Thomas K. Kristensen

Toward an Open-Access Global Database for Mapping, Control, and Surveillance of Neglected Tropical Diseases

Background After many years of general neglect, interest has grown and efforts came under way for the mapping, control, surveillance, and eventual elimination of neglected tropical diseases (NTDs). Disease risk estimates are a key feature to target control interventions, and serve as a benchmark for monitoring and evaluation. What is currently missing is a georeferenced global database for NTDs providing open-access to the available survey data that is constantly updated and can be utilized by researchers and disease control managers to support other relevant stakeholders. We describe the steps taken toward the development of such a database that can be employed for spatial disease risk modeling and control of NTDs. Methodology With an emphasis on schistosomiasis in Africa, we systematically searched the literature (peer-reviewed journals and ‘grey literature’), contacted Ministries of Health and research institutions in schistosomiasis-endemic countries for location-specific prevalence data and survey details (e.g., study population, year of survey and diagnostic techniques). The data were extracted, georeferenced, and stored in a MySQL database with a web interface allowing free database access and data management. Principal Findings At the beginning of 2011, our database contained more than 12,000 georeferenced schistosomiasis survey locations from 35 African countries available under http://www.gntd.org. Currently, the database is expanded to a global repository, including a host of other NTDs, e.g. soil-transmitted helminthiasis and leishmaniasis. Conclusions An open-access, spatially explicit NTD database offers unique opportunities for disease risk modeling, targeting control interventions, disease monitoring, and surveillance. Moreover, it allows for detailed geostatistical analyses of disease distribution in space and time. With an initial focus on schistosomiasis in Africa, we demonstrate the proof-of-concept that the establishment and running of a global NTD database is feasible and should be expanded without delay.

Remote sensing, geographical information system and spatial analysis for schistosomiasis epidemiology and ecology in Africa

Beginning in 1970, the potential of remote sensing (RS) techniques, coupled with geographical information systems (GIS), to improve our understanding of the epidemiology and control of schistosomiasis in Africa, has steadily grown. In our current review, working definitions of RS, GIS and spatial analysis are given, and applications made to date with RS and GIS for the epidemiology and ecology of schistosomiasis in Africa are summarised. Progress has been made in mapping the prevalence of infection in humans and the distribution of intermediate host snails. More recently, Bayesian geostatistical modelling approaches have been utilized for predicting the prevalence and intensity of infection at different scales. However, a number of challenges remain; hence new research is needed to overcome these limitations. First, greater spatial and temporal resolution seems important to improve risk mapping and understanding of transmission dynamics at the local scale. Second, more realistic risk profiling can be achieved by taking into account information on peoples socio-economic status; furthermore, future efforts should incorporate data on domestic access to clean water and adequate sanitation, as well as behavioural and educational issues. Third, high-quality data on intermediate host snail distribution should facilitate validation of infection risk maps and modelling transmission dynamics. Finally, more emphasis should be placed on risk mapping and prediction of multiple species parasitic infections in an effort to integrate disease risk mapping and to enhance the cost-effectiveness of their control.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs.

Control of schistosomiasis in sub-Saharan Africa: progress made, new opportunities and remaining challenges.

Several other journal supplements have documented progress made in the control of schistosomiasis in Egypt, China and Brazil, however, with more than 97% of the schistosome infections now estimated to occur in Africa, the relevance of this special issue in Parasitology cannot be overemphasized. In total, 18 articles are presented, inclusive of a lead-editorial from the WHO highlighting a seminal resolution at the 54th World Health Assembly in 2001 that advocated de-worming. Facilitated by a US

Application of geographic information systems and remote sensing to schistosomiasis control in China

30 million grant from the Bill and Melinda Gates Foundation in 2002, the Schistosomiasis Control Initiative subsequently fostered implementation of large-scale schistosomiasis (and soil-transmitted helminthiasis) control programmes in six selected African countries. From 2005, CONTRAST, a European union-funded consortium, was formed to conduct multi-disciplinary research pertaining to optimisation of schistosomiasis control. Progress made in schistosomiasis control across sub-Saharan Africa since the turn of the new millennium is reviewed, shedding light on the latest findings stemming from clinical, epidemiological, molecular and social sciences research, inclusive of public health interventions with monitoring and evaluation activities. New opportunities for integrating the control of schistosomiasis and other so-called neglected tropical diseases are highlighted, but more importantly, several opportune questions that arise from it frame the remaining challenges ahead for an enduring solution.

Spatial epidemiology in zoonotic parasitic diseases: insights gained at the 1st International Symposium on Geospatial Health in Lijiang, China, 2007

Progress in China on developing prediction models using remote sensing, geographic information systems and climate data with historical infection prevalence and malacology databases is reviewed. Special reference is made to the effects of the Yangtze river Three Gorges dam project on environmental changes that may impact changes in the spatial and temporal distribution and abundance of Schistosoma japonicum in China, and the future success of disease control programs.

Spatially explicit Schistosoma infection risk in eastern Africa using Bayesian geostatistical modelling

The 1st International Symposium on Geospatial Health was convened in Lijiang, Yunnan province, Peoples Republic of China from 8 to 9 September, 2007. The objective was to review progress made with the application of spatial techniques on zoonotic parasitic diseases, particularly in Southeast Asia. The symposium featured 71 presentations covering soil-transmitted and water-borne helminth infections, as well as arthropod-borne diseases such as leishmaniasis, malaria and lymphatic filariasis. The work made public at this occasion is briefly summarized here to highlight the advances made and to put forth research priorities in this area. Approaches such as geographical information systems (GIS), global positioning systems (GPS) and remote sensing (RS), including spatial statistics, web-based GIS and map visualization of field investigations, figured prominently in the presentation.

New insights into the transmission biology of urinary schistosomiasis in Zanzibar

Schistosomiasis remains one of the most prevalent parasitic diseases in the tropics and subtropics, but current statistics are outdated due to demographic and ecological transformations and ongoing control efforts. Reliable risk estimates are important to plan and evaluate interventions in a spatially explicit and cost-effective manner. We analysed a large ensemble of georeferenced survey data derived from an open-access neglected tropical diseases database to create smooth empirical prevalence maps for Schistosoma mansoni and Schistosoma haematobium for a total of 13 countries of eastern Africa. Bayesian geostatistical models based on climatic and other environmental data were used to account for potential spatial clustering in spatially structured exposures. Geostatistical variable selection was employed to reduce the set of covariates. Alignment factors were implemented to combine surveys on different age-groups and to acquire separate estimates for individuals aged ≤20 years and entire communities. Prevalence estimates were combined with population statistics to obtain country-specific numbers of Schistosoma infections. We estimate that 122 million individuals in eastern Africa are currently infected with either S. mansoni, or S. haematobium, or both species concurrently. Country-specific population-adjusted prevalence estimates range between 12.9% (Uganda) and 34.5% (Mozambique) for S. mansoni and between 11.9% (Djibouti) and 40.9% (Mozambique) for S. haematobium. Our models revealed that infection risk in Burundi, Eritrea, Ethiopia, Kenya, Rwanda, Somalia and Sudan might be considerably higher than previously reported, while in Mozambique and Tanzania, the risk might be lower than current estimates suggest. Our empirical, large-scale, high-resolution infection risk estimates for S. mansoni and S. haematobium in eastern Africa can guide future control interventions and provide a benchmark for subsequent monitoring and evaluation activities.

Molecular phylogenetic investigations of the Viviparidae (Gastropoda: Caenogastropoda) in the lakes of the Rift Valley area of Africa

A better understanding of the transmission biology of urinary schistosomiasis in Zanzibar, Tanzania was only possible after the development of molecular DNA markers for identification of Bulinus africanus group snails, the potential intermediate hosts of Schistosoma haematobium. Hitherto, identification of natural populations of B. globosus and B. nasutus was problematic and the intermediate host status and distribution of either species remained speculative. By recourse to molecular markers, snail distribution maps could be drawn, revealing an allopatric distribution and, more importantly, leading to the discovery that B. nasutus played no role in transmission. Indeed, in Unguja the area of active transmission of S. haematobium to humans is confined within the distribution of B. globosus. This strong relationship may prove useful for predicting the distribution of urinary schistosomiasis within Zanzibar and, if snail schistosome compatibilities persist, in other areas nearby, e.g. coastal Tanzania and Kenya. The transmission biology of urinary schistosomiasis in Zanzibar is reviewed, the paper reports on ongoing malacological studies in Zanzibar and Kenya and finally closes by posing the question whether medical malacology forms an essential component associated with mass-scale chemotherapy control programmes.

A molecular phylogeny of apple snails (Gastropoda, Caenogastropoda, Ampullariidae) with an emphasis on African species

The freshwater gastropod family Viviparidae is nearly cosmopolitan, but absent from South America. On the African continent, two genera are recognized; the widespread Bellamya and the monotypic Neothauma, which is confined to Lake Tanganyika. Most of the African Bellamya species are confined to the major lakes of the Rift Valley area in Africa, i.e. Lake Albert, Lake Malawi, Lake Mweru, and Lake Victoria. The phylogenetic analyses of mitochondrial (COI and 16S) and nuclear (H3, 18S and 28S) DNA inferred three major lake-clades; i.e. Lake Victoria/Kyoga/Albert, Lake Malawi and Lake Mweru/Bangweulu. The endemic B. rubicunda from Lake Albert and B. unicolor from Lake Kyoga were inferred to be part of the Lake Victoria clade. Bellamya capillata as identified by shell characters was polyphyletic in gene trees. The monophyletic Bellamya species radiation in Lake Malawi was most nearly related to the Lake Victoria/Kyoga/Albert-clade. Taxa from the Zambian lakes, Mweru and Bangweulu, were inferred together and placed ancestral to the other lakes. Neothauma tanganyicense was inferred as the sister-group to the Zambian Bellamya. Within the lake-clades the endemic radiations show very low genetic diversities (0-4.1% in COI), suggesting much faster morphological divergence than molecular divergence. Alternatively, Bellamya in Africa constitutes only a few species with several sub-species or eco-phenotypic morphs. The African viviparids were inferred to be the sister-group to a clade comprising Asian species, and the relatively low genetic diversity between the clades (12.6-15.5% in COI) makes a recent Miocene dispersal event from Asia to Africa much more likely than an ancient Gondwana vicarience distribution.