60 km area; demographics were based on literature for Sub-Saharan African populations. Background ICT prevalence in 6-7 year olds was anchored at 1.0%, and the prevalence in the remaining population was adjusted by age. Adults≥18 years, women aged 15-40 years (WCBA), children aged 6-7 years, or children≤5 years were sampled. Cluster (CS), simple random sampling (SRS), and TAS-like sampling were simulated, with follow-up testing of the nearest 20, 100, or 500 persons around each infection-marker-positive person. A threshold number of positive persons in follow-up testing indicated a suspected microfocus. Suspected microfoci identified during surveillance and actual microfoci in the simulation were compared to obtain a predictive value positive (PVP). Each parameter set was referred to as a protocol. Protocols were scored by efficiency, defined as the most microfoci identified, the fewest persons requiring primary and follow-up testing, and the highest PVP. Negative binomial regression was used to estimate aggregate effects of different variables on efficiency metrics.

RESULTS

All variables were significantly associated with efficiency metrics. Additional follow-up tests beyond 20 did not greatly increase the number of microfoci detected, but significantly negatively impacted efficiency. Of 3,402 protocols evaluated, 384 (11.3%) identified all five microfoci (PVP 3.4-100.0%) and required testing 0.73-35.6% of the population. All used SRS and 378 (98.4%) only identified all five microfoci if they were 2-3 km diameter or high-intensity (6x or 10x); 374 (97.4%) required ICT or Wb123 testing to identify all five microfoci, and 281 (73.0%) required sampling adults or WCBA. The most efficient CS protocols identified two (40%) microfoci. After limiting to protocols with 1-km radius microfoci of 3x intensity (n = 378), eight identified all five microfoci; all used SRS and ICT and required testing 31.2-33.3% of the population. The most efficient CS and TAS-like protocols as well as those using microfilaremia testing identified only one (20%) microfocus when they were limited to 1-km radius and 3x intensity.

CONCLUSION

In this model, SRS, ICT, and sampling of adults maximized microfocus detection efficiency. Follow-up sampling of more persons did not necessarily increase protocol efficiency. Current approaches towards surveillance, including TAS, may not detect small, low-intensity LF microfoci that could remain after cessation of MDA. The model provides many surveillance protocols that can be selected for optimal outcomes.

Lymphatic filariasis among children and adolescents: spatial identification via socio-environmental indicators to define priority areas for elimination

BACKGROUND

The occurrence of lymphatic filariasis (LF) and its transmission dynamics among children and adolescents are still not clearly elucidated. The aim of this study was to describe the spatial distribution of microfilaremia and its relationship with socio-environmental variables, thereby identifying areas at greater risk of transmission.

METHODS

An ecological study was conducted, in which the analysis unit was formed by districts of the municipality of Jaboatão dos Guararapes in the state of Pernambuco, Brazil. The data source was a parasitological survey. Inadequate sewage disposal, number of people in the household and income of between 0.5 and 1 minimum salary were used to construct the socio-environmental indicator. The districts were then grouped according to the indicator into three risk strata, using the k-means clustering technique.

RESULTS

In the study, 96/8670 (1.1%) of the population were found to present microfilaremia. The high-risk stratum had a mean prevalence rate of 1.9% and a risk of 2.56 (p<0.05), in relation to the low-risk stratum. The middle stratum grouped the households that presented an intermediate risk of transmission, with a prevalence rate of 1.92%.

CONCLUSIONS

The indicator used is a promising tool that enables the precise measurement of the relationship between social deprivation and the prevalence of filarial infection among children. Thus, it can be used to plan control and elimination actions.

Planning schistosomiasis control: investigation of alternative sampling strategies for Schistosoma mansoni to target mass drug administration of praziquantel in East Africa

In schistosomiasis control, there is a need to geographically target treatment to populations at high risk of morbidity. This paper evaluates alternative sampling strategies for surveys of Schistosoma mansoni to target mass drug administration in Kenya and Ethiopia. Two main designs are considered: lot quality assurance sampling (LQAS) of children from all schools; and a geostatistical design that samples a subset of schools and uses semi-variogram analysis and spatial interpolation to predict prevalence in the remaining unsurveyed schools. Computerized simulations are used to investigate the performance of sampling strategies in correctly classifying schools according to treatment needs and their cost-effectiveness in identifying high prevalence schools. LQAS performs better than geostatistical sampling in correctly classifying schools, but at a cost with a higher cost per high prevalence school correctly classified. It is suggested that the optimal surveying strategy for S. mansoni needs to take into account the goals of the control programme and the financial and drug resources available.

Mapping, bayesian geostatistical analysis and spatial prediction of lymphatic filariasis prevalence in Africa

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection.

Bancroftian filariasis in 12 villages in Kwale district, Coast province, Kenya — variation in clinical and parasitological patterns

As part of a larger study on the effects of permethrin-impregnated bednets on the transmission of Wuchereria bancrofti, subjects from 12 villages in the Coastal province of Kenya, south of Mombasa, were investigated. The aims were to update the epidemiological data and elucidate the spatial distribution of W. bancrofti infection. Samples of night blood from all the villagers aged i 1 year were checked for the parasite, and all the adult villagers (aged >/= 15 years) were clinically examined for elephantiasis and, if male, for hydrocele. Overall, 16.0% of the 6531 villagers checked for microfilariae (mff) were found microfilaraemic, although the prevalence of microfilaraemia in each village varied from 8.1%-27.4%. The geometric mean intensity of infection among the microfilaraemic was 322 mff/ml blood. At village level, intensity of the microfilaraemia was positively correlated with prevalence, indicating that transmission has a major influence on the prevalence of microfilaraemia. Clinical examination of 2481 adults revealed that 2.9% had elephantiasis of the leg and that 19.9% of the adult men (10.8%-30.1% of the men investigated in each village) had hydrocele. Although the overall prevalence of microfilaraemia in the study villages had not changed much since earlier studies in the 1970s, both prevalence and intensity varied distinctly between the study villages. Such geographical variation over relatively short distances appears to be a common but seldom demonstrated feature in the epidemiology of bancroftian filariasis, and the focal nature of the geographical distribution should be carefully considered by those mapping the disease.

How to choose geographical units in ecological studies: proposal and application to campylobacteriosis

In spatial epidemiology, the choice of an appropriate geographical unit of analysis is a key decision that will influence most aspects of the study. In this study, we proposed and applied a set of measurable criteria applicable for orienting the choice of geographical unit. Nine criteria were selected, covering many aspects such as biological relevance, communicability of results, ease of data access, distribution of exposure variables, cases and population, and shape of unit. These criteria were then applied to compare various geographical units derived from administrative, health services, and natural frameworks that could be used for the study of the spatial distribution of campylobacteriosis in the province of Quebec, Canada. In this study, municipality was the geographical unit that performed the best according to our assessment and given the specific objectives and time period of the study. Future research areas for optimizing the choice of geographical unit are discussed.

Integrated rapid mapping of neglected tropical diseases in three States of South Sudan: survey findings and treatment needs

Background

Integrated rapid mapping to target interventions for schistosomiasis, soil-transmitted helminthiasis (STH) and lymphatic filariasis (LF) is ongoing in South Sudan. From May to September 2010, three states – Unity, Eastern Equatoria and Central Equatoria – were surveyed with the aim of identifying which administrative areas are eligible for mass drug administration (MDA) of preventive chemotherapy (PCT).

Methods and Principal Findings

Payams (third administrative tier) were surveyed for Schistosoma mansoni, S. haematobium and STH infections while counties (second administrative tier) were surveyed for LF. Overall, 12,742 children from 193 sites were tested for schistosome and STH infection and, at a subset of 50 sites, 3,980 adults were tested for LF. Either S. mansoni or S. haematobium or both species were endemic throughout Unity State and occurred in foci in Central and Eastern Equatoria. STH infection was endemic throughout Central Equatoria and the western counties of Eastern Equatoria, while LF was endemic over most of Central- and Eastern Equatoria, but only in selected foci in Unity. All areas identified as STH endemic were co-endemic for schistosomiasis and/or LF.

Conclusions

The distribution and prevalence of major NTDs, particularly schistosomiasis, varies considerably throughout South Sudan. Rapid mapping is therefore important in identifying (co)-endemic areas. The present survey established that across the three surveyed states between 1.2 and 1.4 million individuals are estimated to be eligible for regular MDA with PCT to treat STH and schistosomiasis, respectively, while approximately 1.3 million individuals residing in Central- and Eastern Equatoria are estimated to require MDA for LF.

Spatial parasite ecology and epidemiology: a review of methods and applications

The distributions of parasitic diseases are determined by complex factors, including many that are distributed in space. A variety of statistical methods are now readily accessible to researchers providing opportunities for describing and ultimately understanding and predicting spatial distributions. This review provides an overview of the spatial statistical methods available to parasitologists, ecologists and epidemiologists and discusses how such methods have yielded new insights into the ecology and epidemiology of infection and disease. The review is structured according to the three major branches of spatial statistics: continuous spatial variation; discrete spatial variation; and spatial point processes.

Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling

Modelling the spatial distributions of human parasite species is crucial to understanding the environmental determinants of infection as well as for guiding the planning of control programmes. Here, we use ecological niche modelling to map the current potential distribution of the macroparasitic disease, lymphatic filariasis (LF), in Africa, and to estimate how future changes in climate and population could affect its spread and burden across the continent. We used 508 community-specific infection presence data collated from the published literature in conjunction with five predictive environmental/climatic and demographic variables, and a maximum entropy niche modelling method to construct the first ecological niche maps describing potential distribution and burden of LF in Africa. We also ran the best-fit model against climate projections made by the HADCM3 and CCCMA models for 2050 under A2a and B2a scenarios to simulate the likely distribution of LF under future climate and population changes. We predict a broad geographic distribution of LF in Africa extending from the west to the east across the middle region of the continent, with high probabilities of occurrence in the Western Africa compared to large areas of medium probability interspersed with smaller areas of high probability in Central and Eastern Africa and in Madagascar. We uncovered complex relationships between predictor ecological niche variables and the probability of LF occurrence. We show for the first time that predicted climate change and population growth will expand both the range and risk of LF infection (and ultimately disease) in an endemic region. We estimate that populations at risk to LF may range from 543 and 804 million currently, and that this could rise to between 1.65 to 1.86 billion in the future depending on the climate scenario used and thresholds applied to signify infection presence.

First evidence of spatial clustering of lymphatic filariasis in an Aedes polynesiensis endemic area

Successful elimination of lymphatic filariasis (LF) requires accurate identification of residual foci of transmission and stringent surveillance strategies to combat potential resurgence. This is challenging in areas where the day-biting Aedes polynesiensis is endemic, such as Samoa, since in previous studies no geographical clustering of infection has been demonstrated. Another challenge for this low prevalence phase is the choice of diagnostic assay as testing for circulating filarial antigen (CFA) or microfilariae (Mf) alone may not have adequate sensitivity. This could be solved by using the commercially available filariasis Cellabs enzyme linked immunosorbent assay (CELISA) to measure antibody. In the current study five Samoan villages were chosen based on previous epidemiological assessments to represent a range of infection prevalences. CFA, Mf, and antibody levels in children ≤ 10 years had been recorded and results linked to household of residence and/or primary school of attendance. To ascertain the location of exposure, two scenarios based on potential foci of transmission around communities and schools were explored. Both scenarios revealed significant spatial clusters of households with infected individuals and a relationship to antibody positive children when they were included in the spatial analysis. Fasitoo-Tai had the highest LF prevalence and largest geographical spatial clusters for both scenarios. In Falefa, spatial clusters were detected only for the primary school scenario. In Tafua, which spanned an area of 19.5 km(2), no spatial clusters were detected. Lastly, in Siufaga, the village with the lowest LF prevalence, significant clustering of infected individuals was observed and, for the primary school scenario, this was geographically related to exposure. These promising findings are the first published evidence of spatial clustering of LF in a day-biting Ae. polynesiensis endemic area.

The applications of model-based geostatistics in helminth epidemiology and control

Funding agencies are dedicating substantial resources to tackle helminth infections. Reliable maps of the distribution of helminth infection can assist these efforts by targeting control resources to areas of greatest need. The ability to define the distribution of infection at regional, national and subnational levels has been enhanced greatly by the increased availability of good quality survey data and the use of model-based geostatistics (MBG), enabling spatial prediction in unsampled locations. A major advantage of MBG risk mapping approaches is that they provide a flexible statistical platform for handling and representing different sources of uncertainty, providing plausible and robust information on the spatial distribution of infections to inform the design and implementation of control programmes. Focussing on schistosomiasis and soil-transmitted helminthiasis, with additional examples for lymphatic filariasis and onchocerciasis, we review the progress made to date with the application of MBG tools in large-scale, real-world control programmes and propose a general framework for their application to inform integrative spatial planning of helminth disease control programmes.

Optimal survey designs for targeting chemotherapy against soil-transmitted helminths: effect of spatial heterogeneity and cost-efficiency of sampling

Implementation of helminth control programs requires information on the distribution and prevalence of infection to target mass treatment to areas of greatest need. In the absence of data, the question of how many schools/communities should be surveyed depends on the spatial heterogeneity of infection and the cost efficiency of surveys. We used geostatistical techniques to quantify the spatial heterogeneity of soil-transmitted helminths in multiple settings in eastern Africa, and using the example of Kenya, conducted conditional simulation to explore the implications of alternative sampling strategies in identifying districts requiring mass treatment. Cost analysis is included in the simulations using data from actual field surveys and control programs. The analysis suggests that sampling four or five schools in each district provides a cost-efficient strategy in identifying districts requiring mass treatment, and that efficiency of sampling was relatively insensitive to the number of children sampled per school.

Integrated mapping of neglected tropical diseases: epidemiological findings and control implications for northern Bahr-el-Ghazal State, Southern Sudan

Background

There are few detailed data on the geographic distribution of most neglected tropical diseases (NTDs) in post-conflict Southern Sudan. To guide intervention by the recently established national programme for integrated NTD control, we conducted an integrated prevalence survey for schistosomiasis, soil-transmitted helminth (STH) infection, lymphatic filariasis (LF), and loiasis in Northern Bahr-el-Ghazal State. Our aim was to establish which communities require mass drug administration (MDA) with preventive chemotherapy (PCT), rather than to provide precise estimates of infection prevalence.

Methods and Findings

The integrated survey design used anecdotal reports of LF and proximity to water bodies (for schistosomiasis) to guide selection of survey sites. In total, 86 communities were surveyed for schistosomiasis and STH; 43 of these were also surveyed for LF and loiasis. From these, 4834 urine samples were tested for blood in urine using Hemastix reagent strips, 4438 stool samples were analyzed using the Kato-Katz technique, and 5254 blood samples were tested for circulating Wuchereria bancrofti antigen using immunochromatographic card tests (ICT). 4461 individuals were interviewed regarding a history of ‘eye worm’ (a proxy measure for loiasis) and 31 village chiefs were interviewed regarding the presence of clinical manifestations of LF in their community. At the village level, prevalence of Schistosoma haematobium and S. mansoni ranged from 0 to 65.6% and from 0 to 9.3%, respectively. The main STH species was hookworm, ranging from 0 to 70% by village. Infection with LF and loiasis was extremely rare, with only four individuals testing positive or reporting symptoms, respectively. Questionnaire data on clinical signs of LF did not provide a reliable indication of endemicity. MDA intervention thresholds recommended by the World Health Organization were only exceeded for urinary schistosomiasis and hookworm in a few, yet distinct, communities.

Conclusion

This was the first attempt to use an integrated survey design for this group of infections and to generate detailed results to guide their control over a large area of Southern Sudan. The approach proved practical, but could be further simplified to reduce field work and costs. The results show that only a few areas need to be targeted with MDA of PCT, thus confirming the importance of detailed mapping for cost-effective control.

Integrated control of neglected tropical diseases (NTDs) is being scaled up in a number of developing countries, because it is thought to be more cost-effective than stand-alone control programmes. Under this approach, treatments for onchocerciasis, lymphatic filariasis (LF), schistosomiasis, soil-transmitted helminth (STH) infection, and trachoma are administered through the same delivery structure and at about the same time. A pre-requisite for implementation of integrated NTD control is information on where the targeted diseases are endemic and to what extent they overlap. This information is generated through surveys that can be labour-intensive and expensive. In Southern Sudan, all of the above diseases except onchocerciasis require further mapping before a comprehensive integrated NTD control programme can be implemented. To determine where treatment for which disease is required, integrated surveys were conducted for schistosomiasis, STH infection, LF, and loiasis, throughout one of ten states of the country. Our results show that treatment is only required for urinary schistosomiasis and STH in a few, yet separate, geographical area. This illustrates the importance of investing in disease mapping to minimize overall programme costs by being able to target interventions. Integration of survey methodologies for the above disease was practical and efficient, and minimized the effort required to collect these data.

Global epidemiology, ecology and control of soil-transmitted helminth infections

Soil-transmitted helminth (STH) infections are among the most prevalent of chronic human infections worldwide. Based on the demonstrable impact on child development, there is a global commitment to finance and implement control strategies with a focus on school-based chemotherapy programmes. The major obstacle to the implementation of cost-effective control is the lack of accurate descriptions of the geographical distribution of infection. In recent years, considerable progress has been made in the use of geographical information systems (GIS) and remote sensing (RS) to better understand helminth ecology and epidemiology, and to develop low-cost ways to identify target populations for treatment. This review explores how this information has been used practically to guide large-scale control programmes. The use of satellite-derived environmental data has yielded new insights into the ecology of infection at a geographical scale that has proven impossible to address using more traditional approaches, and has in turn allowed spatial distributions of infection prevalence to be predicted robustly by statistical approaches. GIS/RS have increasingly been used in the context of large-scale helminth control programmes, including not only STH infections but also those focusing on schistosomiasis, filariasis and onchocerciasis. The experience indicates that GIS/RS provides a cost-effective approach to designing and monitoring programmes at realistic scales. Importantly, the use of this approach has begun to transition from being a specialist approach of international vertical programmes to becoming a routine tool in developing public sector control programmes. GIS/RS is used here to describe the global distribution of STH infections and to estimate the number of infections in school-age children in sub-Saharan Africa (89.9 million) and the annual cost of providing a single anthelmintic treatment using a school-based approach (US$5.0-7.6 million). These are the first estimates at a continental scale to explicitly include the fine spatial distribution of infection prevalence and population, and suggest that traditional methods have overestimated the situation. The results suggest that continent-wide control of parasites is, from a financial perspective, an attainable goal.

A socioenvironmental composite index as a tool for identifying urban areas at risk of lymphatic filariasis

OBJECTIVE

To describe the spatial distribution of lymphatic filariasis and its relationship with the socioenvironmental risk indicator, thus identifying priority localities for interventions in endemic urban areas.

METHODS

The study area was the municipality of Jaboatão dos Guararapes, State of Pernambuco, Brazil. The data sources were a parasitological survey and the 2000 demographic census. From these data, a socioenvironmental composite risk indicator was constructed using the 484 census tracts (CT) as the analysis units, based on the score-formation technique. Census tracts with higher indicator values presented higher risk of occurrences of filariasis.

RESULTS

Six thousand five hundred and seven households were surveyed and 23 673 individuals were examined, among whom 323 cases of microfilaremia were identified. The mean prevalence rate for the municipality was 1.4%. The indicator showed that 73% (237/323) of the cases of microfilaremia were in high-risk areas (third and fourth quartiles) with worse socioenvironmental conditions (RR = 4.86, CI = 3.09-7.73, P < 0.05).

CONCLUSIONS

The socioenvironmental composite risk indicator demonstrated sensitivity, since it was able to identify the localities with greater occurrence of infection. Because it can stratify spaces by using official and available data, it constitutes an important tool for use in the worldwide program for eliminating lymphatic filariasis.

Rapid mapping of schistosomiasis and other neglected tropical diseases in the context of integrated control programmes in Africa

There is growing interest and commitment to the control of schistosomiasis and other so-called neglected tropical diseases (NTDs). Resources for control are inevitably limited, necessitating assessment methods that can rapidly and accurately identify and map high-risk communities so that interventions can be targeted in a spatially-explicit and cost-effective manner. Here, we review progress made with (1) mapping schistosomiasis across Africa using available epidemiological data and, more recently, climate-based risk prediction; (2) the development and use of morbidity questionnaires for rapid identification of high-risk communities of urinary schistosomiasis; and (3) innovative sampling-based approaches for intestinal schistosomiasis, using the lot quality assurance sampling technique. Experiences are also presented for the rapid mapping of other NTDs, including onchocerciasis, loiasis and lymphatic filariasis. Future directions for an integrated rapid mapping approach targeting multiple NTDs simultaneously are outlined, including potential challenges in developing an integrated survey tool. The lessons from the mapping of human helminth infections may also be relevant for the rapid mapping of malaria as its control efforts are intensified.

Delimitation of lymphatic filariasis transmission risk areas: a geo-environmental approach

Background

The Global Programme to Eliminate Lymphatic Filariasis (GPELF) depends upon Mass Drug Administration (MDA) to interrupt transmission. Therefore, delimitation of transmission risk areas is an important step, and hence we attempted to define a geo-environmental risk model (GERM) for determining the areas of potential transmission of lymphatic filariasis.

Methods

A range of geo-environmental variables has been selected, and customized on GIS platform to develop GERM for identifying the areas of filariasis transmission in terms of "risk" and "non-risk". The model was validated through a 'ground truth study' following standard procedure using GIS tools for sampling and Immuno-chromotographic Test (ICT) for screening the individuals.

Results

A map for filariasis transmission was created and stratified into different spatial entities, "risk' and "non-risk", depending on Filariasis Transmission Risk Index (FTRI). The model estimation corroborated well with the ground (observed) data.

Conclusion

The geo-environmental risk model developed on GIS platform is useful for spatial delimitation purpose on a macro scale.

Spatial distribution pattern of oviposition in the mosquito Aedes aegypti in relation to urbanization in Buenos Aires: southern fringe bionomics of an introduced vector

The distribution of Aedes aegypti (L) (Diptera: Culicidae) oviposition in Buenos Aires City is spatially heterogeneous. Oviposition activity was monitored for a year with a grid of 279 traps at 850-m intervals that were serviced weekly. Geostatistics were used for the spatial analysis and generalized linear regression to model oviposition as a function of demographic and environmental variables. The proportion of weeks infested and the total number of eggs showed spatial continuity and were higher in areas that had higher densities of houses and were closer to industrial sites; they were lower in areas with higher human populations or higher densities of flats. When all sites were considered, the spatial structure showed a strong trend, but after regression, the residuals presented lower spatial dependence. When only infested sites were considered, the oviposition variables were spatially autocorrelated and the regression residuals showed little or no spatial dependence. The spatial pattern of Ae. aegypti oviposition in a highly urbanized city such as Buenos Aires seems to be related to the urbanization gradient. These urban environments might present different resource availability or continuity between patches of resources.

The health status of southern children: a neglected regional disparity

PURPOSE

Great variations exist in child health outcomes among states in the United States, with southern states consistently ranked among the lowest in the country. Investigation of the geographical distribution of children's health status and the regional factors contributing to these outcomes has been neglected. We attempted to identify the degree to which region of residence may be linked to health outcomes for children with the specific aim of determining whether living in the southern region of the United States is adversely associated with children's health status.

METHODS

A child health index (CHI) that ranked each state in the United States was computed by using state-specific composite scores generated from outcome measures for a number of indicators of child health. Five indicators for physical health were chosen (percent low birth weight infants, infant mortality rate, child death rate, teen death rate, and teen birth rates) based on their historic and routine use to define health outcomes in children. Indicators were calculated as rates or percentages. Standard scores were calculated for each state for each health indicator by subtracting the mean of the measures for all states from the observed measure for each state. Indicators related to social and economic status were considered to be variables that impact physical health, as opposed to indicators of physical health, and therefore were not used to generate the composite child health score. These variables were subsequently examined in this study as potential confounding variables. Mapping was used to redefine regional groupings of states, and parametric tests (2-sample t test, analysis of means, and analysis-of-variance F tests) were used to compare the means of the CHI scores for the regional groupings and test for statistical significance. Multiple-regression analysis computed the relationship of region, social and economic indicators, and race to the CHI. Simple linear-regression analyses were used to assess the individual effect of each indicator.

RESULTS

A geographic region of contiguous states, characterized by their poor child health outcomes relative to other states and regions of the United States, exists within the "Deep South" (Mississippi, Louisiana, Arkansas, Tennessee, Alabama, Georgia, North Carolina, South Carolina, and Florida). This Deep-South region is statistically different in CHI scores from the US Census Bureau-defined grouping of states in the South. The mean of CHI scores for the Deep-South region was >1 SD below the mean of CHI scores for all states. In contrast, the CHI score means for each of the other 3 regions were all above the overall mean of CHI scores for all states. Regression analysis showed that living in the Deep-South region is a stronger predictor of poor child health outcomes than other consistently collected and reported variables commonly used to predict children's health.

CONCLUSIONS

The findings of this study indicate that region of residence in the United States is statistically related to important measures of children's health and may be among the most powerful predictors of child health outcomes and disparities. This clarification of the poorer health status of children living in the Deep South through spatial analysis is an essential first step for developing a better understanding of variations in the health of children. Similar to early epidemiology work linking geographic boundaries to disease, discovering the mechanisms/pathways/causes by which region influences health outcomes is a critical step in addressing disparities and inequities in child health and one that is an important and fertile area for future research. The reasons for these disparities may be complex and synergistically related to various economic, political, social, cultural, and perhaps even environmental (physical) factors in the region. This research will require the use and development of new approaches and applications of spatial analysis to develop insights into the societal, environmental, and historical determinants of child health that have been neglected in previous child health outcomes and policy research. The public policy implications of the findings in this study are substantial. Few, if any, policies identify these children as a high-risk group on the basis of their region of residence. A better understanding of the depth and breadth of disparities in health, education, and other social outcomes among and within regions of the United States is necessary for the generation of policies that enable policy makers to address and mitigate the factors that influence these disparities. Defining and clarifying the regional boundaries is also necessary to better inform public policy decisions related to resource allocation and the prevention and/or mitigation of the effects of region on child health. The identification of the Deep South as a clearly defined subregion of the Census Bureau's regional definition of the South suggests the need to use more culturally and socially relevant boundaries than the Census Bureau regions when analyzing regional data for policy development.

Residual Spatial Correlation Between Geographically Referenced Observations

BACKGROUND

Analytic methods commonly used in epidemiology do not account for spatial correlation between observations. In regression analyses, this omission can bias parameter estimates and yield incorrect standard error estimates. We present a Bayesian hierarchical model (BHM) approach that accounts for spatial correlation, and illustrate its strengths and weaknesses by applying this modeling approach to data on Wuchereria bancrofti infection in Haiti.

METHODS

A program to eliminate lymphatic filariasis in Haiti assessed prevalence of W. bancrofti infection in 57 schools across Leogane Commune. We analyzed the spatial pattern in the prevalence data using semi-variograms and correlograms. We then modeled the data using (1) standard logistic regression (GLM); (2) non-Bayesian logistic generalized linear mixed models (GLMMs) with school-specific nonspatial random effects; (3) BHMs with school-specific nonspatial random effects; and (4) BHMs with spatial random effects.

RESULTS

An exponential semi-variogram with an effective range of 2.15 km best fit the data. GLMM and nonspatial BHM point estimates were comparable and also were generally similar with the marginal GLM point estimates. In contrast, compared with the nonspatial mixed model results, spatial BHM point estimates were markedly attenuated.

DISCUSSION

The clear spatial pattern evident in the Haitian W. bancrofti prevalence data and the observation that point estimates and standard errors differed depending on the modeling approach indicate that it is important to account for residual spatial correlation in analyses of W. bancrofti infection data. Bayesian hierarchical models provide a flexible, readily implementable approach to modeling spatially correlated data. However, our results also illustrate that spatial smoothing must be applied with care.

Spatial clustering of filarial transmission before and after a Mass Drug Administration in a setting of low infection prevalence

BACKGROUND: In the global program for the elimination of lymphatic filariasis (LF) longitudinal assessment of the prevalence of microfilaremia and antigenemia is recommended to monitor the effect of mass treatment on transmission. Additional monitoring tools such as entomologic and antibody methods may be useful in identifying residual foci of infection. In this study, we characterized serologic markers of infection and exposure spatially both before and after mass treatment, in an area of initial low Wuchereria bancrofti infection prevalence. METHODS: Consenting persons in the sentinel community were tested for circulating microfilaria and antigen (by immunochromatographic test) before and after the 1st annual mass drug administration of diethylcarbamazine and albendazole. A cohort of 161 persons provided serum specimens both years that were tested for antifilarial IgG (1 and 4) antibody. Every house was mapped using a differential Global Positioning System; this information was linked to the serologic data. W. bancrofti infection in the mosquito vector was assessed with year-round collection. Multiple linear regression was used to investigate the influence of antigen-positive persons on the antifilarial antibody responses of antigen-negative neighbors. RESULTS: After mass treatment, decreases were observed in the sentinel site in the overall prevalence of antigen (10.4% to 6.3%) and microfilaremia (0.9 to 0.4%). Of the persons in the cohort that provided serum specimens both years, 79% received treatment. Antigen prevalence decreased from 15.0% to 8.7%. Among 126 persons who received treatment, antigen and antifilarial IgG1 prevalence decreased significantly (p = 0.002 and 0.001, respectively). Among 34 persons who did not receive treatment, antifilarial IgG1 prevalence increased significantly (p = 0.003). Average antifilarial IgG1 levels decreased in households with high treatment coverage and increased in households that refused treatment. Each 10-meter increase in distance from the residence of a person who was antigen-positive in 2000 was associated a 4.68 unit decrease in antifilarial IgG1 level in 2001, controlling for other factors (p = 0.04). DISCUSSION: Antifilarial antibody assays can be used as a measure of filarial exposure. Our results suggest that micro-scale spatial heterogeneity exists in LF exposure and infection. Treatment appeared to be associated with reduced exposure at the sub-community level, suggesting the need to achieve high and homogeneous coverage. Public health messages should note the benefits of having one's neighbors receive treatment with antifilarial drugs.

Mathematical modelling and the control of lymphatic filariasis

The current global initiative to eliminate lymphatic filariasis represents one of the largest mass drug administration programmes ever conceived for the control of a parasitic disease. Yet, it is still not known whether the WHO-recommended primary strategy of applying annual single-dose mass chemotherapy with a combination of two drugs for 4-6 years will effectively break parasite transmission from all endemic communities. Here we review recent work on the development and application of a deterministic mathematical model of filariasis transmission, to show how models of parasite transmission will help resolve the key currently debated questions regarding the ultimate effectiveness of the global strategy to control filariasis. These critical questions include the required duration of mass treatment in different endemic areas, the optimal drug coverage required to meet control targets within prescribed timeframes, the impact and importance of adding vector control to mass chemotherapy regimens, and the likelihood of the development of drug resistance by treated worm populations. The results demonstrate the vital role that integrating these models into control programming can have in providing effective decision-support frameworks for undertaking the optimal design and monitoring of regional and global filariasis-control programmes. Operationally, the models show that the effectiveness of the strategy to achieve filariasis control will be determined by successfully addressing two key factors: the need to maintain high community treatment coverages, and the need to include vector control measures especially in areas of high endemicity.

Spatial variation of Anopheles-transmitted Wuchereria bancrofti and Plasmodium falciparum infection densities in Papua New Guinea

The spatial variation of Wuchereria bancrofti and Plasmodium falciparum infection densities was measured in a rural area of Papua New Guinea where they share anopheline vectors. The spatial correlation of W. bancrofti was found to reduce by half over an estimated distance of 1.7 km, much smaller than the 50 km grid used by the World Health Organization rapid mapping method. For P. falciparum, negligible spatial correlation was found. After mass treatment with anti-filarial drugs, there was negligible correlation between the changes in the densities of the two parasites.