Community-based field implementation scenarios of a short message service reporting tool for lymphatic filariasis case estimates in Africa and Asia.

Background: Lymphatic filariasis (LF) is a neglected tropical disease (NTD) targeted for global elimination by 2020. Currently there is considerable international effort to scale-up morbidity management activities in endemic countries, however there remains a need for rapid, cost-effective methods and adaptable tools for obtaining estimates of people presenting with clinical manifestations of LF, namely lymphoedema and hydrocele. The mHealth tool '' allows health workers in endemic areas to use their own mobile phones to send clinical information in a simple format using short message service (SMS). The experience gained through programmatic use of the tool in five endemic countries across a diversity of settings in Africa and Asia is used here to present implementation scenarios that are suitable for adapting the tool for use in a range of different programmatic, endemic, demographic and health system settings.

Methods: A checklist of five key factors and sub-questions was used to determine and define specific community-based field implementation scenarios for using the tool in a range of settings. These factors included: (I) tool feasibility (acceptability; community access and ownership); (II) LF endemicity (high; low prevalence); (III) population demography (urban; rural); (IV) health system structure (human resources; community access); and (V) integration with other diseases (co-endemicity).

Results: Based on experiences in Bangladesh, Ethiopia, Malawi, Nepal and Tanzania, four implementation scenarios were identified as suitable for using the tool for searching and reporting LF clinical case data across a range of programmatic, endemic, demographic and health system settings. These include: (I) urban, high endemic setting with two-tier reporting; (II) rural, high endemic setting with one-tier reporting; (III) rural, high endemic setting with two-tier reporting; and (IV) low-endemic, urban and rural setting with one-tier reporting.

Conclusions: A decision-making framework built from the key factors and questions, and the resulting four implementation scenarios is proposed as a means of using the tool. This framework will help national LF programmes consider appropriate methods to implement a survey using this tool to improve estimates of the clinical burden of LF. Obtaining LF case estimates is a vital step towards the elimination of LF as a public health problem in endemic countries.