Introduction to a Landscape Analysis of Multisectoral Approaches for Prevention and Control of Infectious and Vector-Borne Diseases.

The Swiss Development Cooperation, Canada's International Development Research Centre, the Swiss Tropical Public Health Institute, and the UNICEF/United Nations Development Programme (UNDP)/World Bank/World Health Organization (WHO) Special Programme for Research and Training in Tropical Diseases (TDR) collaborated on a project to review, understand and promote the use of multisectoral approaches (MSAs) in the prevention and control of vector-borne diseases (VBDs). The objectives of the project were to support a landscape analysis of how MSAs have been used in the prevention and control of VBDs; to develop a theoretical framework for guiding the implementation of interventions; and to test the recommendations in real-life conditions. To realize these objectives, the project supported several activities, including commissioning a series of scientific reviews on MSAs in 5 thematic areas, sharing the key findings of these reviews in workshops and events, and developing a guidance framework for the implementation of MSAs. These activities have produced the theoretical framework that will be tested in real-life conditions through the support of case studies. The collaboration on implementing multisectoral activities against VBDs will continue among TDR, the Swiss Tropical Public Health Institute, and new partners such as the WHO Water Sanitation and Hygiene Group, UNDP, and UN-Habitat, in order to face the challenges identified and propose solutions tailored to specific contexts. The prevention and control of VBDs require strong and adapted MSAs with the full participation of all relevant sectors.

Malaria ecotypes and stratification.

To deal with the variability of malaria, control programmes need to stratify their malaria problem into a number of smaller units. Such stratification may be based on the epidemiology of malaria or on its determinants such as ecology. An ecotype classification was developed by the World Health Organization (WHO) around 1990, and it is time to assess its usefulness for current malaria control as well as for malaria modelling on the basis of published research. Journal and grey literature was searched for articles on malaria or Anopheles combined with ecology or stratification. It was found that all malaria in the world today could be assigned to one or more of the following ecotypes: savanna, plains and valleys; forest and forest fringe; foothill; mountain fringe and northern and southern fringes; desert fringe; coastal and urban. However, some areas are in transitional or mixed zones; furthermore, the implications of any ecotype depend on the biogeographical region, sometimes subregion, and finally, the knowledge on physiography needs to be supplemented by local information on natural, anthropic and health system processes including malaria control. Ecotyping can therefore not be seen as a shortcut to determine control interventions, but rather as a framework to supplement available epidemiological and entomological data so as to assess malaria situations at the local level, think through the particular risks and opportunities and reinforce intersectoral action. With these caveats, it does however emerge that several ecotypic distinctions are well defined and have relatively constant implications for control within certain biogeographic regions. Forest environments in the Indo-malay and the Neotropics are, with a few exceptions, associated with much higher malaria risk than in adjacent areas; the vectors are difficult to control, and the anthropic factors also often converge to impose constraints. Urban malaria in Africa is associated with lower risk than savanna malaria; larval control may be considered though its role is not so far well established. In contrast, urban malaria in the Indian subcontinent is associated with higher risks than most adjacent rural areas, and larval control has a definite, though not exclusive, role. Simulation modelling of cost-effectiveness of malaria control strategies in different scenarios should prioritize ecotypes where malaria control encounters serious technical problems. Further field research on malaria and ecology should be interdisciplinary, especially with geography, and pay more attention to juxtapositions and to anthropic elements, especially migration.

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.