5 Sep 2017

Mwingira U, et al. PLoS Negl Trop Dis 11(7): e0005748. https://doi.org/10.1371/journal.pntd.0005748

Introduction

Lymphatic filariasis (LF) is a disabling and disfiguring disease that can cause clinical conditions such as lymphoedema-elephantiasis (LE) and hydrocoele. In order to certify elimination of LF, endemic countries are required not only to prove the interruption of disease transmission through mass drug administration, but also to provide a minimum package of care to each person with LE and hydrocoele to alleviate the suffering of those affected in LF endemic areas. Collecting data on the number and whereabouts of individuals affected by LF is a crucial step for each country that strives to meet the WHO elimination dossier requirements. However, there are currently no specific guidelines on how to obtain patient estimates, although additional guidance is anticipated in a forthcoming WHO Morbidity Management and Disability Prevention toolkit. The authors undertook a patient identification survey using an innovative approach of SMS reporting system previously tested in rural settings to identify patients in densely populated urban areas in Dar es Salaam, Tanzania, thereby supporting Tanzania’s progress in eliminating LF and highlighting how an SMS-based approach to LF patient identification can generate new data on the number of LF clinical cases in a large urban area.

Methods

The study, conducted in 2015, used a health community-led door-to-door survey approach and incorporated the MeasureSMS-Morbidity reporting tool to rapidly collate and monitor the data. The MeasureSMS-Morbidity system stores individual-level data sent via SMS on LF patients’ location, sex, age, clinical condition, severity of condition and number of acute attacks in the past 6 months which can be viewed in real time. The study consisted of a training period, a patient identification and reporting period, and a data verification period. The patient identification and reporting processes were conducted using a two-tier approach which relied on training frontline health workers, who in turn trained Community Health Volunteers (CHVs) responsible for patient identification through door-to-door survey. Patients self-reported their conditions after being shown illustrations of LE and hydrocele. The CHV would then confirm the condition and its severity through examination except for cases of hydrocele, and record the information on a paper form. At the end of each day this paper form was given to their designated data reporter, who transferred the information to a master form, and sent the information in via SMS. Following this patient identification process, a verification process was undertaken by a verification team – consisting of a clinical officer and, when possible, the original patient identifier – for a sample of patients in order to check the accuracy of the reported conditions.

Results

In all three districts surveyed, a total of 6889 patients were reported, of which 2251 patients were reported to suffer from LE, 4169 patients were reported to suffer from hydrocele and 469 were reported to be burdened with both forms of the disease. The number of hydrocele cases reported was almost twice that of LE cases reported. Kinondoni district had the highest number of reported patients in absolute terms (2846, 138.9 per 100,000), followed by Temeke (2550, 157.3 per 100,000) and Ilala (1493, 100.5 per 100,000). Summary of error rates show that error rates increased towards the end of the patient identification period. The authors postulate that this increase was due to the fact that data reporters who experienced the most difficulties with the reporting tool took the longest to submit data.

Discussion and comments

The data collected through this study indicated that LF burden in Dar es Salaam was higher than previously anticipated. Furthermore, the results from the study provided crucial information which would help guide further morbidity management and disability prevention activities now that the geographic distribution of the disease is known. The authors noted the implementation challenge of relocating patients after the initial patient identification process, and suggested that additional training on the staging and severity of clinical conditions could improve the accuracy of reported data. But, the ability to view and assess data in real time was a great asset that not only yielded valuable patient estimates but also facilitated efficient provision of care to patients and built data management capacity within the national program team.